literature review in unemployment

Systematic Literature Review: Unemployment Rate as factors affecting the Gross Domestic Product, Inflation Rate, and Population

11 Pages Posted: 1 Jun 2022

Pauline Dela Cruz

World Citi Colleges

Marmelo V. Abante

World Citi Colleges - Quezon City - Graduate School Department

Florinda Garcia-Vigonte

Bulacan State University; World Citi Colleges - Quezon City - Graduate School Department

Date Written: May 27, 2022

Unemployment is one idea that explains how economies' production structures, sectoral developments, and regional and national developments. Covid-19 affects the unemployment rate, GDP, Inflation Rate, and Population. This is a systematic literature review, and the researcher used PRISMA in determining the literature used in this study. Out of 101 related topics in google scholar, only 6 were selected in this study. The COVID-19 health crisis is a great shock that is making a change in the lives and livelihoods of individuals around the globe. Apparently, and unfortunately, the pandemic reversed some of these gains. It wiped out 1.7 million wages and salary jobs in just 12 months until January 2021. The pandemic caused and created long-lasting effects on employment. Thus, it created a big impact on the economy. A phenomenon is known as hysteresis employment. Moreover, three transmission channels of the pandemic on modern employment have been listed: A higher number of job seekers-like those who lost jobs, dropouts from school, and new labor markets entrants that remain unemployed; next is the large re-allocation of job sectors; and companies that are modifying their businesses that rely on the uses of technology. These will exacerbate further the skill mismatch in the labor market. The methodology used a systematic literature review, wherein inclusion and exclusion criteria are set to narrow the research to studies for comprehensive analysis. The inclusion criteria were: 1) They were published between 2017 and 2022) they were published as an academic journal, 3) they were written in the English language, 4) they were original or empirical studies, and 5) the studies are focused on the analysis on how the Gross Domestic Product, Inflation rate, and population affects the Unemployment rate. The exclusion criteria were as follows: 1) Excluding the duplicated studies. 2) Excluding non-English studies. 3) Excluding studies that did not focus on the unemployment rate. The literature search was limited to 2017-2022. Hence, J D Urrutia et al. (2017) demonstrate that only the inflation rate, out of the five independent variables, has no significant link with the dependent variable, with a p-value of 0.178, which is more than the level of significance of 0.01 if the null hypothesis is accepted there is no significant relationship between the dependent and independent variable. Meanwhile, GDP shows a negative connection with the Unemployment Rate but a significant linear association with the unemployment rate based on their Pearson coefficient of determination (J D Urrutia et al., 2017). Moreover, the population shows a negative connection with the Unemployment Rate but a significant linear association with the unemployment rate based on their Pearson coefficient of determination (J D Urrutia et al., 2017). SARIMA (6, 1, 5) x (0, 1, 1) 4 is the formulated model for estimating and forecasting the unemployment rate in the Philippines. Forecasted values are within six to eight percent of actual values, and they are shown to be 72 percent accurate. Important determinants of the unemployment rate, Labor Force Rate, and Population are discovered. In addition, the dependent variable is Granger-caused by population, GDP, and GNI. These factors can influence the unemployment rate. Any change in those factors can cause the unemployment rate to rise or fall (J D Urrutia et al., 2017). When unemployment falls, disposable income grows, demand rises, and prices rise.

Keywords: Unemployment rate, Gross Domestic Product, Population, and Inflation rate

JEL Classification: A10

Suggested Citation: Suggested Citation

Pauline Dela Cruz (Contact Author)

World citi colleges ( email ).

Philippines

World Citi Colleges - Quezon City - Graduate School Department ( email )

Bulacan state university ( email ).

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Analysis of the COVID-19 impacts on employment and unemployment across the multi-dimensional social disadvantaged areas

This is the study of economic impacts in the context of social disadvantage. It specifically considers economic conditions in regions with pre-existing inequalities and examines labor market outcomes in already socially vulnerable areas. The economic outcomes remain relatively unexplored by the studies on the COVID-19 impacts. To fill the gap, we study the relationship between the pandemic-caused economic recession and vulnerable communities in the unprecedented times. More marginalized regions may have broader economic damages related to the pandemic. First, based on a literature review, we delineate areas with high social disadvantage. These areas have multiple factors associated with various dimensions of vulnerability which existed pre-COVID-19. We term these places “ multi-dimensional social disadvantaged areas ”. Second, we compare employment and unemployment rates between areas with high and low disadvantage. We integrate geospatial science with the exploration of social factors associated with disadvantage across counties in Tennessee which is part of coronavirus “red zone” states of the US southern Sunbelt region. We disagree with a misleading label of COVID-19 as the “great equalizer”. During COVID-19, marginalized regions experience disproportionate economic impacts. The negative effect of social disadvantage on pandemic-caused economic outcomes is supported by several lines of evidence. We find that both urban and rural areas may be vulnerable to the broad social and economic damages. The study contributes to current research on economic impacts of the COVID-19 outbreak and social distributions of economic vulnerability. The results can help inform post-COVID recovery interventions strategies to reduce COVID-19-related economic vulnerability burdens.

1. Introduction: social disadvantage

Pandemics create severe disruptions to a functioning society. The economic and social disruptions intersect in complex ways and affect physical and mental health and illness ( Wu et al, 2020 ). Additionally, loss of jobs, wages, housing, or health insurance, as well as disruption to health care, hospital avoidance, postponement of planned medical treatment increase mortality, e.g., premature deaths ( Kiang et al., 2020 ; Petterson et al., 2020 ). The COVID-19, misleadingly labelled the “great equalizer” implies everyone is equally vulnerable to the virus, and that the economic activity of almost everyone is similarly impacted regardless of social status ( Jones & Jones, 2020 ). We set out to answer whether economic vulnerability is equally distributed during the COVID-19-caused economic recession or whether is it based on structural disadvantages? Is the social distribution of economic vulnerability magnified in regions with pre-existing social disparities, thus, creating new forms of inequalities? Knowledge of what areas experience the greater economic burden will help identify the most economically vulnerable communities relevant to post-COVID recovery interventions ( Qian and Fan, 2020 ).

Current studies on the impacts of COVID-19 largely focus on medical aspects including the COVID diagnosis and treatment ( Cai et al., 2020 ; Kass et al., 2020 ; O’Hearn et al., 2021 ; Price-Haywood et al., 2020 ). Non-medical urban research primarily concentrates on the impact of COVID on cities by studying factors related to environmental quality including meteorological parameters, and air and water quality ( Sharifi and Khavarian-Garmsir, 2020 ). COVID-related socio-economic impacts on cities are relatively less well studied, especially during the later stages of the recession.

Many pre-pandemic disparities unfold during COVID-19. To illustrate, residents of Black and Latino communities are suffering disproportionately higher unemployment rates, greater mortality due to the COVID-19 ( Thebault, Tran, & Williams, 2020 ; Wade, 2020 ), higher hospitalizations ( O’Hearn et al., 2021 ) and financial troubles. In contrast, some attributes make persons and communities more resilient. In China’s context, these include higher worker education and family economic status, membership in Communist Party, state-sector employment, and other traditional markers. These factors protect people from the pandemic-related financial stress and diminish its adverse economic effects ( Qian and Fan, 2020 ). Building on these recent studies on economic impacts, this social justice research focuses on areas with pre-existing social disadvantages. We study the role of social disadvantage and its impact on labor market during the COVID.

The distribution of economic vulnerability may potentially be related to COVID-19 conditions including those of economic burdens for people living in the pandemic epicenters ( Creţan and Light, 2020 ). Similarly, socio-economic disruptions create “a characteristic mosaic pattern in the region” ( Krzysztofik et al., 2020 , p. 583). The disruptions are strongly correlated with the spatial distribution of the COVID-19-related health effects. This study is set in Tennessee which is part of coronavirus “red zone” states of the US southern Sunbelt region. It is among the U.S. states with the highest rates of cases per capita, with 137,829 cases per 1 million people, or the 6th highest as of August 13, 2021 ( Worldometers, 2020 ; https://www.worldometers.info/coronavirus/country/us/ ). The study seeks to explore the impacts of social disadvantage on economy. The impact is measured by employment and unemployment in unprecedented times in the US context of prolonged disruptions to the health system, society, and economy intersecting in complex ways ( Kiang et al., 2020 ). We answer the following questions: (1) Do communities with high social disadvantage already burdened pre-COVID-19 by the lack of income, healthcare access, lacking resources, have less jobs available during the COVID-19 pandemic? (2) Do these areas simultaneously experience higher unemployment compared with other areas in the context of the pandemic?

The paper is organized as follows: Section 1 introduces the topic, provides the background information on social disadvantage and a brief description of the study implementation. It further discusses the links between employment and unemployment, and coronavirus, respectively, and introduces the study area. Section 2 describes in detail materials and methods used in the study. Section 3 provides the theory and calculations. Section 4 reports the results, and Section 5 offers a discussion. Finally, the paper concludes with conclusions found in Section 6 .

1.1. Background

Certain socio-economic and demographic conditions burden some communities more than others including racial and ethnic minorities, lower-income groups, and rural residents. The conditions include lacking economic opportunities and other inequalities ( Petterson et al., 2020 ) caused by social environment. Prior to the pandemic, it was challenging to live in areas with high social disadvantage where residents already have increased vulnerability to poor health due to greater psychosocial stress such as discrimination, unhealthy behaviors, and poorer health status ( Hajat et al., 2015 ). This is true for poor, marginalized communities elsewhere as spatial segregation of disadvantaged and marginalized communities decreases life opportunities for their members who have limited relationships with broader communities ( Méreiné-Berki et al., 2021 ). Within the context of studying disadvantaged urban communities, a recent work by Creţan et al. (2020) focused on the everyday manifestations of contemporary stigmatization of the urban poor using the case study of the Roma people who have been historically subject to state discrimination, ghettoization, inadequate access to education, housing, and the labor market for many decades in the past in multicultural urban societies of Central and Eastern Europe. The inequalities may persist and even increase if left unaddressed during pandemics ( Wade, 2020 ) leading to stark COVID-19-related health and economic disparities. Indeed, during the COVID-19, economic impacts of the pandemic disproportionately affect marginalized groups. The impact of coronavirus was harsh for those people as many of the already existing disparities unfold during COVID-19: black communities in the United States are disproportionately affected by higher death rates due to the COVID-19 virus ( Thebault et al., 2020 ), unemployment, and financial stress. Other growing COVID-19 research similarly suggests that elsewhere outside of the United States, areas that were disadvantaged prior to the pandemic with high rates of poverty and unemployment tended to be affected the strongest by the COVID-19 with the largest concentration of cases, while other spatially segregated ethnicity-based communities (e.g., the Roma) that have been vulnerable decades prior to COVID-19, saw an increase in the existing discrimination and stigmatization experiencing greater marginalization even during the current COVID-19 pandemic period ( Crețan & Light, 2020 ).

To achieve greater economic stability, and secure a dynamic labor market, countries in the global north and south for several decades have been increasing service employment much of which is low wage. The recent book Corona and Work around the Globe ( Eckert and Hentschke, 2020 ) describes the tremendous impact of the pandemic on human life and livelihoods as it sheds light on various experiences of workers during COVID-19 in various countries. Among the dramatically different cases worldwide, Germany which for decades has been promoting the low-wage sector to combat unemployment, provides a good example. The official approach to handling a disease differed substantially depending on whether the infected individuals were working people from the low- or upper-wage sector of the economy: applying a strict lockdown to the entire high-rise building where ethnic workers lived and preventing them from going to work in the former case and granting permission to work from home in the latter ( Mayer-Ahuja, 2020 ). The plight of the agricultural migrant workers who come to Germany from Eastern and Southeastern Europe, subjected during the pandemic to low wages or no payments and poor working and living conditions, however, is shared among the workers of low-wage sector across all countries who are more likely to get infected due to higher exposure and direct contact, but often experience unfair treatment based on ethnicity, migration and class status.

In yet another case set in the U.K., disadvantaged households have experienced intensified disadvantage during the COVID-19 as they could not access vital necessities, already stretched for resources pre-COVID-19. As provision of services or employment was discontinued due to their closure, disadvantaged households had significant impacts on their income level, mental health and wellbeing, education, nutrition, and domestic violence. In the absence of the key support of public institutions including schools, community centers, and social services, care for the most vulnerable members such as elderly, children, the disabled, have been absorbed by households ( Bear et al., 2020 ).

Another aspect experienced by workers during the pandemic is the total loss of earnings which is especially harsh in places with precarious employment even under normal circumstances. Informal workers in India who represent the vast majority of working population (over 93%), with no social security benefits and absent job security, experienced prolonged periods of time of no work due to lockdown and suspended transport services preventing them from getting to their workplaces, many on the verge of starvation ( Banerjee, 2020 ). This study looks into this aspect of COVID-19 economic impacts and confirms the findings of the growing COVID-19 research.

However, not only the poorest and marginalized people, but also marginalized regions are more likely to suffer from broader social and economic damages related to the pandemic compared with more privileged areas ( Creţan and Light, 2020 ; Krzysztofik et al., 2020 ). When disadvantages combine, it may lead to environment-driven COVID-19-related disparities in health. Besides a direct health effect, disadvantaged communities are disproportionally experiencing other side effects of COVID-19 such as negative labor market outcomes including forced unemployment, loss of income and social isolation. Studies found the extreme vulnerability of cities and urban areas exposed during the global pandemic ( Batty, 2020 ; Gössling et al., 2020 ). We argue that rural areas may be equally vulnerable to the broad range of social and economic damages if there is a spatial concentration of factors related to various dimensions of vulnerability.

This study is situated in the context of social disadvantage. Prior studies developed the methodology of the delineation of disadvantaged residential communities proxied by low-income workers ( Antipova, 2020 ). Disadvantaged low-income workers can be defined as those with inadequate access to material and social resources in the study area. However, this is a narrow approach which uses only a single dimension of a disadvantage, that of worker low earnings and misses other social inequality indicators. Accordingly, an approach adopted in this study identifies areas where socio-economic and demographic attributes each associated with multiple dimensions of social disadvantage are spatially co-locating. Spatial segregation of disadvantaged and marginalized communities decreases life opportunities for their members who have limited relationships with wider communities ( Méreiné-Berki et al., 2021 ). We identify these attributes based on a thorough literature review. Thus, we simultaneously consider multiple factors associated with disadvantage capturing a multi-dimensional social disadvantage. To meet the objective, we integrate geospatial science with the exploration of predictive geographic and social factors associated with disadvantage across counties in TN. The geospatial analysis includes point interpolation within the Geographic Information System (GIS) environment for the generation of a surface from a sample of social disadvantage values. This allowed us to visualize the spatial extent of disadvantaged communities. The focus is on labor market outcomes which are important indicators of society well-being. We study the association between pre-existing inequalities and COVID-19-related employment and unemployment rates. Thus, we identify the role of social disadvantage on labor market conditions in the context of the ongoing pandemic-caused economic recession.

Prior research determined the key metrics of social disadvantage. Conditions contributing to various aspects of disadvantage include poverty, occupations with low earnings, low rent, segregation and discrimination-related residential concentrations of minorities, and exposure to poor air quality ( Bullard, 2000 ). The recent COVID-19-related literature focuses on the separate effect of minorities, Hispanics, crowded households, dense areas, obesity, poverty, air pollution exposure and identifies those as important COVID-19 health risk factors ( Finch & Hernández Finch, 2020 ; Golestaneh et al., 2020 ; Han et al., 2020 ; Millett et al., 2020 ). These community-level variables result in neighborhood disadvantage comprising sub-standard housing quality, crowded conditions, poverty- and violence-caused stress which combined increase the risk of disease and other negative outcomes in life among socially disadvantaged groups ( Malhotra et al., 2014 ). The demographic and socio-economic attributes selected to represent the various aspects of social disadvantage in this research include minorities and ethnicities, poverty, housing crowdedness, educational attainment, underlying population health conditions, and pre-COVID-19 unemployment which may collectively drive a greater vulnerability to the COVID-19 infection and mortality as well as loss in employment and higher unemployment. It is challenging to isolate the separate effects of the multiple risk factors. By “critically analyzing the theoretically intended meaning of a concept” ( Song et al., 2013 ), a composite variable can be created to logically represent a multi-dimensional social disadvantage .

The following subsection briefly describes study implementation. First, we locate areas of disadvantage where multiple factors associated with various aspects of disadvantage co-locate spatially and term these places “multi-dimensional social disadvantaged areas”. Then, we examine how employment and unemployment were impacted in these already socially vulnerable areas. We map geographical inequalities in employment and unemployment rates during the period of COVID-19-related economic recession. For the first objective, we identify socially disadvantaged counties within TN which is part of coronavirus “red zone” states of the US southern Sunbelt region applying consistent criteria. For the second objective, we compare employment and unemployment outcomes between areas with high and low disadvantage.

1.1.1. Employment and coronavirus

This subsection discusses the role of employment and how it was impacted by the COVID-19-caused economic recession. The literature recognizes the complex interrelationship between employment and overall health and well-being. Negative COVID-19 impacts on urban economy include loss of citizens' income, while movement restrictions and ‘stay home’ measures adversely impacted tourism and hospitality and small- and medium sized businesses due to the closure of markets, food outlets and social spaces ( Wilkinson et al., 2020 ).

Millions of essential or blue-collar workers are still doing their jobs out of necessity and because they cannot telecommute and work jobs that cannot be done from home and have higher exposure to the virus. Some racial groups disproportionally have jobs that do not allow them to work from home and where social distancing is a challenge. Prior studies find that workplaces of low-income individuals tend to be close to their residential spaces, and disproportionately concentrated in lower-wage industries such as hospitality and retail services ( Antipova, 2020 ). These industries commonly represent essential services experiencing higher exposure to the COVID virus through workplaces. At the same time, minorities and lower-income groups often live in inner-ring suburbs with older housing and aging infrastructure ( Antipova, 2020 ) in multiunit structures and in multigenerational households which inhibit the ability to practice social distancing increasing the risks of disease occurrence and deaths ( Qualls et al., 2017 ). In addition, minorities and lower-income groups have fewer options for protecting both their health and economic well-being ( Gould and Wilson, 2020 ). Nearly two-thirds of Hispanic people (64.5%) considered at high risk for coronavirus live with at least one person who is unable to work from home, compared to 56.5% of black and less than half (47%) of white Americans, according to a recent study ( Selden and Berdahl, 2020 ).

Despite the pandemic-induced layoffs, job hires have occurred by major retailers such as Walmart and e-commerce giant Amazon, and takeout and delivery-based services such as Domino’s Pizza and Papa John’s which may become permanent positions. These workplaces may match the job skill sets of low-income residents of vulnerable communities. However, oftentimes many low-income workers benefitted less, even when jobs were created during the COVID-19. To illustrate, big technology companies (i.e., communication services: Netflix, Tencent, Facebook, T-Mobile; information technology: Microsoft, Nvidia, Apple, Zoom Video, PayPal, Shopify; consumer discretionary: Amazon, Tesla, Alibaba, etc.) prospered in the pandemic with the financial success measured by equity value added ( Financial Times, 2020 ). Workers who lost jobs in low-income segment such as hospitality sector may be hired by retailers such as Kroger or CVS. However, many others from the communities with high social disadvantage may not have a skill set needed at technology firms that benefit from the working from home trend and hire skilled workers including software engineers and product designers. Cross-industry employment shifts plays a minor role in total job creation, while employer-specific factors primarily account for job reallocation ( Barrero et al., 2020 ).

1.1.2. Unemployment and coronavirus

This subsection discusses how unemployment was impacted by the COVID-19-caused economic recession. An economic recession occurs when there is a substantial drop in overall economic activity diffused throughout the economy for longer than a few months. While past recessions were driven by an inherently economic or financial shock, the current recession is caused by a public health crisis ( Weinstock, 2020 ). COVID-19 caused a drop in consumer demand across all industrial sectors resulting in economic recession and massive unemployment where not only hourly workers but salaried professionals lost their jobs ( Petterson et al., 2020 ). A range of factors contributed to the spatial variation in economic damage including the share of jobs in industries delivering non-essential services to in-person customers ( Dey and Loewenstein, 2020 ), declines in personal consumption caused by individual fears of contracting COVID-19 ( Goolsbee and Syverson, 2020 ), and the implementation of social policies including stay-at-home orders and business shutdowns ( Gupta et al., 2020 ).

Unemployment rate is defined as a percentage of unemployed workers in the total labor force. The rate is published monthly by the Bureau of Labor Statistics (BLS) which uses both the establishment data (captured by the Current Employment Statistics program) and household surveys (Current Population Survey) to generate the labor market data ( Bureau of Labor Statistics (BLS), 2020b ). A person is unemployed if they were not employed during the survey’s reference week and who had actively searched for a job in the 4-week period ending with the reference week, and were presently available for work ( BLS, 2020b ).

Caused by the COVID-19, the unemployment rate reached a peak in April 2020 at 14.7% nationwide, an unprecedented joblessness amount since employment data collection started in 1948. It exceeded the previous peaks during the Great Recession and after ( Falk et al., 2020 ). The official unemployment rate may have been over 20%, since the actual level of joblessness could have been understated due to local unemployment rate measurement errors ( Coibion et al., 2020 ). In addition, the unemployment rate was understated due to a geographically widespread misclassification of those who was not at work but considered employed and non-inclusion of labor force non-participants who still counted as employed ( Bureau of Labor Statistics (BLS), 2020a ). Further, the COVID-19 caused the rapid rate of change in unemployment at the national level challenging accurate forecast of the monthly unemployment rate ( Weinstock, 2020 ).

Overall, current unemployment (using the most recently available county-level data at the time of writing for December 2020) is still elevated and is almost twice as high as it was back in February 2020 which represented the business cycle peak with the peak of payroll employment. March 2020 was the first month of the subsequent current economic recession as declared by The National Bureau of Economic Research (NBER, 2020) caused by the COVID-19 pandemic which turned out the worst downturn after the Great Recession. As Fig. 1 shows using the Current Population Survey data (Series ID: LNS14000000) from the BLS, during the prior recessions the unemployment rate rose gradually reaching its peak, and in the pandemic-caused recession it increased unprecedentedly to its peak over one month, from March 2020 to April 2020 by 10.3% (from 3.5% in February 2020 to 4.4% in March 2020 to 14.7% in April). After that, the rate declined as workers continued to return to work to 6.3% in December 2020.

U.S. Historical unemployment rate for workers 16 years and over, January 1948 to December 2020, % (seasonally adjusted).

Some communities can absorb the impact of economic downturns due to more favorable economic and social factors protecting residents from adversity. Yet other communities are witnessing the effect of rising unemployment in the time of COVID-19. Loss of income and livelihood has further effects: as wages drop, more people are forced into poverty while simultaneously people's health is impacted. Unemployment impacts all-cause mortality. Fig. 2 presents the dynamics of unemployment distribution across counties in TN for the selected months. Shown are pre-COVID-19 unemployment rates as of August 2019 ( Fig. 2 a), followed by May 2020 ( Fig. 2 b) where even the lowest levels of unemployment exceed the highest rates of the pre-pandemic period even in wealthy counties around Nashville (seen in the legend entries), August 2020 ( Fig. 2 c), and September 2020 ( Fig. 2 d). The overall unemployment abates somewhat during the later stage, and the general spatial pattern resembles that of the pre-COVID-19 period with higher unemployment concentrated in the southwestern corner of the state around Memphis.

Dynamics of unemployment rate across counties in TN for selected months: (a) August 2019, (b) May 2020; (c) August 2020; (d) September 2020.

1.1.3. Study area

Tennessee is home to large cities including Nashville (the county seat), Memphis, Knoxville and Chattanooga. Despite urban diversified economy, there was a steep decline in the number of international and domestic tourists impacting urban economy. Among cities listed above, Memphis, located in Shelby County, is a shrinking city with a declining population base. Urban shrinkage makes cities more vulnerable due to very negative impacts on urban economy. Shrinking cities are characterized by higher unemployment rates, depopulation (as people with higher economic and social status leave elsewhere), and a higher share of older people (increasing a share of individuals with underlying health conditions) ( Haase et al., 2014 ; Hartt 2019 ; Hoekveld 2012 ; Krzysztofik et al., 2020 ). The shrinking cities have higher exposure to extreme socioeconomic phenomena, including financial stress due to the decreases in the city’s budget. Decreasing budget in its turn has further urban development implications since implementation of some plans deemed of lesser priority such as environmental and cultural may be delayed and cancelled altogether ( Kunzmann, 2020 ; Sharifi and Khavarian-Garmsir, 2020 ).

Tennessee is one of the US southern Sunbelt states which had infection surges since summer 2020 due to the aggressive push for economy opening by then-President Trump administration. The pandemic has affected unemployment for every state in the United States ( Falk et al., 2020 ). Fig. 3 portrays selected industries impacted by the economic recession in Tennessee using seasonally adjusted data on employees on nonfarm payrolls for November 2019 (as a base period), September–November 2020. Unemployment rates concentrate disproportionately in sectors providing in-person non-essential services where some demographic groups are overrepresented. This results in substantially higher unemployment rates for those workers ( Cortes and Forsythe, 2020 ; Fairlie, 2020 ). Accordingly, it can be seen in Fig. 3 that in Tennessee, among the reported industries, leisure and hospitality has suffered the most, followed by jobs in government, education and health services, professional and business services, and trade, transportation, utilities. There was a slight increase in jobs in financial activities from 2019 to 2020 ( Bureau of Labor Statistics (BLS), 2020a ). The hardest hit industries tend to employ demographic groups such as women, minorities, low-income workers, and younger workers who have experienced greater job losses ( Murray and Olivares, 2020 ).

Employees on nonfarm payrolls by selected industry sector, seasonally adjusted, in TN.

2. Materials and methods

In the absence of fine-scale monthly data on employment and unemployment, we sourced county-level data from the Bureau of Labor Statistics (BLS) to track monthly changes in employment and unemployment in Tennessee (retrieved from https://www.bls.gov/lau/ ). Labor force data were extracted from this official primary source.

We used a comparative assessment approach to analyze the COVID-19-based labor market outcomes including the rates of COVID-19-related employment and unemployment attributable to social disadvantage conditions. For this, we stratify data based on community disadvantage status, and combine data in a comparative assessment framework. We proceed and identify disadvantaged communities using the methodology described below. Next, we test the hypothesis that in areas with high social disadvantage where more essential workers are more likely to reside, the unemployment is higher while employment opportunities are lower by comparing unemployment and employment rates within these communities to those of more privileged communities.

3. Theory/calculation

We focus on the areas where the multiple risk factors identified in the recent literature co-locate spatially and term these places “ multi-dimensional social disadvantaged areas ”. We carried out a rigorous literature review of the variables to stand in for social disadvantage in this research. The following demographic and socio-economic factors have been selected to represent community’s vulnerability: (1) Minorities and ethnicity; (2) Crowded households; (3) Poverty; (4) Education; (5) Underlying medical conditions (obesity); and (6) Unemployment. For the 1st variable, minorities and ethnicity , we used percent minority population and Hispanic ethnicity as studies commonly use race and ethnicity as vulnerability metrics (as explained in Section 2 Background information). For the 2nd variable, crowded households , we used percent households that are multigenerational as an indicator of crowdedness, and thus, indicating area’s disadvantage with a high share of such households. For the 3rd variable, poverty , we chose percent of households below 100% of federal poverty level which is also known as the poverty line. It is an economic measure of income. The poverty guidelines are updated annually by the US Department of Health and Human Services to indicate the minimum income needed by a family for housing, food, clothing, transportation, and other basic necessities and to determine eligibility for certain welfare benefits. This measure was used because less affluent and less privileged households have fewer means and less access to various resources to cope with the effects of financial crises ( Pfeffer et al., 2013 ). Low-income households may be especially vulnerable to wage losses during the outbreak ( Qian and Fan, 2020 ). For the 4th variable, education , we used percent of population with less than high school diploma since lower educational attainment is an indicator of poverty and thus captures social disadvantage, while workers with better education have higher economic resilience when challenged with a large-scaled social shock ( Cutler et al., 2015 ; Kalleberg, 2011 ). For the 5th variable, underlying medical conditions , we used percent population with obesity as the top risk for COVID-19-related hospitalization. Supported by several lines of evidence, both domestically and internationally, obesity may predispose to more severe COVID-19 outcomes ( O’Hearn et al., 2021 ). Finally, for the 6th variable, unemployment , unemployment rate (averaged from August 2019 to January 2020 to adjust for seasonality) was used as a marker of overall vulnerability as it is linked to overall mortality. Further, regions with higher unemployment are more susceptible to business-cycle fluctuations, and thus, are more socially and economically vulnerable.

These socio-economic and demographic attributes (minority population, Hispanic ethnicity, federal poverty level, crowded households, adult obesity, lower educational attainment, and unemployment) have been used in this research to create a composite variable to represent a multi-dimensional social disadvantage (also referred to as vulnerability). Due to different variances in the original variables, we standardized them to prevent a disproportionate impact which may be caused by any one original variable with a large variance. The z-score transformation was applied by averaging the original variables and computing z scores with a mean of 0 and values ranging from negative to positive numbers ( Song et al., 2013 ).

Thus, the original variables were converted to z-scores to preserve the distribution of the raw scores and to ensure the equal contributions of the original variables. Next, we created a composite variable capturing a multi-dimensional social disadvantage. It was calculated by summing standardized z-scores of the original risk factors. The higher value can be interpreted as higher disadvantage while the lower value means more privileged communities. Based on the frequency distribution of values of the composite variable, we established a cut-off value for the composite variable to designate communities with high or low exposure to social disadvantage. We used the following method to determine the cut-off value of the composite variable. The values greater than 3.38 correspond to 1 standard deviation above the mean (or, the 88th percentile in the value distribution) indicating communities in the top 12 percent of social disadvantage and therefore, a higher share of factors contributing to disadvantage. This value was used to differentiate communities according to their disadvantage status. We identified twelve counties with high social disadvantage (N high  = 12), and other counties represent more privileged communities (N low  = 83). To test whether the taken approach correctly identifies disadvantaged communities, we conducted a Wilcoxon two-sample test for the variables of interest ( Table 1 ). We report the results of the estimates in the following section. The above socio-economic and demographic population characteristics come from the 2018 American Community Survey (ACS) 5-year data, an annual nationwide survey conducted by the US Census Bureau, available for various geographic units and applied for areal units within the study area ( U. S. Census Bureau, 2020 ).

Descriptive statistics.

The basic descriptive demographic and socio-economic characteristics of the TN population are shown in Table 1 . It includes the summaries for communities with high and low social disadvantage allowing to compare the variables of interest between these communities. The following variables are reported: percent African American, percent Hispanic, median income, percent of people over 25 years who are less than high school graduates, estimated percent of obese adults, percent households below 100% of federal poverty level, and percent of multi-generation households. The factors comprising social disadvantage were statistically significantly different than those extant in more privileged counties. Compared with the general TN population, the disadvantaged cohort was generally more likely to be of non-Hispanic Black race; more impoverished; with less educational attainment, more obese, and had more households with crowded conditions.

To visualize social disadvantage and show how it varies across the space, we used our sample of social disadvantage measurements and created a surface of social disadvantage within the study area using the Geographic Information System (GIS). The interpolated surface was derived from an Inverse Distance Weighted technique ( Watson and Philip, 1985 ). Fig. 4 presents the surface illustrating that both urban and rural counties in Tennessee are subject to social disadvantage.

Social disadvantage within the study area.

We examined how unemployment changed from August 2019 to December 2020. Currently, all counties have substantially higher unemployment compared with that prior to COVID. Fig. 5 presents the results of the Nonparametric One-Way ANOVA test showing the distribution of Wilcoxon scores for unemployment rate for all counties in Tennessee combined, regardless of social disadvantage status, for 17 months. A statistically significant difference is found for unemployment rates between the pre-COVID period and the period since April 2020, with current unemployment rates although decreased but still significantly higher compared with those prior to the recession.

Nonparametric One-Way ANOVA and distribution of Wilcoxon scores for unemployment rate for all counties combined for 17 months (August 2019–October 2020), regardless of social disadvantage status.

We compared employment and unemployment rates for Tennessee counties stratified by the type of social disadvantage separately for each month. Fig. 6 presents the average employment and unemployment rates by community disadvantage from August 2019 to December 2020 in a graphical form. The results of the non-parametric Wilcoxon test for employment and unemployment rates are presented in Table 2 . Pre-COVID and before the unemployment peak in April 2020, communities with high social disadvantage consistently had less jobs and greater unemployment, which we tested statistically and found a significant difference for both outcomes of the labor market between communities by their disadvantage status ( Table 2 ). Shown in Table 2 , in April and May 2020, during the peak of unemployment and immediately after, unemployment rates observed in both types of communities were high with no statistical difference. In June, the differences again became prominent, when there were more jobs available in more advantaged areas and employment rate remained consistently greater in areas with less disadvantage. Also in June, unemployment rate remained consistently greater in areas with higher disadvantage. This month saw the greater difference in both outcomes since the COVID-19 than pre-pandemic (supported by higher p-values). Compared with all TN population, residents of disadvantaged counties had less jobs available and were more likely to be unemployed during all periods except for April and May.

Mean employment and unemployment stratified by community disadvantage status.

Wilcoxon Two-Sample Test: Distribution of Wilcoxon scores in employment and unemployment rates by community disadvantage status by month (August 2019–December 2020).

We examined the percent change in both labor market outcomes. Fig. 7 presents the percent change in mean employment ( Fig. 7 a), and mean unemployment by community disadvantage ( Fig. 7 b). The percent change in employment and unemployment was relatively small in both types of community during the pre-COVID period. However, the overall fluctuations in both conditions were greater in communities with high social disadvantage (evidenced by a greater range between ups and downs for disadvantaged communities shown with the black-colored symbols). On the other hand, employment and unemployment were more stable in more privileged communities (shown with the grey-colored symbols in the Fig. 7 ). During the unemployment peak in April 2020, the change in percent employment was −11.5 points from the previous month even in more advantaged counties, while the unemployment in April increased by 10.42 percentage points in disadvantaged counties.

Percent change in (a) mean employment; (b) mean unemployment by community disadvantage.

We show how various factors of social disadvantage intersect and combined impact economic vulnerability measured by unemployment rate. Fig. 8 reports the link between unemployment and social disadvantage pre-COVID (unemployment rate was averaged over August 2019–January 2020 in Fig. 8 a), and during COVID (unemployment rate for November 2020 is shown in Fig. 8 b). During the COVID pandemic, its impact is even stronger as evidenced by a greater slope of the line of fit, larger coefficients, and a greater R-squared value ( Fig. 8 b). The strong relationship between these factors of social disadvantage and economic outcomes in COVID-19 might inform post-COVID recovery intervention strategies to reduce COVID-19-related economic vulnerability burdens. For example, in the light of findings on socio-economic and demographic subpopulations at a higher risk for economic damages, prioritization of economic relief distribution might be based on community disadvantage status targeting individuals from areas with existing inequalities to increase economic resilience of marginalized communities.

Unemployment and Social disadvantage: (a) pre-COVID (averaged August 2019–January 2020); (b) during COVID (November 2020).

5. Discussion

Current studies on the impacts of COVID-19 tend to focus on medical aspects while non-medical urban research mostly analyzes the role of environmental quality. To better understand the full effects of pandemics on communities and minimize the various impacts as well as to improved response, other aspects need to be examined. This includes studying less researched themes including socio-economic impacts consisting of both social impacts and social factors making individuals and communities less resilient and more vulnerable to the effects of the COVID. Additionally, economic impacts of the pandemic-caused recession so far remain relatively underexplored and need to be investigated ( Sharifi and Khavarian-Garmsir, 2020 ).

Communities are often severely segregated along wealth and social lines in developing and developed world ( Wilkinson et al., 2020 ). We study the role of social factors and the impact of the COVID on labor market conditions in Tennessee. Specifically, we studied the impacts of social environment on employment and unemployment through the concept of a multi-dimensional social disadvantage by using geospatial science.

A recent study identified factors which can make a community more vulnerable to the pandemic’s effects using as a case study the province of Silesia in Poland, one of the largest industrial and mining regions in Europe. Specialized functions such as mining-oriented industries, large care centers, polycentricity, and urban shrinkage make communities most at risk due to very negative impacts on urban economy ( Krzysztofik et al., 2020 ). Since vulnerability is always very context-specific, we found a combination of different causal factors of social disadvantage captured by a composite variable making communities most at risk during the COVID reflected in broader social and economic outcomes. In creating a composite variable to capture social disadvantage logically and meaningfully, the following variables were used: % African American, % Hispanic, % below 100% federal poverty level, % population with less than high school diploma (an indicator of poverty), % multi-generation households (an indicator of crowdedness), % estimated obese adults reporting to be obese with the BMI 30 or greater, % unemployed. The proposed method can be generalized beyond the study area and used as a tool by policy makers using consistent criteria for the delineation of areas carrying a greater risk for the more severe impact by the pandemic due to co-existence and co-location of the multi-dimensional social disadvantage factors which are more likely to experience further socio-economic disruptions.

Current urban research on COVID economic impacts found that some cities are more vulnerable than others and are most at risk. Cities with an undiversified economic structure with industries where a large number of workers are shoulder-to-shoulder share cramped spaces for a prolonged time and where social distancing is challenging (e.g., meat-packing and poultry processing plants), cities relying on tourism as well as cities that have large care centers, polycentric cities, and shrinking cities are the most vulnerable to negative impacts on urban economy. The urban hotel market, city tax revenues, citizens' income, tourism and hospitality, small- and medium sized firms, urban food supply chain, and migrant workers are all impacted ( Krzysztofik et al., 2020 ). Other recent studies similarly concluded that the COVID has revealed the extreme vulnerability of cities and urban areas disrupting tourism and affecting supply chains in cities ( Batty, 2020 ; Gössling et al., 2020 ). We support this statement but also find that rural areas can experience a broad range of social and economic damages related to COVID.

Before and during the COVID-19 period, money laundering, limitations of economic development, environmental pollution and uncontrolled deforestation, population displacement, institutional incompetence, and corruption of political elites have been debated including corruption and conflagration in Bucharest before the pandemic ( Creţan & O’Brien, 2020 ), as well as other contestations on selling masks and different medical products highlighted in different countries during the pandemic period. Following catalytic events, the affected community may respond to long-held concerns with demands to address these problems bringing about important changes to the systems. Marginalized stigmatized minorities may effectively overcome discriminatory laws, higher poverty and other constraints and influence public opinion and politics in their favor through collective action via various strategies including protests against corruption and the inaction of the political leaders in Romania in 2015 forcing the resignation of the Government, and protests in the US in the aftermath of police violence against black people have been documented ( Creţan & O’Brien, 2020 ; Fryer, 2019 ). During the COVID-19, the non-payment of wages and poor working and living conditions caused seasonal workers in Germany to protest against this unfair treatment, however, generating low coverage in the national press ( Mayer-Ahuja, 2020 ).

6. Conclusions

Some socio-economic and demographic conditions consistently and significantly impact some communities more often than others, particularly based on ethnic minority status, low income, and rural location. The conditions include systemic issues such as fragmented health care system (within which some individuals do not get health care in a timely fashion), racism and structural disparities in education, income, wealth, a consistent lack of economic opportunity, environmental factors, transportation and housing ( Petterson et al., 2020 ). These factors interact in complex ways resulting in persisting social environment-driven health and other inequalities which if left unaddressed will only increase.

Respectively, among policies goals across the Global North enhancing wellbeing and social mobility for disadvantaged and marginalized families, creating socially mixed, heterogeneous neighborhoods (that is, desegregation) is promoted to avoid spatial segregation based on racial and ethnic membership and class while supporting social cohesion ( Méreiné-Berki et al., 2021 ). Importantly, a marginalized community is not a homogeneous group as the lived experience of disadvantage within the communities is variegated: respectively, policies to improve socio-spatial integration and addressing the various causes of extreme poverty including social, economic, and cultural that improve social equity have been suggested since desegregation on its own is insufficient (( Méreiné-Berki et al., 2021 ). Sustainable planning may mitigate consequences of urban sprawl noted in the urban studies literature including urban blight which is the greatest in poorest areas entrapping the low-income residents in the inner city where they have only limited regional mobility and access to job opportunities at the urban edge. Understanding the links between a development of a metropolitan-wide blight remediation strategy toward a sustainable urban form and welfare enhancing among the disadvantaged populations needs to be further investigated.

During public health crises, the importance of the central role of the community has been highlighted especially when some state-based social services may be less available due to lockdown. Rather than inventing new solutions, voluntary informal social networks that have been generated by communities utilize local assets and resources ( Bear et al., 2020 ). Community-based initiatives may rely on the voluntary sector, faith- and charities-based organizations, and social enterprises for various services including help with visiting housebound people, or using them as a distribution hub for food distribution to families in need.

In conclusion, in this study, we situated the research on economic impacts of the COVID in the broader context of social disadvantage with findings both domestically and from other countries in line with those in our study. The earlier misleading view of the global epidemic representing a systematic disadvantage that may affect and limit everyone’s economic activity, with any socioeconomic status or from any geographic location, was rejected. Our finding indicates that certain factors may increase people's vulnerability to the financial stress related to COVID-19. We find support that the social distribution of economic vulnerability is magnified in regions with pre-existing social disparities, creating new forms of disparity ( Qian and Fan, 2020 ).

This work was supported by the UTHSC/UofM SARS-CoV-2/COVID-19 Research CORNET (Collaboration Research Network) Award.

CRediT authorship contribution statement

Anzhelika Antipova: Conceptualization, Formal analysis, Methodology, Visualization, Writing – original draft, Writing – review & editing.

Declaration of competing interest

The author declares no conflict of interest.

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South African Journal of Economic and Management Sciences

On-line version  issn 2222-3436 print version  issn 1015-8812, s. afr. j. econ. manag. sci. vol.23 n.1 pretoria  2020, http://dx.doi.org/10.4102/sajems.v23i1.3049 .

ORIGINAL RESEARCH

A systematic literature review of the implementation and evaluation of the JOBS programme: A suggested framework for South Africa

Rachéle Paver I , II ; Hans De Witte I , II ; Sebastiaan Rothmann II ; Anja Van den Broeck II , III ; Roland Blonk II , IV , V

I Research Group Work, Organisational and Personnel Psychology, KU Leuven, Belgium II Optentia Research Focus Area, North-West University, Vanderbijlpark, South Africa III Work and Organization Studies, KU Leuven, Brussels, Belgium IV Healthy Living, Toegepast Natuurwetenschappelijk Onderzoek (TNO), Leiden, the Netherlands V Department of Human Resource Studies, Tilburg University, Tilburg, the Netherlands

Correspondence

BACKGROUND : South Africa is challenged with high levels of unemployment, comprising many people with low levels of education and also individuals who have never held a job before. Despite having many vulnerable participants, interventions aimed at the unemployed generally exclude psychosocial training and are methodologically weak. AIM : The JOBS programme, a scientifically sound intervention, has been developed specifically to help people affected by unemployment to cope with the psychological effects. As a means of applying such a programme in South Africa, this study aimed to develop a framework based on the insights gained on the implementation and evaluation of the JOBS programme. METHODS : The study comprised a systematic review of literature regarding the JOBS intervention and its derivatives ( n = 34). RESULTS : The results revealed that populations similar to the unemployed in South Africa had benefitted significantly regarding re-employment and mental health outcomes. CONCLUSION : Suggestions derived from the literature included aiming the programme at the most vulnerable unemployed in South Africa: the youth and long-term unemployed. Furthermore, expanding the programme by adding an entrepreneurial component may yield positive results, considering the lack of employment opportunities in South Africa.

Keywords : JOBS programme; employment interventions; systematic literature review; unemployment; South Africa.

Introduction

South Africa is facing an unemployment crisis: currently 29.1% of people in South Africa are jobless (Stats SA 2019). While statistics may indicate the magnitude of the problem at hand, they fail to depict the nature and severe impact of unemployment. Unemployment is not only associated with societal and economic ramifications; it also has serious psychological consequences for those who are unemployed (see Strandh et al. 2014; Wanberg 2012).

Numerous interventions have been implemented to alleviate unemployment (Independent Evaluation Group 2013; McCarthy 2008). Despite the benefits of evidence-based practices (see Heckman, Lalonde & Smith 1999; Ravallion 2008), it is startling to see that most vocational interventions are consensus-based - implying that the interventions are based on what the stakeholders think is necessary, without the supporting evidence to prove what is really needed (Marais & Matebesi 2013). Considering the urgency of unemployment, the shortage of evidence-based practices in South Africa is a concern.

One profound example of a scientifically sound employment initiative is the JOBS programme (Caplan et al. 1989). The JOBS intervention seeks to enhance the employability of jobseekers by equipping them with the necessary job search, social and problem-solving skills to support them in their job search efforts. Several factors contribute to the achieved outcomes. Two of the strengths of the programme are its strong theoretical foundation and empirically tested evidence (Vinokur & Price 2015). Likewise, the comprehensive protocol guiding the programme contributes significantly to successful dissemination undertakings (Curran, Wishart & Gingrich 1999). Extensive evidence of the effectiveness of the JOBS programme has previously been reported (Price & Vinokur 2014).

Due to the encouraging results, several JOBS derivatives have been implemented in other countries. These programmes include the Työhön Job Search Programme in Finland (Vuori et al. 2002), the Jobs in China programme (Price & Fang 2002), the Job-Search programme in Israel (Shirom Vinokur & Price 2008), the Winning New Jobs (WNJ) programme in Ireland (Barry et al. 2006) and the JOBS intervention in the Netherlands (Brenninkmeijer & Blonk 2011). Although these programmes have proven to be reliable in different economic contexts (Vinokur et al. 1995a), they have been implemented mainly in developed countries, except for China. The lack of evidence-based practices in South Africa, together with the successful replication of the JOBS programme, creates an opportunity to explore whether such an intervention can be tailored to suit the South African context.

Much effort has been devoted to developing materials that explicitly explain the procedures and dynamics of the JOBS programme (Curran et al. 1999). Yet investigating literature pertaining to the execution and subsequent outcomes of the JOBS programme may assist further dissemination. A greater understanding of typical components of an intervention - implementation and evaluation - can be used to serve as guiding principles for application and assessment in the South African context. Based on the above statement of the research problem, the objectives of this research were:

To review literature regarding the implementation (context and process aspects) and evaluation (promoting and impeding effects) of the JOBS programme and variations of it.

Based on the previous findings, to develop a framework to assist with the implementation and evaluation of the JOBS programme in South Africa.

To make recommendations for future research and practice.

Research design

Research approach

A systematic literature review was done to achieve the objectives of this study. A systematic review identifies the main scientific contributions relevant to a specific topic by conducting extensive literature searches of published and unpublished studies (Tranfield, Denyer & Smart 2003). This review aimed to identify literature containing information about the JOBS programme and variations of it. Transparent and reproducible procedures were used to enhance the quality and outcomes of the review process.

Research method

Targeted body of literature

Before starting with the review, the founders of the JOBS programme and the web page of the Michigan Prevention Research Center (MPRC) were consulted to obtain information regarding the JOBS programme and its dissemination. Electronic searches were undertaken to allocate articles identified on the web page. Next, a search was conducted to ascertain whether possible articles were excluded. Databases such as Google Scholar and EBSCOhost (Academic Search Premier, Africa-Wide Information, American Doctoral Dissertations, PsycARTICLES and PsycINFO) were utilised to find the relevant articles.

Search terms and selected criteria

It was anticipated that the articles worth including in the review would refer to the JOBS programme in the articles themselves. Therefore, numerous searches were conducted by including the authors involved (as obtained from the dissemination page) with the term Job Opportunities and Basic Skills programme (e.g. AUTHOR: Vuori; IN-TEXT: 'JOBS program*'). Because another programme, called the JOBS Program, yielded additional results when searching for 'Jobs Program*', it was necessary to include the various authors. The search string consisted of two search concepts joined by the Boolean operator AND; the second string contained a list of authors joined by the Boolean operator OR. The following search string was entered in the databases: [1] IN-TEXT: 'jobs program*' [2] AUTHOR: 'Barry', 'Caplan'; 'Choi'; 'Kessler' 'Price'; 'Schul'; 'Van Ryn' 'Vinokur' and 'Vuori'.

To prevent the omission of essential articles, a complementary search was performed. Reference lists of the selected articles were reviewed for more relevant publications. During the process, it became evident that there were indeed articles that did not refer to the JOBS programme in their content. Therefore, an additional search was conducted using the authors involved from the different variations of the JOBS programme and each of the different JOBS variations (e.g. AUTHOR: 'Barry'; IN-TEXT: 'Winning New Jobs'). The second search string again consisted of two search concepts joined by the Boolean operator AND; the first string contained a list of names for variations of the JOBS programme and the second a list of authors, with both strings joined by the Boolean operator OR. The following search string was entered in the databases: (1) IN-TEXT: Jobs in China Project, Job-search Intervention, Työhön Job Search Program, or Winning New Jobs (2) AUTHOR: 'Blonk', 'Brenninkmeijer', 'Choi', 'Donaldson', 'Fang', 'Friedland', 'Ling', 'Shirom', and 'Turner'.

Criteria for including articles were as follows:

Articles and chapters had to be peer-reviewed.

Articles and chapters had to be written in English.

Articles had to be about the JOBS programme or variations of it.

The study population had to be unemployed people.

Gathering the data

Conference proceedings and papers to which access was limited or where no full-text papers were available were excluded. Price and Vinokur (2014) mention that the JOBS programme has previously been executed in Sweden and South Korea; however, the literature seemed limited and unavailable. Furthermore, the JOBS programme has also been implemented in organisational and school contexts. Considering that the circumstances of the participants are not the same, these studies were omitted. The inclusion and exclusion criteria narrowed the scope of this review. Finally, 34 articles met all the inclusion criteria ( Figure 1 ).

Analysis and presentation of the data

Implementation and evaluation aspects were studied to gain a better understanding of the JOBS programme and its derivatives.

Implementation is described as the process of putting a plan into action to achieve objectives (Miller, Wilson & Hickson 2004). To ensure sufficient programme fidelity and to effectively replicate the JOBS, it seemed necessary to study the various components involved in executing such a programme. Evaluation can be described as the determination of the merit, worth and significance of an area of interest using criteria directed by specific standards for purposes of decision-making (Richards & Schmidt 2002). Evaluation practices are a crucial component in the success of evidence-based programmes (Jané-Llopis et al. 2005). To develop a framework aimed at guiding the implementation and evaluation of the JOBS programme in South Africa, the following aspects of the papers included in the systematic literature review were studied ( Table 1 ).

Assessment of methodological quality

An additional reviewer - a researcher involved in the broader project - was consulted to ensure methodological quality. After the duplicates had been removed, both the researcher and reviewer were involved in selecting studies to remain in the systematic review based on their abstracts and full content.

Ethical considerations

Ethical clearance was obtained from the Humanities and Health Research Ethics Committee (HHREC), North-West University, with ethical clearance number: NWU-HS-2018-0006.

The literature review comprised 34 studies. The predetermined criteria, as per Table 1 , guided the systematic review. The main aspects regarding the implementation and evaluation of the JOBS programme and variations of it were tabulated. The summarised findings are reported below.

Implementation

This section contains information about the context in which the various programmes were implemented as well as participant and programme specifics.

The JOBS programme has been implemented in numerous states and countries, in all of which the context has differed to some degree (see Appendix 1 ). The unemployment rates, as reported in the studies included, varied from 4% to 20% (Brenninkmeijer & Blonk 2011; Vuori et al. 2002). Additionally, the unemployed seemed to be supported by welfare benefits, also safeguarding them against severe financial hardship. Unemployment grants differed, depending on the social policies of the countries involved (Vinokur & Price 2015).

Participants

Biographical variables

According to Vinokur and Price (2015), benefits of the JOBS programmes did not seem to be distributed equally to all the participants. Some findings are reported below; yet it should be noted that only a few of the studies included mentioned the impact of demographic variables on the intended outcomes. Findings regarding participants' demographic variables were not always consistent and sufficient to substantiate these relationships. Compared to other demographic variables, education had the strongest impact on the outcomes of the job search interventions.

Gender: Female participants seemed to suffer greater economic losses and experience more difficulties regaining employment (Vinokur et al. 2000). Yet women generally benefitted more from the programme than their male counterparts (MPRC 2003). They were more likely to (1) obtain employment six months after the intervention (Shirom et al. 2008), (2) score higher on participant engagement (Caplan et al. 1989), (3) experience positive group participation (Vuori et al. 2005) and (4) participate voluntarily (Vuori et al. 2002).

Age: Unemployed people between the ages of 16 and 65 were generally the targeted population. The mean age of participants in the studies included was 36 (Standard deviation [SD] = 9). Vuori et al. (2005) state that younger participants were usually more positive and found employment more easily than older participants, but showed a higher tendency of non-participation (Van Ryn & Vinokur 1992; Vinokur et al. 2000; Vinokur, Price & Caplan 1991a). The training programme seemed to also have a positive impact on older participants regarding improved job search skills and increased self-confidence (Price & Choi 2001).

Level of education: The majority of participants in the programmes involved had a secondary level of education (equivalent to 12 years of schooling; mean of all the studies: 40.65%). Participants with higher levels of education more often gained in terms of obtaining re-employment (MPRC 2003), increases in job search self-efficacy (Choi, Price & Vinokur 2003), a lower likelihood of major depressive episode diagnosis (Vinokur et al. 2000) and non-participation (Caplan et al. 1989; Van Ryn & Vinokur 1992; Vinokur et al. 2000), and higher levels of voluntary participation (Vuori et al. 2002). Despite these positive findings, in some other studies, it was evident that the programme also clearly yielded mental health benefits and economic benefits for those less educated and most disadvantaged in terms of the job market (Price & Choi 2001; Vinokur, Price & Schul 1995b).

Duration of unemployment: The JOBS programme was originally designed to prevent further deterioration in mental health among the unemployed and was not specifically intended to deal with potential problems associated with long-term unemployment (Caplan et al. 1989). Therefore, the majority of the initial studies included only those who had been unemployed for less than 13 weeks (Caplan et al. 1989; Price et al. 1992; Van Ryn & Vinokur 1992; Vinokur et al. 1991a, 1991b, 1995a, 2000; Vinokur, Price & Caplan 1996; Vinokur & Schul 1997). However, because the long-term unemployed were reported as the most vulnerable, more recent developments included participants who had been unemployed for longer periods (Brenninkmeijer & Blonk 2011; Malmberg-Heimonen & Vuori 2005; Price & Choi 2001; Reynolds, Barry & Gabhainn 2010; Vuori et al. 2005).

Population, sample size and recruitment

Population: Eligibility criteria required individuals to be aged between 16 and 65. Prospective screening questionnaires were used in some studies to determine participants' risk score for poor mental health (Vinokur et al. 1995b). However, those who showed major signs of mental illness, serious psychosocial problems or behavioural problems or who scored extremely high on depression symptoms were omitted from the study (Brenninkmeijer & Blonk 2011; Vinokur et al. 1995a).

Sample size: Most of the studies included were conducted as a part of large-scale field experiments, ranging from 1087 to 3402 participants. Smaller-scale studies ranged from 125 to 672 participants. Sample sizes did not seem to influence the results achieved or the sustainability of the programmes. It was rather the use (or lack) of effective methods that seemed to have an impact on the outcomes (Price & Vinokur 2014).

Recruitment: The primary method used to recruit participants was through recruiters who approached individuals eligible for employment benefits while collecting grants at employment offices. In studies including an experimental and control group, participants were told about the two programmes on job-seeking methods. One programme was described as a workshop consisting of five half-day sessions (the experimental condition); the other was described as a self-guided programme, in which participants received a booklet with job search information (the control condition). To prevent biases, participants had to show no preference for a type of intervention (experimental or control condition; Caplan et al. 1989; Vinokur et al. 1995a).

Voluntary or enforced participation: Participants from some programmes had to participate in the job search workshop to qualify for welfare benefits (Brenninkmeijer & Blonk 2011; Lee & Vinokur 2007). When studying the impact of voluntary or enforced participation, a Finnish study showed that enforced participation did not increase re-employment; however, it impaired the positive mental health impacts of the programme. Further analysis demonstrated that enforced participation in job search training decreased re-employment among the longer-term unemployed workers (Malmberg-Heimonen & Vuori 2005).

Dropout rates: In the US programmes, on average, 59% (varying by 5%) of participants failed to show up for the intervention (Caplan et al. 1989; Vinokur et al. 1995a). Consequently, dropout rates could be anticipated and, therefore, twice as many participants were recruited and allocated to intervention groups in the Israeli study (Shirom et al. 2008). In the Malmberg-Heimonen and Vuori (2005) study, it was surprising to find that response rates did not differ much among the enforced, voluntary and control groups (94%, 92%, and 91%).

The information presented below was derived from the JOBS training manual (Curran et al. 1999).

The JOBS programme entails two main processes. On the one hand, job search skills (the actual content of the programme) are taught to participants, while, on the other hand, empowerment of the participants, by applying the programme's underlying principles in the method of delivery, is the true underlying mission of the workshop. The following aspects guided the method of delivery used by the trainers:

Referent power: Moderate self-disclosures shared by facilitators create an environment in which participants feel safe to reveal their concerns and experiences. These also contribute to creating an atmosphere of unconditional acceptance and to enhancing feelings of being normal and valued.

Guiding behaviour: Specific positive feedback is given to participants to reinforce positive behaviour. Strategies used to generate positive feedback include active listening, observation and reflecting on what participants have shared as a means of showing participants that they are valued.

Inoculation against setbacks: The group is encouraged to identify potential setbacks and difficulties in the job search process. Strategies are developed to overcome the identified challenges and, consequently, participants realise that their problems can be solved. Participants are asked to commit themselves to action by selecting and vowing to undertake a solution most appealing to them.

Social support: Social support forms an integral part of the underlying processes, as exercises are specifically designed to create opportunities for facilitators and participants to support each other. An environment where participants are unconditionally accepted is created. Such a safe environment contributes to participants feeling comfortable to express their opinions and reveal their feelings.

Active leaning: The learning process relies greatly on participants' knowledge and skills. Participants acquire job search skills by using active learning methods, elicited using group discussions and brainstorming sessions.

In contrast to traditional top-down, trainer-focused training methods, the JOBS programme relies heavily on its individual-focused approach. The delivery principles mentioned above contribute to the strong individual-focused approach. Principles are continuously applied and integrated and form the basis on which the content is delivered.

The programme consists of five sessions. During the first session, participants discover their job skills; the second session focuses on dealing with obstacles related to employment; the third session is used to introduce participants to some job search techniques; the fourth session covers topics such as curriculum vitae writing and preparing participants for job interviews; during the fifth session participants rehearse skills acquired throughout the week. The workshop concludes with a certificate ceremony, during which facilitators boost participants' confidence by highlighting their strengths and skills and providing each participant with a sincere and inspiring message.

The JOBS protocol describes the programme processes meticulously. Yet these processes are flexible and can be altered, depending on the needs of the groups, without losing the intended effects of the programme. The majority of the disseminated versions of the JOBS programme were implemented strictly according to the protocol. The content differed in terms of minor language, cultural, procedural and scheduling changes to suit different contexts. To maintain the standard of the JOBS programme, all materials were piloted and approved. It is worth mentioning that, when the protocol was somewhat neglected, it was reported that the programme was less successful in achieving the intended outcomes (Shirom et al. 2008).

Participants were rewarded monetarily for participation or each returned questionnaire (varying between $5.00 and $15.00, depending on the currency of the country). In cases where questionnaires were not returned, an additional amount was issued on the completion of their questionnaires. This incentive was reported to result in a substantial increase in response rates (about 20%; Shirom et al. 2008). Participants in the JOBS programme and Netherlands JOBS programme also received a certificate of participation for completing the programme (Brenninkmeijer & Blonk 2011; Caplan et al. 1989).

Researchers obtained higher response rates when offering incentives: in cases with relatively high dropout rates, no mention of rewards or incentives was evident (Barry et al. 2006; Reynolds et al. 2010; Shirom et al. 2008). The same finding was, however, not true in the WNJ California studies, which managed to retain approximately 70% of their participants, seemingly without the use of incentives (Choi et al. 2003).

Facilitators

Pairing: Teams consisting of one male and one female trainer are prescribed by Curran et al. (1999) to complement each other well. An untested assumption existed that a pair of trainers reduced deviation from the principles of the JOBS programme. However, the assumed benefits of having male-female pair facilitators have not yet been tested. Benefit-cost research could determine whether the cost of using two trainers, rather than one, is outweighed by the benefits that are generated (Price et al. 1998).

Prerequisites: Facilitators were generally social workers, labour advisors, educational counsellors or high school teachers. It was suggested that facilitators ought to be skillful in working with people (public speaking and communications backgrounds). Because trained individuals (that is, mental health professionals, such as counsellors or clinicians) might execute strongly embedded techniques not necessarily consistent with unemployment-related counselling methods, professional training was not a prerequisite (Caplan et al. 1989).

Programme-related training: Facilitators had to undergo extensive formal training. The content of the training covered understanding of group processes, theoretical foundations of the programme and extensive rehearsal in the form of pilot studies. The duration of training varied from 6 to 30 days (48 h-240 h). The reason for the extensive training was that facilitators were not only conveyors of information, but also experts in navigating the group processes, with the ability to connect emotionally with the participants and facilitate interactions in a group setting. To promote conformity, trainers' performance was evaluated by trained supervisors.

Duration of the programme

Some of the findings yielded by the original JOBS trial encouraged the revision of the programme, which consequently led to the development of the JOBS II intervention (Vinokur et al. 1995a). The first version (the JOBS I programme) spanned eight 3 h sessions, over a two-week period (four mornings per week; Caplan et al. 1989). To increase programme efficiency and the attendance of participants, meeting hours were reduced by 30%, delivered over five 4 h sessions in a one-week period in the JOBS II (Vinokur et al. 1995a). The majority of disseminated versions of the JOBS programme continued to apply the programme following the JOBS II protocol. In some groups, the Finnish programme was delivered over four days, as the first day was used to deal with recently laid-off workers' negative emotions (Vuori et al. 2002) - an illustration of how the programme can be altered to meet the needs of the group, without affecting the outcomes.

Group sizes

Guidelines of the JOBS programme suggest groups consisting of 12-20 participants (Curran et al. 1999). There were exceptions, where the groups ranged from three to 110 participants per group (median = 11; Malmberg-Heimonen & Vuori 2005). Although only a few studies reported on the impact of group sizes, larger groups seemed to have more negative experiences than smaller groups (Vuori et al. 2005).

Venue of training

Venues such as community centres, school classrooms, churches and union halls, easily accessible to participants, were mostly used. Venues had to be large enough to accommodate 25 people and furnished with movable chairs, arranged in a semicircular layout. Such a layout was reported to be most effective in delivering the group intervention (Curran et al. 1999).

Stakeholder involvement

Crucial to the success of the WNJ programme in Ireland was that the developers of the original JOBS programme were involved from the outset and contributed to obtaining buy-in from strategic stakeholder agencies. Despite a substantial initial investment of resources for demonstration, neither the WNJ in California nor the JOBS in China project continued beyond their initial stages, as commitment of resources for continuation was not offered by the government or other stakeholders. Therefore, the success of programme dissemination depended considerably on the involvement of, and support received from, stakeholders (Vinokur & Price 2015).

This section is comprised of information regarding evaluation of the processes and the impact of the JOBS programme.

Methodology

Data collection method

Self-administered questionnaires were used to assess participants' attitudes, intentions, various behavioural components and experience of the workshop (Van Ryn & Vinokur 1992). In cases of unreturned questionnaires or where participants failed to show up for the workshop, telephonic interviews were conducted (Barry et al. 2006).

Research design and data collection intervals

Randomised field study designs were used to investigate the intervention effect between experimental and control conditions (Caplan et al. 1989; Vinokur et al. 1995a; Vuori et al. 2002). Programmes that made use of a randomised field study design had three to four interval times, namely pre-intervention (two weeks before the programme), post-intervention (directly after the programme), post-post-intervention (between two and six months after the programme) and long-term follow-ups, varying from 12 to 32 months after the intervention (Barry et al. 2006; Brenninkmeijer & Blonk 2011; Vinokur et al. 1991a). Other programmes only tested pre-intervention and post-intervention to determine the impact of the programme (Lee & Vinokur 2007; Shirom et al. 2008).

Process evaluation

To determine the internal validity and the strength and integrity of the JOBS programmes, two types of analysis were generally conducted. These process measures consisted of testing the integrity of randomisation and strength of the programme (Vinokur et al. 1995a).

Effectiveness of randomisation

The first check to determine the validity of the programme was to determine whether the statistical analyses were conducted on a randomised (true) experimental design. This was established by comparing the demographic and other tested variables of the experimental and control conditions at baseline to identify possible differences. In cases where differences were found, these variables were controlled for in further analyses (Vinokur et al. 1995a).

Manipulation checks, integrity and strength of the intervention

The second test was to test the strength and integrity of the intervention through self-reported questionnaires at the end of each session. Participants were asked to evaluate their experience of facilitators and the programme. These evaluations were used to determine whether various intervention elements had been implemented and had operated as designed (Vinokur et al. 1995a). Participants who scored high on these measures also reported higher levels of internal control and job-seeking self-efficacy (Choi et al. 2003), decreases in depression and anger, and increases in self-esteem and quality of life (Caplan et al. 1989). Also, trainer skills (one of the evaluated variables) exhibited during group interactions contributed to increased re-employment, even at the 12-month follow-up (Reynolds et al. 2010).

Two additional methods were used to ensure the quality of the programme and a high level of trainer adherence to the protocol. Firstly, members of the research team frequently observed programme trainers: after each session, constructive feedback was given to trainers. Secondly, the facilitators met weekly to discuss skill-related topics they encountered during their sessions (Vinokur et al. 1995b).

Impact evaluation

The positive outcomes of the JOBS programme were documented amply. Below are some of the most prominent findings related to the two core objectives of the JOBS programmes: prevention of poor mental health and promotion of re-employment, and other post-hoc outcomes.

Prevention of poor mental health: Participation in the intervention resulted in increased self-esteem, self-efficacy and social assertiveness among participants; consequently, participants also showed improved psychological and mental health and well-being (Lee & Vinokur 2007; Reynolds et al. 2010). Furthermore, long-term effects of the programme revealed that participants experienced lower symptoms of depression (Price et al. 1992; Vuori & Silvonen 2005), improved self-esteem (Reynolds et al. 2010) and an enhanced ability to deal with setbacks. A noteworthy finding is that participants screened for showing higher risk for depression seemed to benefit the most in terms of mental health and re-employment outcomes (Vinokur et al. 1995b).

Promotion of re-employment: Several programmes demonstrated increased rates of re-employment, with an average of 46% after the intervention, compared to the control group, with an average of 18% (Brenninkmeijer & Blonk 2011; Caplan et al. 1989; Donaldson 2012; Shirom et al. 2008; Vuori et al. 2005). Programme participants also showed higher motivation to persist in job search efforts (Caplan et al. 1989), were employed in better jobs (in terms of earnings and job satisfaction) (Vinokur et al. 1991b), were employed faster, had less recurring episodes of unemployment (Vinokur & Price 2015) and experienced reduced economic hardship after being employed (Barry et al. 2006). Results remained over time, as long-term effects of the programme revealed that participants, compared to their counterparts, experienced higher re-employment (Brenninkmeijer & Blonk 2011). Another crucial finding is that both the Työhön and the Netherland's JOBS programmes confirmed the effectiveness of the intervention to help even the more vulnerable long-term unemployed gain employment (Brenninkmeijer & Blonk 2011; Vuori et al. 2002).

Consequential outcomes: Finally, the JOBS programme demonstrated substantial cost-benefit effectiveness because the higher earnings led, on average, to higher tax revenues and decreased welfare grants for governments (Vinokur et al. 1991b).

The purpose of this study was to review literature regarding the JOBS programme and variations of it, with the intention of developing a framework that could guide the successful implementation and evaluation of the JOBS programme within the South African context. To gain a better understanding of the components related to the implementation of the JOBS programme, the contexts in which the programme have previously been implemented and the targeted population, as well as aspects regarding the programme, were studied. Based on the findings of the systematic review, as well as context-specific matters, a framework is proposed for the implementation and evaluation of the JOBS programme within the South African context (see Appendix 2 ).

In terms of contextual differences between developed countries (where the JOBS programme has previously been implemented), and developmental countries (e.g. South Africa), some differences are crucial to consider when implementing an employment programme, such as the JOBS intervention. While the unemployment rates of the involved developed countries averaged 12%, more than 27% (37.3% when including those who have stopped looking for employment; Stats SA 2018) of South Africans are currently unemployed. Moreover, it has been reported that 69% of these individuals have been unemployed for longer than a year (Stats SA 2018). In South Africa, unlike the other countries, unemployment grants safeguarding people from financial hardship are not available. Also, the unemployed are generally situated in rural areas isolated from major economic activity. With limited job opportunities, jobseekers feel discouraged, and deprived of a chance to compete in the labour market (Du Toit et al. 2018). Fortunately, the JOBS programme is specifically designed to deal with such conditions, yet it remains important to be cognisant of the impact of contextual factors on potential participants' state of mind.

With regard to participant-related matters, the reviewed literature showed that young and old, educated and less educated participants had previously benefitted from the JOBS interventions. However, it is important to note that South Africa has a youth unemployment rate of 52% (aged between 15 and 24; Stats SA 2018); 62% of the unemployed population have never even held a job before (Stats SA 2017); and 57% of South Africans have an education of less than matric (Grade 12). Therefore, although the unemployed in general could benefit from the programme, it is suggested to target vulnerable populations, such as younger, less educated and long-term unemployed individuals, as it may yield promising results.

Furthermore, participants from previous studies were reached at employment services offices. Because unemployment grants are not available in South Africa, participants cannot be reached on a large scale in a similar way. Therefore, different strategies of reaching the intended population should be considered. Suggestions include making use of newspaper and radio advertisements, and government agencies working with jobseekers, or working with youth and community leaders. One programme in particular tested the effectiveness of forced versus voluntary participation. Findings revealed that enforced participation did not increase re-employment and impaired the positive mental health impact of the programme (Malmberg-Heimonen & Vuori 2005). Giving participants the autonomy to participate voluntarily in the programme seems to yield more positive benefits. This may be an important finding for policymakers, as a precondition for receiving unemployment grants is often enforced attendance of a job search programme. Yet responsibility also rests with workshop trainers to be particularly devoted in creating an environment to which participants choose to return.

Considering the possibility that participants showing a preference to partake in employment programmes may be somewhat more intrinsically motivated, at the same time, it is those who show a higher risk of depressive symptoms that may benefit more (Vinokur et al. 1995a). Thus, careful attention should be paid to recruitment measures, ensuring that both the motivated and those who may be at risk of depressive symptoms are reached through recruitment methods, as they are equally important in achieving intended programme outcomes. Similarly, some programmes made use of screening questionnaires to identify participants at risk of poor mental health (Vinokur et al. 1995b); those who scored exceptionally high on depression symptoms or showed major signs of mental illness were omitted from the programme (Brenninkmeijer & Blonk 2011). As previously mentioned, given that many of the unemployed in South Africa may be severely discouraged, it is recommended to refrain from screening participants to identify high-risk cases, as it may result in the exclusion of participants who may benefit from the programme.

The next implementation aspect investigated related to programme-related matters. In line with previous adaptations of the JOBS programme, it is suggested to tailor the content of the manuals and activities to better suit the context and to increase cultural acceptability (Barry et al. 2006; Brenninkmeijer & Blonk 2011). Due to slow economic growth and the lack of skills in specific disadvantaged populations, changes in conditions of obtaining a job may be difficult (Vinokur & Price 2015). A solution that may fill both of these voids could be to consider fostering an entrepreneurial mindset among programme participants. People working in the informal sector often have a lower education level (although not lower wages) compared to those employed in the formal sector (Kim 2002), which may be a suitable solution within the South African context.

Furthermore, the ability to facilitate and understand group processes, build feelings of competence and create an environment of unconditional acceptance were essential requirements for facilitators. Yet education levels of the facilitators were not reported as particularly important. Due to the great demand for social work in South Africa, a shortfall of qualified social workers exists, which often results in employing people at social services offices who are less skilled and experienced (Collin 2017). Failure to grasp the importance of, and means of executing, the principal components of the programme may be problematic for the successful execution of the programme. Consequently, involving trainers knowledgeable and experienced in this area, while at the same time having the ability to relate to participants, should be considered. These may typically include individuals with higher degrees, coming from a similar background, who can also serve as role models for participants. Additionally, trainers should have the ability to adopt an individual-focused training approach, aimed at the enhancement of active learning among participants, instead of taking on the traditional role of teacher.

A noteworthy lesson was that the success of the programme lies greatly in the adherence to the designed protocols, as fewer of the anticipated outcomes were achieved when the protocol was neglected (Shirom et al. 2008). The majority of workshops included between 12 and 18 participants per group, as it was effective and economical. Ideally, delivery was guided by two training facilitators, as two were more capable of monitoring the behaviour and reactions of participants (Vinokur & Price 2015). Also, five half-day sessions, compared to longer two-week sessions, seemed to be more effective in keeping participants engaged. A vital lesson could be learned from the Finnish study that allowed for a debriefing day. During this session former appointed employees had an opportunity to deal with negative emotions caused by their dismissals (Vuori et al. 2005). Providing participants with such a venting opportunity may have made them more receptive to the programme.

Lastly, the founders of the JOBS programme strongly advised involving an effective champion, advocating for the programme at the policy level from the outset. It was also suggested that service delivery agencies be included that were open to applying innovative initiatives. Furthermore, a continuous flow of resources and funding seemed fundamental to the success and sustainability of large-scale programmes (Price & Vinokur 2014). In the South African context, economic development departments in local governments, supported by training providers, could act as champions of the JOBS programme.

This study also explored three elements (methodology, process and impact) related to the evaluation of the JOBS programme. The investigated studies were either conducted with a randomised field or quasi-experiment design as the chosen methodology, with self-reported questionnaires as the main data collection method. Considering the effectiveness of these designs in reporting the effectiveness and changes over time, it is suggested to use a similar approach. Furthermore, attrition was a pervasive problem experienced by most of the studies. However, offering incentives and recruiting more participants due to anticipated dropouts yielded higher attendance rates (Caplan et al. 1989; Shirom et al. 2008).

Aspects contributing to the process evaluation of the intervention included randomisation and manipulation checks of the studies included. To ensure internal validity, comparisons between the control and experimental groups' demographic and other variables were tested for possible biases. Furthermore, the strength and integrity of the various interventions were assessed by means of self-reported questionnaires at the end of each workshop. Several benefits can be gained from delivering a programme that is valid and reliable. Firstly, as mentioned earlier, adhering to programme protocols is strongly recommended, as the intended outcomes are achieved through reliable practices. Secondly, ensuring that participants experience the programme positively has previously been shown to increase engagement and, consequently, has led to other outcomes, such as decreased depression and anger, increased internal control, job-seeking self-efficacy and self-esteem (Vinokur et al. 1995a; Vinokur & Schul 1997).

With regard to the JOBS programme's impact, one of the most significant findings was the beneficial re-employment outcomes for those who had been unemployed for a moderate length of time (longer than a year; Brenninkmeijer & Blonk 2011; Vuori et al. 2002). Likewise, findings from examined literature also showed beneficial mental health and re-employment outcomes, particularly for high-risk participants (Vinokur & Schul 1997). These findings are valuable as it was found in a South African study that approximately 70% of the unemployed population was categorised as desperate or discouraged (Van der Vaart et al. 2018). The unemployed in both clusters generally came from poor socio-economic backgrounds, had relatively low levels of education, had limited opportunities for odd jobs or temporary employment, and were quite pessimistic. Given the capability of the JOBS programme to produce significant outcomes for high-risk participants, it appears that it could hold valuable outcomes, also for those who have been unemployed for long periods and may be truly discouraged.

Limitations and recommendations

Some limitations of this study need to be considered. Firstly, only peer-reviewed articles and book chapters that were written in English were included in the current study. Since the JOBS programme has been implemented in the Netherlands, Israel, Finland and China, where other official languages occur, the possibility of excluding potential articles exists. Secondly, access to some articles (Jobs in China project and Työhön trainers' manual) was limited, or they could not be found, resulting in their omission from the review (i.e. Fang & Ling 2001; Mäkitalo, Tervahartiala & Saarinen 1997; Price 2001). In the third place, due to the nature of intervention studies, it is possible that only studies yielding significant results were published. Although all versions of the JOBS programme known to the developers were reported, it is possible that there may be unpublished efforts. Consequently, meaningful lessons that could have been learnt from these papers were not available. However, much effort was invested in systematically searching for and including all possible studies. Lastly, the study did not include articles where the JOBS programme had been applied in work-to-school and organisational contexts. Although these programmes may have yielded valuable findings, these studies were omitted, as the aim of this study was to specifically focus on the most effective methods to assist the unemployed.

This study reviewed literature about the JOBS programme as a means of extending our knowledge of applying such a job search intervention in a South African context. Therefore, core aspects regarding the implementation and evaluation of the JOBS programme and variations of it were investigated. Specifically, implementation features such as contextual factors, participant characteristics and programme aspects were studied, while evaluation features included impact and process evaluation components.

Evidently, the success of the JOBS programme largely depended on following the protocol. Thus, studying the previously performed methods and outcomes of the JOBS programme, in various contexts, may serve as a valuable guideline to prescribe possible best practices. The integration of included literature and important aspects regarding the South African context produced a framework that could be valuable in the implementation and evaluation of the JOBS programme in South Africa.

Acknowledgements

This work was supported by the Experiences of Unemployment Research Project funded by the Flemish Interuniversity Council - University Development Cooperation (VLIR-UOS). We are truly grateful for this opportunity.

Competing interests

The authors have declared that no competing interest exists.

Authors' contributions

This publication was based on the PhD thesis of R.P. H.D.W., S.R. and A.V.d.B. were co-authors as well as supervisors of the project. R.B. made conceptual contributions to the manuscript.

Funding information

Flemish Interuniversity Council - University Development Cooperation (VLIR-UOS), ZEIN2013PR397.

Data availability statement

The main aspects regarding the implementation and evaluation of the JOBS programme and variations of it were tabulated. A summary table can be requested from the first author. The literature review comprised 34 studies; these articles can be requested from the first author.

The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.

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Donaldson, S.I. & Gooler, L.E., 2002, 'Theory-driven evaluation of the Work and Health initiative: A focus on winning new jobs', American Journal of Evaluation , 23(3), 341-346.         [  Links  ]

Fang, L. & Ling, W., 2001, Jobs in China: A seven city project , Institute of Psychology, National Academy of Sciences, Beijing.         [  Links  ]

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Mäkitalo, M., Tervahartiala, T. & Saarinen, M., 1997, Työhön Työhöohjelma Ohjaajan käsikirja [Työhön program trainers' manual] , Finnish Institute of Occupational Health, Helsinki.         [  Links  ]

McCarthy, P., 2008, South Africa's 'door knockers': Young people and unemployment in metropolitan South Africa , Centre for Development and Enterprise, Johannesburg.         [  Links  ]

Michigan Prevention Research Center (MPRC), 2013, The JOBS project for the unemployed: Update , Michigan Prevention Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI.         [  Links  ]

Price, R.H., 2001, 'Winning new jobs in China. Preface' in L. Fang & W. Ling (eds.), Jobs in China: A seven city project , Institute of Psychology, Chinese Academy of Sciences, Beijing, Republic of China.         [  Links  ]

Price, R.H., Choi, J.N., & Lim, S., 2006, 'Beyond the iron rice bowl: Life stage and family dynamics in unemployed Chinese workers', in M. Warner & G. Lee (eds.), Unemployment in China , pp.123-142, Routledge, London, UK.         [  Links  ]

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Price, R.H. & Vinokur, A.D., 2014, 'The JOBS program: Impact on job seeker motivation reemployment, and mental health', in U. Klehe & E.A.J. van Hooft (eds.), Oxford handbook of job loss and job search , pp. 575-590, Oxford University Press, Oxford, UK.         [  Links  ]

Ravallion, M., 2008, Evaluation in the practice of development , Working paper No. 4547, World Bank Publications, Washington, DC.         [  Links  ]

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Vinokur, A.D., Price, R.H., Caplan, R.D., Van Ryn, M. & Curran, J., 1995a, 'The jobs I preventive intervention for unemployed individuals: Short-and long-term effects on reemployment and mental health', in L.R. Murphy, J.J. Hurrell Jr, S.L. Sauter & G.P. Keita (eds.), Job stress interventions , pp. 125-138, American Psychological Association, Washington, DC.         [  Links  ]

Received: 28 Feb. 2019 Accepted: 06 Nov. 2019 Published: 25 Feb. 2020

The context of the countries and states in which the JOBS programme have been implemented.

The overall findings regarding the implementation and evaluation of the JOBS programme.

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February 24, 2021

Acts of Congress and COVID-19: A Literature Review on the Impact of Increased Unemployment Insurance Benefits and Stimulus Checks 1

Elena Falcettoni , and Vegard Nygaard

Introduction

Congress passed the first COVID-19 relief package for businesses and individuals in March 2020, when the Coronavirus Aid, Relief and Economic Security (CARES) Act was enacted, providing, among other things, one-time stimulus checks for individuals, extended unemployment insurance (UI) benefits, relief for state and local governments, liability protection, and the Paycheck Protection Program for small-business loan forgiveness.

The COVID-19 pandemic has kept economists busy analyzing many aspects of economic side of the coronavirus impact. This note is meant to present an overview of what economists have analyzed regarding the implications of two of the main components of the CARES Act that affect individuals: the increased UI benefits and the stimulus checks. We present the findings from the literature on these two policies with an eye on potential future governmental interventions.

Taken together, these two components have been effective at providing stimulus and lowering poverty. In the aggregate, Kaplan et al. (2020) (PDF) find that the initial UI benefits and stimulus payments boosted aggregate consumption by 2 percentage points, while Bayer et al. (2020) show that the CARES transfers reduced the output loss due to the pandemic by up to 5 percentage points. The rest of the note will focus on the individual impact of each of these two policies and their heterogeneous impact across the U.S. population. By summarizing the impact of these two provisions of the CARES Act, we hope that this note will inform readers about the potential impact of similar provisions in the subsequent stimulus bill passed in December 2020 as well as any potential future actions.

Importantly, this note will not focus on the large COVID-19 literature that discusses health impacts, distancing measures, epidemiological models, pandemic-induced mortality changes, or the impact of other policies, domestic or foreign. For a more general review of these other topics, please refer to Brodeur et al. (2020) .

Unemployment Insurance Benefits

CARES provisions. The CARES Act provisions prescribed 13 weeks of federally-funded benefits under the new Pandemic Emergency Unemployment Compensation (PEUC) program in addition to the standard state-administered UI programs for those currently receiving UI benefits and new applicants. These benefits were then extended for another 13 weeks (and potentially for another 7 following those) through the Extended Benefits program. Normal benefits included an additional $600 per week for up to four months, which is a provision that expired on July 31, 2020. On August 8, a reduced weekly check of $300 was reinstated for an additional 6 weeks subject to state application. All states but South Dakota applied for it. Finally, there is also a new program, the Pandemic Unemployment Assistance (PUA), for individuals who are self-employed, who are seeking part-time employment, or who otherwise would not qualify for regular UI benefits. The PUA program provides up to 39 weeks of benefit. Importantly, the CARES Act also required states to relax the criterion of actively searching for work to qualify for these benefits to account for illness, quarantine, and movement restrictions.

Impact of COVID-19 on unemployment. The COVID-19 pandemic has affected employment greatly, especially in lower-pay and nonessential occupations, as shown in Liu and Mai (2020) . Over March and April 2020, job losses were larger for these occupations, especially for those with higher physical proximity or lower work-from-home feasibility. Between April and June 2020, the industries that were hit harder also recouped more jobs, but the recovery was far from full. Chetty et al. (2020a) show that although high-wage workers experienced a recession, it lasted only a few weeks, they rarely lost jobs, and their job market is now almost back to normal. In contrast, many low-wage workers lost their jobs because of the pandemic and experienced a recession that lasted for several months, with a job market that is still far from normal. Forsythe et al. (2020a) show that nearly all industries and occupations saw contraction in postings and spikes in UI claims, with essential jobs taking the smallest hit and leisure and hospitality services the biggest hit. The pandemic-induced increase in unemployment led to the largest rise in UI claims in U.S. history (see, i.a., Cajner et al. 2020 , Chetty et al. 2020b (PDF) , Goldsmith-Pinkham and Sojourner 2020 , and Kong and Prinz 2020 for indicators of labor-market changes during this period). The results found in these papers and the patterns in the data suggest that extended and increased UI benefits are key components of any potential stimulus bill meant to counteract the negative impact of the pandemic on the labor market.

Effectiveness of UI benefits and difficulty to reach the most marginalized. The effectiveness of the UI benefits has been well-documented. Faria-e-Castro (2020) finds that UI benefits are successful at stimulating consumption, leading to an increase in GDP. Han et al. (2020) show that UI benefits, their expansion, and the stimulus checks led to a decline in poverty during the pandemic, which would have risen in the absence of these programs. Cortes and Forsythe (2020) show that 49 percent of the UI and CARES benefits went to workers who were in the bottom third of the earnings distribution before the pandemic happened, which reversed the increase in labor-earnings inequality that followed the beginning of the pandemic because of the concentration of job losses among low-paying jobs. Montenovo et al. (2020) document the disparities in job losses by occupation and relate the pre-pandemic sorting by gender, race, and ethnicity into different occupations and industries to the gaps in unemployment across these categories. Bhutta et al. (2020) use detailed data from the Survey of Consumer Finances to estimate that an additional 38 percent typical working families would be able to cover six months of expenses after an unexpected income disruption, such as a job loss, under the increased UI benefits implemented with the CARES Act compared to the standard UI benefits alone. The immediate effectiveness of UI benefits to meet basic needs is also documented by Karpman and Acs (2020) (PDF) and Giannarelli et al. (2020) (PDF) , both of which also discuss the difficulty to reach the poorest part of the population. Delays in payment of UI benefits, also due to an overwhelmed system, are also documented in Bitler et al. (2020) . Parolin et al. (2020) (PDF) also provide evidence for the challenges involved with reaching the most-marginalized parts of the population and they argue for the need of an expansion of UI benefits to contain poverty. In particular, they show that minorities were hit particularly hard by the pandemic and that the expiration of the CARES Act benefits led to an increase in poverty which was even higher than pre-pandemic levels. Bell et al. (2020) (PDF) find that in California alone, communities of concentrated poverty and with a higher share of racial and/or ethnic minorities have received UI benefits at such a lower rate than wealthier, whiter communities that the number of regular UI beneficiaries would have been 23 percent higher if the rate of receipt of UI benefits across the two types of communities had been equalized. Since it was particularly difficult to reach the individuals in the population who would benefit the most from these programs, this evidence is suggestive of a need for even-greater outreach from the government to the most-marginalized parts of the U.S. population.

Temporary vs. permanent layoffs. While UI benefits have been generally effective, a separate strand of this literature analyzes the difference in impact between unemployment types: those who are on temporary layoffs and those who are permanent job losers. The individuals on temporary layoffs are those who are only unemployed on a temporary basis because they lost their job because of the lockdown but they expect their unemployment to end as soon as the lockdown ends. The individuals who are permanent job losers are those who lost their job but who do not expect to resume their job as soon as the lockdown is over. Barrero et al. (2020) estimate that 42 percent of pandemic-induced layoffs will result in permanent job loss. Carroll et al. (2020) (PDF) use a consumer model in which individuals are part of three possible employment categories (employment, temporary layoff, permanent job loss) and then estimate the impact of the combination of increased UI benefits and stimulus checks on consumer spending, with findings broken down by consumer category. They note that spending would be lower even without unemployment shocks because measures to contain the pandemic, such as lockdowns, reduced access to goods and services and thus limited spending opportunities. The employed, by definition, do not receive any UI benefits. Those individuals who are on temporary layoffs particularly benefit from the CARES Act provisions, which provide them with the means to smooth their consumption throughout transitory shocks. Their spending recovers fully within a year. For those individuals who are permanent job losers, the authors estimate that regular consumption spending takes three years to recover on average. The impact of UI benefits is high, but the permanent job losers would particularly benefit from an expansion of UI benefits if the lockdown were extended, because unemployment shock is always longer than the length of the lockdown itself. Because the increased UI benefits have already expired, employment has not yet come back to normal, and further restrictions are being put into place, we can interpret these results to mean that the permanent job losers would benefit from an extension of UI benefits as long as restrictions are in place: Their unemployment status will persist even after pandemic-induced restrictions end. Gregory et al. (2020) also differentiate between those on temporary layoffs and those who are permanent job losers and find that the lockdown disproportionately disrupts the latter group, because it takes them much longer to find a new job. The difference between a temporary pandemic-induced unemployment and a more permanent job loss is important to inform policy, as discussed in Gallant et al. (2020) (PDF) and in Forsythe et al. (2020b) (PDF) , who suggest that policies designed to prop up labor demand would be successful.

Generosity of UI benefits and return-to-work decisions. The effectiveness of the UI benefits is also due to their generosity: As reported by Ganong et al. (2020) , this generosity leads to a median replacement rate (the level of total UI benefits divided by the pre-unemployment wage) of 134 percent. They find that around two-thirds of workers have a replacement rate greater than 100 percent (as in, they receive higher benefits than the wage they used to receive.) This generosity has spurred a lot of discussion on whether such high benefits would reduce workers' willingness to go back to work because they suddenly make more than their previous wage (see, for example, Barrero et al. 2020 ) . Both Petrosky-Nadeau (2020) and Boar and Mongey (2020) show that this is not the case because the UI benefits are too small and too short-lived to induce individuals to give up a return-to-work offer. Their findings are confirmed by data evidence showing that return-to-work and employment rates were not lower in states where the UI benefit expansion was larger (see Altonji et al. 2020 (PDF) , Bartik et al. 2020 , Dube 2020 , and Marinescu et al. 2020 ) . In the very short term, Fang et al. (2020) find that expanded UI benefits would lead to higher unemployment in the second half of the year, with larger effects with higher benefits, but that the policy would still enhance well-being for the population as a whole.

Optimality of UI benefits. The studies discussed so far analyzed the effectiveness of UI benefits and their impact on return-to-work offers, but they did not focus on whether the policy intervention was optimal. Theoretically, Guerrieri et al. (2020) show that abundant social insurance (bundled with a loosening of monetary policy) is a key ingredient of an optimal policy response in a pandemic where such a policy would reallocate income from workers in sectors that are not particularly affected by the pandemic to workers in sectors that are. Bredemeier et al. (2020) PDF (PDF) provide evidence for this result quantitatively. Mitman and Rabinovich (2020) find that the $600/week-policy was close to optimal and that UI benefits should be optimally increased at the start of the crisis but then lowered as the economy reopens to align incentives to return to work. Nevertheless, coupling extended UI benefits with a re-employment bonus would be an even better option because individuals would receive much-needed help while maintaining all incentives to search for a job. It is worth noting that the previously discussed studies both empirically and quantitatively show that return-to-work rates were not significantly affected by increased UI benefits, therefore indicating that the more-generous UI benefits did not induce the unemployed to choose to remain unemployed when offered a job. Birinci et al. (2020) find that the optimal policy would bundle UI benefits with payroll subsidies. Kapička and Rubert (2020) analyze the optimal policy by including virus transmission and by examining what labor-market policy would save the most lives and find that it would have been optimal to shut down businesses, impose a quarantine several weeks before the pandemic peak, and move a quarter of workers out of employment to limit transmission.

Stimulus Checks

CARES provisions. The CARES Act provision prescribes a direct cash payment of $1,200 for each adult with an annual income of $75,000 or less plus $500 for each child. For incomes higher than $75,000, the benefit begins to phase out and is nil for any income at or above $99,000.

Impact of stimulus checks on spending. Carroll et al. (2020) (PDF) use their model to also estimate the impact of the stimulus checks on consumer spending for consumers in each of the three employment categories: those who are employed, those who are on temporary layoffs, and those who are permanent job losers. The employed are the ones who suffer the least and save the highest share of the stimulus check upon receipt, but their spending rebounds as soon as the lockdown ends. The lack of spending choices available during the lockdown induces the saving, but once those choices become available again, those individuals' healthy finances allow spending to rebound. For the other two groups, both the individuals on temporary layoffs who expect to resume their jobs once the lockdown ends and the individuals who are permanent job losers who do not expect to resume their jobs, the unemployment insurance benefits provide a much bigger impact on their spending because of the larger per-individual amount. For those individuals who are permanent job losers in particular, the impact of the checks on immediate consumption is quite small because they know they will need to smooth that check over a longer period. For the employed, whose spending is affected only by the stimulus, the authors find that, even without a lockdown, only about 20 percent of the stimulus amount would be spent immediately. The fact that only 20 percent of the checks would be spent even in the absence of any restrictive measures is indicative of the impact that the pandemic directly had on spending. This impact is also evident in household-level bank-account data, as in Bachas et al. (2020) , in weekly state-level data, as in Kobayashi et al. (2020) , and in the aggregate, as verified by the Bureau of Labor Statistics (2020) analysis in April, which showed that aggregate income rose because of the policy interventions despite the output and consumption decline caused by the restriction measures.

Optimality of stimulus checks. The previously discussed papers take government interventions as given. The optimality of these interventions, however, is not examined. By contrast, Nygaard et al. (2020) (PDF) analyze what would be the (constrained-)optimal allocation of the stimulus checks under information that can be observed by the government through the individuals' tax returns, such as the individuals' marital status, age, income, or number of children. To derive the optimal allocation of stimulus checks, they first use a life-cycle consumption-savings model with heterogeneous consumers to predict the consumption responses to $100 increments of cash transfers by age, income, marital status, and number of children. They then compare all feasible allocations of the stimulus checks across households to examine whether the government could both spend less and achieve more stimulus than was achieved under the CARES Act, and derive the allocation that leads to the highest stimulus effect. They find that the poor and the young, especially those with children, should have received a larger check, which is an allocation that would have allowed for the same stimulus effect at half the cost of the actual allocation. Nygaard et al. (2020) (PDF) further study the optimal allocation of a second round of stimulus checks. They find that the first round of checks was not large enough. Consequently, the optimal second-round policy is similar to the optimal first-round policy: Money should be allocated to the young and to poor households with children. Their findings also suggest that a stricter income requirement would lead to a larger stimulus effect.

Empirical analysis of spending patterns following stimulus. A separate strand of this growing literature uses large administrative datasets, such as transaction records, or large-scale surveys (such as Wozniak et al. 2020 , among others) to measure how consumption changed following the pandemic. Bhutta et al. (2020) estimate that an additional 2 percent of typical working families would be able to cover six months of expenses after an unexpected income disruption, such as a job loss, thanks to the receipt of the stimulus check. Baker et al. (2020) find that recipients on average spent about a third of the stimulus checks within a few weeks, with larger effects for poorer consumers. Coibion et al. (2020) find that individuals reported having spent or planned to spend around 40 percent of the total transfer on average, and the amount is higher for the unemployed, the more financially constrained, those in larger households, those who are less educated, and those who qualified for smaller transfers. Armantier et al. (2020) find that 29 percent of all stimulus payments was used for consumption, with another 35 percent used to pay down debt and the rest saved. Chetty et al. (2020a) find that stimulus payments to low-income households had large effects on their consumption. Karger and Rajan (2020) use transaction-level data during the two weeks before and after the stimulus check to analyze the change in credit- and debit-card spending immediately following the stimulus receipt. They find that the poor spent most of their check, while those in better financial health spent 23 percent of their transfer. Sahm et al. (2020) find that poorer individuals spend most of their checks to repay debt and that the richest individuals save the largest share of the amount received. Misra et al. (2020) use transaction-level data from debit cards to find that about 40 percent of every dollar in stimulus is spent within the first four days from receipt and to document geographical differences in spending. Li et al. (2020) also document geographical differences by using transaction-level data from debit cards owned by low-income households, and also find that the stimulus payments had a positive and sizable effect on spending for low-income households and that the positive effect from the stimulus payment was four times as high in absolute value as the negative effect that the lockdown had on spending for the same group. Positive effects on the poverty level were also found by Han et al. (2020) . All of these data findings are consistent with the models discussed above: The poor, the young, and those with children are likely to benefit from higher amounts of stimulus because they are more financially constrained and would spend a higher amount of the transfer received for any check amount.

Difficulty to reach the most marginalized. Finally, while the most disadvantaged would benefit the most from these stimulus payments, Bitler et al. (2020) discuss how many individuals remained and still are in distress despite the unprecedented policy response due to delays in implementation, the modest payments outside of UI benefits, and statutory requirements that exclude individuals that would benefit the most from the payments themselves. In particular, Marr et al. (2020) (PDF) estimate that 12 million non-tax-return filers who are eligible for the stimulus check did not automatically receive it and had to request it. Because of this extra hurdle, there was a difference of nearly 20 percentage points in the receipt rate of stimulus checks between those eligible individuals below and and those above the poverty rate, at the expense of the poorer individuals. The papers discussed suggest that an implementation that does not favor those who are the most in need is far from an optimal allocation of the stimulus checks and leads to payments being made to those who would consume less of the overall payment because of their better financial health, and therefore to a lower stimulus effect overall. References Altonji, Joseph, et al. " Employment Effects of Unemployment Insurance Generosity During the Pandemic. (PDF) " Yale University Manuscript (2020).

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1. A version of this note was published in Covid Economics, Vetted and Real-Time Papers 64 (2021):186-201. Return to text

The views expressed in this Note are the views of the authors' only and do not represent the views of the colleagues at the Board of Governors or the views of the Federal Reserve System as a whole.

Falcettoni, Elena, and Vegard Nygaard (2021). "Acts of Congress and COVID-19: A Literature Review on the Impact of Increased Unemployment Insurance Benefits and Stimulus Checks," FEDS Notes. Washington: Board of Governors of the Federal Reserve System, February 24, 2021, https://doi.org/10.17016/2380-7172.2848.

Disclaimer: FEDS Notes are articles in which Board staff offer their own views and present analysis on a range of topics in economics and finance. These articles are shorter and less technically oriented than FEDS Working Papers and IFDP papers.

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Drivers and consequences of land degradation on livestock productivity in sub-saharan africa: a systematic literature review.

1. Introduction

2. materials and methods, 2.1. study design, 2.2. pertinence and state of the matter studied, 2.3. literature search, 2.4. inclusion and exclusion criteria.

2.5. Data Extraction and Synthesis

2.6. data analysis, 3. results and discussion, 3.1. primary drivers of land degradation in sub-saharan rangelands.

3.2. Impact of Land Degradation on Livestock Health, Productivity, and Mortality

3.3. Socio-Economic Consequences of Reduced Livestock Productivity

3.4. Effectiveness of Mitigation and Adaptation Strategies

3.5. Key Themes and Insights from the Word Cloud on Land Degradation, Rangelands, and Livestock in Sub-Saharan Africa

3.6. insights from the co-occurrence network diagram on land degradation, rangelands, and livestock in sub-saharan africa, 4. recommendations for policy makers in charge of these problems and future research directions, 5. potential limitations, 6. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

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Slayi, M.; Zhou, L.; Dzvene, A.R.; Mpanyaro, Z. Drivers and Consequences of Land Degradation on Livestock Productivity in Sub-Saharan Africa: A Systematic Literature Review. Land 2024 , 13 , 1402. https://doi.org/10.3390/land13091402

Slayi M, Zhou L, Dzvene AR, Mpanyaro Z. Drivers and Consequences of Land Degradation on Livestock Productivity in Sub-Saharan Africa: A Systematic Literature Review. Land . 2024; 13(9):1402. https://doi.org/10.3390/land13091402

Slayi, Mhlangabezi, Leocadia Zhou, Admire Rukudzo Dzvene, and Zolisanani Mpanyaro. 2024. "Drivers and Consequences of Land Degradation on Livestock Productivity in Sub-Saharan Africa: A Systematic Literature Review" Land 13, no. 9: 1402. https://doi.org/10.3390/land13091402

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Kursk , oblast (region), western Russia . The oblast is centred on Kursk city . It extends across the southern end of the Central Russian Upland . The surface is a rolling plateau , broken by broad, shallow valleys. Almost everywhere the natural forest - steppe vegetation has been replaced by farming, which in some parts has caused severe gully erosion . About three-fourths of the oblast ’s land is arable, and grains, sugar beets, hemp, potatoes, and other vegetables are grown; pig keeping also is important. Most local industry is concerned with processing farm produce, but there are also large machine-building and chemical industries in Kursk city. In the 1950s exploitation of the extensive iron-ore deposits, known as the Kursk Magnetic Anomaly , was begun near Zhelezogorsk and developed very rapidly; much is mined by open-pit methods. Area 11,500 square miles (29,800 square km). Pop. (2006 est.) 1,183,884.

Evaluation of High-Quality Development Level of Regional Economy and Exploration of Index Obstacle Degree: A Case Study of Henan Province

• Published: 06 September 2024

Cite this article

• Jun Zhou 1 ,
• Tang-fei Hu 3 ,
• Zhengqi Wei   ORCID: orcid.org/0000-0002-1699-3321 2 &
• Dandan Ji 4  

As China’s economy transitions from a phase of high-speed growth to one of high-quality development, the study of high-quality economic development has become increasingly important. Assessing and analyzing the current level of high-quality economic development can provide guiding recommendations for future economic transformation and high-quality growth. This research constructs an evaluation index system for high-quality economic development based on panel data from Henan Province spanning from 2006 to 2021. The entropy weight method combined with the TOPSIS model is utilized to determine the weights of each indicator and to assess the level of high-quality economic development in Henan Province; a coupling coordination model is employed to analyze the degree of coupling and coordination among its subsystems; and a barrier degree model is applied to identify the main obstacles to high-quality economic development in Henan Province. The study finds that (1) the proportion of technology market turnover has the most significant impact on high-quality economic development, while the revenue sharing level has the least. (2) During the research period, both the level of high-quality economic development in Henan Province and the subsystems of economic structure, innovation drive, regional coordination, and social welfare have shown an upward trend. (3) The coupling coordination degree of the subsystems increases at a rate of approximately 9% per year. (4) The obstacle degree of the economic stability, regional coordination, and infrastructure subsystems is on the rise, while that of the economic structure, opening up level, and social welfare subsystems is decreasing. (5) The inhibitory effects of the urban–rural income coordination level, the coordination level of urban and rural consumption, the community service level, the global unemployment rate, and the global trade level have intensified since 2017. Based on the aforementioned research findings, this paper proposes a series of policy recommendations. The translation ensures logical coherence and enhances the overall quality and readability of the content.

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Zhou, J., Hu, Tf., Wei, Z. et al. Evaluation of High-Quality Development Level of Regional Economy and Exploration of Index Obstacle Degree: A Case Study of Henan Province. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-02252-w

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Received : 18 April 2023

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DOI : https://doi.org/10.1007/s13132-024-02252-w

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