Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jul, 2011, Volume 79, Issue 4

Nature or Nurture? Learning and the Geography of Female Labor Force Participation

https://doi.org/10.3982/ECTA7767
p. 1103-1138

Alessandra Fogli, Laura Veldkamp

One of the most dramatic economic transformations of the past century has been the entry of women into the labor force. While many theories explain why this change took place, we investigate the process of transition itself. We argue that local information transmission generates changes in participation that are geographically heterogeneous, locally correlated, and smooth in the aggregate, just like those observed in our data. In our model, women learn about the effects of maternal employment on children by observing nearby women. When few women participate in the labor force, data are scarce and participation rises slowly. As information accumulates in some regions, the effects of maternal employment become less uncertain and more women in that region participate. Learning accelerates, labor force participation rises faster, and regional participation rates diverge. Eventually, information diffuses throughout the economy, beliefs converge to the truth, participation flattens out, and regions become more similar again. To investigate the empirical relevance of our theory, we use a new county‐level data set to compare our calibrated model to the time series and geographic patterns of participation.


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Supplemental Material

Supplement to "Nature or Nurture? Learning and the Geography of Female Labor Force Participation"

A zip file containing replication files for the manuscript.

Supplement to "Nature or Nurture? Learning and the Geography of Female Labor Force Participation"

This appendix contains details about the dynamic panel estimation, international evidence about labor force, details about survey data, and sources and summary statistics for all the county-level data.

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