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Unemployment and Development

Ying Feng (), David Lagakos and James Rauch ()
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Ying Feng: University of California, San Diego

No 2018-083, Working Papers from Human Capital and Economic Opportunity Working Group

Abstract: This paper draws on household survey data from countries of all income levels to measure how average unemployment rates vary with income per capita. We document that unemployment is increasing with GDP per capita. Furthermore, we show that this fact is accounted for almost entirely by low-educated workers, whose unemployment rates are strongly increasing in GDP per capita, rather than by high-educated workers, whose unemployment rates are not correlated with income. To interpret these facts, we build a model with workers of heterogeneous ability and two sectors: a traditional sector, in which self-employed workers produce output without reward for ability; and a modern sector, in which firms hire in frictional labor markets, and output increases with ability. Countries differ exogenously in the productivity level of the modern sector. The model predicts that as productivity rises, the traditional sector shrinks, as progressively less-able workers enter the modern sector, leading to a rise in overall unemployment and in the ratio of low-educated to high-educated unemployment rates. Quantitatively, the model accounts for around one third of the cross-country patterns we document.

Keywords: unemployment; causal effects of education; ability effects; household survey data (search for similar items in EconPapers)
JEL-codes: E24 E26 O11 O41 (search for similar items in EconPapers)
Date: 2018-11
New Economics Papers: this item is included in nep-dge and nep-mac
Note: M
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http://humcap.uchicago.edu/RePEc/hka/wpaper/Feng_L ... ment-development.pdf First version, October 2018 (application/pdf)

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Working Paper: Unemployment and Development (2018) Downloads
Working Paper: Unemployment and Development (2018) Downloads
Working Paper: Unemployment and Development (2018) Downloads
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