Olivieri, Sergio

Global Practice on Poverty, The World Bank
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Poverty and growth, Poverty measurement, Distributional impact of shocks, Labor informality, Inequality, Social Protection and Labor
Global Practice on Poverty, The World Bank
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Last updated July 12, 2023
Sergio Olivieri is an economist in the Poverty Reduction and Equity department of the World Bank, based in Washington, DC.  His main research areas are ex-ante analysis of the distributional impact of macroeconomic shocks, understanding the main channels through which economic growth affects poverty reduction, income distribution and multidimensional poverty. Olivieri has published articles about labor informality, polarization, mobility and inequality issues, most of them focused on Latin-American countries. He has also contributed to research reports on inequality, poverty, social cohesion and macroeconomic shocks. Before joining the Bank, Olivieri worked as a consultant for the Inter-American Development Bank, the United Nation Development Program and the European Commission. He has taught courses on micro-simulation and micro-decomposition techniques for public servants and staff in international organizations around the world. He has also worked as an assistant professor of labor economics in the Department of Economics of Universidad National de La Plata in Buenos Aires, and as a researcher in the university's Center of Distributional, Labor and Social Studies.
Citations 5 Scopus

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    Updating the Poverty Estimates in Serbia in the Absence of Micro Data : A Microsimulation Approach
    (World Bank, Washington, DC, 2014-05) Cojocaru, Alexandru ; Olivieri, Sergio
    The continued poverty impact of the financial crisis in Serbia is difficult to establish beyond 2010 because of the lack of survey data. This paper tackles this difficulty. It uses a micro-simulation approach that accounts for a key pathway of the financial crisis in Serbia, the labor market. The results suggest a further increase in poverty in 2011 on account of a continued deterioration of the labor market indicators and despite a recovering gross domestic product. In order to evaluate the forecast, the model is applied to generate forecasts for previous years (2009 and 2010), which are compared with realized poverty estimates. The micro-simulation model performs well in predicting poverty dynamics during 2009-10 and less so during 2008-09. The accuracy of the predictions improves when the response of the social protection system is accounted for.