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Americans More Upbeat on the Economy; Biden’s Job Rating Remains Very Low

1. views of the nation’s economy, table of contents.

• The economy, past and future; top concerns
• Biden’s job performance, personal traits
• Other findings on partisan compromise and the House GOP impeachment inquiry
• Why do Americans rate the nation’s economy as they do?
• Cost of goods, housing remain top economic concerns
• Partisans’ views of Biden’s personal characteristics
• Perceptions of Biden over time
• Biden’s job approval ratings
• Biden’s presidency in the long run
• Acknowledgments
• The American Trends Panel survey methodology

About three-in-ten Americans (28%) currently rate national economic conditions as excellent or good, while a similar share (31%) say they are poor and about four-in-ten (41%) view them as “only fair.”

While ratings remain substantially lower than they were prior to the start of the COVID-19 pandemic , they are more positive than they were last spring – when just 19% viewed the economy in positive terms.

Expectations for future economic conditions are also more positive than they were last spring: Today, roughly a quarter say that they expect economic conditions will be better a year from now (26%) – up from 17% in April 2023.

At the same time, the share who says conditions will be worse has declined by 13 percentage points. About four-in-ten say they expect conditions will be about the same.

As has long been the case , partisans who share the party of the president have more positive views of economic conditions than those who support the opposing party. Today, 44% of Democrats and Democratic leaners say the nation’s economy is excellent or good. This compares with 13% of Republicans and GOP leaners.

Similarly, Democrats are more likely than Republicans to say they expect economic conditions a year from now will be better than they are today: 34% of Democrats say this, compared with 20% of Republicans.

There are substantial differences among Democrats in views of the nation’s economy – particularly by age and income.

Younger Democrats are much less likely than older Democrats to view current economic conditions in positive terms. Among Democrats under 30, a quarter view the economy positively. This share rises to 34% among those ages 30 to 49, 56% among those 50 to 64, and 70% among those 65 and older.

There are also significant differences by race and ethnicity. White Democrats are more likely than Black, Hispanic and Asian Democrats to say the economy is excellent or good.

Democrats in different income groups also diverge in their evaluations of the nation’s economy. Democrats with higher household incomes are more positive about economic conditions than Democrats with lower incomes. A clear majority of upper-income Democrats (60%) say the economy is doing excellent or good. By comparison, 32% of those with lower incomes view the economy positively, while a majority say it is only fair (40%) or poor (28%).

Across Republican groups, economic assessments vary less drastically. Republicans overwhelmingly rate the economy negatively: Just 15% or less across demographic groups say national economic conditions are good or excellent.

However, there are some differences in how negative GOP assessments are. For instance, upper-income Republicans are more likely to say the economy is doing only fair (48%) rather than poorly (36%), while lower-income Republicans are more likely to say poor (49%) rather than only fair (38%).

In an open-ended question which asked Americans to explain the reasons for their overall evaluation of the nation’s economy (as excellent, good, only fair, or poor), people provide wide-ranging answers.

Among the 28% of Americans who say the nation’s economy is doing excellent or good, many offer overwhelmingly positive reasons for why they rate the economy this way. A large share (43%) note the country’s low unemployment, while 18% say that inflation is coming down or is lower than it has been in recent months. Roughly one-in-ten mention wage growth, while a similar share (9%) say strong stock market performance contributes to their rating. And 5% say the reason for their rating is that the U.S. is outperforming expectations or otherwise doing better than other countries in terms of economic growth.

Among the 72% of adults who say the economy is doing only fair or poor, most offer negative reasons for why they rate the economy the way they do. Those who say the economy is only fair are slightly more likely to offer a mix of positive and negative responses than those who say the economy is poor . However, respondents in both groups offer similar reasons for their ratings.

Among those who say the nation’s economy is only fair or poor, high inflation or high costs of various goods are frequently mentioned: 28% say high inflation is a main reason they evaluate the economy as only fair or poor, while roughly two-in-ten cite the high cost of living. Along this same theme, 6% point to the high cost of food and groceries while identical shares say the high cost of housing and high interest rates are a main reason they view the economy as doing only fair or poor.

Other issues are also mentioned: 15% say the lack of good paying jobs or low wages is a major reason for their rating while 7% point to the national debt and government spending. Another 5% give a negative response about Biden’s or Democrats’ economic policies more broadly.

Majorities of Americans continue to express a high level of concern about the price of food and consumer goods (72% say they are very concerned about this) and the cost of housing (64%). About half (51%) say they are very concerned about the price of gasoline and energy. More than eight-in-ten say they are at least somewhat concerned about each of these economic issues.

Other economic issues rank lower on the public’s list of concerns. Smaller shares of Americans say they are very concerned about the stability of banks and financial institutions (27%), people who want to work being unable to find jobs (31%) or the performance of the stock market (18%).

Majorities in both parties are very concerned about the cost of goods and housing

Republicans and Democrats are fairly aligned in their economic concerns. Majorities in both groups say they are very concerned about the cost of food, consumer goods and housing. And substantially smaller shares express concern about the stability of banks or the performance of the stock market.

However, Republican concern about the price of food and consumer goods is more widespread than Democratic concern (82% vs. 63%). And the partisan gap on concerns about the price of gasoline and energy is even wider: A 64% majority of Republicans say they are very concerned about the cost of gas, compared with 40% of Democrats.

Partisans’ expectations for the year ahead

As has been the case for the last three years , Democrats are more likely than Republicans to say the upcoming year will be better than the last. Two-thirds of Democrats say 2024 will be better than 2023, while 43% of Republicans say the same.

This dynamic in feelings about the new year – with Democrats expressing more optimism than Republicans – has held true since 2021. Then, 83% of Democrats said 2021 would be better than 2020 while 48% of Republicans agreed. In 2020, the pattern was the reverse. Republicans were more likely to say 2020 would be better than 2019 compared with Democrats (78% vs. 36%, respectively).

In Pew Research Center surveys dating back to 2006 (when the question was first asked), Americans who identify with or lean toward the president’s party have tended to be more optimistic about the coming year than those who associate with the opposing party.

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The National Economics Challenge

America’s premier competition for high school students.

The tools of economic analysis teach students to think logically, use data smartly, and build analytic and problem-solving skills

Each year, close to 10,000 students from across the nation take the chance to shine while being tested on key micro and macroeconomic principles, as well as their knowledge of the world economy. 

The National Economics Challenge provides a platform for high school students of economics to compete with their peers on a national scale and make themselves and their schools proud.

The 2024 National Economics Challenge semi-finals will take place April 22-26, 2024. The finals will be hosted in New York, NY on June 1-3, 2024.

Building knowledge, confidence, and camaraderie

The National Economics Challenge has a unique method for engaging, motivating, and rewarding high school students, making it a fun learning experience they’ll never forget. Participants compete for cash prizes, recognition, and bragging rights in one of two divisions: The Adam Smith division is for advanced placement, baccalaureate, honors students, and returning competitors, and the David Ricardo Division is for students participating in the NEC for the first time and who have taken no more than one economics course.

Working in local teams with instructors and economics professionals serving as coaches, students compete first at the state level. The winning team from each state moves on to the First Round National Challenge to vie for their spot in the National Semi-Finals.

The top four teams in the semi-finals advance and receive an all-expense paid trip to New York City to compete and earn cash prizes:

1st place $1,000 | 2nd place $500 | 3rd place $250 | 4th place $125

Sign up for the national economics challenge.

To register a team, please start by selecting your state in the drop-down below. The National Economics Challenge (NEC) is the country’s only economics competition of its kind for high school students. It tests micro and macroeconomic principles as well as knowledge of the world economy.

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How Is the Economy Doing?

By Ben Casselman and Lauren Leatherby Sept. 13, 2022

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The U.S. economy is in a strange place right now. Job growth is slowing , but demand for workers is strong . Inflation is high (but not as high as last spring). Consumers are spending more in some areas, but cutting back in others. Job openings are high but falling, while layoffs are low and … well, it depends what indicator you watch.

This is one snapshot of where the economy stands, based on an analysis of how various indicators compare with their historical levels and whether they’ve been getting better or worse in recent months.

How conditions are faring for jobs, income, consumers and production :

Currently bad

Currently good

GETTING BETTER

GOOD AND GETTING BETTER

Capital goods

Unemployment

Manufacturing

and trade sales

earnings growth

GETTING WORSE

GOOD BUT GETTING WORSE

BAD BUT GETTING BETTER

There is no universally accepted definition of a “good” number of jobs or rate of wage growth, which means the exact placement of the various measures is somewhat subjective. Still, the patterns are revealing: The indicators are concentrated in the lower right-hand quadrant, meaning most of the economy is doing well, but slowing down.

Even in the best of times, it can be hard to get a handle on what’s happening in an economy with 150 million workers and $20 trillion worth of annual output. And these are far from the best of times. The pandemic and its ripple effects are continuing to disrupt global supply chains and keeping millions of Americans out of work . The war in Ukraine has pushed up gas and food prices, and added a new source of uncertainty. The Federal Reserve is trying to beat back the fastest inflation in decades — and threatening to cause a recession in the process.

By one common definition, the United States is already in a recession, because gross domestic product has declined for two consecutive quarters . Most economists consider that definition too simplistic , and prefer to look at a broader array of indicators across a variety of categories. They also say that to understand how the economy is doing, it is important to consider both levels and rates of change. It matters, for example, not only whether unemployment is low or high, but also whether it is rising or falling.

It also helps to consider the latest data in historical context. The graphics below show how this economic moment compares with recessions of the past 40 years, using the end of the second quarter as a benchmark. In most cases, the latest numbers don’t look much like the recessions of the past, although many show signs of a slowdown.

How current conditions compare with recessions over the last 40 years

Graphic shows year-over-year percentage change. Data for 2022 is presented as if a recession began in June, which marks the end of a second consecutive quarter of declines in gross domestic product. (An official designation of whether the United States is in a recession will be made in the future and will rely on several other indicators.)

If there is one part of the economy that is clearly doing well right now, it is the job market. Employers have added nearly six million jobs in the past year, and the unemployment rate recently matched a 50-year low. Employers would hire even more workers if they could find them: There were more than 11 million job openings at the end of July.

Still, not everything is rosy. The share of adults who are either working or actively looking for work is still well below its prepandemic level , which helps explain the frequent complaints from businesses that they can’t find enough workers. After months of strong gains, hiring slowed in August, and the total number of jobs remains millions below where it would be if the pandemic had never happened.

Layoffs, as measured through filings for unemployment claims, began rising earlier this year but have since edged back down; however, another measure, from a different survey, did not show a similar increase.

If layoffs pick up, watch out: In the past, when unemployment has increased even modestly, it has almost always meant the economy is in a recession.

Income and Prices

Graphic shows year-over-year percentage change. Data for 2022 is presented as if a recession began in June, which marks the end of a second consecutive quarter of declines in gross domestic product. Personal income data excludes transfer payments and is adjusted for inflation. Growth in hourly wages shows earnings for production and nonsupervisory employees.

Workers have seen their pay rise significantly in the past two years, as the hot labor market has given workers the leverage to demand raises. Other types of income, including from businesses and investments, have been rising too. The problem is, prices have been rising about as fast — or in some cases even faster.

The National Bureau of Economic Research, the semiofficial arbiter of recessions in the United States, focuses on personal income that is adjusted for inflation and excludes unemployment benefits and other government transfer payments. That indicator is still rising, in part because it measures income in the aggregate — meaning not how much the average person makes, but how much everyone, collectively, makes. When more people are working, overall incomes go up.

Many individuals, though, are falling behind. Inflation hit a four-decade high earlier this year, and though it has ebbed a bit in the past two months, no one is sure how long that will last. Even with the recent cooldown, average hourly earnings have risen more slowly than prices this year, although gains have been stronger among lower earners. Other measures of wages tell a similar story. And even without adjustments for inflation, wage gains have been slowing in recent months — a possible sign that workers’ rare moment of leverage may be nearing its end.

How current conditions compare to recessions over the last 40 years

Graphic shows year-over-year percentage change. Data for 2022 is presented as if a recession began in June, which marks the end of a second consecutive quarter of declines in gross domestic product. Consumer spending data and manufacturing and trade sales data are adjusted for inflation.

Economic indicators might be pointing in different directions, but this much is clear: Americans feel terrible about the economy right now. Consumer sentiment, as measured by a long-running survey from the University of Michigan, recently hit a record low — lower even than in the first weeks of the pandemic, when tens of millions of people lost their jobs overnight.

In the past, falling consumer sentiment has been a fairly reliable recession indicator. Consumer spending accounts for about 70 percent of G.D.P., so when people stop spending, the economy is almost guaranteed to run into hard times. So far, however, Americans haven’t acted on their dour mood by cutting back. Even in the face of high prices, people have continued to shell out for plane tickets, restaurant meals and other small luxuries. And now consumer sentiment is showing some signs of improvement as gas prices fall.

Interpreting the consumer economy is tough right now, however, because of how the pandemic disrupted spending patterns. Many people are eager to catch up on deferred travel and experiences, even if they have to pay more for them, which could cause spending on services like these to hold up even if the economy slows. Spending on goods, meanwhile, soared in the pandemic, as people traded gym memberships for home exercise equipment. Goods spending has now begun to slow. But supply-chain snarls have complicated the picture — rising car sales, for example, might mean that demand is strong, but it also might mean that production problems are easing and that there are finally more vehicles available to buy.

Graphic shows year-over-year percentage change. Data for 2022 is presented as if a recession began in June, which marks the end of a second consecutive quarter of declines in gross domestic product. Capital goods data excludes aircraft and military equipment.

Historically, one of the surest indicators of a coming recession has been a decline in orders for industrial equipment — companies don’t invest in so-called capital goods such as new machinery or delivery trucks when they’re worried that demand is about to fall sharply. Right now, though, those signals are being blurred by the same issues that make it hard to interpret consumer spending data. If manufacturers pull back now, is it because of falling demand, or because they can’t get the parts they need?

There is one sector that is, unequivocally, behaving as if we’re headed for a recession: housing. Ever since the Federal Reserve began raising interest rates this year, builders have been reducing construction, and would-be buyers have been pulling out of the market. So far, however, there is little sign of a surge in foreclosures or of the financial stresses caused by the last housing bust.

A slowdown that stays confined to one or two sectors doesn’t constitute a recession, which by definition involves a sustained decline in activity across a broad swath of the economy. It might not be obvious right away, but when a recession does hit, it will show up in virtually every major indicator.

Methodology

In the chart at the top of this story, the horizontal axis places indicators based on how they compare with their historical levels. For indicators that generally rise over time, such as payroll employment and consumer spending, the placement is based on how the current levels compare with their prepandemic path (specifically, the linear trend from 2017 to 2019). Employment, for example, is still somewhat below its previous trend line, so it is shown as slightly negative, while consumer spending is far above its trend, so it is most of the way to the positive (right) side of the chart.

For indicators with no long-run trend, placement is based on how current levels compare with their average from 2010 to 2019. The unemployment rate, for example, is substantially better than its long-run average, so it is shown as solidly positive.

The vertical axis is based on the change over the past three months. Employment growth has slowed but remains positive, so it is shown as positive, while the unemployment rate rose in August, so it is shown as slightly negative.

All indicators are converted to a consistent scale to allow for comparisons. So even though the unemployment rate is measured in percentage points and building permits are measured in thousands of units, we can see on the chart that the housing market is eroding faster than the labor market.

Sources: U.S. Bureau of Labor Statistics; U.S. Employment and Training Administration; U.S. Bureau of Economic Analysis; University of Michigan; U.S. Census Bureau; Board of Governors of the Federal Reserve System; Federal Reserve Bank of St. Louis

An official website of the United States government

U.S. Economy at a Glance

Perspective from the bea accounts.

BEA produces some of the most closely watched economic statistics that influence decisions of government officials, business people, and individuals. These statistics provide a comprehensive, up-to-date picture of the U.S. economy. The data on this page are drawn from featured BEA economic accounts.

National Economic Accounts

Gross domestic product, first quarter 2024 (advance estimate).

Real gross domestic product (GDP) increased at an annual rate of 1.6 percent in the first quarter of 2024, according to the “advance” estimate. In the fourth quarter of 2023, real GDP increased 3.4 percent. The increase in the first quarter primarily reflected increases in consumer spending and housing investment that were partly offset by a decrease in inventory investment. Imports, which are a subtraction in the calculation of GDP, increased.

• Current release:  April 25, 2024
• Next release:  May 30, 2024

Gross Domestic Product, First Quarter 2024 (Advance Estimate) CHART - HP

Personal Income and Outlays, March 2024

Personal income increased $122.0 billion (0.5 percent at a monthly rate) in March. Disposable personal income (DPI)—personal income less personal current taxes—increased $104.0 billion (0.5 percent). Personal outlays—the sum of personal consumption expenditures (PCE), personal interest payments, and personal current transfer payments—increased $172.1 billion (0.9 percent) and consumer spending increased $160.9 billion (0.8 percent). Personal saving was $671.0 billion and the personal saving rate—personal saving as a percentage of disposable personal income—was 3.2 percent in March.

• Current release:  April 26, 2024
• Next release:  May 31, 2024

Personal Income and Outlays, March 2024 CHART

Industry Economic Accounts

International economic accounts, u.s. international transactions, 4th quarter and year 2023.

The U.S. current-account deficit narrowed by $1.6 billion, or 0.8 percent, to $194.8 billion in the fourth quarter of 2023, according to statistics released today by the U.S. Bureau of Economic Analysis. The revised third-quarter deficit was $196.4 billion. The fourth-quarter deficit was 2.8 percent of current-dollar gross domestic product, down less than 0.1 percent from the third quarter.

• Current Release:  March 21, 2024
• Next Release:  June 20, 2024

U.S. International Transactions 4th Quarter, '23 Chart 1

U.S. International Investment Position, 4th Quarter and Year 2023

The U.S. net international investment position, the difference between U.S. residents’ foreign financial assets and liabilities, was -$19.77 trillion at the end of the fourth quarter of 2023, according to statistics released today by the U.S. Bureau of Economic Analysis (BEA). Assets totaled $34.54 trillion, and liabilities were $54.31 trillion. At the end of the third quarter, the net investment position was -$18.11 trillion (revised).

• Current Release:  March 27, 2024
• Next Release:  June 26, 2024

U.S. International Investment Position, 4th Quarter and year '23 CHART

U.S. International Trade in Goods and Services, February 2024

The U.S. goods and services trade deficit increased in February 2024 according to the U.S. Bureau of Economic Analysis and the U.S. Census Bureau. The deficit increased from $67.6 billion in January (revised) to $68.9 billion in February, as imports increased more than exports. The goods deficit decreased $0.3 billion in February to $91.4 billion. The services surplus decreased $1.6 billion in February to $22.5 billion.

• Current Release:  April 4, 2024
• Next release:  May 2, 2024

Goods and Services Trade Deficit, February '24

New Foreign Direct Investment in the United States, 2022

Expenditures by foreign direct investors to acquire, establish, or expand U.S. businesses totaled $177.5 billion in 2022, down $185.1 billion from $362.6 billion in 2021.

• Current release:  July 10, 2023
• Next release:  July 2024

New Foreign Direct Investment Expenditures by Type, '99-'22 Chart

Regional Economic Accounts

Gross domestic product by state and personal income by state, 4th quarter 2023 and preliminary 2023.

Real gross domestic product (GDP) increased in all 50 states and the District of Columbia in the fourth quarter of 2023, with the percent change ranging from 6.7 percent in Nevada to 0.2 percent in Nebraska

• Current Release:  March 29, 2024
• Next Release:  June 28, 2024

Gross Domestic Product by State and Personal Income by State, 4th Quarter '23 and Preliminary '23 - CHART

Personal Income by County and Metropolitan Area, 2022

In 2022, personal income, in current dollars, increased in 1,964 counties, decreased in 1,107, and was unchanged in 43. Personal income increased 2.1 percent in the metropolitan portion of the United States and 1.3 percent in the nonmetropolitan portion.

• Current Release:  November 16, 2023
• Next Release:  November 14, 2024

Personal Income by County and Metropolitan Area, 2022 CHART

Personal Consumption Expenditures by State, 2022

Nationally, personal consumption expenditures (PCE), in current dollars, increased 9.2 percent in 2022 after increasing 12.9 percent in 2021. PCE increased in all 50 states and the District of Columbia, with the percent change ranging from 11.8 percent in Idaho to 6.4 percent in Louisiana.

• Current Release: October 4, 2023
• Next release: October 3, 2024

Personal Consumption Expenditures by State: Percent Change, '21-'22

Reimagining the global economy: Building back better in a post-COVID-19 world

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Subscribe to Global Connection

November 17, 2020

The COVID-19 global pandemic has produced a human and economic crisis unlike any in recent memory. The global economy is experiencing its deepest recession since World War II, disrupting economic activity, travel, supply chains, and more. Governments have responded with lockdown measures and stimulus plans, but the extent of these actions has been unequal across countries. Within countries, the most vulnerable populations have been disproportionately affected, both in regard to job loss and the spread of the virus.

The implications of the crisis going forward are vast. Notwithstanding the recent announcement of vaccines, much is unknown about how the pandemic will spread in the short term and beyond, as well as what will be its lasting effects. What is clear, however, is that the time is ripe for change and policy reform. The hope is that decisionmakers can rise to the challenge in the medium term to tackle the COVID-19 virus and related challenges that the pandemic has exacerbated—be it the climate crisis, rising inequality, job insecurity, or international cooperation.

In this collection of 12 essays, leading scholars affiliated with the Global Economy and Development program at Brookings present new ideas that are forward-looking, policy-focused, and that will guide policies and shape debates in a post-COVID-19 world.

Sustainable Development Goals

Authors: Homi Kharas , John W. McArthur

Some have questioned whether the pandemic has put attaining the already ambitious 17 Sustainable Development Goals (SDGs) out of reach, and whether they should be scaled back and deprioritized. In this essay, Homi Kharas and John McArthur argue that the SDGs remain as relevant as ever and that the goals can in fact provide a handrail for recovery policy.

Continue reading

Leadership at the local level

Authors: Anthony F. Pipa , Max Bouchet

The pandemic has revealed the importance of good leadership at the local level. In this essay, Anthony F. Pipa and Max Bouchet explore the role that global cities can have in driving a sustainable recovery.

Multilateralism

Authors: Kemal Derviş

Given the global nature of the pandemic,  there have been  calls for greater international cooperation. In this essay, Kemal Derviş examines the state of  multilateralism  and presents lessons of caution as its future is reimagined.

Rebooting the climate agenda

Authors: Amar Bhattacharya

Shared recognition of the   climate agenda is central to global cooperation.  In this essay, Amar Bhattacharya explores  how   international action   can  pursue  a   recovery  that produces sustainable, inclusive, and resilient growth.  

The international monetary and financial system

Authors: Brahima Sangafowa Coulibaly , Eswar Prasad

The pandemic has exposed the weaknesses in the international financial system and the need to improve the financial safety net for emerging and developing countries. In this essay, Brahima Coulibaly and Eswar Prasad make the case for an international monetary and financial system that is fit for purpose to help countries better withstand shocks like a global pandemic.

The future of global supply chains

Authors: David Dollar

International trade has slowed, and existing trade challenges, including automation, new data flows, and the rise of protectionism, could accelerate post-COVID. In this essay, David Dollar discusses these challenges, the future of global supply chains, and the implications for international trade.

The global productivity slump

Authors: Alistair Dieppe , M. Ayhan Kose

COVID-19 could further accelerate the fall in global productivity, which has been slowing since the global financial crisis. Evidence from other recent pandemics such as SARS and Ebola show their negative impact on investment growth and productivity. In this essay, Alistair Dieppe and Ayhan Kose argue that policy approaches to boost productivity must be country-specific and well-targeted.

Dislocation of labor markets

Authors: Marcela Escobari , Eduardo Levy Yeyati

Throughout the world, the health and economic costs of the pandemic have been felt harder by less well-off populations. On the jobs front, the pandemic is affecting labor markets differently across and within advanced and developing countries as low-wage, high-contact jobs are disproportionally affected. In this essay, Marcela Escobari and Eduardo Levy Yeyati explore the future of work and policies for formalizing and broadening labor protections to bolster resiliency.

Tackling the inequality pandemic

Authors: Zia Qureshi

Technology, globalization, and weakening redistribution policies are leading to rising inequality in many countries. To tackle inequality, Zia Qureshi discusses policies to better harness technology for fostering inclusive economic growth.

The human costs of the pandemic

Authors: Carol Graham

Evidence suggests that the poor have been suffering higher emotional costs during the pandemic. In this essay, Carol Graham offers a look into well-being measurement and strategies to combat the effects of the lockdowns.

The complexity of managing COVID-19

Authors: Alaka M. Basu , Kaushik Basu , Jose Maria U. Tapia

From strict lockdowns to ensuring sufficient supplies of personal protective equipment to sending students home from school, governments around the world have enacted varying measures to respond to the virus. In this essay, Alaka M. Basu, Kaushik Basu, and Jose Maria U. Tapia examine how governments in emerging markets have managed the crisis so far, as they design governance strategies that both reduce the spread of infection and avoid prohibiting economic activity.

Global education

Authors: Emiliana Vegas , Rebecca Winthrop

COVID-19 disrupted education systems everywhere and has accelerated education inequality as seen through what service governments could provide: At one point during the pandemic, 1 in 4 low-income countries was able to provide remote education, while 9 in 10 high-income countries were able to. In this essay, Emiliana Vegas and Rebecca Winthrop present an aspirational vision for transforming education systems to better serve all children.

Global Trade Sustainable Development Goals

Global Economy and Development

Eswar Prasad, Caroline Smiltneks

April 14, 2024

Robin Brooks

April 11, 2024

The Brookings Institution, Washington DC

10:00 am - 11:30 am EDT

What is economic growth? And why is it so important?

The goods and services that we all need are not just there – they need to be produced – and growth means that their quality and quantity increase..

Good health, a place to live, access to education, nutrition, social connections, respect, peace, human rights, a healthy environment, and happiness. These are just some of the many aspects we care about in our lives.

At the heart of many of these aspects that we care about are needs for which we require particular goods and services . Think of those that are needed for the goals on the list above – the health services from nurses and doctors, the home you live in, or the teachers who provide education.

Poverty, prosperity, and growth are often measured in monetary terms, most commonly as people’s income. But while monetary measures have some important advantages, they have the big disadvantage that they are abstract. In the worst case, monetary measures – like GDP per capita – are so abstract that we forget what they are actually about: people’s access to goods and services.

The point of this text is to show why economic growth is important and how the abstract monetary measures tell us about the reality of people’s material living conditions around the world and throughout history:

• In the first part, I want to explain what economic growth is and why it is so difficult to measure.
• In the second part, I will discuss the advantages and disadvantages of several measures of growth, and you will find the latest data on several of these measures so that we can see what they tell us about how people’s material living conditions have changed.

What are these goods and services that I’m talking about?

Have a look around yourself right now. Many of the things you see are products that were produced by someone so that you can use them: the trousers you are wearing, the device you are reading this on, the electricity that powers it, the furniture around you, the toilet that is nearby, the sewage system it is connected to, the bus or car or bicycle you took to get where you are, the food you had this morning, the medications you will receive when you get sick, every window in your home, every shirt in your wardrobe, and every book on your shelf.

At some point in the past, many of these products were not available. The majority did not have access to the most basic goods and services they needed. A recent study on the history of global poverty estimates that just two centuries ago, roughly three-quarters of the world "could not afford a tiny space to live, food that would not induce malnutrition, and some minimum heating capacity.” 1

Let’s look at the history of the last item on that list above, books.

A few centuries ago, the only way to produce a book was for a scribe to copy it word-for-word by hand. Book production was a slow process; it took a scribe about eight months of daily work to produce a single copy of the Bible. 2

It was so laborious that only very few books were produced. The chart shows the estimates of historians. 3

But then, in the 15th century, the goldsmith Johannes Gutenberg combined the idea of movable letters with the mechanism that he knew from the wine presses in his hometown. He developed the printing press. Gutenberg developed a new production technology, and it changed things dramatically. Instead of spending months to produce one book, a worker was now able to produce several books a day.

As the printing press spread across Europe, book production soared. Books, which were previously only available to a tiny elite, became available to more and more people.

This is one example of how growth is possible and what economic growth is : an increase in the production of goods and services that people produce for each other.

A list of goods and services that people produce for each other

Before we get to a more detailed definition of economic growth, it’s helpful to remind ourselves of the astonishingly wide range of goods and services that people produce. I think this is helpful because measures of economic output can easily become abstract. This abstraction means we easily lose the mental connection to the goods and services such measures actually talk about.

This list of goods and services isn’t meant as a definitive list, but it helped me to think about the relevance of poverty and growth: 4

At home: Light in your home at night; the sewage system; a shower; vacuum cleaner; fridge; heating; air conditioning; electricity; windows; a toilet – even a flush toilet; soap; a balcony or a garden; running water; warm water; cutlery and dishes; a hut – or even a warm apartment or house; an oven; sewing machine; a stove (that doesn’t poison you ); carpet; toilet paper; trash bags; music recordings or even online streaming of the world’s music and film; garbage collection; radio; television; a washing machine; 5 furniture; telephone; a comfortable bed, and a room for one’s own.

Food: The most fundamental need is to have enough food. For much of human history, a large share of people suffered from hunger , and millions still do .

But we also need to have a richer and more varied diet to get all of the nutrients we need. Unfortunately, billions still suffer from micronutrient deficiency .

Also, think of clean drinking water; reliable markets and stores with a wide range of available goods; food that rarely poisons you (pasteurized milk, for example); spices; tea and coffee; kitchen utensils and practical ingredients (from a bag of flour to canned soups or a yogurt); chocolate and sweets; fresh fruit and vegetables; bread; take-away food or the possibility to go to a restaurant; ways to protect your food from spoiling (from the cold chain that delivers the goods to the cellophane to wrap it with); wine or beer; fertilizer ( very important); and tractors to work the fields.

Knowledge: Education from primary up to university level; books; data that allows us to understand the world around us; newspapers; vocational training; kindergartens; and scientific knowledge to understand ourselves and the world around us.

Infrastructure: Public transportation with buses, subways, and trains; roads; paved roads; airplanes; bridges; financial services (including bank accounts, ATMs, and credit cards); cities; a network of competent workers that can help you to fix problems; postal services (that delivers fast); national parks; street cleaning; public swimming pools (even private pools); firefighters; parks; online shopping; weather forecasts; and a waste management system.

Tools and technologies: Pencils, ballpoint pens, and paper; lawnmowers; cars; car mechanics; bicycles; power tools like drills (even battery-powered ones); a watch; computers and laptops; smartphones (with GPS and a good camera); being able to stay in touch with distant friends or family members (or even visiting them); GPS; batteries; telephones and mobiles; video calls; WiFi; and the internet right here.

Social services: Caretakers for those who are disabled, sick, or elderly; protection from crime; non-profit organizations financed by the public, by donations or by philanthropies; insurance (against many different risks); and a legal system with judges and lawyers that implement the rule of law.

There is also a wide range of transfer payments, which in themselves are not services (they are transfers) but which become more affordable as a society becomes more prosperous: sick leave and disability benefits; unemployment benefits; and being able to help others with a regular donation of some of your income to an effective charity . 6

Life and free time : tents; travel and holidays; surfboards; skis; board games; hotels; playgrounds; children’s toys; courses to learn hobbies (from painting to musical instruments or courses on the environment around us); a football; pets; the cinema, theater or a music concert; clothes (even comfortable and good-looking ones that keep you warm and protect you from the rain); shoes (even shoes for different purposes); shoe repair; the contraceptive pill and the ability to choose if and when to have children; sports classes from rock climbing to pilates and yoga; cigarettes (not all goods that people produce for each other are good for them); 7 a musical instrument; a camera; and parties to celebrate life.

Health and staying well: Dentists; antibiotics; surgeries; anesthesia; mental health care from psychologists and psychiatrists; vaccines; public sewage; a haircut; a massage; midwives; ambulances; modern medicine; band-aids; pharmaceutical drugs; sanitary pads; toothbrushes; dental floss (some do floss); disinfectants; glasses; sunglasses; contact lenses; hearing aids; and hospitals – including very well-equipped, modern hospitals that offer CT scans, which include intensive care units and allow heart or brain surgery or organ transplants.

Specific needs and wishes: Most of the products listed above are generally helpful to people. But often, the goods and services that are most important to one individual are very specific.

As I’m writing this, I have a big cast on my left leg after I broke it. These days, I depend on products that I had no use for just three weeks ago. To move around, I need two long crutches, and to prevent thrombosis, I need to inject a blood thinner every day. After I broke my leg, I needed the service of nurses and doctors. They had to rely on a range of medical equipment, such as X-ray machines. To get back on my feet, I might need the service of physiotherapists.

We all have very specific needs or wishes for particular goods and services. Some needs arise from bad luck, like an injury. Others are due to a new phase in life – think of the specific goods and services you need when you have a baby or when you take care of an elderly person. And yet others are due to specific interests – think of the needs of a fisherman, or a pianist, or a painter.

All of these goods and services do not just magically appear. They need to be produced. At some point in the past, the production of most of them was zero, and even the most essential ones were extremely scarce. So, if you want to know what economic growth means for your life, look at the list above.

What is economic growth?

So, how can we define what economic growth is?

A definition that can be found in so many publications that I don’t know which one to quote is that economic growth is “an increase in the amount of goods and services produced per head of the population over a period of time.”

The definition in the Oxford Dictionary is almost identical: “Economic growth is the increase in the production of goods and services per head of population over a stated period of time”. And the definition in the Cambridge Dictionary is similar. It defines growth as “an increase in the economy of a country or an area, especially of the value of goods and services the country or area produces.”

In the following footnote, you find more definitions. Bringing these definitions together and taking into account the economic literature more broadly, I suggest the following definition: Economic growth is an increase in the quantity and quality of the economic goods and services that a society produces.

I prefer a definition that is slightly longer than most others. If you want a shorter definition, you can speak of ‘products’ rather than ‘goods and services’, and you can speak of ‘value’ rather than mentioning both the quantity and quality aspects separately.

The most important change in quantity is from zero to one when a new product becomes available. Many of the most important changes in history became possible when new goods and services were developed; think of antibiotics, vaccines, computers, or the telephone.

You find more thoughts on the definition of growth in the footnote. 8

What are economic goods and services?

Many definitions of economic growth simply speak of the production of ‘goods and services’ collectively. This sidesteps a key difficulty in its definition and measurement. Economic growth is not concerned with all goods and services but with a subset of them: economic goods and services.

In everything we do – even in our most mundane activities – we continuously ‘produce’ goods and services in some form. Early in the morning, once we’ve brushed our teeth and made ourselves toast, we have already produced one service and one good. Should we count the tooth-brushing and the toast-making towards the economic production of the country we live in? The question of where to draw the line isn’t easy to answer. But we have to draw the line somewhere. If we don’t, we end up with a concept of production that is so broad that it becomes meaningless; we’d produce a service with every breath we take and every time we scratch our nose.

The line that we have to draw to define the economic goods and services is called the ‘production boundary’. The sketch illustrates the idea. The production boundary defines those goods and services that we consider when we speak about economic growth.

For a huge number of goods or services, there is no question that they are of the ‘economic’ type. But for some of them, it can be complicated to decide on which side of the production boundary they fall. One example is the question of whether the production of illegal goods should be included. Another is whether production within a household should be included – should we consider it as economic production if we grow tomatoes in our backyard and make soup from them? Different authors and different measurement frameworks have given different answers to these questions. 9

There are some characteristics that are helpful in deciding on which side of the boundary a particular product falls. 10 Economic goods and services are those that can be produced and that are scarce in relation to the demand for them. They stand in contrast to free goods, like sunlight, which are abundant, or those many important aspects in our lives that cannot be produced, like friendships. 11 Our everyday language has this right: we don’t refer to the sun or our friendships as a good or service that we ‘produce’.

An economic good or service is provided by people to each other as a solution to a problem they are faced with, and this means that they are considered useful by the person who demands it.

A last characteristic that helps decide whether you are looking at an economic product is “delegability”. An activity is considered to be production in an economic sense if it can be delegated to someone else. This would include many of the goods and services on that long list we considered earlier but would exclude your breathing, for example.

Because economic goods are scarce in relation to the demand for them, human effort is required to produce them. 12 A shorter way of defining growth is, therefore, to say that it is an increase in the production of those products that people produce for each other.

The majority of goods and services on that long list above are uncontroversially of the economic type – everything from the light bulbs and furniture in your home to the roads and bridges that connect your home with the rest of the world. They are scarce in relation to the demand for them and have to be produced by someone; their production is delegable, and they are considered useful by those who want them.

It’s worth recognizing that many of the difficulties in defining the production boundary arise from the effort to make measures of economic production as comparable as possible.

To give just one concrete example of the type of considerations that make the discussion about specific definitions so difficult, let’s look at how the production boundary is drawn in the housing sector.

Imagine two countries that are identical except for one aspect: home ownership. In Country A, everyone rents their homes, and the total sum of annual rent amounts to €2 billion per year. In Country B, everyone owns their own home, and no one pays rent. To provide housing is certainly an economic service, but if we only counted monetary transactions, then we would get the false impression that the value of goods and services in Country A is €2 billion higher than in Country B. To avoid such misjudgment, the production boundary includes the housing services that are provided without any monetary transactions. In National Accounts, statisticians take into account the “imputed rental value of owner-occupied housing” – those households who own their home get assigned an imputed rental value. In the imagined scenario, these imputed rents would amount to €2 billion in Country B so that the prosperity of people in these two countries would be judged to be identical.

It is the case more broadly that National Account figures (like GDP) do include important non-market goods and services that are not included in household survey measures of people’s income. GDP does not only include the housing services by owner-occupied housing but also the provision of most goods and services that are provided by the government or nonprofit institutions.

How can we measure economic growth?

Many discussions about economic growth are extraordinarily confusing. People often talk past one another.

I believe the key reason for this is that the discussion of what economic growth is gets muddled up with how it is measured .

While it is straightforward enough to define what growth is, measuring growth is very, very difficult.

In the worst cases, measures of growth are mixed up with a definition of growth. Growth is often measured as an increase in income or inflation-adjusted GDP per capita. But these measures are not the definition of it – just like life expectancy is a measure of population health but is certainly not the definition of population health.

To see how difficult it is to measure growth, take a moment to think about how you would measure it. How would you determine whether the quantity and quality of all economic goods and services produced by a society increased or decreased over time?

Finding a measure means that you have to find a way to express a huge amount of relevant information in a single metric. As the sketch shows, you have to first measure the quantity and quality of all the many, many goods and services that get produced and then find a way to aggregate all of these measurements into one summarizing metric. No matter what measure you propose for such a difficult task, there will always be problems and shortcomings in any proposal you might make.

In the following section, I will show four possible ways of measuring growth and present some data for each of them to see how they can inform us about the history of material living conditions.

Measuring economic growth by tracking access to particular goods and services

One possible way to measure growth is to make a list of some specific products that people want and to see what share of the population has access to them.

We do this very often at Our World in Data . The chart here shows the share of the world population that has access to four basic resources. All of these statistics measure some particular aspect of economic growth.

You can switch this chart to any country in the world via the “Change country” option. You will find that, judged by this metric, some countries achieved rapid growth – like Indonesia – while others only saw very little growth, like Chad.

The advantage of measuring growth in this way is that it is concrete. It makes clear what exactly is growing, and it’s clear which particular goods and services people gain access to.

The downside is that it only captures a small part of economic growth. There are many other goods and services that people want in addition to water, electricity, sanitation, and cooking technology. 13

You could, of course, expand this approach of measuring growth to many more goods and services, but this is usually not done for both practical and ethical considerations:

One practical reason is that a list of all the products that people value would be extremely long. Keeping lists that track people’s access to all products would be a daunting task: hundreds of different toothbrushes, thousands of different dentists, hundreds of thousands of different dishes in different restaurants, and many millions of different books. 14 If you wanted to measure growth across all goods and services in this way, you’d soon employ half the country in the statistical office.

In practice, any attempt to measure growth as access to particular products, therefore, means that you look only at a relatively small number of very particular goods and services that statisticians or economists are interested in. This is problematic for ethical reasons. It should not be up to the statisticians or economists to determine which few products should be considered valuable.

You might have realized this problem already when you read my list at the beginning of this text. You might have disagreed with the things that I put on that list and thought that some other goods and services were missing. This is why it is important to track incomes and not just access to particular goods: measuring people’s income is a way of measuring the options that they have rather than the choices that they make. It respects people’s judgment to decide for themselves what they find most important for their lives.

On our site, you find many more such metrics of growth that capture whether people have access to particular goods and services:

• This chart shows the share of US households having access to specific technologies.
• This chart shows the share that has health insurance.
• This chart shows access to schools.

Measuring economic growth by tracking the ratio between people’s income and the prices of particular goods and services

To measure the options that a person’s income represents, we have to compare their income with the prices of the goods and services that they want. We have to look at the ratio between income and prices.

The chart here does this for one particular product – books – and brings us back to the history of growth in the publishing sector that we started with. 15 Shown is the ratio between the average income that a worker receives and the price of a book. It shows how long the average worker had to work to buy one book. Note that this data is plotted on a logarithmic axis.

Before the invention of the printing press in the 15th century, the price was often as high as several months of work. The fact that books were unaffordable for almost everyone should not be surprising. It corresponds to what we’ve seen earlier that it took a scribe several months to produce a single book.

The chart also shows how this changed when the printing press increased the productivity of publishing. As the labor required to produce a book declined from many months of work to less than a day, the price fell from months of wages to mere hours.

This shows us how an innovation in technology raises productivity and how an increase in production makes it more affordable. How it increases the options that people have.

Global inequality: How do incomes compare in countries around the world?

In the previous section, we measured growth as the ratio between income and the price of one particular good. But of course, we could do the same for all the many goods and services that people want. This ratio – the ratio between the nominal income that people receive and the prices that people have to pay for goods and services – is called ‘real income’ . 16

Real income = Nominal income / price of goods and services

Real income grows when people’s nominal income increases or when the prices of goods and services decrease.

In contrast to many of the other metrics on Our World in Data, a person’s real income does not matter for its own sake but because it is a means to an end. A means to many ends, in fact.

Economic growth – measured as an increase in people’s real income – means that the ratio between people’s income and the prices of what they can buy is increasing: goods and services become more affordable, and people become less poor. It is because a person has more choices as their income grows that economists care so much about these monetary measures of prosperity.

The two most prominent measures of real income are GDP per capita and people’s incomes, as determined through household surveys.

They are shown in this chart.

Before we get back to the question of economic growth, let’s see what these measures of real income tell us about the economic inequality in the world today.

Both measures show that global inequality is very large. In a rich country like Denmark, an average person can purchase goods and services for $54 a day, while the average Ethiopian can only afford goods and services that cost $3 per day.

Both measures of real incomes in this chart are measured in international dollars, which means that they take into account the level of prices in each country (using purchasing power parity conversion factors). This price adjustment is done in such a way that one international-$ is equivalent to the purchasing power of one US-$ in the US . An income of int.-$3 in Ethiopia, for example, means that it allows you to purchase goods and services in Ethiopia that would cost US-$3 in the US . All dollar values in this text are given in international dollars, even though I often shorten it to just the $-sign.

If you are living in a rich country and you want to have a sense of what it means to live in a poor country – where incomes are 20 times lower – you can imagine that the prices for everything around you suddenly increase 20-fold. 17 If all the things you buy suddenly get 20-times more expensive your real income is 20-times lower. A loaf of bread doesn’t cost $2 but $40, a pair of jeans costs $400, and an old car costs $40,000. If you ask yourself how these price increases would change your daily consumption and your day-to-day life, you can get a sense of what it means to live in a poor country.

The two shown measures of real income differ:

• The data on the vertical axis is based on surveys in which researchers go from house to house and ask people about their economic situation. In some countries, people are asked about their income, while in other countries, people are asked about their expenditure – expenditure is income minus savings. In poor countries, these two measures are close to each other since poor people do not have the chance to save much.
• On the other hand, GDP per capita starts at the aggregate level and divides the income of the entire economy by the number of people in that country. GDP per capita is higher than per capita survey income because GDP is a more comprehensive measure of income. As we’ve discussed before, it includes an imputed rental value of owner-occupied housing and other differences, such as government expenditure.

Income as a measure of economic prosperity is much more abstract than the metrics we looked at previously. The comparison of incomes of people around the world in this scatterplot measures options, not choices. It shows us that the economic options for billions of people are very low. The majority of the world lives on very low incomes of less than $20, $10, or even $5 per day. In the next section, we’ll see how poverty has changed over time.

• GDP per capita vs. Daily income of the poorest 10%
• GDP per capita vs. Daily average income

Global poverty and growth: How have incomes changed around the world?

Economic growth, as we said before, is an increase in the production of the quantity and quality of the economic goods and services that a society produces. The total income in a society corresponds to the total sum of goods and services the society produces – everyone’s spending is someone else’s income. This means that the average income corresponds to the level of average production, so that the average income in a society increases when the production of goods and services increases.

Average production = average income

In this final section, let’s see how incomes have changed over time, first as documented in survey incomes and then via GDP per capita.

Measuring economic growth by tracking incomes as reported in household surveys

The chart shows the income of people around the world over time, as reported in household surveys. It shows the share of the world population that lives below different poverty lines: from extremely low poverty lines up to $30 per day, which corresponds to notions of poverty in high-income countries .

Many of the poorest people in the world rely on subsistence farming and do not have a monetary income. To take this into account and make a fair comparison of their living standards, the statisticians who produce these figures estimate the monetary value of their home production and add it to their income.

Again, the prices of goods and services are taken into account: these are measures of real incomes. As explained before, incomes are adjusted for price differences between countries, and they are also adjusted for inflation. As a consequence of these two adjustments, incomes are expressed in international dollars in 2017 prices, which means that these income measures express what you would have been able to buy with US dollars in the US in 201 7.

Global economic growth can be seen in this chart as an increasing share of the population living on higher incomes. In 2000 two thirds of the world lived on less than $6.85 per day. In the following 19 years, this share fell by 22 percentage points.

In 2020 and 2021 — during the economic recession that followed the pandemic — the size of the world economy declined, and the share of people in poverty increased . As soon as global data for this period is available, we will update this chart.

The data shows that global poverty has declined, no matter what poverty line you choose. It also shows that the majority of the world still lives on very low incomes. As we’ve seen, we can describe the same reality from the production side: the global production of the goods and services that people want has increased, but there is still not enough production of even very basic products. Most people in the world do not have access to them.

An advantage of household survey data over GDP per capita is that it captures the inequality of incomes within a country. You can explore this inequality with this chart by switching to see the data for an individual country via the ‘Change country’ button.

Measuring economic growth by tracking GDP per capita

GDP per capita is a broader measure of real income, and in contrast to survey income, it also takes government expenditures into account. A lot of thinking has gone into the construction of this very prominent metric so that it is comparable not only over time but also across countries. This makes it especially useful as a measure to understand the economic inequality in the world, as we’ve seen above. 18

Another advantage of this measure is that historians have reconstructed estimates of GDP per capita that go back many centuries. This historical research is an extremely laborious task , and researchers have dedicated many years of work to these reconstructions. The ‘Maddison Project’ brings together these long-run reconstructions from various researchers, and thanks to these efforts, we have a good understanding of how incomes have changed over time.

The chart shows how average incomes in different world regions have changed over the last two centuries. Looking at the latest data, you see again the very large inequality between different parts of the world today. You now also see the history of how we got here: small increases in production in some world regions and very large increases in those regions where people have the highest incomes today.

One of the very first countries to achieve sustained economic growth was the United Kingdom. In this chart, we see the reconstructions of GDP per capita in the UK over the last centuries.

It is no accident that the shape of this chart is very similar to the chart on book production at the beginning of this text – very low and almost flat for many generations and then quickly rising. Both of these developments are driven by changes in production.

Average income corresponds to average production, and societies around the world were able to produce very few goods and services in the past. There were no major exceptions to this reality. As we see in this chart, global inequality was much lower than today: the majority of people around the world were very poor.

To get a sense of what this means, you can again take the approach we’ve used to understand the inequality in the world today. When incomes in today’s rich countries were 20 times lower, it was as if all the prices around you today would suddenly increase 20-fold. But in addition to this, you have to consider that all the goods and services that were developed since then disappeared – no bicycle, no internet, no antibiotics. All that’s left for you are the goods and services of the 17th century, but all of them are 20 times more expensive than today. The majority of people around the world, including in today’s richest countries, live in deep poverty.

Just as we’ve seen in the history of book production, this changed once new production technologies were introduced. The printing press was an exceptionally early innovation in production technology; most innovations happened in the last 250 years. The starting point of this rise out of poverty is called the Industrial Revolution.

The printing press made it possible to produce more books. The many innovations that made up the Industrial Revolution made it possible to increase the production of many goods and services. Compare the effort that it takes for a farmer to reap corn with a scythe to the possibilities of a farmer with a tractor or a combined harvester, or think of the technologies that made overland travel faster – from walking on foot to traveling in a horse buggy to taking the train or car; or think of the effort it took to build those roads that the buggies once traveled on with the modern machinery that allows us to produce the corresponding public infrastructure today .

The production of a myriad of different goods and services followed trajectories very similar to the production of books – flat and low in the past and then steeply increasing. The rise in average income that we see in this chart is the result of the aggregation of all these production increases.

In the past, before societies achieved economic growth, the only way for anyone to become richer was for someone else to become poorer; the economy was a zero-sum game. In a society that achieves economic growth, this is no longer the case. When average incomes increase, it becomes possible for people to become richer without someone else becoming poorer.

This transition from a zero-sum to a positive-sum economy is the most important change in economic history (I wrote about it here ) and made it possible for entire societies to leave the extreme poverty of the past behind.

Conclusion: The history of global poverty reduction has just begun

The chart shows the global history of extreme poverty and economic growth.

In the top left panel, you can see how global poverty has declined as incomes increased; in the other eight panels, you see the same for all world regions separately. The starting point of each trajectory shows the data for 1820 and tells us that two centuries ago, the majority of people lived in extreme poverty, no matter where in the world they were at home.

Back then, it was widely believed that widespread poverty was inevitable. But this turned out to be wrong. The trajectories show how incomes and poverty have changed in each world region. All regions achieved growth – the goods and services that people need saw their production and quality increase – and the share living in extreme poverty declined. 19

This historical research was done by Michail Moatsos and is based on the ‘cost of basic needs’-approach as suggested by Robert Allen (2017) and recommended by the late Tony Atkinson. 20 The name ‘extreme poverty’ is appropriate as this measure is based on an extremely low poverty threshold. It takes us back to what I mentioned at the very beginning; this historical research tells us – as the author puts it – that three-quarters of the world "could not afford a tiny space to live, food that would not induce malnutrition, and some minimum heating capacity.”

Since then, all world regions have made progress against extreme poverty – some much earlier than others – but in particular, in Sub-Saharan Africa, the share of people living in deep poverty is still very high.

The last two centuries were the first time in human history that societies have achieved sustained economic growth, and the decline of global poverty is one of the most important achievements in history. But it is still a very long way to go.

This is what we see in this final chart. The red line shows the share of people living in extreme poverty that we just discussed. Additionally, you now also see the share living on less than $3.65, $6.85, and $30 per day. 21

The world today is very unequal, and the majority of the world still lives in poverty: 47% live on less than $6.85 per day, and 84% live on less than $30. Even after two centuries of progress, we are still in the early stages. The history of global poverty reduction has only just begun.

That the world has made substantial progress but nevertheless still has a long way to go is the case for many of the world’s very large problems. I’ve written before that all three statements are true at the same time: The world is much better, the world is awful, and the world can be much better. This is very much the case for global poverty. The world is much less poor than in the past, but it is still very poor, and it remains one of the largest problems we face.

Some writers suggest we can end poverty by simply reducing global inequality. This is not the case. I’m very much in favor of reducing global inequality, and I hope I do what I can to contribute to this. But it is important to be clear that a reduction of inequality alone would still mean that billions around the world would live in very poor conditions. Those who don’t see the importance of growth are not aware of the extent of global poverty. The production of many crucial goods and services has to increase if we want to end it. How much economic growth is needed to achieve this? This is the question I answered in this recent text .

To solve the problems we face, it is not enough to increase overall production. We also need to make good decisions about which goods and services we want to produce more of and which ones we want less of. Growth doesn’t just have a rate, it also has a direction, and the direction we choose matters – for our own happiness and for achieving a sustainable future .

I hope this text was helpful in making clear what economic growth is. It is necessary to remind ourselves of that because we mostly talk about poverty and growth in monetary terms. The monetary measures have the disadvantage that they are abstract, perhaps so abstract that we even forget what growth is actually about and why it is so important. The goods and services that we all need are not just there – they need to be produced – and economic growth means that the quality and quantity of these goods and services increase, from the food that we eat to the public infrastructure we rely on.

The history of economic growth is the history of how societies leave widespread poverty behind by finding ways to produce more of the goods and services that people need – all the very many goods and services that people produce for each other: look around you now.

Acknowledgments: I would like to thank Joe Hasell and Hannah Ritchie for very helpful comments on draft versions of this article.

Our World in Data presents the data and research to make progress against the world’s largest problems. This article draws on data and research discussed in our topic pages on Economic Inequality , Global Poverty , and Economic Growth .

Version history: In October 2023, I copy-edited this article; it was a minor update, and nothing substantial was changed.

Michail Moatsos (2021) – Global extreme poverty: Present and past since 1820. Published in OECD (2021), How Was Life? Volume II: New Perspectives on Well-being and Global Inequality since 1820 , OECD Publishing, Paris, https://doi.org/10.1787/3d96efc5-en .

At the time when material prosperity was so poor, living conditions were extremely poor in general; close to half of all children died .

Historian Gregory Clark reports the estimate that scribes were able to copy about 3,000 words of plain text per day.

See Clark (2007) – A Farewell to Alms: A Brief Economic History of the World. Clark (2007). In it, Clark quotes his earlier working paper with Patricia Levin as the source of these estimates. Gregory Clark and Patricia Levin (2001) – “How Different Was the Industrial Revolution? The Revolution in Printing, 1350–1869.”

There are about 760,000 words in the bible (it differs between various translations and languages; here is an overview of some translations).

This implies that the production of one copy of the Bible meant 253.3 days (8.3 months) of daily work.

Copying the text was not the only step in the production process for which productivity was low. The ink had to be made, parchment had to be produced and cut, and many other steps involved laborious work.

Wikipedia’s article about scribes reports sources that estimate that the production time per bible was even longer than 8 months.

Clark himself states in the same publication that “Prior to that innovation, books had to be copied by hand, with copyists on works with just plain text still only able to copy 3,000 words per day. Producing one copy of the Bible at this rate would take 136 man-days.” Since the product of 136 and 3000 is only 408,000, it is unclear to me how Clark has arrived at this estimate – 408,000 words are fewer words than in the Tanakh and other versions of the bible.

The data is taken from Eltjo Buringh and Jan Luiten Van Zanden (2009) – Charting the “Rise of the West”: Manuscripts and Printed Books in Europe, a Long-Term Perspective from the Sixth through Eighteenth Centuries. In The Journal of Economic History Vol. 69, No. 2 (June 2009), pp. 409-445. Online here .

Western Europe in this study is the area of today’s Great Britain, Ireland, France, Belgium, Netherlands, Germany, Switzerland, Italy, Spain, Sweden, and Poland.

On the history and economics of book production, see also the historical work of Jeremiah Dittmar.

I’ve relied on several sources to produce this list. One source was the simple descriptions of the consumption bundles that are relied upon for CPI measurement – like this one from Germany’s statistical office . And I have also relied on the national accounts themselves.

This list is also inspired partly by this list of Gwern and I’m also grateful for the feedback that I got via Twitter to earlier versions of this list. [ Here I shared the list on Twitter ]

This is Hans Rosling’s talk on the magic of the washing machine – worth watching if you haven’t seen it.

Of course all of these transfer payments have a service component to them, someone is managing the payment of the disability benefits etc.

Because smoking causes a large amount of suffering and death I do not find cigarettes valuable, but my opinion is not what matters for a list of goods and services that people produce for each other. Whether some good is considered to be part of the domestic product depends on whether it is a good that some people want, not whether you or I want it. More on this below.

Very similar to the definitions given above is the definition that Kimberly Amadeo gives: “Economic growth is an increase in the production of goods and services over a specific period.”

“Economic growth is an increase in the production of economic goods and services, compared from one period of time to another” is the definition at Investopedia .

Alternatively, to my definition, I think it can be useful to think of economic growth as not directly concerned with the output as such but with the capacity to produce this output. The NASDAQ’s glossary defines growth in that way: “An increase in the nation's capacity to produce goods and services.”

Wikipedia defines economic growth as follows: “Economic growth can be defined as the increase in the inflation-adjusted market value of the goods and services produced by an economy over time.” Definitions that are based on how growth is measured strike me as wrong – just like life expectancy is a measure of population health and hardly the definition of population health. I will get back to this mistake further below in this text.

An aspect that I emphasize more explicitly than others is the quality of the goods and services. People obviously do just care about the number of goods, and in the literature on growth, the measurement of changes in quality is a central question. Many definitions speak more broadly about the ‘value’ of the goods and services that are produced, but I think it is worth emphasizing that growth is also concerned with a rise in the quality of goods and services.

OECD – Measuring the Non-Observed Economy: A Handbook .

The relevant numbers are not small. For the US alone, “illegal drugs add $108 billion to measured nominal GDP in 2017, illegal prostitution adds $10 billion, illegal gambling adds $4 billion, and theft from businesses adds $109 billion” if they were to be included in the US National Accounts. This is according to the report by Rachel Soloveichik (2019) – Including Illegal Activity in the U.S. National Economic Accounts . Published by the BEA.

Ironmonger (2001) – Household Production. In International Encyclopedia of the Social & Behavioral Sciences. Pages 6934-6939. https://doi.org/10.1016/B0-08-043076-7/03964-4

Or for some longer run data on the US: Danit Kanal and Joseph Ted Kornegay (2019) – Accounting for Household Production in the National Accounts: An Update, 1965–2017 . In the Survey of Current Business.

Helpful references that discuss how the production boundary is drawn (and how it changed over time) are: Lequiller and Blades – Understanding National Accounts (available in various editions) Diane Coyle (2016) – GDP: A Brief but Affectionate History https://press.princeton.edu/books/paperback/9780691169859/gdp

The definition of the production boundary by Statistics Finland

Itsuo Sakuma (2013) – The Production Boundary Reconsidered. In The Review of Income and Wealth. Volume 59, Issue 3; Pages 556-567.

Diane Coyle (2017) – Do-it-Yourself Digital: The Production Boundary and the Productivity Puzzle. ESCoE Discussion Paper 2017-01, Available at SSRN: http://dx.doi.org/10.2139/ssrn.2986725

A more general way of thinking about free goods and services is to consider them as those for which the supply is hugely greater than the demand.

Their production, therefore, has an opportunity cost, which means that if someone obtains an economic good, someone is giving up on something for it – this can either be the person themselves or society more broadly. Free goods, in contrast, are provided with zero opportunity cost to society.

It is also the case that the international statistics on these measures often have very low cutoffs for what it means ‘to have access’; this is, for example, the case for what it means to have access to energy.

10 years ago, Google counted there were 129,864,880 different books, and since then, the number has increased further by many thousands of new books every day.

This chart is from Jeremiah Dittmar and Skipper Seabold (2019) – New Media New Knowledge – How the printing press led to a transformation of European thought . I was unfortunately not able to find the raw data anywhere and could not redraw this chart; if someone knows where this (or comparable) data can be found, please let me know.

In the language of economists, the nominal value is measured in terms of money, whereas the real value is measured against goods or services. This means that the real income is the income adjusted for inflation (it is adjusted for the changes in prices of goods and services). Thereby, it allows comparisons that tell us the quantity and quality of the goods and services that people were able to purchase at different points in time.

I learned this way of thinking about it from Twitter user @Kirsten3531, who responded with this idea to a tweet of mine here https://twitter.com/Kirsten3531/status/1389553625308045317

We’ve discussed one such consideration that is crucial for comparability when we consider how to take into account the value of owner-occupied housing.

Whether economic growth translates into the reduction of poverty depends not only on the growth itself but also on how the distribution of income changes. The poverty metrics shown in this chart and in previous charts take both of these aspects – the average level of production/income and its distribution – into account.

Jutta Bolt and Jan Luiten van Zanden (2021) – The GDP data in the chart is taken from The Long View on Economic Growth: New Estimates of GDP, How Was Life? Volume II: New Perspectives on Well-being and Global Inequality since 1820 , OECD Publishing, Paris, https://doi.org/10.1787/3d96efc5-en .

The latest data point for the poverty data refers to 2018, while the latest data point for GDP per capita refers to 2016. In the chart, I have chosen the middle year (2017) as the reference year.

The ‘cost of basic needs’-approach was recommended by the ‘World Bank Commission on Global Poverty’, headed by Tony Atkinson, as a complementary method in measuring poverty.

The report for the ‘World Bank Commission on Global Poverty’ can be found here .

Tony Atkinson – and, after his death, his colleagues – turned this report into a book that was published as Anthony B. Atkinson (2019) – Measuring Poverty Around the World. You find more information on Atkinson’s website .

The CBN-approach Moatsos’ work is based on what was suggested by Allen in Robert Allen (2017) – Absolute poverty: When necessity displaces desire. In American Economic Review, Vol. 107/12, pp. 3690-3721, https://doi.org/10.1257/aer.20161080 .

Moatsos describes the methodology as follows: “In this approach, poverty lines are calculated for every year and country separately, rather than using a single global line. The second step is to gather the necessary data to operationalize this approach alongside imputation methods in cases where not all the necessary data are available. The third step is to devise a method for aggregating countries’ poverty estimates on a global scale to account for countries that lack some of the relevant data.” In his publication – linked above – you find much more detail on all of the shown poverty data. The speed at which extreme poverty declined increased over time, as the chart shows. Moatsos writes, “It took 136 years from 1820 for our global poverty rate to fall under 50%, then another 45 years to cut this rate in half again by 2001. In the early 21st century, global poverty reduction accelerated, and in 13 years, our global measure of extreme poverty was halved again by 2014.”

These are the same global poverty estimates – based on household surveys – we discussed above.

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Harvard International Economics

Essay contest (hieec).

HIEEC provides students the opportunity to demonstrate an accomplished level of writing and understanding of economic theory. Through the contest, students hone their academic and professional skills and exhibit their knowledge. 

HIEE C 202 3 -2024

Hieec 2023-2024 is now closed. .

The 2023-2024  Harvard International Economics Essay Contest is sponsored by the Harvard Undergraduate Economics Association (HUEA). This essay competition is open to high school studen ts of any year and is a fantastic opportunity to demonstrat e an accom plished level of writing and understanding of economic the ory. T hrough the contest, student competitors hone their academic and professional skills and exhibit their knowledge to future employers and academic programs. 

Competitors must construct a convincing argument using economic theory and real-world examples. Winning essays will be published on our website  and will be available for the greater Harvard community to read. Essays should focus on argumentation supported with facts and references, although data-based support is also welcome.

Yiheng Lyu​

Audrey Ku k​

Hyoungjin Jin

Juyoung Chun

Kevin Zhang

Matthew Choi

Mikayil Sadikhov

Raunak Agarwal

Vallabh Himakunthala

Highly Commended

Aronima Biswas

Aryan Nangia

Kridaya Gupta

Leonardo Jia

Rohan Mathur

Anagha Chakravarti

Amberlynn Gong

Neha Shanavas

Donghyeon Oh

2023-2024  Essay Questions

Advances in artificial intelligence (AI) have the potential to affect growth, inequality, productivity, innovation, and employment. OpenAI’s ChatGPT, in particular, has greatly increased public awareness about the significance of AI and its implications for the future. What impact will the development of AI have on economic inequality, the composition of the workforce, and economic output as a whole? How can nations prepare for the micro and macroeconomic changes brought about by AI?

Measuring national and global economic activity allows us to understand how economies change in size and structure—how they grow and contract. In addition to Gross Domestic Product (GDP), government budgets, and the money supply, alternatives like the Human Development Index (HDI) and Gross National Income (GNI) are used to assess economic progress. What are the advantages of our current economic indices, including GDP, HDI, GNI, government budgets, and the money supply, and in what areas are they lacking? Which of these indices do you find most helpful, and how can we enhance or combine them to improve our understanding of economic measurement?

Proponents of income redistribution support the idea that redistribution policies will increase economic stability and give more opportunities to the less wealthy. Others, however, are more skeptical and believe it could have negative consequences for economic growth. Current methods of redistribution include taxation, welfare, public services, and other monetary policies. What strategies for income redistribution should the U.S. adopt from other countries? What economic impacts could a wealth tax or super millionaire tax have? What type of redistribution is most effective and feasible? What would be the impacts of the U.S. enacting universal basic income? Discuss the implications of any of these issues and feel free to expand on other areas of economic redistribution.

As the United States weighs the impacts of China’s rise to global prominence, economics and national security have become increasingly intertwined. As a result, the United States government has imposed both tariffs and investment restrictions on China to limit the nation’s access to both US markets and intellectual property (specifically in sensitive industries such as semiconductors). What are the economic implications of these policies for United States firms, consumers, and workers? Discuss the most important perspectives of the US-China trade war and provide suggestions on how both countries can manage the prospect of a changing economic order.

2nd November 2023 – Essay titles released

11:59pm EST 5th January 2024  – Essay submission deadline

Late February 2024*  – Highly Commended and Finalists notified

Early March 2024 * – Winners notified, results published on the website

*We received a high volume of submissions, therefore we anticipate  that it will take us a couple m ore w eeks to release the results. 

Entrants must choose one of the four prompts and write a response to it with a strict limit of 1500 words. Submission must be via the HUEA website and entrants are limited to submitting one essay with only the first submission being considered. Each essay submission will have a $20 reading fee which should be paid upon submission of the essay. If this fee will impose a significant financial burden on your family, please email us. The deadline for submitting the essay is 11:59pm EST January 5th, 2024. ​

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*Be sure to read all the details in the submission form carefully before submitting, as failure to complete any of the steps correctly may result in your submission not being considered.

The essays will be judged by the board of the HUEA, with the top 10 submissions being adjudicated by the esteemed Harvard professor and 2016 Economics Nobel Prize winner Oliver Hart.

The top three winning essays will be published ( with the author’s permission) on our website. A finalist s list of the top  submissions will be published online and adjudicated by 2016 Economics Nobel Prize Winner Oliver Hart. A list of names that will receive the "Highly Commended" distinction will also be published online​. The judges' decisions are final.

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The word limit of 1500 must be strictly adhered to. Any words past the limit will be truncated. This limit excludes references, footnotes, titles, headers and footers.

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Past Winners

2022  prompts an d winners.

In recent years and decades, many countries have seen fertility rates drop, potentially leading to falling populations. Currently, China has a fertility rate of 1.3, one of the lowest in the world. However, in 2021, China experienced GDP growth of 8% with output totaling $17.7 trillion. Will this lowered fertility rate (with potential to fall further) affect China’s economic growth and policy? How so? What, if anything, can the Chinese government do to limit the risk of falling fertility rates?

U.S. mortgage rates recently passed 7%, making the purchase of a new home increasingly unaffordable. Meanwhile, the United States has suffered from a chronic shortage of available housing for decades, particularly in urban areas, leading to what many scholars and advocates call an affordability crisis. Why is housing so unaffordable in the U.S.? What can (or should) be done by private actors, state and local governments, and the federal government to alleviate the affordability crisis?

It is often suggested that a tradeoff exists between economic growth and the health of the environment, especially now as the threat of climate change becomes more dire. What economic risks does a changing climate pose? Can economic growth be consistent with a healthy environment? What policies, either market-based or otherwise, should governments enact to protect the environment while posing the least danger to economic efficiency? 

Central banks such as the Federal Reserve in the U.S. and the Bank of England in the UK manage their nation’s macroeconomies with the goal of ensuring price stability and maximum employment. Globally, inflation rates are rising to levels not seen since the 1980s, particularly in the U.S. and European countries. To what extent should the monetary policies of central banks in various Western countries differ or resemble one another as a reaction to the specific causes of inflation facing their economies?

​ Click below to view each winner's essay

Ashwin t elang  *   nanxi jiang   *   duncan wong, 2019 wi n ner.

https://www.economicsreview.org/post/when-is-one-choice-one-t oo-many

2020 Winners

https://www.economicsreview.org/post/covid-19-and-the-market

https://www.economicsreview.org/post/automation-and-jobs-this-time-is-different

https://www.economicsreview.org/post/making-rational-decisions

News from the Columbia Climate School

How Climate Change Impacts the Economy

The Fourth National Climate Assessment , published in 2018, warned that if we do not curb greenhouse gas emissions and start to adapt, climate change could seriously disrupt the U.S. economy. Warmer temperatures, sea level rise and extreme weather will damage property and critical infrastructure, impact human health and productivity, and negatively affect sectors such as agriculture, forestry, fisheries and tourism. The demand for energy will increase as power generation becomes less reliable, and water supplies will be stressed. Damage to other countries around the globe will also affect U.S. business through disruption in trade and supply chains.

A recent report  examined how climate change could affect 22 different sectors of the economy under two different scenarios: if global temperatures rose 2.8˚ C from pre-industrial levels by 2100, and if they increased by 4.5˚ C. The study projected that if the higher-temperature scenario prevails, climate change impacts on these 22 sectors could cost the U.S. $520 billion each year. If we can keep to 2.8˚ C, it would cost $224 billion less. In any case, the U.S. stands to suffer large economic losses due to climate change, second only to India, according to another study .

We are already seeing the economic impacts of the changing climate. According to Morgan Stanley, climate disasters have cost North America $415 billion in the last three years, much of that due to wildfires and hurricanes.

In 2017, Texas’s estimated losses from Hurricane Harvey were $125 billion; Hurricane Sandy caused about $71 billion of damages in 2012. And while it’s not yet possible to directly link climate change to hurricanes, warmer temperatures and higher sea levels are known to enhance their intensity and destructiveness.

“Science advances also give us more detailed spatial information to say which assets and operations are in harm’s way with climate change—for example say, just how many buildings will be inundated due to sea level rise,” said climatologist Radley Horton, associate research professor at Lamont-Doherty Earth Observatory. But the indirect economic impacts may be felt long before an actual disaster.

“For example, it’s not just whether a building is underwater or not,” he said. “What’s important are the harder-to-define things like when does societal risk perception shift? It may be that buildings lose their value before the water actually arrives, once people realize that eventually the water’s going to arrive. We need deeper thinking about the interconnection between physical and social systems.”

Here are some of the many ways that climate change will likely affect our economy, both directly and indirectly.

Agriculture

The sector most vulnerable to climate risk is agriculture.

Environmental economist Geoffrey Heal, a professor in the Columbia Business School, explained that although agriculture makes up a fairly small part of the total U.S. economy, “locally these effects could be big. There are about a dozen states in the Midwest that are very dependent on agriculture and they could take quite a big hit.”

They already have. Extreme rainfall events have increased 37 percent in the Midwest since the 1950s, and this year, the region has experienced above normal amounts of rain and snowmelt that have caused historic flooding.

Many fields have washed away and livestock have drowned; Nebraska alone lost $440 million worth of cattle, and as of March, Iowa had suffered $1.6 billion in losses.

The National Oceanic and Atmospheric Administration (NOAA) expects the coming months to bring even more flooding, which could impact our food supply. To date, farmers have only planted 67 percent of their corn crop compared to last June, when they had planted 96 percent. This lost yield could cause prices for animal feed and ethanol to rise, and potentially disrupt marketplaces at home and abroad. As a result of climate change impacts, the Midwest is projected to lose up to 25 percent of its current corn and  soybean yield by 2050.

In addition to flooding, increased heat and drought will likely reduce crop yields. According to a 2011  National Academy of Sciences report , for every degree Celsius the global thermostat rises, there will be a 5 to 15 percent decrease in overall crop production. Many commodity crops such as corn, soybean, wheat, rice, cotton, and oats do not grow well above certain temperature thresholds. In addition, crops will be affected by less availability of water and groundwater, increased pests and weeds, and fire risk. And as farmers struggle to stay afloat by finding ways to adapt to changing conditions, prices will likely increase and be passed along to consumers.

Infrastructure

Much of our society’s critical infrastructure is at risk from flooding. “Sea level rise could potentially cause a loss of value of assets in the trillions of dollars—probably anywhere from two to five trillion dollars—by the end of the century,” said Heal. “That’s loss from damage to housing, damage to airports on the coasts, damage to docks, the railway line that runs up and down the East Coast all of which is within a few feet of sea level, damage to I-95 which runs also along the coast. And that’s just the East Coast. If you take a global perspective, this is repeated around the world.” Much of this infrastructure will likely need to be repaired or replaced.

Military bases are also vulnerable. According to a  2016 report published by the Center for Climate and Security policy institute, sea level rise could flood parts of military bases along the East and Gulf coasts for up to three months a year as soon as 2050. Inland military installations near rivers are also vulnerable, because they can overflow with heavy precipitation, which is expected to become more common as the atmosphere warms. Extreme weather will necessitate more maintenance and repair for runways and roads, infrastructure and equipment.

In addition, our communication systems will be affected. A 2018 study   found that over 4,000 miles of fiber optic cable as well as data centers, traffic exchanges and termination points — the lifeblood of the global information network — are at risk from sea level rise. According to NOAA’s sea level rise projections, this infrastructure could be underwater by 2033 because most of it is buried along highways and coastlines. When it was built 25 years ago, climate change was not a concern, so while the cables are water resistant, they are not waterproof. New York, Miami and Seattle and large service providers including CenturyLink, Intelliquent and AT&T are most at risk. Threats to the internet infrastructure could have huge implications for businesses in the U.S.

Human health and productivity

If temperatures rise 4.5˚ C by 2090, 9,300 more people will die in American cities due to the rising heat. The annual losses associated with extreme temperature-related deaths alone are projected to be $140 billion.

Increasing warmth and precipitation will also add to the risk of waterborne and foodborne diseases and allergies, and spur the proliferation of insects that spread diseases like Zika, West Nile, dengue and Lyme disease into new territories. Extreme weather and climate-related natural disasters can also exacerbate mental health issues. The most vulnerable populations, such as the elderly, children, low-income communities and communities of color, will be most affected by these health impacts.

Temperature extremes are also projected to cause the loss of two billion labor hours each year by 2090, resulting in $160 billion of lost wages. Because of heat exposure, productivity in the Southeast and Southern Great Plains regions is expected to decline by 3 percent, and some counties of Texas and Florida could lose more than 6 percent of labor hours each year by 2100. According to a 2014 Rhodium Group study, the largest climate change-related economic losses in the U.S. will be from lost labor productivity.

Two billion dollars could be lost in winter recreation due to less snow and ice. For example, rapid warming in the Adirondack Mountains could decimate the winter activity sector, which makes up 30 percent of the local economy.

In addition, as water temperatures increase, water quality could suffer due to more frequent and more intense algae blooms, which can be toxic, thus curtailing recreational water activities and freshwater fishing. More frequent and severe wildfires will worsen air quality and discourage tourism. Sea level rise could submerge small islands and coastal areas, while deforestation and its destructive impacts on biodiversity could make some tourist destinations less attractive.

Businesses and the financial market

Climate change and its impacts across the globe will threaten the bottom line of businesses in a variety of ways. The frequency and intensity of extreme weather, both in the U.S. and in other countries, can damage factories, supply chain operations and other infrastructure, and disrupt transport. Drought will make water more expensive, which will likely affect the cost of raw materials and production. Climate volatility may force companies to deal with uncertainty in the price of resources for production, energy transport and insurance. And some products could become obsolete or lose their market, such as equipment related to coal mining or skiing in an area that no longer has snow.

Whether in the U.S. or abroad, new regulations such as carbon pricing and subsidies that favor a competitor may affect a business’s bottom line. A company’s reputation could also suffer if it’s seen as doing something that hurts the environment. And investors and stakeholders are increasingly worried about the potential for “stranded assets”—those that become prematurely obsolete or fall out of favor, and must be recorded as a loss, such as fossil fuels that many believe should stay in the ground or real estate in a newly designated flood plain.

In 2018, the Carbon Disclosure Project asked more than 7,000 companies to assess their financial risks from climate change. The CDP found that, unless they took preemptive measures, 215 of the world’s 500 biggest companies could lose an estimated one trillion dollars due to climate change, beginning within five years. For example, Alphabet (Google’s parent company) will likely have to deal with rising cooling costs for its data centers. Hitachi Ltd.’s suppliers in Southeast Asia could be disrupted by increased rainfall and flooding. Some companies have already been impacted by climate change-related losses. Western Digital Technologies, maker of hard disks, suffered enormous losses in 2011 after flooding in Thailand disrupted its production.

PG&E became liable for fire damages and had to file for bankruptcy after its power lines sparked California’s deadliest wildfire last fall. And GE cost its investors $193 billion between 2015 and 2018 because it overestimated demand for natural gas and underestimated the transition to renewable energy.

“The movement away from fossil fuels will have a big impact which could affect banks and investment firms that have relationships with the fossil fuel industry,” said Heal. “For example, the stock market value of the U.S. coal industry in 2011 was something like $37 billion. Today it’s about $2 billion. So anybody that lent a lot of money to the coal industry 10 years back would be in trouble. One of the things worrying those in the financial field is that this could happen to the oil and gas industry. So people who have invested in them or lent money to them are potentially at risk.”

Climate change and opportunity

The good news is that climate change also presents business opportunities. The Carbon Disclosure Project reported that 225 of the world’s 500 biggest companies believe climate change could generate over $2.1 trillion in new business prospects.

There will be more opportunity in clean energy, resilient and green buildings, and energy efficiency. Hybrid and electric vehicle production and the electric public transit sector are expected to grow. Construction of green infrastructure and more resilient coastal infrastructure could create many new jobs. Carbon capture and sequestration and uses of captured CO2  present opportunities, especially in light of the new 45Q federal tax credits. In addition, there are forward-thinking new businesses—witness the dramatic rise of Beyond Meat, the company selling plant-based burgers at Carl’s Jr. and A&W.

As the Arctic sea ice melts, new shipping lines will open up for trade, substantially cutting transport time. The warming Arctic could also offer more prospects for oil and gas drilling. Weather satellites and radar technology will be in demand to monitor extreme weather. Air conditioning and cooling products will be needed around the world. Biotech companies are developing new crops that are resistant to climate change impacts. Pharmaceutical companies expect increased demand for drugs to combat diseases such as malaria and dengue and other infectious diseases. And the market for military equipment and private security services may expand because the scarcity of resources could trigger civil unrest and conflict.

What individuals, businesses and governments can do to protect themselves

How much climate change will hurt the economy depends on what measures we take to adapt to and prepare for it.

Individuals

Individuals need to consider the implications of climate change when choosing where to spend and invest their money. And be aware that while a particular risk may not seem to be factored into prices yet, things could turn on a dime when the realization of risk sinks in, resulting in a massive redistribution of wealth. So it’s best not to buy or move to an area near wild lands, which have a higher risk of wildfires. Don’t move into a flood zone or buy real estate in an area that’s vulnerable to sea level rise. And in any case, purchase flood and fire insurance, and diversify your investments.

Individuals should also think about different opportunities in terms of new places that people are moving to. And, if possible, people who work outdoors in construction, agriculture or tourism should consider alternative jobs within the sector or new industries to work in.

Businesses and financial entities

Businesses need to scrutinize their operations carefully. “There’s a groundswell towards the view that any companies that fail to study their exposure to extreme weather and fail to disclose the types of vulnerabilities, including indirect ones, are going to have a hard time in the future,” said Horton. “Are companies looking at what’s coming down the road and making strategies to deal with it? I think investors are going to demand that and the companies that don’t do that are going to have trouble getting underwriting, getting infrastructure funded by the Moody’s of the world, and getting insurance.” He added that he’s seen a change in the last three or four years in what his students are demanding and believes that young people in the future will not work for companies that are not thinking about climate change.

Banks and funds need to analyze where their investments are and see if they are vulnerable to climate change. Have they invested in someone who has coastal property, or given a loan to a fossil fuel company or in agriculture operations that might be affected by climate change? Sixty-three percent of financial risk managers surveyed now believe climate change is a major concern. As a result, “The total value of funds that have integrated environmental, social and governance factors into their investment process has more than quadrupled since 2014, rising to $485 billion as of April,” reported the Wall Street Journal .

Governments

Governments should proactively think about the risks their communities face before disaster strikes.

They should be investing in resiliency measures such as hardening infrastructure, improving water resources, building redundancy into important systems, moving people out of harm’s way and improving health care services. “You want to do it before the disaster but you also need to be cognizant that the only time people will listen seems to be right after a disaster,” said Horton. “Those are also the times when money’s available to rebuild.”

Government leaders are currently debating whether the country can afford the Green New Deal (an ambitious plan to address climate change) or something like it. The question should be, ‘can we afford not to afford it?’ Nobel Prize-winning economist Joseph Stiglitz, a professor at Columbia University, wrote in an op ed , “We will pay for climate breakdown one way or another, so it makes sense to spend the money now to reduce emissions rather than wait until later to pay a lot more for the consequences… It’s a cliché, but it’s true: An ounce of prevention is worth a pound of cure.”

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Degrowth is the most effective solution. Eco-sufficiency and life quality are more important than profit maximization. Please read https://www.degrowth.info or https://en.wikipedia.org/wiki/Degrowth

how os quality of life gonna go up when people have less resources from degrowth

Don’t state the obvious. You said the quite part out loud.

Well, many people will have the chance to grow and adapt, making this obvious statment stupid. Many have already died, and many more will, but we can eventually get better. I don’t have much faith though.

Hey there, this was a very informative and we’ll written article. Thank you kindly

Right. Helps a lot in an essay!

I used this for a essay and this helped a lot! Thanks!

Hello, This is a big problem economically and globally. Climate change has impacted us in so many ways.

https://www.cbsnews.com/video/climate-refugees-the-quest-for-a-haven-from-extreme-weather-events/#x

Is this all rights reserved? Can I use some info from here?

why was this made, and how the hell does texas have enough buildings to cost 71 billion dollars in damages.

because they built buildings

To Renee Cho,

I first want to start off by saying thank you for sharing your knowledge of this subject with the world. It’s extremely important to share these types of ideas publicly, and it’s helpful when trying to formulate an opinion on this subject when you aren’t an expert on it.  I agree with your article. I think Climate change, if not dealt with, can have a bigger effect on our lives than we often think. Yes, the climate and earth would suffer, but so will our economy in the years leading up to the point of no return. The damage to the supply chain and factories, which you mentioned, is a huge deal. If our supply can’t withstand the strength of the demand in the future, then we will have more problems than just climate change. Because of the genera; nature of the market however, businesses will start to see that renewable energy is more profitable, and the market will start to shift. If fossil fuels become obsolete, companies wont run the risk of receiving a bad reputation for using them. I hope that this is what our economy will look like soon, instead of companies holding onto fossil fuels and other things that are harmful to our earth. They can’t make money if the world isn’t safe to make it on.  Another thing I found interesting is how instead of just focusing on what businesses need to do to mitigate this issue, you also target the individual consumer. Individuals play a big part in the market and economic health, so the choices they make can really make a difference in how climate change affects our economy.  Everyone needs to read this article, or articles like this; it’s crucial that you understand how not only the world is affected by this issue, but how you as an individual are affected as well. 

Can i use the above stated information for an article to be published in our college Magazine

This article is great! very informative can i use some of the content for my assignment?

All people must start to learn to control and reduce emission of greenhouse gases.

This was incredibly helpful, thank you!!

I like the article! it’s very descriptive.

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Economics Essay Examples

Ace Your Essay With Our Economics Essay Examples

Published on: Jun 6, 2023

Last updated on: Jan 31, 2024

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Are you struggling to understand economics essays and how to write your own?

It can be challenging to grasp the complexities of economic concepts without practical examples.

But don’t worry! 

We’ve got the solution you've been looking for. Explore quality examples that bridge the gap between theory and real-world applications. In addition, get insightful tips for writing economics essays.

So, if you're a student aiming for academic success, this blog is your go-to resource for mastering economics essays.

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What is an Economics Essay?

An economics essay is a written piece that explores economic theories, concepts, and their real-world applications. It involves analyzing economic issues, presenting arguments, and providing evidence to support ideas. 

The goal of an economics essay is to demonstrate an understanding of economic principles and the ability to critically evaluate economic topics.

Why Write an Economics Essay?

Writing an economics essay serves multiple purposes:

• Demonstrate Understanding: Showcasing your comprehension of economic concepts and their practical applications.
• Develop Critical Thinking: Cultivating analytical skills to evaluate economic issues from different perspectives.
• Apply Theory to Real-World Contexts: Bridging the gap between economic theory and real-life scenarios.
• Enhance Research and Analysis Skills: Improving abilities to gather and interpret economic data.
• Prepare for Academic and Professional Pursuits: Building a foundation for success in future economics-related endeavors.

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If you’re wondering, ‘how do I write an economics essay?’, consulting an example essay might be a good option for you. Here are some economics essay examples:

Short Essay About Economics

A Level Economics Essay Examples

Here is an essay on economics a level structure:

Band 6 Economics Essay Examples

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Economics essay pdf

Economics essay introduction

Economics Extended Essay Examples

In an economics extended essay, students have the opportunity to delve into a specific economic topic of interest. They are required to conduct an in-depth analysis of this topic and compile a lengthy essay. 

Here are some potential economics extended essay question examples:

• How does foreign direct investment impact economic growth in developing countries?
• What are the factors influencing consumer behavior and their effects on market demand for sustainable products?
• To what extent does government intervention in the form of minimum wage policies affect employment levels and income inequality?
• What are the economic consequences of implementing a carbon tax to combat climate change?
• How does globalization influence income distribution and the wage gap in developed economies?

IB Economics Extended Essay Examples 

IB Economics Extended Essay Examples

Economics Extended Essay Topic Examples

Extended Essay Research Question Examples Economics

Tips for Writing an Economics Essay

Writing an economics essay requires specific expertise and skills. So, it's important to have some tips up your sleeve to make sure your essay is of high quality:

• Start with a Clear Thesis Statement: It defines your essay's focus and argument. This statement should be concise, to the point, and present the crux of your essay.
• Conduct Research and Gather Data: Collect facts and figures from reliable sources such as academic journals, government reports, and reputable news outlets. Use this data to support your arguments and analysis and compile a literature review.
• Use Economic Theories and Models: These help you to support your arguments and provide a framework for your analysis. Make sure to clearly explain these theories and models so that the reader can follow your reasoning.
• Analyze the Micro and Macro Aspects: Consider all angles of the topic. This means examining how the issue affects individuals, businesses, and the economy as a whole.
• Use Real-World Examples: Practical examples and case studies help to illustrate your points. This can make your arguments more relatable and understandable.
• Consider the Policy Implications: Take into account the impacts of your analysis. What are the potential solutions to the problem you're examining? How might different policies affect the outcomes you're discussing?
• Use Graphs and Charts: These help to illustrate your data and analysis. These visual aids can help make your arguments more compelling and easier to understand.
• Proofread and Edit: Make sure to proofread your essay carefully for grammar and spelling errors. In economics, precision and accuracy are essential, so errors can undermine the credibility of your analysis.

These tips can help make your essay writing journey a breeze. Tailor them to your topic to make sure you end with a well-researched and accurate economics essay.

To wrap it up , writing an economics essay requires a combination of solid research, analytical thinking, and effective communication. 

You can craft a compelling piece of work by taking our examples as a guide and following the tips.

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• Social Sciences /

Lifelines of National Economy

• Updated on  
• Jul 27, 2021

A strong transportation and communication network plays an imperative role in building a prosperous nation. There are multifarious benefits of ensuring the development of advanced systems of transportation and communication in a country as they not only connect the varied regions and states as well as people through a smooth network but also significantly contribute to the economy as well. The 7th chapter of Class 10 Social Science is focused on the essential lifelines of the national economy, i.e. its transportation and communication networks like roadways, railways, waterways, airways, seaports, and pipelines, etc. as well as modes of communication and how they contribute to the economy. This blog summarizes this chapter and its key pointers which you must cover while studying this topic.

This Blog Includes:

Golden quadrilateral super highways, national highways, state highways, district roads, other roads, border roads, classification of the road network in india: construction material, national waterways, inland waterways, communication, international trade, tourism as trade, lifelines of national economy slideshare, lifelines of national economy mcq.

Lifelines of National Economy Class 10 PDF

India has one of the largest road networks in the world. Roads play a crucial role in ensuring the economic progress of our country. The expanse of the road network in the country is around 54.7 lakh km. Here are a few reasons why roads are considered more important than other modes of transportation:

• The construction cost of roads is much cheaper when compared with laying railway tracks.
• Roads can be easily laid to cover geographically remote locations, unlike railways.
• Movement of goods and travelling on roads is economical.
• Roads can reach the steep slopes of the Himalayas and other hilly terrains.
• Roads offer end-to-end connectivity.
• Roads offer last-mile connectivity to airports, railway stations, and seaports.

Classification of the Road Network in India: Geographical Location

The road network in India is classified on the basis of geographical location and capacity. Majorly they are divided into six different types depending on their purpose and capacity.

Studying the chapter on Lifelines of National Economy, you will get to know about the Golden Quadrilateral Super Highways which is a network of highways that connect the top four metropolitan cities of the country namely – Delhi, Mumbai, Kolkata, and Chennai. The construction and maintenance of these highways are carried out by the NHAI (National Highways Authority of India).

The National Highways are the next big network of roads. These are maintained by the CPWD (Central Public Works Department). The historical Sher-Shah Suri Marg that runs between Delhi and Amritsar is known as National Highway No.1. Each national highway is assigned a unique numerical code.

As the name implies, these roads are under the purview of each state government. They link a state capital with district capitals and are constructed and maintained by the SPWD (State Public Works Department).

These roads connect the district headquarters with other towns and villages in the district. They are constructed and maintained by the Zilla Parishad as stated in Lifelines of National Economy. 

Rural roads connecting rural villages with nearby towns fall under this category. These roads receive grants under the PMGSY (Pradhan Mantri Gramin Sadak Yojana) for maintenance and construction.

These are the roads that lie on India’s borders connecting our country with our neighbours. The Border Roads Organisation was established in 1960 for the construction and maintenance of strategic roads in the north-eastern and northern border states.

Related Read: The Rise of Nationalism in Europe Class 10 Study Notes

Apart from the classification of roads with respect to their geographical location, the chapter titled Lifelines of a National Economy also has also another category of road networks on the basis of construction material. The classification of roads as per the construction material used is as follows:

• Metalled Roads – These are all-season roads and are made of concrete, cement, or bitumen of coal.
• Unmetalled Roads – These roads do not withstand the rainy season.

Next to the roadways, railways are the major mode of transportation in India. Railways not only ply passengers but also carry tons of bulky goods on long and short distances. Railways have always occupied a major role in the nation’s economy. However, there are certain troubles plaguing rail transport and the key issues faced by railways are:

• It is difficult to lay railway tracks on sandy plains.
• Construction of bridges is required for laying railway tracks across river beds.
• In the hilly terrain of the Indian peninsula, railway tracks are laid via low hills, tunnels or gaps.
• Construction of railway lines in the Himalayan mountainous region is unfavourable due to several factors like – sparse population, uneven terrain, and lack of economic opportunities.

Pipelines are a large network of pipes that usually run underground. This network is used to transport and distribute crucial fluids like – water, petroleum, crude oil, natural gas to thermal power plants, and fertilizer factories. Even solids are transported via the underground pipeline network, by converting it into a slurry. The three important pipelines in the country as mentioned in Lifelines of National Economy:

• From Hazira in Gujarat to Jagdishpur in Uttar Pradesh
• From Salaya in Gujarat to Jalandhar in Punjab
• From the oil fields in upper Assam to Kanpur in Uttar Pradesh

Waterways are used for transporting bulky and heavy goods. They are the cheapest modes of transportation and offer several advantages like – fuel-efficiency and eco-friendly. As per the chapter on Lifelines of National Economy, here are the types of national waterways-

There are five national waterways in India. They are:

The major inland waterways in the country are Zuari and Cumberjua, Mandavi, Sunderbans, the backwaters of Kerala and Barak.

The bulk of India’s foreign trade is carried from its major seaports. There are two major and 200 minor/intermediate (notified non-majors) ports in India. The major ports are that can be counted as one of the lifelines to the national economy are:

• Kandla in Kutch is the first port to be built post-independence. It is also called the Deendayal Port.
• Mumbai is the biggest port in India. It’s a natural port and has a well-sheltered harbour.
• Chennai port has a long history and is one of the oldest artificial ports in the country. 
• Kolkata is an inland river port.
• Mangalore port in Karnataka is one of the major exporters of iron ore.
• Mormugao port in Goa is another premier port that exports iron ore.
• Paradip port, Odisha is another exporter of iron ore.
• Kochi, Kerala is the south-westernmost port in India and is situated at the entrance of a backwater lagoon.
• Tuticorin port, Tamil Nadu is the south-easternmost port in India.
• Visakhapatnam is one of the well-protected ports in the country. It is a landlocked port.
• Haldia port is a subsidiary port and was developed to relieve the pressure on Kolkata port.

Amongst the pivotal lifelines of the National Economy, Airways correspond to the Air-based mode of transport. It is a modern, fast, comfortable and prestigious mode of transport in India. Development of airways has opened the access to difficult to reach areas like – hilly terrains, dense forests and dreary deserts. Air transport in India was nationalized in 1953. Air India is the national carrier and offers both domestic and international air services. Today, there are several private players in the air transport sector.

Pawan Hans Helicopters Ltd offers helicopter services to ONGC (Oil and Natural Gas Corporation) to reach offshore operations centres and other difficult and inaccessible terrains.

The major modes of communication in our country are as stated in the chapter on lifelines of the national economy are television, press, radio, films, etc.

• The Indian postal network is the biggest postal network in the world. Besides personal written communications, it also offers parcel services. Envelopes and cards are considered first-class mail and are airlifted between stations. Journals, periodicals, and magazines are considered second-class mail and are sent via land and water transport.
• India has one of the largest telecom networks in Asia. Mass communication in India is used for entertainment as well as to create awareness of national policies and programs. The major modes of mass communication in India are newspapers, magazines, televisions, radio, films, and books.
• The national radio channel – Akashwani broadcasts in national, regional, and local languages.
• Doordarshan is the national television channel and broadcasts in national, regional, and local languages.
• In India, newspapers are published in over 100 languages.

Check Out: Streams After 10th

The exchange of goods and services between the two countries is known as international trade. The lesson on lifelines of national economy states that international trade is one of the crucial economic parameters. Goods sent out from the country are known as exports and goods brought into the country are known as import.

The major commodities exported from India include jewellery and gems, agriculture and allied products, chemicals, etc. The major commodities imported to India include electronics, machinery, petroleum and crude products, gems and jewellery, base metals, etc. Trade balance is the difference between export and import.

• When exports exceed imports, it is termed as a favourable trade balance.
• When imports exceed exports, it is known as the unfavourable trade balance.

The final section in the chapter on the Lifelines of National Economy deals with the importance of the tourism sector. In India, more than 15 million people are a direct part of the tourism sector. Tourism in India helps in:

• Promoting national integration
• Providing support to local handicrafts
• Promoting understanding about Indian heritage and culture

Foreign tourists visit India for eco-tourism, adventure tourism, heritage tourism, cultural tourism, business tourism, and medical tourism.

• Lifelines of National Economy Class 10 MCQ Question 1. What is the name given to the International Airport at Kolkata? (a) Jawaharlal Nehru (b) Meenambakkam (c) Rajiv Gandhi (d) Netaji Subhash Chandra Bose

2. Which one of the following is an inland riverine port? [Delhi 2012] (a) Kandla (b) Kolkata (c) Mumbai (d) Tuticorin

3. Which one of the following is not the means of mass communication? (a) Cards and envelopes (b) Radio (c) Newspaper (d) Films

4. The longest pipeline connects (a) Hazira to Kanpur (.b) Salaya to Jalandhar (c) Flazira to Jagdishpur (d) Koyali to Haldia

We hope that through these detailed notes, you have understood the chapter on Lifelines of National Economy. Unsure about selecting a stream after 10th? Our Leverage Edu experts are here to help you choose the best stream based on your choices and future goals. Sign up for a free session with us today!

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Essay on Indian Economy for Students and Children

500+ words essay on indian economy.

India is mainly an agricultural economy . Agricultural activities contribute about 50% of the economy. Agriculture involves growing and selling of crops, poultry, fishing, cattle rearing, and animal husbandry. People in India earn their livelihood by involving themselves in many of these activities. These activities are vital to our economy. The Indian economy has seen major growth in the last few decades. The credit for this boom largely goes to the service sector. Agriculture and associated activities have also been improvised to match the global standards and the export of various food products has seen an upward trend thereby adding to the economic growth. The industrial sector does not lag behind a bit. A number of new large scale, as well as small scale industries, have been set up in recent times and these have also proved to have a positive impact on the Indian economy.

Government’s Role in Economic Growth

Majority of the working Indian population was and is still engaged in the agriculture sector. Growing crops, fishing, poultry and animal husbandry were among the tasks undertaken by them. They manufactured handicraft items that were losing their charm with the introduction of the industrial goods. The demand for these goods began to decline. The agricultural activities also did not pay enough.

The government identified these problems as hindering the economic growth of the country and established policies to curb them. Promotion of cottage industry, providing fair wages to the laborers and providing enough means of livelihood to the people were some of the policies laid by the government for the country’s economic growth.

Get the huge list of more than 500 Essay Topics and Ideas

The Rise of the Industrial Sector

The government of India also promoted the growth of small scale and large scale industry as it understood that agriculture alone would not be able to help in the country’s economic growth. Many industries have been set up since independence. A large number of people shifted from the agricultural sector to the industrial sector in an attempt to earn better.

Today, we have numerous industries manufacturing a large amount of raw material as well as finished goods. The pharmaceutical industry, iron and steel industry , chemical industry, textile industry, automotive industry, timber industry, jute, and paper industry are among some of the industries which have contributed a great deal in our economic growth.

The Growth in Service Sector

The service sector has also helped in the growth of our country. This sector has seen growth in the last few decades. The privatization of the banking and telecom sectors has a positive impact on the service sector. The tourism and hotel industries are also seeing a gradual growth. As per a recent survey, the service sector is contributing to more than 50% of the country’s economy.

Indian Economy after Demonetization

The worst affected were the people in the rural areas who did not have access to internet and plastic money. This affects many big and small businesses in the country very badly. Several of them were shut down as a result of this. While the short term effects of demonetization were devastating, this decision did have a brighter side when looked at from long term perspective.

The positive impact of demonetization on the Indian economy is a breakdown of black money, the decline in fake currency notes, increase in bank deposits, demonetization stopped the flow of black money in the real estate sector to ensure a fair play, increase in digital transactions, cutting monetary support for terrorist activities.

Many of our industries are cash-driven and sudden demonetization left all these industries starving. Also, many of our small scale, as well as large scale manufacturing industries, suffered huge losses thereby impacting the economy of the country negatively. Many factories and shops had to be shut down. This did not only impact the businesses but also the workers employed there. Several people, especially the laborers, lost their jobs.

The Indian economy undergoes several positive changes since independence. It is growing at a good pace. However, the rural regions of our country are still under-developed. The government must make efforts to improve the economic condition of these areas.

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National Differences in Political Economy Essay

What i learned.

International business operations and activities are faced with various difficulties due to political, cultural, and legal differentials amid different countries. Different nations advance their economy at dissimilar rates and thus yield varying economic growth as well as development. Political systems and legal structures in a given country determine how successful and healthy the economy ranks.

The government and its functional bodies thus represent an important facet in shaping business stability and performance. Collective systems of governance put more emphasis on collective goals rather than personal goals while individualized systems emphasize personal goals. Socialism tries to encourage business people to enhance democratic rights in order to create an active market, both locally and internationally.

Government owned corporations perform poorly due to lack of accountability (Hill, 2011). Therefore, the freedom of enterprise and decision making advocated by individualized economy is essential to valuable economic performance. Citizens oversee a democratic political stance, either directly or through elective seats. Thus, political systems make decisions that represent the will of the people and thus minimize abuse of power.

In a totalitarian political system, a single party or individual makes decisions, exercises total powers and controls all functions. In this case, citizens are not represented, and hence cases of rights violation and irregular policies are rampant. A perfect market economy functions to offer quality services to all.

Therefore, demand along with supply forces determines economic status. However, monopolistic markets take advantage of few suppliers in relation to consumers, and exploit consumers by charging higher prices than would be at equilibrium (Hill, 2011). In a political system, legal system is important in order to set rules and laws to be followed by each person.

The legal system guides business relations by applying the law of contract that ensures that parties fulfill their pledges. Therefore, governments get involved in businesses by formulating policies and laws that effectuate the aspect of advanced economic activities and relations.

The role of the political system includes ensuring that individual property rights are safeguarded. This prevents theft and misuse and hence guarantees maximum utilization for personal and national benefit. However, this aspect is different in various nations due to policy differential and the level of compliance with the law. Corruption jeopardizes economic activities and thus hinders growth and development in countries highly affected.

Therefore, fighting corruption is essential in ensuring valuable and efficient national growth and international business’ competitive base (Hill, 2011). Intellectual rights include patents, trademarks, and copyrights that protect an individual’s work such as music, formulas, and other innovations. The government should implement policies aimed at maximum protection of personal ideas in order to guarantee international competition.

Economic development is affected by political, legal, as well as economic systems. Different countries perform at varying economic levels when gross national income is measured comparative to each other. Hence, a country’s level of economic development is affected by political and legal decisions. Economic growth and development are motivated by innovations and entrepreneurial actions that promote trade. Therefore, useful policies and economic environments guarantee success in local and international businesses.

However, this is not always the case as national legal systems differ in their functioning and usefulness. In addition, education system is also significant to economic development (Hill, 2011). The level of investment in education varies in different countries and hence a country that values education has higher growth rates. To improve the world economy, international money market needs to be stabilized through stable politics along with ensuring a free flow of the factors of production.

Hill, C. H. (2011). International business: Competing in the global marketplace. New York City: Irwin professional pub.

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IvyPanda. (2023, November 27). National Differences in Political Economy. https://ivypanda.com/essays/national-differences-in-political-economy/

"National Differences in Political Economy." IvyPanda , 27 Nov. 2023, ivypanda.com/essays/national-differences-in-political-economy/.

IvyPanda . (2023) 'National Differences in Political Economy'. 27 November.

IvyPanda . 2023. "National Differences in Political Economy." November 27, 2023. https://ivypanda.com/essays/national-differences-in-political-economy/.

1. IvyPanda . "National Differences in Political Economy." November 27, 2023. https://ivypanda.com/essays/national-differences-in-political-economy/.

Bibliography

IvyPanda . "National Differences in Political Economy." November 27, 2023. https://ivypanda.com/essays/national-differences-in-political-economy/.

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• Published: 17 April 2024

The economic commitment of climate change

• Maximilian Kotz   ORCID: orcid.org/0000-0003-2564-5043 1 , 2 ,
• Anders Levermann   ORCID: orcid.org/0000-0003-4432-4704 1 , 2 &
• Leonie Wenz   ORCID: orcid.org/0000-0002-8500-1568 1 , 3  

Nature volume  628 ,  pages 551–557 ( 2024 ) Cite this article

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• Environmental economics
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Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons 1 , 2 , 3 , 4 , 5 , 6 . Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes 7 , 8 . Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

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Investment incentive reduced by climate damages can be restored by optimal policy

Climate economics support for the UN climate targets

Projections of the macroeconomic damage caused by future climate change are crucial to informing public and policy debates about adaptation, mitigation and climate justice. On the one hand, adaptation against climate impacts must be justified and planned on the basis of an understanding of their future magnitude and spatial distribution 9 . This is also of importance in the context of climate justice 10 , as well as to key societal actors, including governments, central banks and private businesses, which increasingly require the inclusion of climate risks in their macroeconomic forecasts to aid adaptive decision-making 11 , 12 . On the other hand, climate mitigation policy such as the Paris Climate Agreement is often evaluated by balancing the costs of its implementation against the benefits of avoiding projected physical damages. This evaluation occurs both formally through cost–benefit analyses 1 , 4 , 5 , 6 , as well as informally through public perception of mitigation and damage costs 13 .

Projections of future damages meet challenges when informing these debates, in particular the human biases relating to uncertainty and remoteness that are raised by long-term perspectives 14 . Here we aim to overcome such challenges by assessing the extent of economic damages from climate change to which the world is already committed by historical emissions and socio-economic inertia (the range of future emission scenarios that are considered socio-economically plausible 15 ). Such a focus on the near term limits the large uncertainties about diverging future emission trajectories, the resulting long-term climate response and the validity of applying historically observed climate–economic relations over long timescales during which socio-technical conditions may change considerably. As such, this focus aims to simplify the communication and maximize the credibility of projected economic damages from future climate change.

In projecting the future economic damages from climate change, we make use of recent advances in climate econometrics that provide evidence for impacts on sub-national economic growth from numerous components of the distribution of daily temperature and precipitation 3 , 7 , 8 . Using fixed-effects panel regression models to control for potential confounders, these studies exploit within-region variation in local temperature and precipitation in a panel of more than 1,600 regions worldwide, comprising climate and income data over the past 40 years, to identify the plausibly causal effects of changes in several climate variables on economic productivity 16 , 17 . Specifically, macroeconomic impacts have been identified from changing daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall that occur in addition to those already identified from changing average temperature 2 , 3 , 18 . Moreover, regional heterogeneity in these effects based on the prevailing local climatic conditions has been found using interactions terms. The selection of these climate variables follows micro-level evidence for mechanisms related to the impacts of average temperatures on labour and agricultural productivity 2 , of temperature variability on agricultural productivity and health 7 , as well as of precipitation on agricultural productivity, labour outcomes and flood damages 8 (see Extended Data Table 1 for an overview, including more detailed references). References  7 , 8 contain a more detailed motivation for the use of these particular climate variables and provide extensive empirical tests about the robustness and nature of their effects on economic output, which are summarized in Methods . By accounting for these extra climatic variables at the sub-national level, we aim for a more comprehensive description of climate impacts with greater detail across both time and space.

Constraining the persistence of impacts

A key determinant and source of discrepancy in estimates of the magnitude of future climate damages is the extent to which the impact of a climate variable on economic growth rates persists. The two extreme cases in which these impacts persist indefinitely or only instantaneously are commonly referred to as growth or level effects 19 , 20 (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for mathematical definitions). Recent work shows that future damages from climate change depend strongly on whether growth or level effects are assumed 20 . Following refs.  2 , 18 , we provide constraints on this persistence by using distributed lag models to test the significance of delayed effects separately for each climate variable. Notably, and in contrast to refs.  2 , 18 , we use climate variables in their first-differenced form following ref.  3 , implying a dependence of the growth rate on a change in climate variables. This choice means that a baseline specification without any lags constitutes a model prior of purely level effects, in which a permanent change in the climate has only an instantaneous effect on the growth rate 3 , 19 , 21 . By including lags, one can then test whether any effects may persist further. This is in contrast to the specification used by refs.  2 , 18 , in which climate variables are used without taking the first difference, implying a dependence of the growth rate on the level of climate variables. In this alternative case, the baseline specification without any lags constitutes a model prior of pure growth effects, in which a change in climate has an infinitely persistent effect on the growth rate. Consequently, including further lags in this alternative case tests whether the initial growth impact is recovered 18 , 19 , 21 . Both of these specifications suffer from the limiting possibility that, if too few lags are included, one might falsely accept the model prior. The limitations of including a very large number of lags, including loss of data and increasing statistical uncertainty with an increasing number of parameters, mean that such a possibility is likely. By choosing a specification in which the model prior is one of level effects, our approach is therefore conservative by design, avoiding assumptions of infinite persistence of climate impacts on growth and instead providing a lower bound on this persistence based on what is observable empirically (see Methods section ‘Empirical model specification: fixed-effects distributed lag models’ for further exposition of this framework). The conservative nature of such a choice is probably the reason that ref.  19 finds much greater consistency between the impacts projected by models that use the first difference of climate variables, as opposed to their levels.

We begin our empirical analysis of the persistence of climate impacts on growth using ten lags of the first-differenced climate variables in fixed-effects distributed lag models. We detect substantial effects on economic growth at time lags of up to approximately 8–10 years for the temperature terms and up to approximately 4 years for the precipitation terms (Extended Data Fig. 1 and Extended Data Table 2 ). Furthermore, evaluation by means of information criteria indicates that the inclusion of all five climate variables and the use of these numbers of lags provide a preferable trade-off between best-fitting the data and including further terms that could cause overfitting, in comparison with model specifications excluding climate variables or including more or fewer lags (Extended Data Fig. 3 , Supplementary Methods Section  1 and Supplementary Table 1 ). We therefore remove statistically insignificant terms at later lags (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). Further tests using Monte Carlo simulations demonstrate that the empirical models are robust to autocorrelation in the lagged climate variables (Supplementary Methods Section  2 and Supplementary Figs. 4 and 5 ), that information criteria provide an effective indicator for lag selection (Supplementary Methods Section  2 and Supplementary Fig. 6 ), that the results are robust to concerns of imperfect multicollinearity between climate variables and that including several climate variables is actually necessary to isolate their separate effects (Supplementary Methods Section  3 and Supplementary Fig. 7 ). We provide a further robustness check using a restricted distributed lag model to limit oscillations in the lagged parameter estimates that may result from autocorrelation, finding that it provides similar estimates of cumulative marginal effects to the unrestricted model (Supplementary Methods Section 4 and Supplementary Figs. 8 and 9 ). Finally, to explicitly account for any outstanding uncertainty arising from the precise choice of the number of lags, we include empirical models with marginally different numbers of lags in the error-sampling procedure of our projection of future damages. On the basis of the lag-selection procedure (the significance of lagged terms in Extended Data Fig. 1 and Extended Data Table 2 , as well as information criteria in Extended Data Fig. 3 ), we sample from models with eight to ten lags for temperature and four for precipitation (models shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ). In summary, this empirical approach to constrain the persistence of climate impacts on economic growth rates is conservative by design in avoiding assumptions of infinite persistence, but nevertheless provides a lower bound on the extent of impact persistence that is robust to the numerous tests outlined above.

Committed damages until mid-century

We combine these empirical economic response functions (Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) with an ensemble of 21 climate models (see Supplementary Table 5 ) from the Coupled Model Intercomparison Project Phase 6 (CMIP-6) 22 to project the macroeconomic damages from these components of physical climate change (see Methods for further details). Bias-adjusted climate models that provide a highly accurate reproduction of observed climatological patterns with limited uncertainty (Supplementary Table 6 ) are used to avoid introducing biases in the projections. Following a well-developed literature 2 , 3 , 19 , these projections do not aim to provide a prediction of future economic growth. Instead, they are a projection of the exogenous impact of future climate conditions on the economy relative to the baselines specified by socio-economic projections, based on the plausibly causal relationships inferred by the empirical models and assuming ceteris paribus. Other exogenous factors relevant for the prediction of economic output are purposefully assumed constant.

A Monte Carlo procedure that samples from climate model projections, empirical models with different numbers of lags and model parameter estimates (obtained by 1,000 block-bootstrap resamples of each of the regressions in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) is used to estimate the combined uncertainty from these sources. Given these uncertainty distributions, we find that projected global damages are statistically indistinguishable across the two most extreme emission scenarios until 2049 (at the 5% significance level; Fig. 1 ). As such, the climate damages occurring before this time constitute those to which the world is already committed owing to the combination of past emissions and the range of future emission scenarios that are considered socio-economically plausible 15 . These committed damages comprise a permanent income reduction of 19% on average globally (population-weighted average) in comparison with a baseline without climate-change impacts (with a likely range of 11–29%, following the likelihood classification adopted by the Intergovernmental Panel on Climate Change (IPCC); see caption of Fig. 1 ). Even though levels of income per capita generally still increase relative to those of today, this constitutes a permanent income reduction for most regions, including North America and Europe (each with median income reductions of approximately 11%) and with South Asia and Africa being the most strongly affected (each with median income reductions of approximately 22%; Fig. 1 ). Under a middle-of-the road scenario of future income development (SSP2, in which SSP stands for Shared Socio-economic Pathway), this corresponds to global annual damages in 2049 of 38 trillion in 2005 international dollars (likely range of 19–59 trillion 2005 international dollars). Compared with empirical specifications that assume pure growth or pure level effects, our preferred specification that provides a robust lower bound on the extent of climate impact persistence produces damages between these two extreme assumptions (Extended Data Fig. 3 ).

Estimates of the projected reduction in income per capita from changes in all climate variables based on empirical models of climate impacts on economic output with a robust lower bound on their persistence (Extended Data Fig. 1 ) under a low-emission scenario compatible with the 2 °C warming target and a high-emission scenario (SSP2-RCP2.6 and SSP5-RCP8.5, respectively) are shown in purple and orange, respectively. Shading represents the 34% and 10% confidence intervals reflecting the likely and very likely ranges, respectively (following the likelihood classification adopted by the IPCC), having estimated uncertainty from a Monte Carlo procedure, which samples the uncertainty from the choice of physical climate models, empirical models with different numbers of lags and bootstrapped estimates of the regression parameters shown in Supplementary Figs. 1 – 3 . Vertical dashed lines show the time at which the climate damages of the two emission scenarios diverge at the 5% and 1% significance levels based on the distribution of differences between emission scenarios arising from the uncertainty sampling discussed above. Note that uncertainty in the difference of the two scenarios is smaller than the combined uncertainty of the two respective scenarios because samples of the uncertainty (climate model and empirical model choice, as well as model parameter bootstrap) are consistent across the two emission scenarios, hence the divergence of damages occurs while the uncertainty bounds of the two separate damage scenarios still overlap. Estimates of global mitigation costs from the three IAMs that provide results for the SSP2 baseline and SSP2-RCP2.6 scenario are shown in light green in the top panel, with the median of these estimates shown in bold.

Damages already outweigh mitigation costs

We compare the damages to which the world is committed over the next 25 years to estimates of the mitigation costs required to achieve the Paris Climate Agreement. Taking estimates of mitigation costs from the three integrated assessment models (IAMs) in the IPCC AR6 database 23 that provide results under comparable scenarios (SSP2 baseline and SSP2-RCP2.6, in which RCP stands for Representative Concentration Pathway), we find that the median committed climate damages are larger than the median mitigation costs in 2050 (six trillion in 2005 international dollars) by a factor of approximately six (note that estimates of mitigation costs are only provided every 10 years by the IAMs and so a comparison in 2049 is not possible). This comparison simply aims to compare the magnitude of future damages against mitigation costs, rather than to conduct a formal cost–benefit analysis of transitioning from one emission path to another. Formal cost–benefit analyses typically find that the net benefits of mitigation only emerge after 2050 (ref.  5 ), which may lead some to conclude that physical damages from climate change are simply not large enough to outweigh mitigation costs until the second half of the century. Our simple comparison of their magnitudes makes clear that damages are actually already considerably larger than mitigation costs and the delayed emergence of net mitigation benefits results primarily from the fact that damages across different emission paths are indistinguishable until mid-century (Fig. 1 ).

Although these near-term damages constitute those to which the world is already committed, we note that damage estimates diverge strongly across emission scenarios after 2049, conveying the clear benefits of mitigation from a purely economic point of view that have been emphasized in previous studies 4 , 24 . As well as the uncertainties assessed in Fig. 1 , these conclusions are robust to structural choices, such as the timescale with which changes in the moderating variables of the empirical models are estimated (Supplementary Figs. 10 and 11 ), as well as the order in which one accounts for the intertemporal and international components of currency comparison (Supplementary Fig. 12 ; see Methods for further details).

Damages from variability and extremes

Committed damages primarily arise through changes in average temperature (Fig. 2 ). This reflects the fact that projected changes in average temperature are larger than those in other climate variables when expressed as a function of their historical interannual variability (Extended Data Fig. 4 ). Because the historical variability is that on which the empirical models are estimated, larger projected changes in comparison with this variability probably lead to larger future impacts in a purely statistical sense. From a mechanistic perspective, one may plausibly interpret this result as implying that future changes in average temperature are the most unprecedented from the perspective of the historical fluctuations to which the economy is accustomed and therefore will cause the most damage. This insight may prove useful in terms of guiding adaptation measures to the sources of greatest damage.

Estimates of the median projected reduction in sub-national income per capita across emission scenarios (SSP2-RCP2.6 and SSP2-RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ). a , Impacts arising from all climate variables. b – f , Impacts arising separately from changes in annual mean temperature ( b ), daily temperature variability ( c ), total annual precipitation ( d ), the annual number of wet days (>1 mm) ( e ) and extreme daily rainfall ( f ) (see Methods for further definitions). Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Nevertheless, future damages based on empirical models that consider changes in annual average temperature only and exclude the other climate variables constitute income reductions of only 13% in 2049 (Extended Data Fig. 5a , likely range 5–21%). This suggests that accounting for the other components of the distribution of temperature and precipitation raises net damages by nearly 50%. This increase arises through the further damages that these climatic components cause, but also because their inclusion reveals a stronger negative economic response to average temperatures (Extended Data Fig. 5b ). The latter finding is consistent with our Monte Carlo simulations, which suggest that the magnitude of the effect of average temperature on economic growth is underestimated unless accounting for the impacts of other correlated climate variables (Supplementary Fig. 7 ).

In terms of the relative contributions of the different climatic components to overall damages, we find that accounting for daily temperature variability causes the largest increase in overall damages relative to empirical frameworks that only consider changes in annual average temperature (4.9 percentage points, likely range 2.4–8.7 percentage points, equivalent to approximately 10 trillion international dollars). Accounting for precipitation causes smaller increases in overall damages, which are—nevertheless—equivalent to approximately 1.2 trillion international dollars: 0.01 percentage points (−0.37–0.33 percentage points), 0.34 percentage points (0.07–0.90 percentage points) and 0.36 percentage points (0.13–0.65 percentage points) from total annual precipitation, the number of wet days and extreme daily precipitation, respectively. Moreover, climate models seem to underestimate future changes in temperature variability 25 and extreme precipitation 26 , 27 in response to anthropogenic forcing as compared with that observed historically, suggesting that the true impacts from these variables may be larger.

The distribution of committed damages

The spatial distribution of committed damages (Fig. 2a ) reflects a complex interplay between the patterns of future change in several climatic components and those of historical economic vulnerability to changes in those variables. Damages resulting from increasing annual mean temperature (Fig. 2b ) are negative almost everywhere globally, and larger at lower latitudes in regions in which temperatures are already higher and economic vulnerability to temperature increases is greatest (see the response heterogeneity to mean temperature embodied in Extended Data Fig. 1a ). This occurs despite the amplified warming projected at higher latitudes 28 , suggesting that regional heterogeneity in economic vulnerability to temperature changes outweighs heterogeneity in the magnitude of future warming (Supplementary Fig. 13a ). Economic damages owing to daily temperature variability (Fig. 2c ) exhibit a strong latitudinal polarisation, primarily reflecting the physical response of daily variability to greenhouse forcing in which increases in variability across lower latitudes (and Europe) contrast decreases at high latitudes 25 (Supplementary Fig. 13b ). These two temperature terms are the dominant determinants of the pattern of overall damages (Fig. 2a ), which exhibits a strong polarity with damages across most of the globe except at the highest northern latitudes. Future changes in total annual precipitation mainly bring economic benefits except in regions of drying, such as the Mediterranean and central South America (Fig. 2d and Supplementary Fig. 13c ), but these benefits are opposed by changes in the number of wet days, which produce damages with a similar pattern of opposite sign (Fig. 2e and Supplementary Fig. 13d ). By contrast, changes in extreme daily rainfall produce damages in all regions, reflecting the intensification of daily rainfall extremes over global land areas 29 , 30 (Fig. 2f and Supplementary Fig. 13e ).

The spatial distribution of committed damages implies considerable injustice along two dimensions: culpability for the historical emissions that have caused climate change and pre-existing levels of socio-economic welfare. Spearman’s rank correlations indicate that committed damages are significantly larger in countries with smaller historical cumulative emissions, as well as in regions with lower current income per capita (Fig. 3 ). This implies that those countries that will suffer the most from the damages already committed are those that are least responsible for climate change and which also have the least resources to adapt to it.

Estimates of the median projected change in national income per capita across emission scenarios (RCP2.6 and RCP8.5) as well as climate model, empirical model and model parameter uncertainty in the year in which climate damages diverge at the 5% level (2049, as identified in Fig. 1 ) are plotted against cumulative national emissions per capita in 2020 (from the Global Carbon Project) and coloured by national income per capita in 2020 (from the World Bank) in a and vice versa in b . In each panel, the size of each scatter point is weighted by the national population in 2020 (from the World Bank). Inset numbers indicate the Spearman’s rank correlation ρ and P -values for a hypothesis test whose null hypothesis is of no correlation, as well as the Spearman’s rank correlation weighted by national population.

To further quantify this heterogeneity, we assess the difference in committed damages between the upper and lower quartiles of regions when ranked by present income levels and historical cumulative emissions (using a population weighting to both define the quartiles and estimate the group averages). On average, the quartile of countries with lower income are committed to an income loss that is 8.9 percentage points (or 61%) greater than the upper quartile (Extended Data Fig. 6 ), with a likely range of 3.8–14.7 percentage points across the uncertainty sampling of our damage projections (following the likelihood classification adopted by the IPCC). Similarly, the quartile of countries with lower historical cumulative emissions are committed to an income loss that is 6.9 percentage points (or 40%) greater than the upper quartile, with a likely range of 0.27–12 percentage points. These patterns reemphasize the prevalence of injustice in climate impacts 31 , 32 , 33 in the context of the damages to which the world is already committed by historical emissions and socio-economic inertia.

Contextualizing the magnitude of damages

The magnitude of projected economic damages exceeds previous literature estimates 2 , 3 , arising from several developments made on previous approaches. Our estimates are larger than those of ref.  2 (see first row of Extended Data Table 3 ), primarily because of the facts that sub-national estimates typically show a steeper temperature response (see also refs.  3 , 34 ) and that accounting for other climatic components raises damage estimates (Extended Data Fig. 5 ). However, we note that our empirical approach using first-differenced climate variables is conservative compared with that of ref.  2 in regard to the persistence of climate impacts on growth (see introduction and Methods section ‘Empirical model specification: fixed-effects distributed lag models’), an important determinant of the magnitude of long-term damages 19 , 21 . Using a similar empirical specification to ref.  2 , which assumes infinite persistence while maintaining the rest of our approach (sub-national data and further climate variables), produces considerably larger damages (purple curve of Extended Data Fig. 3 ). Compared with studies that do take the first difference of climate variables 3 , 35 , our estimates are also larger (see second and third rows of Extended Data Table 3 ). The inclusion of further climate variables (Extended Data Fig. 5 ) and a sufficient number of lags to more adequately capture the extent of impact persistence (Extended Data Figs. 1 and 2 ) are the main sources of this difference, as is the use of specifications that capture nonlinearities in the temperature response when compared with ref.  35 . In summary, our estimates develop on previous studies by incorporating the latest data and empirical insights 7 , 8 , as well as in providing a robust empirical lower bound on the persistence of impacts on economic growth, which constitutes a middle ground between the extremes of the growth-versus-levels debate 19 , 21 (Extended Data Fig. 3 ).

Compared with the fraction of variance explained by the empirical models historically (<5%), the projection of reductions in income of 19% may seem large. This arises owing to the fact that projected changes in climatic conditions are much larger than those that were experienced historically, particularly for changes in average temperature (Extended Data Fig. 4 ). As such, any assessment of future climate-change impacts necessarily requires an extrapolation outside the range of the historical data on which the empirical impact models were evaluated. Nevertheless, these models constitute the most state-of-the-art methods for inference of plausibly causal climate impacts based on observed data. Moreover, we take explicit steps to limit out-of-sample extrapolation by capping the moderating variables of the interaction terms at the 95th percentile of the historical distribution (see Methods ). This avoids extrapolating the marginal effects outside what was observed historically. Given the nonlinear response of economic output to annual mean temperature (Extended Data Fig. 1 and Extended Data Table 2 ), this is a conservative choice that limits the magnitude of damages that we project. Furthermore, back-of-the-envelope calculations indicate that the projected damages are consistent with the magnitude and patterns of historical economic development (see Supplementary Discussion Section  5 ).

Missing impacts and spatial spillovers

Despite assessing several climatic components from which economic impacts have recently been identified 3 , 7 , 8 , this assessment of aggregate climate damages should not be considered comprehensive. Important channels such as impacts from heatwaves 31 , sea-level rise 36 , tropical cyclones 37 and tipping points 38 , 39 , as well as non-market damages such as those to ecosystems 40 and human health 41 , are not considered in these estimates. Sea-level rise is unlikely to be feasibly incorporated into empirical assessments such as this because historical sea-level variability is mostly small. Non-market damages are inherently intractable within our estimates of impacts on aggregate monetary output and estimates of these impacts could arguably be considered as extra to those identified here. Recent empirical work suggests that accounting for these channels would probably raise estimates of these committed damages, with larger damages continuing to arise in the global south 31 , 36 , 37 , 38 , 39 , 40 , 41 , 42 .

Moreover, our main empirical analysis does not explicitly evaluate the potential for impacts in local regions to produce effects that ‘spill over’ into other regions. Such effects may further mitigate or amplify the impacts we estimate, for example, if companies relocate production from one affected region to another or if impacts propagate along supply chains. The current literature indicates that trade plays a substantial role in propagating spillover effects 43 , 44 , making their assessment at the sub-national level challenging without available data on sub-national trade dependencies. Studies accounting for only spatially adjacent neighbours indicate that negative impacts in one region induce further negative impacts in neighbouring regions 45 , 46 , 47 , 48 , suggesting that our projected damages are probably conservative by excluding these effects. In Supplementary Fig. 14 , we assess spillovers from neighbouring regions using a spatial-lag model. For simplicity, this analysis excludes temporal lags, focusing only on contemporaneous effects. The results show that accounting for spatial spillovers can amplify the overall magnitude, and also the heterogeneity, of impacts. Consistent with previous literature, this indicates that the overall magnitude (Fig. 1 ) and heterogeneity (Fig. 3 ) of damages that we project in our main specification may be conservative without explicitly accounting for spillovers. We note that further analysis that addresses both spatially and trade-connected spillovers, while also accounting for delayed impacts using temporal lags, would be necessary to adequately address this question fully. These approaches offer fruitful avenues for further research but are beyond the scope of this manuscript, which primarily aims to explore the impacts of different climate conditions and their persistence.

Policy implications

We find that the economic damages resulting from climate change until 2049 are those to which the world economy is already committed and that these greatly outweigh the costs required to mitigate emissions in line with the 2 °C target of the Paris Climate Agreement (Fig. 1 ). This assessment is complementary to formal analyses of the net costs and benefits associated with moving from one emission path to another, which typically find that net benefits of mitigation only emerge in the second half of the century 5 . Our simple comparison of the magnitude of damages and mitigation costs makes clear that this is primarily because damages are indistinguishable across emissions scenarios—that is, committed—until mid-century (Fig. 1 ) and that they are actually already much larger than mitigation costs. For simplicity, and owing to the availability of data, we compare damages to mitigation costs at the global level. Regional estimates of mitigation costs may shed further light on the national incentives for mitigation to which our results already hint, of relevance for international climate policy. Although these damages are committed from a mitigation perspective, adaptation may provide an opportunity to reduce them. Moreover, the strong divergence of damages after mid-century reemphasizes the clear benefits of mitigation from a purely economic perspective, as highlighted in previous studies 1 , 4 , 6 , 24 .

Historical climate data

Historical daily 2-m temperature and precipitation totals (in mm) are obtained for the period 1979–2019 from the W5E5 database. The W5E5 dataset comes from ERA-5, a state-of-the-art reanalysis of historical observations, but has been bias-adjusted by applying version 2.0 of the WATCH Forcing Data to ERA-5 reanalysis data and precipitation data from version 2.3 of the Global Precipitation Climatology Project to better reflect ground-based measurements 49 , 50 , 51 . We obtain these data on a 0.5° × 0.5° grid from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) database. Notably, these historical data have been used to bias-adjust future climate projections from CMIP-6 (see the following section), ensuring consistency between the distribution of historical daily weather on which our empirical models were estimated and the climate projections used to estimate future damages. These data are publicly available from the ISIMIP database. See refs.  7 , 8 for robustness tests of the empirical models to the choice of climate data reanalysis products.

Future climate data

Daily 2-m temperature and precipitation totals (in mm) are taken from 21 climate models participating in CMIP-6 under a high (RCP8.5) and a low (RCP2.6) greenhouse gas emission scenario from 2015 to 2100. The data have been bias-adjusted and statistically downscaled to a common half-degree grid to reflect the historical distribution of daily temperature and precipitation of the W5E5 dataset using the trend-preserving method developed by the ISIMIP 50 , 52 . As such, the climate model data reproduce observed climatological patterns exceptionally well (Supplementary Table 5 ). Gridded data are publicly available from the ISIMIP database.

Historical economic data

Historical economic data come from the DOSE database of sub-national economic output 53 . We use a recent revision to the DOSE dataset that provides data across 83 countries, 1,660 sub-national regions with varying temporal coverage from 1960 to 2019. Sub-national units constitute the first administrative division below national, for example, states for the USA and provinces for China. Data come from measures of gross regional product per capita (GRPpc) or income per capita in local currencies, reflecting the values reported in national statistical agencies, yearbooks and, in some cases, academic literature. We follow previous literature 3 , 7 , 8 , 54 and assess real sub-national output per capita by first converting values from local currencies to US dollars to account for diverging national inflationary tendencies and then account for US inflation using a US deflator. Alternatively, one might first account for national inflation and then convert between currencies. Supplementary Fig. 12 demonstrates that our conclusions are consistent when accounting for price changes in the reversed order, although the magnitude of estimated damages varies. See the documentation of the DOSE dataset for further discussion of these choices. Conversions between currencies are conducted using exchange rates from the FRED database of the Federal Reserve Bank of St. Louis 55 and the national deflators from the World Bank 56 .

Future socio-economic data

Baseline gridded gross domestic product (GDP) and population data for the period 2015–2100 are taken from the middle-of-the-road scenario SSP2 (ref.  15 ). Population data have been downscaled to a half-degree grid by the ISIMIP following the methodologies of refs.  57 , 58 , which we then aggregate to the sub-national level of our economic data using the spatial aggregation procedure described below. Because current methodologies for downscaling the GDP of the SSPs use downscaled population to do so, per-capita estimates of GDP with a realistic distribution at the sub-national level are not readily available for the SSPs. We therefore use national-level GDP per capita (GDPpc) projections for all sub-national regions of a given country, assuming homogeneity within countries in terms of baseline GDPpc. Here we use projections that have been updated to account for the impact of the COVID-19 pandemic on the trajectory of future income, while remaining consistent with the long-term development of the SSPs 59 . The choice of baseline SSP alters the magnitude of projected climate damages in monetary terms, but when assessed in terms of percentage change from the baseline, the choice of socio-economic scenario is inconsequential. Gridded SSP population data and national-level GDPpc data are publicly available from the ISIMIP database. Sub-national estimates as used in this study are available in the code and data replication files.

Climate variables

Following recent literature 3 , 7 , 8 , we calculate an array of climate variables for which substantial impacts on macroeconomic output have been identified empirically, supported by further evidence at the micro level for plausible underlying mechanisms. See refs.  7 , 8 for an extensive motivation for the use of these particular climate variables and for detailed empirical tests on the nature and robustness of their effects on economic output. To summarize, these studies have found evidence for independent impacts on economic growth rates from annual average temperature, daily temperature variability, total annual precipitation, the annual number of wet days and extreme daily rainfall. Assessments of daily temperature variability were motivated by evidence of impacts on agricultural output and human health, as well as macroeconomic literature on the impacts of volatility on growth when manifest in different dimensions, such as government spending, exchange rates and even output itself 7 . Assessments of precipitation impacts were motivated by evidence of impacts on agricultural productivity, metropolitan labour outcomes and conflict, as well as damages caused by flash flooding 8 . See Extended Data Table 1 for detailed references to empirical studies of these physical mechanisms. Marked impacts of daily temperature variability, total annual precipitation, the number of wet days and extreme daily rainfall on macroeconomic output were identified robustly across different climate datasets, spatial aggregation schemes, specifications of regional time trends and error-clustering approaches. They were also found to be robust to the consideration of temperature extremes 7 , 8 . Furthermore, these climate variables were identified as having independent effects on economic output 7 , 8 , which we further explain here using Monte Carlo simulations to demonstrate the robustness of the results to concerns of imperfect multicollinearity between climate variables (Supplementary Methods Section  2 ), as well as by using information criteria (Supplementary Table 1 ) to demonstrate that including several lagged climate variables provides a preferable trade-off between optimally describing the data and limiting the possibility of overfitting.

We calculate these variables from the distribution of daily, d , temperature, T x , d , and precipitation, P x , d , at the grid-cell, x , level for both the historical and future climate data. As well as annual mean temperature, \({\bar{T}}_{x,y}\) , and annual total precipitation, P x , y , we calculate annual, y , measures of daily temperature variability, \({\widetilde{T}}_{x,y}\) :

the number of wet days, Pwd x , y :

and extreme daily rainfall:

in which T x , d , m , y is the grid-cell-specific daily temperature in month m and year y , \({\bar{T}}_{x,m,{y}}\) is the year and grid-cell-specific monthly, m , mean temperature, D m and D y the number of days in a given month m or year y , respectively, H the Heaviside step function, 1 mm the threshold used to define wet days and P 99.9 x is the 99.9th percentile of historical (1979–2019) daily precipitation at the grid-cell level. Units of the climate measures are degrees Celsius for annual mean temperature and daily temperature variability, millimetres for total annual precipitation and extreme daily precipitation, and simply the number of days for the annual number of wet days.

We also calculated weighted standard deviations of monthly rainfall totals as also used in ref.  8 but do not include them in our projections as we find that, when accounting for delayed effects, their effect becomes statistically indistinct and is better captured by changes in total annual rainfall.

Spatial aggregation

We aggregate grid-cell-level historical and future climate measures, as well as grid-cell-level future GDPpc and population, to the level of the first administrative unit below national level of the GADM database, using an area-weighting algorithm that estimates the portion of each grid cell falling within an administrative boundary. We use this as our baseline specification following previous findings that the effect of area or population weighting at the sub-national level is negligible 7 , 8 .

Empirical model specification: fixed-effects distributed lag models

Following a wide range of climate econometric literature 16 , 60 , we use panel regression models with a selection of fixed effects and time trends to isolate plausibly exogenous variation with which to maximize confidence in a causal interpretation of the effects of climate on economic growth rates. The use of region fixed effects, μ r , accounts for unobserved time-invariant differences between regions, such as prevailing climatic norms and growth rates owing to historical and geopolitical factors. The use of yearly fixed effects, η y , accounts for regionally invariant annual shocks to the global climate or economy such as the El Niño–Southern Oscillation or global recessions. In our baseline specification, we also include region-specific linear time trends, k r y , to exclude the possibility of spurious correlations resulting from common slow-moving trends in climate and growth.

The persistence of climate impacts on economic growth rates is a key determinant of the long-term magnitude of damages. Methods for inferring the extent of persistence in impacts on growth rates have typically used lagged climate variables to evaluate the presence of delayed effects or catch-up dynamics 2 , 18 . For example, consider starting from a model in which a climate condition, C r , y , (for example, annual mean temperature) affects the growth rate, Δlgrp r , y (the first difference of the logarithm of gross regional product) of region r in year y :

which we refer to as a ‘pure growth effects’ model in the main text. Typically, further lags are included,

and the cumulative effect of all lagged terms is evaluated to assess the extent to which climate impacts on growth rates persist. Following ref.  18 , in the case that,

the implication is that impacts on the growth rate persist up to NL years after the initial shock (possibly to a weaker or a stronger extent), whereas if

then the initial impact on the growth rate is recovered after NL years and the effect is only one on the level of output. However, we note that such approaches are limited by the fact that, when including an insufficient number of lags to detect a recovery of the growth rates, one may find equation ( 6 ) to be satisfied and incorrectly assume that a change in climatic conditions affects the growth rate indefinitely. In practice, given a limited record of historical data, including too few lags to confidently conclude in an infinitely persistent impact on the growth rate is likely, particularly over the long timescales over which future climate damages are often projected 2 , 24 . To avoid this issue, we instead begin our analysis with a model for which the level of output, lgrp r , y , depends on the level of a climate variable, C r , y :

Given the non-stationarity of the level of output, we follow the literature 19 and estimate such an equation in first-differenced form as,

which we refer to as a model of ‘pure level effects’ in the main text. This model constitutes a baseline specification in which a permanent change in the climate variable produces an instantaneous impact on the growth rate and a permanent effect only on the level of output. By including lagged variables in this specification,

we are able to test whether the impacts on the growth rate persist any further than instantaneously by evaluating whether α L  > 0 are statistically significantly different from zero. Even though this framework is also limited by the possibility of including too few lags, the choice of a baseline model specification in which impacts on the growth rate do not persist means that, in the case of including too few lags, the framework reverts to the baseline specification of level effects. As such, this framework is conservative with respect to the persistence of impacts and the magnitude of future damages. It naturally avoids assumptions of infinite persistence and we are able to interpret any persistence that we identify with equation ( 9 ) as a lower bound on the extent of climate impact persistence on growth rates. See the main text for further discussion of this specification choice, in particular about its conservative nature compared with previous literature estimates, such as refs.  2 , 18 .

We allow the response to climatic changes to vary across regions, using interactions of the climate variables with historical average (1979–2019) climatic conditions reflecting heterogenous effects identified in previous work 7 , 8 . Following this previous work, the moderating variables of these interaction terms constitute the historical average of either the variable itself or of the seasonal temperature difference, \({\hat{T}}_{r}\) , or annual mean temperature, \({\bar{T}}_{r}\) , in the case of daily temperature variability 7 and extreme daily rainfall, respectively 8 .

The resulting regression equation with N and M lagged variables, respectively, reads:

in which Δlgrp r , y is the annual, regional GRPpc growth rate, measured as the first difference of the logarithm of real GRPpc, following previous work 2 , 3 , 7 , 8 , 18 , 19 . Fixed-effects regressions were run using the fixest package in R (ref.  61 ).

Estimates of the coefficients of interest α i , L are shown in Extended Data Fig. 1 for N  =  M  = 10 lags and for our preferred choice of the number of lags in Supplementary Figs. 1 – 3 . In Extended Data Fig. 1 , errors are shown clustered at the regional level, but for the construction of damage projections, we block-bootstrap the regressions by region 1,000 times to provide a range of parameter estimates with which to sample the projection uncertainty (following refs.  2 , 31 ).

Spatial-lag model

In Supplementary Fig. 14 , we present the results from a spatial-lag model that explores the potential for climate impacts to ‘spill over’ into spatially neighbouring regions. We measure the distance between centroids of each pair of sub-national regions and construct spatial lags that take the average of the first-differenced climate variables and their interaction terms over neighbouring regions that are at distances of 0–500, 500–1,000, 1,000–1,500 and 1,500–2000 km (spatial lags, ‘SL’, 1 to 4). For simplicity, we then assess a spatial-lag model without temporal lags to assess spatial spillovers of contemporaneous climate impacts. This model takes the form:

in which SL indicates the spatial lag of each climate variable and interaction term. In Supplementary Fig. 14 , we plot the cumulative marginal effect of each climate variable at different baseline climate conditions by summing the coefficients for each climate variable and interaction term, for example, for average temperature impacts as:

These cumulative marginal effects can be regarded as the overall spatially dependent impact to an individual region given a one-unit shock to a climate variable in that region and all neighbouring regions at a given value of the moderating variable of the interaction term.

Constructing projections of economic damage from future climate change

We construct projections of future climate damages by applying the coefficients estimated in equation ( 10 ) and shown in Supplementary Tables 2 – 4 (when including only lags with statistically significant effects in specifications that limit overfitting; see Supplementary Methods Section  1 ) to projections of future climate change from the CMIP-6 models. Year-on-year changes in each primary climate variable of interest are calculated to reflect the year-to-year variations used in the empirical models. 30-year moving averages of the moderating variables of the interaction terms are calculated to reflect the long-term average of climatic conditions that were used for the moderating variables in the empirical models. By using moving averages in the projections, we account for the changing vulnerability to climate shocks based on the evolving long-term conditions (Supplementary Figs. 10 and 11 show that the results are robust to the precise choice of the window of this moving average). Although these climate variables are not differenced, the fact that the bias-adjusted climate models reproduce observed climatological patterns across regions for these moderating variables very accurately (Supplementary Table 6 ) with limited spread across models (<3%) precludes the possibility that any considerable bias or uncertainty is introduced by this methodological choice. However, we impose caps on these moderating variables at the 95th percentile at which they were observed in the historical data to prevent extrapolation of the marginal effects outside the range in which the regressions were estimated. This is a conservative choice that limits the magnitude of our damage projections.

Time series of primary climate variables and moderating climate variables are then combined with estimates of the empirical model parameters to evaluate the regression coefficients in equation ( 10 ), producing a time series of annual GRPpc growth-rate reductions for a given emission scenario, climate model and set of empirical model parameters. The resulting time series of growth-rate impacts reflects those occurring owing to future climate change. By contrast, a future scenario with no climate change would be one in which climate variables do not change (other than with random year-to-year fluctuations) and hence the time-averaged evaluation of equation ( 10 ) would be zero. Our approach therefore implicitly compares the future climate-change scenario to this no-climate-change baseline scenario.

The time series of growth-rate impacts owing to future climate change in region r and year y , δ r , y , are then added to the future baseline growth rates, π r , y (in log-diff form), obtained from the SSP2 scenario to yield trajectories of damaged GRPpc growth rates, ρ r , y . These trajectories are aggregated over time to estimate the future trajectory of GRPpc with future climate impacts:

in which GRPpc r , y =2020 is the initial log level of GRPpc. We begin damage estimates in 2020 to reflect the damages occurring since the end of the period for which we estimate the empirical models (1979–2019) and to match the timing of mitigation-cost estimates from most IAMs (see below).

For each emission scenario, this procedure is repeated 1,000 times while randomly sampling from the selection of climate models, the selection of empirical models with different numbers of lags (shown in Supplementary Figs. 1 – 3 and Supplementary Tables 2 – 4 ) and bootstrapped estimates of the regression parameters. The result is an ensemble of future GRPpc trajectories that reflect uncertainty from both physical climate change and the structural and sampling uncertainty of the empirical models.

Estimates of mitigation costs

We obtain IPCC estimates of the aggregate costs of emission mitigation from the AR6 Scenario Explorer and Database hosted by IIASA 23 . Specifically, we search the AR6 Scenarios Database World v1.1 for IAMs that provided estimates of global GDP and population under both a SSP2 baseline and a SSP2-RCP2.6 scenario to maintain consistency with the socio-economic and emission scenarios of the climate damage projections. We find five IAMs that provide data for these scenarios, namely, MESSAGE-GLOBIOM 1.0, REMIND-MAgPIE 1.5, AIM/GCE 2.0, GCAM 4.2 and WITCH-GLOBIOM 3.1. Of these five IAMs, we use the results only from the first three that passed the IPCC vetting procedure for reproducing historical emission and climate trajectories. We then estimate global mitigation costs as the percentage difference in global per capita GDP between the SSP2 baseline and the SSP2-RCP2.6 emission scenario. In the case of one of these IAMs, estimates of mitigation costs begin in 2020, whereas in the case of two others, mitigation costs begin in 2010. The mitigation cost estimates before 2020 in these two IAMs are mostly negligible, and our choice to begin comparison with damage estimates in 2020 is conservative with respect to the relative weight of climate damages compared with mitigation costs for these two IAMs.

Data availability

Data on economic production and ERA-5 climate data are publicly available at https://doi.org/10.5281/zenodo.4681306 (ref. 62 ) and https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5 , respectively. Data on mitigation costs are publicly available at https://data.ene.iiasa.ac.at/ar6/#/downloads . Processed climate and economic data, as well as all other necessary data for reproduction of the results, are available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

Code availability

All code necessary for reproduction of the results is available at the public repository https://doi.org/10.5281/zenodo.10562951  (ref. 63 ).

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Acknowledgements

We gratefully acknowledge financing from the Volkswagen Foundation and the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the Government of the Federal Republic of Germany and Federal Ministry for Economic Cooperation and Development (BMZ).

Open access funding provided by Potsdam-Institut für Klimafolgenforschung (PIK) e.V.

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Extended data figures and tables

Extended data fig. 1 constraining the persistence of historical climate impacts on economic growth rates..

The results of a panel-based fixed-effects distributed lag model for the effects of annual mean temperature ( a ), daily temperature variability ( b ), total annual precipitation ( c ), the number of wet days ( d ) and extreme daily precipitation ( e ) on sub-national economic growth rates. Point estimates show the effects of a 1 °C or one standard deviation increase (for temperature and precipitation variables, respectively) at the lower quartile, median and upper quartile of the relevant moderating variable (green, orange and purple, respectively) at different lagged periods after the initial shock (note that these are not cumulative effects). Climate variables are used in their first-differenced form (see main text for discussion) and the moderating climate variables are the annual mean temperature, seasonal temperature difference, total annual precipitation, number of wet days and annual mean temperature, respectively, in panels a – e (see Methods for further discussion). Error bars show the 95% confidence intervals having clustered standard errors by region. The within-region R 2 , Bayesian and Akaike information criteria for the model are shown at the top of the figure. This figure shows results with ten lags for each variable to demonstrate the observed levels of persistence, but our preferred specifications remove later lags based on the statistical significance of terms shown above and the information criteria shown in Extended Data Fig. 2 . The resulting models without later lags are shown in Supplementary Figs. 1 – 3 .

Extended Data Fig. 2 Incremental lag-selection procedure using information criteria and within-region R 2 .

Starting from a panel-based fixed-effects distributed lag model estimating the effects of climate on economic growth using the real historical data (as in equation ( 4 )) with ten lags for all climate variables (as shown in Extended Data Fig. 1 ), lags are incrementally removed for one climate variable at a time. The resulting Bayesian and Akaike information criteria are shown in a – e and f – j , respectively, and the within-region R 2 and number of observations in k – o and p – t , respectively. Different rows show the results when removing lags from different climate variables, ordered from top to bottom as annual mean temperature, daily temperature variability, total annual precipitation, the number of wet days and extreme annual precipitation. Information criteria show minima at approximately four lags for precipitation variables and ten to eight for temperature variables, indicating that including these numbers of lags does not lead to overfitting. See Supplementary Table 1 for an assessment using information criteria to determine whether including further climate variables causes overfitting.

Extended Data Fig. 3 Damages in our preferred specification that provides a robust lower bound on the persistence of climate impacts on economic growth versus damages in specifications of pure growth or pure level effects.

Estimates of future damages as shown in Fig. 1 but under the emission scenario RCP8.5 for three separate empirical specifications: in orange our preferred specification, which provides an empirical lower bound on the persistence of climate impacts on economic growth rates while avoiding assumptions of infinite persistence (see main text for further discussion); in purple a specification of ‘pure growth effects’ in which the first difference of climate variables is not taken and no lagged climate variables are included (the baseline specification of ref.  2 ); and in pink a specification of ‘pure level effects’ in which the first difference of climate variables is taken but no lagged terms are included.

Extended Data Fig. 4 Climate changes in different variables as a function of historical interannual variability.

Changes in each climate variable of interest from 1979–2019 to 2035–2065 under the high-emission scenario SSP5-RCP8.5, expressed as a percentage of the historical variability of each measure. Historical variability is estimated as the standard deviation of each detrended climate variable over the period 1979–2019 during which the empirical models were identified (detrending is appropriate because of the inclusion of region-specific linear time trends in the empirical models). See Supplementary Fig. 13 for changes expressed in standard units. Data on national administrative boundaries are obtained from the GADM database version 3.6 and are freely available for academic use ( https://gadm.org/ ).

Extended Data Fig. 5 Contribution of different climate variables to overall committed damages.

a , Climate damages in 2049 when using empirical models that account for all climate variables, changes in annual mean temperature only or changes in both annual mean temperature and one other climate variable (daily temperature variability, total annual precipitation, the number of wet days and extreme daily precipitation, respectively). b , The cumulative marginal effects of an increase in annual mean temperature of 1 °C, at different baseline temperatures, estimated from empirical models including all climate variables or annual mean temperature only. Estimates and uncertainty bars represent the median and 95% confidence intervals obtained from 1,000 block-bootstrap resamples from each of three different empirical models using eight, nine or ten lags of temperature terms.

Extended Data Fig. 6 The difference in committed damages between the upper and lower quartiles of countries when ranked by GDP and cumulative historical emissions.

Quartiles are defined using a population weighting, as are the average committed damages across each quartile group. The violin plots indicate the distribution of differences between quartiles across the two extreme emission scenarios (RCP2.6 and RCP8.5) and the uncertainty sampling procedure outlined in Methods , which accounts for uncertainty arising from the choice of lags in the empirical models, uncertainty in the empirical model parameter estimates, as well as the climate model projections. Bars indicate the median, as well as the 10th and 90th percentiles and upper and lower sixths of the distribution reflecting the very likely and likely ranges following the likelihood classification adopted by the IPCC.

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Kotz, M., Levermann, A. & Wenz, L. The economic commitment of climate change. Nature 628 , 551–557 (2024). https://doi.org/10.1038/s41586-024-07219-0

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Received : 25 January 2023

Accepted : 21 February 2024

Published : 17 April 2024

Issue Date : 18 April 2024

DOI : https://doi.org/10.1038/s41586-024-07219-0

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Best Compare and Contrast Essay Examples

National economics: united states and china.

1082 words | 4 page(s)

From the beginning of the foundation of the American constitution, the United States has embraced the democratic federal structure, allowing the people to voice their opinions and elect chosen representatives to reflect their beliefs on local, state, and national levels. The American health care system is outspoken when compared to the vast majority of industrialized nations, as there is no uniform structure and no universal coverage provided. Unlike many other countries, the education system in the United States requires private funding to progress into the university level whether the funding is a result of scholarships, out-of-pocket spending, or the most common option which includes student loans. Unlike the United States, China is a socialist republic that is operated by one unified group known as the Communist Party of China which utilizes Internal Reference to monitor and manage disagreements within the population. Close to 100 percent of the population holds basic health care coverage, yet public insurance typically covers less than half of all medical expenses.

Generally speaking, there are three specific classifications that are identified in financial systems. These include command, traditional, and market economies. Within the first, a national government will decide everything related to the means of production, including what goods and services will be made, in what way, and who the base of consumers will be (eNotes, 2009). This is the most uncommon, as it is often indicative of a totalitarian structure. Consequently, such economies are typically observed in communist countries including but not limited to China and North Korea. Conversely, in a market economy, the base of consumers are the determinants of means of production through their own individual decisions with respect to purchasing various goods and services (eNotes, 2009).

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Finally, a traditional economy follows generations of old, continuing to produce what has always been made in the exact same manner in which it has always been made (eNotes, 2009). Given the limitations of this particular structure, it is difficult to ascertain any particular nation whose economy fully embraces such a system. Therefore, the closest connection could be made to nations which share little connection to the economy on a global scale, such as Bhutan or Afghanistan. This paper will attempt to compare and contrast the economic structures of the two largest financial superpowers in the world (the United States and China) in addition to analyzing their own strengths and weaknesses.

From the beginning of the foundation of the American constitution, the United States has embraced the democratic federal structure, allowing the people to voice their opinions and elect chosen representatives to reflect their beliefs on local, state, and national levels (Bureau of Economic Analysis, 2018). Despite how well the system has prevented uprisings and civil entanglements over the past 2 centuries when compared to outside nations, the country has fallen privy to significant internal corruption due to its capitalistic structure; a system which allows private ownership and control over virtually all goods, services, and events that take place (Bureau of Economic Analysis, 2018). Those of sufficient monetary resources are often culprits of a behavior known as lobbying, the act of influencing decisions on the federal level with the use of massive funding; typically in the multi-billion dollar spectrum. The national flag symbolizes the successful union of the 50 states which represent the territory, and the 13 stripes are indicative of the original 13 colonies which collaborated in the declaration of independence from Great Britain during the Revolutionary War (Colonial Flag, n.d.). Colors have their own purpose in a similar way, as the red symbolizes valor and hardiness, the blue signifies justice and vigilance, and the white symbolizes purity (Colonial Flag, n.d.).

The American health care system is outspoken when compared to the vast majority of industrialized nations, as there is no uniform structure and no universal coverage provided. Instead of existing strictly as a single payer, multi payer, or national service, the American system is considered a hybrid of the three. More than 50 percent of all health care spending is a direct result of private funding (Bureau of Economic Analysis, 2018). Within this 50 percent, approximately 20 comes from private business and close to 30 from household income (Bureau of Economic Analysis, 2018). The rest of the spending, though much smaller, is a byproduct of local, state, and federal government spending.

Prior to the option of higher education services, American students are required to attend both primary and secondary school for a combined time period of 12 years which span grades 1 through 12. Near the age of 6, the average child living in the United States begins attendance of elementary school and soon attends middle school close to 6 years later. Upon completion of high school, the student is either granted a Diploma through conventional means or through the completion of examinations necessary to acquire General Education Development (GED) (Bureau of Economic Analysis, 2018). Unlike many other countries, the education system in the United States requires private funding to progress into the university level whether the funding is a result of scholarships, out-of-pocket spending, or the most common option which includes student loans (Bureau of Economic Analysis, 2018). Those who achieve a bachelor’s degree or higher are met with the lowest rates of unemployment and the highest rates of median annual income while those with an education below such threshold experiences higher unemployment and lower annual earnings probabilities.

Unlike the United States, China is a socialist republic that is operated by one unified group known as the Communist Party of China which utilizes Internal Reference to monitor and manage disagreements within the population (Thyne, n.d.). Post 1949, corruption in China is primarily attributed to the ruling party’s involution and its failure to adapt to changes instantiated by market liberalization reform (Thyne, n.d.). The red flag is symbolic of the people’s traditional color and the communist revolution which dominates the national infrastructure (World Atlas, n.d.). Of the 5 yellow stars, the largest represents the government while the four smaller ones are indicative of the population’s various social classes (World Atlas, n.d.). Close to 100 percent of the population holds basic health care coverage, yet public insurance typically covers less than half of all medical expenses. Despite this, the nation is beginning to implement requirements that state insurance will cover the vast majority of costs and plans to offer affordable care to all citizens by 2020 (Thyne, n.d.). Furthermore, the nation boasts the largest education system on the planet with more than 9 million students participating in the National Higher Education Entrance. Investment into this field also accounts for nearly 4 percent of the country’s GDP (Thyne, n.d.).

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The U.S. economy slowed down in the first three months of 2024, report shows

Scott Horsley

The U.S. economy grew more slowly than expected in the first three months of the year. But consumers are still spending money — especially on services such as travel and restaurant meals.

SCOTT DETROW, HOST:

But first, the U.S. economy downshifted the first three months of this year. The government report out today shows the economy grew less than half as fast in the first quarter as it did during the previous three months. The news triggered a sell-off in the stock market. The Dow Jones Industrial Average tumbled 375 points. NPR's Scott Horsley joins me now. Hey, Scott.

SCOTT HORSLEY, BYLINE: Hi - good to be with you.

DETROW: So investors were not happy about the slowdown. How big of a concern is this?

HORSLEY: Today's report shows the economy grew at an annual rate of just 1.6% in the first quarter. That is a marked downshift from the previous quarter, when we grew at nearly 3.5%. But, you know, that headline figure may overstate just how hard we hit the brakes. Some of the drop-off came from one-time factors, which really don't tell us much about the underlying economy.

If you zoom in on consumer spending, which is the biggest driver of economic growth, that actually held up pretty well. Americans did spend less on big-ticket items like cars and furniture in the first three months of the year. Those things are often financed, so high interest rates are likely taking a toll. But economist Shannon Grein of Wells Fargo notes people continue to ramp up their spending on services like restaurant meals and travel.

SHANNON GREIN: I think the overall report was still consistent with an economy that's pretty much firing on all cylinders.

HORSLEY: Indeed, services spending rose at an annual rate of 4% in the first quarter, which is fast enough to keep the economy chugging along and potentially fast enough to put some upward pressure on inflation. In fact, today's report shows a key measure of inflation ticked up in the first quarter, so that's something the Federal Reserve is going to be keeping a close eye on.

DETROW: And, of course, they've been keeping interest rates high. How are people paying for all of this spending?

HORSLEY: You know, some people are relying on credit to finance their spending, which is costly if you don't pay off that balance every month. But a lot of this spending is being bankrolled by people's paychecks. You know, we still got a very strong labor market. Lots of people are working. Wages are going up. And most people are not saving a lot of what they earn, so that money's going right back out the door as spending.Today's report also shows business investment held up pretty well in the first quarter, and there was a surprisingly big jump in housing investment.

DETROW: Yeah. That was interesting, especially since, as we've been saying throughout the conversation, mortgage rates are still pretty high. What's going on there?

HORSLEY: Yeah. Those high mortgage rates are definitely dragging down the housing market. Sales of existing homes are down, and there aren't a lot of older homes on the market, but that's giving an unexpected boost to new home construction. Investment in new homes was way up in the first quarter. Shawn Woods is a home builder in Kansas City. He says about 1 out of 3 homes sold in that area is now newly built.

SHAWN WOODS: The inventory that people can find for a new home is new construction, which is great for us as homebuilders, helping out our sales a lot. March and April have been really good months. We're looking for continued good momentum through the spring.

HORSLEY: Woods and other home builders have also been downsizing some of their homes, maybe cutting back on some of the luxury finishes in order to craft a product that home buyers can afford.

WOODS: Before the pandemic, there's no way we could get under really 325,000, and we have reengineered some of our plans, taken different specifications and things like that. And we're bringing new homes to the market now in the 286 to 290 range, starting price. So that's helped immensely.

HORSLEY: That's especially important now that mortgage rates are up above 7%.

DETROW: That's NPR's Scott Horsley. Scott, thanks so much.

HORSLEY: You're welcome.

Copyright © 2024 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.

NPR transcripts are created on a rush deadline by an NPR contractor. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.

• CBSE Notes For Class 10
• Class 10 Social Science Geography
• Chapter 7 Lifelines Of National Economy

CBSE Notes Class 10 Geography Chapter 7 - Lifelines of National Economy

The pace of development of a country depends upon the production of goods and services as well as their movement over space. Today, the world has been converted into a large village with the help of efficient and fast-moving transport. Today, India is well-linked with the rest of the world. In CBSE Notes Class 10 Geography Chapter 7 – Lifelines of National Economy, you will see how modern means of transport and communication serve as lifelines of our nation and its modern economy.

• Chapter 1 Resources and Development
• Chapter 2 Forest and Wildlife Resources
• Chapter 3 Water Resources
• Chapter 4 Agriculture
• Chapter 5 Minerals and Energy Resources
• Chapter 6 Manufacturing Industries

CBSE Notes Class 10 Geography Chapter 7 – Lifelines of National Economy

The movement of goods and services can be over three important domains of our earth, i.e., land, water and air. Based on these, transport can also be classified into land, water and air transport. Let’s discuss them in detail.

India has one of the largest road networks in the world, aggregating about 54.7 lakh km. The growing importance of road transport over rail transport is mentioned below:

• The construction cost of roads is much lower than that of railway lines.
• Roads can cover more geographically harder locations that cannot be done by the railways.
• Roads can negotiate higher gradients of slopes and can be easily built-in traverse mountains such as the Himalayas.
• Road transport is economical.
• It also provides door-to-door service.
• Road transport provides links between railway stations, air and seaports.

In India, roads are classified into the following six classes according to their capacity.

Golden Quadrilateral Super Highways

Golden Quadrilateral is a network of Highways connecting India’s four top metropolitan cities, namely Delhi, Kolkata, Chennai, and Mumbai. These highway projects are being implemented by the National Highway Authority of India (NHAI).

National Highways

The National Highways are a network of trunk roads that are laid and maintained by the Central Public Works Department (CPWD). The historical Sher-Shah Suri Marg is called National Highway No.1, between Delhi and Amritsar.

State Highways

Roads linking a state capital with different district headquarters are known as State Highways. These roads are constructed and maintained by the State Public Works Department (PWD).

District Roads

These roads connect the district headquarters with other places in the district. These roads are maintained by the Zila Parishad.

Other Roads

Rural roads, which link rural areas and villages with towns, are classified under this category. These roads received special impetus under the Pradhan Mantri Grameen Sadak Yojana.

Border Roads

Border Roads Organisation constructs and maintains roads in the bordering areas of the country. This organisation was established in 1960 for the development of roads of strategic importance in the northern and north-eastern border areas.

Roads can also be classified on the basis of the type of material used for their construction, such as:

• Metalled roads may be made of cement, concrete or even bitumen or coal. These are all-weather roads.
• Unmetalled roads go out of use in the rainy season.

Railways are the principal mode of transportation for carrying huge loads and bulky goods for long and short distances in India. Railways have become more important in India’s economy. However, rail transport suffers from certain problems as well, which are mentioned below:

• Construction of bridges is required across rivers’ wide beds for laying down the railway lines.
• In the hilly terrains of the peninsular region, railway tracks are laid through low hills, gaps or tunnels.
• The Himalayan mountainous regions are also unfavourable for the construction of railway lines due to the highest elevation points in the surface, sparse population and lack of economic opportunities.
• It is difficult to lay railway lines on sandy plains.

A pipeline network uses pipes, usually underground, to transport and distribute fluids. These are used to transport water, crude oil, petroleum products and natural gas, fertilizer factories and big thermal power plants. Solids can also be transported through a pipeline when converted into a slurry.

There are 3 important networks of pipeline transportation in the country.

• From oil field in upper Assam to Kanpur (Uttar Pradesh)
• From Salaya in Gujarat to Jalandhar in Punjab
• From Hazira in Gujarat to Jagdishpur in Uttar Pradesh

Waterways are the cheapest means of transport. They are most suitable for carrying heavy and bulky goods. It is a fuel-efficient and environment-friendly mode of transport.

The National Waterways in India are:

• N.W. No.1 – The Ganga River between Allahabad and Haldia (1620 km).
• N.W. No.2 – The Brahmaputra River between Sadiya and Dhubri (891 km).
• N.W. No.3 – The West-Coast Canal in Kerala (Kottapurma-Kollam, Udyogamandal and Champakkara canals-205 km).
• N.W. No.4 – Specified stretches of Godavari and Krishna rivers along with the Kakinada Puducherry stretch of canals (1078 km).
• N.W. No.5 – Specified stretches of river Brahmani along with Matai river, delta channels of Mahanadi and Brahmani rivers and East Coast Canal (588 km).

Inland waterways in India are Mandavi, Zuari and Cumberjua, Sunderbans, Barak and the backwaters of Kerala through which transportation takes place.

Major Sea Ports

India’s trade with foreign countries is carried from the ports. There are 2 major and 200 notified non-major (minor/intermediate) ports in India.

Here is the list of major ports in India:

• Kandla in Kachchh was the first port to be developed after independence. It is also known as the Deendayal Port.
• Mumbai is the biggest port with a spacious natural, and well-sheltered harbour.
• Marmagao Port (Goa) is the premier iron ore exporting port of India.
• Mangalore Port, located in Karnataka, caters to the export of iron ore.
• Kochchi is the extreme southwestern port located at the entrance of a lagoon.
• Tuticorin Port is situated in the extreme southeast.
• Chennai is one of the oldest artificial ports in India.
• Visakhapatnam is the deepest landlocked and well-protected port
• Paradwip Port, located in Odisha, specialises in the export of iron ore.
• Kolkata is an inland riverine port.
• Haldia port was developed as a subsidiary port in order to relieve growing pressure on the Kolkata port.

The airway is the fastest, most comfortable and most prestigious mode of transport. Air travel has made access easier to the terrain areas like high mountains, dreary deserts, dense forests and long oceans. Air transport was nationalised in 1953. Air India provides domestic and international air services.

Pawanhans Helicopters Ltd. provides helicopter services to Oil and Natural Gas Corporation in its off-shore operations in inaccessible areas and difficult terrains. But, air travel is not within the reach of the common people.

To know about the Smart Cities of India, watch the below video

Communication

The major means of communication in India are television, radio, press, films, etc.

The Indian postal network is the largest in the world. It handles parcels as well as personal written communications.

• First-class mail is airlifted between stations covering both land and air.
• Second-class mail includes book packets, registered newspapers and periodicals. They are carried by surface mail, covering land and water transport.

India has one of the largest telecom networks in Asia. Subscriber Trunk Dialling (STD) facilities all over India have been made possible by integrating the development of space technology with communication technology.

• Mass communication provides entertainment and creates awareness among people about various national programmes and policies. It includes radio, television, newspapers, magazines, books and films.
• India Radio Channel (Akashwani) broadcasts a variety of programmes in national, regional and local languages.
• Doordarshan, the national television channel, is one of the largest terrestrial networks in the world.
• India publishes a large number of newspapers in about 100 languages and dialects.

International Trade

The exchange of goods among people, states and countries is referred to as trade . Trade between two countries is called international trade . It is considered as the economic barometer for a country. Export and import are the components of the trade. The balance of trade of a country is the difference between its export and import.

• When the value of export exceeds the value of imports, it is called a favourable balance of trade .
• If the value of imports exceeds the value of exports, it is termed an unfavourable balance of trade .

The commodities exported from India to other countries include gems and jewellery, chemicals and related products, agriculture and allied products, etc.

The commodities imported to India include petroleum crude and products, gems and jewellery, chemicals and related products, base metals, electronic items, machinery, agriculture and allied products.

Tourism as a Trade

More than 15 million people are directly engaged in the tourism industry. Tourism in India:

• Promotes national integration
• Provides support to local handicrafts and cultural pursuits
• Helps in the development of international understanding of Indian culture and heritage. Foreign tourists visit India for heritage tourism, eco-tourism, adventure tourism, cultural tourism, medical tourism and business tourism.

We hope these  CBSE Class 10 Social Science Notes helped you in your studies. Keep learning and stay tuned for more updates on CBSE and NCERT. Download the BYJU’S App and subscribe to the YouTube channel to access interactive maths and science videos.

Frequently Asked Questions on CBSE Class 10 Geography Notes Chapter 7 Lifelines of Natural Economy

What is the meaning of ‘economy’.

An economy is a large set of interrelated production and consumption activities that aid in determining how scarce resources are allocated.

When was the Indian postal service started?

Warren Hastings had taken the initiative under the East India Company to start the Postal Service in the country in 1766.

What is the meaning of ‘International trade’?

International trade is the exchange of capital, goods, and services across international borders or territories because there is a need or want of goods or services.

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