How can labour market performance in emerging economies be improved? We use the new OECD Jobs Strategy framework to discuss how emerging economies can confront the dual challenge of low productivity and inclusiveness in a context of widespread informality. We argue that pervasive informality implies that large parts of the workforce do not have access to social insurance or basic regulatory protections. It also limits the ability of the government to collect taxes and hence the resources at its disposal to confront the challenge of promoting inclusive growth. A comprehensive approach is needed that simultaneously promotes formality and reaches out to the most vulnerable.
The recent revival of protectionism has prompted further interests in the domestic employment effects of imports, in particular from China. In a VoxEU column, I and my coauthor Olaf van Vliet examine the association between Chinese imports and domestic employment effects in 17 sectors across 18 OECD countries with diverse labour market institutions. The results indicate that employment fell in sectors that are more exposed to imports from China, especially among low-skilled workers. You can find our open-access research paper here.
Divergence between the evolution of GDP per capita and the income of a “typical” household as measured in household surveys is giving rise to a range of serious concerns, especially in the USA. In a new paper published in Review of Income and Wealth, together with Brian Nolan and Max Roser we investigate the extent of that divergence and the factors that contribute to it across 27 OECD countries, using data from OECD National Accounts and the Luxembourg Income Study. While GDP per capita has risen faster than median household income in most of these countries over the period these data cover, the size of that divergence varied very substantially, with the USA a clear outlier. The paper distinguishes a number of factors contributing to such a divergence, and finds wide variation across countries in the impact of the various factors. These findings have serious implications for the monitoring and assessment of changes in household incomes and living standards over time.
Large multilateral organisations like WHO and the UN rely heavily on average income data in determining eligibility for, and the allocation of, development assistance for health. This column tests this paradigm by analysing the determinants of health outcomes for 99 countries. A country’s epidemiological surroundings, poverty gap, and institutional capacity appear to be much better predictors of health outcomes than gross national income. These findings suggest alternative metrics that could be leveraged in allocating development assistance for health.
From today onwards, I am working as a research fellow at the Overseas Development Institute (ODI) in London! I am part of their Social Protection and Social Policy team. I am very excited to contribute to their work on social protection and development; including studying and advising on the rise of the gig economy in low and middle income countries, taxes & transfers, and health insurance coverage. You can find my ODI profile here – and please reach out if you have overlapping interests.
Technological change presents an occupational risk for individuals in routine work, as these occupations are more prone to being automated. In a paper forthcoming with Comparative Political Studies with David Rueda, we show with survey data for 17 European countries between 2002-2012 that individuals in routine occupations prefer public insurance against the increased risk of future income loss resulting from automation. We conclude that vulnerability to automation is an important determinant of the demand for redistribution.