The Unassuming Economist

Source: VoxEU CEPR

“Rising inequality and firms’ market power pose challenges to the aims of inclusive growth and shared prosperity. Nevertheless, growth and equity need not be mutually exclusive. This column argues that economic dynamism is crucial for achieving sustained growth and more equal market outcomes (Figure 1). It shows that countries that experienced faster growth over the last four decades have lower market inequality in the 2010s. Policy should be aimed at supporting sophisticated export industries, fostering innovation and creative destruction, and promoting competition.“

Figure 1: Relationship between long-run economic growth and market inequality (1974-2014)

Source: International Labor Organization

The report examines the impacts of the COVID-19 crisis on global and regional trends in employment, unemployment, and labor force participation, as well as on job quality, informal employment, and working poverty. It also offers an extensive analysis of trends in temporary employment both before and during the pandemic.

On the basis of the latest economic growth forecasts, the ILO is projecting that total hours worked globally in 2022 will remain almost 2 percent below their pre-pandemic level when adjusted for population growth, corresponding to a deficit of 52 million full-time equivalent jobs (assuming a 48-hour working week). Global unemployment is projected to stand at 207 million in 2022, surpassing its 2019 level by some 21 million. Region-wise, the European and Pacific regions are projected to come closest to that goal, whereas the outlook is the most negative for Latin America and the Caribbean and for SouthEast Asia.

The report also goes on to discuss ways for ensuring a sustainable and inclusive recovery. Action points highlighted in the adoption of the Global Call to Action for a Human Centred Recovery from the COVID-19 Crisis that is Inclusive, Sustainable and Resilient at the June 2021 ILO Conference are centered on the theme of addressing systemic and structural inequalities and other long-term social and economic challenges, such as climate change, that pre-date the pandemic.

The outbreak of the novel Coronavirus, or COVID-19, has exacerbated economic and social inequalities. Several studies have tried to capture the impact of the same using extensive qualitative and quantitative data, spanning diverse categories like economic backgrounds, geographical regions, sex, caste, color, and other such social identities, inter alia.

The NBER paper, Inequality in the Times of a Pandemic (2022), by Stefanie Stantcheva, maps findings “related to inequalities across the income distribution, sectors and regions, gender, and inequalities in education inputs for children from different socioeconomic backgrounds”.

On similar lines but delving deeper on the issue of income inequalities, the paper, Epidemics, pandemics and income inequality (2022) in Health Economics Review attempts to understand how the outbreak of diseases like the Coronavirus, Ebola, Avian flu, etc., have impacted income distributions in the first two decades of the 21st century. The paper develops a model that indicates a positive association between these health crises and income inequality. To empirically test theoretical predictions, it explores the effect on the Gini coefficient of a dummy variable that indicates the occurrence of an epidemic or a pandemic in a country in a given year and the number of deaths per 100,000. To properly address potential endogeneity, the authors implement a Three-Stage-Least Squares technique. The estimation shows that the number of deaths per 100,000 population variable has a statistically significant positive effect on the Gini coefficient, especially when COVID-19 data is included.

Building upon their earlier work on the same topic, economists Monica Langella and Alan Manning of the Centre for Economic Performance, London School of Economics, further assess spatial differences and trends in internal migration to understand unemployment adjustment in the United Kingdom.

Abstract– “This paper uses UK census data to investigate how unemployment affects residential mobility using small areas as potential destinations and origins and four decades of data. It finds that both in- and out-migration are affected by local unemployment – but also that there is a very high ‘cost of distance’, so most moves are very local. We complement the study with individual longitudinal data to analyse individual heterogeneities in mobility. We show that elasticities to local unemployment are different across people with different characteristics. For instance, people who are better educated are more sensitive, the same applies to homeowners. Ethnic minorities are on average less sensitive to local unemployment rates and tend to end up in higher unemployment areas when moving.”

The paper offers comprehensive coverage of contrasting evidence, which on one hand shows that theoretically migration from economically depressed to booming areas must tackle unemployment, but on the other makes one question if this principle still holds owing to empirical results found from studies conducted in the US labor market (M. Dao, D. Furceri, P. Loungani, 2017). It proceeds to offer reasons to support the claim that migration response to economic booms has been observed to slow down on several instances, and reconciles the diverse range of evidence available from experiences of different countries.

Click here to read the full paper.

From a new IMF Working Paper (2022) by Katharina Bergant, Miss Anke Weber, and Andrea Medici.

Summary:

“Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United States over the last four decades. Employing a price index that appears appropriate for low-income households, we show that poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our results are threefold. First, we identify the poor as more likely to be minorities, without a college education, never married, and living in the Midwest. Second, the importance of some factors, such as race and ethnicity, for determining poverty has declined over the last decades but they remain significant. Third, we find that social and economic factors can only partially capture the likelihood of being poor, pointing to the possibility that random factors (“bad luck”) could play a significant role.”