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

Publication Search Results

Now showing 1 - 3 of 3
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    Evaluating the Accuracy of Homeowner Self-Assessed Rents in Peru
    (World Bank, Washington, DC, 2019-08) Ceriani, Lidia ; Olivieri, Sergio ; Ranzani, Marco
    Attributing a rental value to the dwellings of homeowners is essential in various contexts, including distributional analysis and the compilation of national accounts, consumer price indexes (CPIs), and purchasing power parity indexes. One of the methods for making the attribution is to use homeowner estimates of the market rental value they would pay (receive) for their dwellings if these were rented. This is known as homeowner self-assessed rent. However, homeowner estimates may not be accurate because of the way questions aimed at soliciting such information are phrased, the sentimental attachment of the homeowners to the properties, lack of information about rental markets, and other reasons. Yet, researchers and practitioners often neglect to ascertain the accuracy of homeowner assessments. This study argues that comparing unconditional or conditional means may be misleading if one has not ascertained whether the observable characteristics of homeowner and tenant dwellings are similar. Using Peruvian data from 2003 to 2017, the study tests the accuracy of self-assessed rental values with matching estimators. In Metropolitan Lima, homeowners typically provide accurate estimates of the rental market values of their dwellings. In rural areas, market rental values are underestimated by homeowners in more instances. The direction and magnitude of the inaccuracies in Metropolitan Lima and in rural areas are comparable and range between −25 percent and −20 percent.
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    Big Data for Sampling Design: The Venezuelan Migration Crisis in Ecuador
    (World Bank, Washington, DC, 2020-07) Munoz, Juan ; Munoz, Jose ; Olivieri, Sergio
    The worsening of Ecuador's socioeconomic conditions and the rapid inflow of Venezuelan migrants demand a rapid government response. Representative information on the migration and host communities is vital for evidence-based policy design. This study presents an innovative methodology based on the use of big data for sampling design of a representative survey of migrants and host communities' populations. This approach tackles the difficulties posed by the lack of information on the total number of Venezuelan migrants—regular and irregular—and their geographical location in the country. The total estimated population represents about 3 percent of the total Ecuadoran population. Venezuelans settled across urban areas, mainly in Quito, Guayaquil, and Manta (Portoviejo). The strategy implemented may be useful in designing similar exercises in countries with limited information (that is, lack of a recent census or migratory registry) and scarce resources for rapidly gathering socioeconomic data on migrants and host communities for policy design.
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    Housing, Imputed Rent, and Households' Welfare
    (World Bank, Washington, DC, 2019-08) Ceriani, Lidia ; Olivieri, Sergio ; Ranzani, Marco
    Housing is the largest durable good consumed by households. As such, any consumption-based measure of welfare, to be comprehensive, must include the value of the flow of services households derive from their dwellings, the so-called imputed rent. However, estimating imputed rents is a daunting task, which researchers and practitioners tend to overlook. This paper is the first attempt to assess the distributional impact of including housing in the welfare aggregate; the paper tests two estimation methods and analyzes four developing countries. The distributional impact cannot be predicted a priori, and evidence suggests it is context and method specific. Although changes in poverty and inequality are always statistically significant, they are only occasionally larger than one percentage point. By contrast, shared prosperity exhibits sizable changes, which might also determine international re-rankings. Albeit the inclusion of imputed rents reshuffles the set of poor households, observed changes in the socioeconomic profiling of the poor are unlikely to affect pro-poor policy design.