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Surjit Bhalla, Karan Bhasin, and Mr. Arvind Virmani
The paper presents estimates of poverty [extreme poverty PPP$1.9 and PPP$3.2] and consumption inequality in India for each of the years 2004-5 through the pandemic year 2020-21. These estimates include, for the first time, the effect of in-kind food subsides on poverty and inequality. Extreme poverty was as low as 0.8 percent in the pre-pandemic year 2019, and food transfers were instrumental in ensuring that it remained at that low level in pandemic year 2020. Post-food subsidy inequality at .294 is now very close to its lowest level 0.284 observed in 1993/94.
Andras Komaromi, Mr. Diego A. Cerdeiro, and Yang Liu
Rising prices and reports of empty shelves in major economies have drawn attention to the functioning of supply chains that normally operate smoothly in the background. Among the issues, the long delays that port congestion may have caused in delivering goods to consumers and firms have been gathering increasing attention. We shed light on these issues leveraging a unique data set on maritime transport. Two main features emerge. First, at the world level, we find that shipping times jumped upwards as soon as the COVID crisis hit, and after a marked acceleration from end-2020, delays surpassed 1.5 days on average by December 2021 – or roughly a 25 percent increase in global travel times. The estimated additional days in transit for the average shipment in December 2021 can be compared to an ad-valorem tariff of 0.9 to 3.1 percent. The midpoint of this range is approximately equal, in absolute value, to the global applied tariff reduction achieved over the 14-year period from 2003 to 2017. Second, not all congestion appears related to increased demand. Many ports, especially since mid-2021, exhibit longer wait times despite handling less cargo than pre-pandemic. Infrastructure upgrading is therefore likely a necessary, but not sufficient condition for building resilience during a crisis where other factors (such as labor shortages) may also become binding.
Ana Lariau and Lucy Qian Liu
We analyze the differential impact of the COVID-19 crisis on the Spanish labor market across population groups, as well as its implications for income inequality. The main finding is that young, less educated, and low skilled workers, as well as women are the most affected by the COVID-19 shock in terms of job loss rates. The differential impacts were especially acute at the height of the pandemic in 2020 and remain robust after taking into account the heterogeneity of sector characteristics. Given that these vulnerable groups were positioned in the lower end of the income distribution before the crisis, we hypothesize that income inequality likely has increased due to the pandemic. Policies aiming at reducing inequality in the labor market need to go beyond measures that target the hardest-hit sectors and support the vulnerable groups more directly.
Katharina Bergant, Miss Anke Weber, and Andrea Medici
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.