Tracking the impact of COVID-19 on economic inequality at high frequency.

Pandemics have historically had a significant impact on economic inequality. However, official inequality statistics are only available at low frequency and with considerable delay, which challenges policymakers in their objective to mitigate inequality and fine-tune public policies. We show that using data from bank records it is possible to measure economic inequality at high frequency. The approach proposed in this paper allows measuring, timely and accurately, the impact on inequality of fast-unfolding crises, like the COVID-19 pandemic. Applying this approach to data from a representative sample of over three million residents of Spain we find that, absent government intervention, inequality would have increased by almost 30% in just one month. The granularity of the data allows analyzing with great detail the sources of the increases in inequality. In the Spanish case we find that it is primarily driven by job losses and wage cuts experienced by low-wage earners. Government support, in particular extended unemployment insurance and benefits for furloughed workers, were generally effective at mitigating the increase in inequality, though less so among young people and foreign-born workers. Therefore, our approach provides knowledge on the evolution of inequality at high frequency, the effectiveness of public policies in mitigating the increase of inequality and the subgroups of the population most affected by the changes in inequality. This information is fundamental to fine-tune public policies on the wake of a fast-moving pandemic like the COVID-19.

Who wants to work in a rural health post? The role of intrinsic motivation, rural background and faith-based institutions in Ethiopia and Rwanda.

OBJECTIVE: To understand the factors influencing health workers' choice to work in rural areas as a basis for designing policies to redress geographic imbalances in health worker distribution. METHODS: A cohort survey of 412 nursing and medical students in Rwanda provided unique contingent valuation data. Using these data, we performed a regression analysis to examine the determinants of future health workers' willingness to work in rural areas as measured by rural reservation wages. These data were also combined with those from an identical survey in Ethiopia to enable a two-country analysis. FINDINGS: Health workers with higher intrinsic motivation - measured as the importance attached to helping the poor - as well as those who had grown up in a rural area and Adventists who had participated in a local bonding scheme were all significantly more willing to work in a rural area. The main result for intrinsic motivation in Rwanda was strikingly similar to the result obtained for Ethiopia and Rwanda combined. CONCLUSION: Intrinsic motivation and rural origin play an important role in health workers' decisions to work in a rural area, in addition to economic incentives, while faith-based institutions can also influence the decision.

For public service or money: understanding geographical imbalances in the health workforce.

Geographical imbalances in the health workforce have been a consistent feature of nearly all health systems, and especially in developing countries. In this paper we investigate the willingness to work in a rural area among final year nursing and medical students in Ethiopia. Analysing data obtained from contingent valuation questions for final year students from three medical schools and eight nursing schools, we find that there is substantial heterogeneity in the willingness to serve in rural areas. Using both ordinary least squares and maximum likelihood regression analysis, we find that household consumption and the student's motivation to help the poor are the main determinants of willingness to work in a rural area. We carry out a simulation on how much it would cost to get a target proportion of health workers to take up a rural post.