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Kimball's failed replication of Reinhart-Rogoff finding cited in argument for tempered public response to social science research results

Edin and Shaefer's book on destitute families in America reviewed in NYT

Johnston says rate of daily marijuana use among college students now greater than rate of daily cigarette smoking

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Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Next Brown Bag

Monday, Oct 12
Joe Grengs, Policy & Planning for Social Equity in Transportation

Life Expectancy and the Timing of Life History Events in Developing Countries

Archived Abstract of Former PSC Researcher

Anderson, Kermyt G. 2010. "Life Expectancy and the Timing of Life History Events in Developing Countries." Human Nature-an Interdisciplinary Biosocial Perspective, 21(2): 103-123.

Life history theory predicts that greater extrinsic mortality will lead to earlier and higher fertility. To test this prediction, I examine the relationship between life expectancy at birth and several proxies for life history traits (ages at first sex and first marriage, total fertility rate, and ideal number of children), measured for both men and women. Data on sexual behaviors come from the Demographic and Health Surveys (DHS). Two separate samples are analyzed: a cross-sectional sample of 62 countries and a panel sample that includes multiple cross-sectional panels from 48 countries. Multivariate regression analysis is used to control for potential confounding variables. The results provide only partial support for the predictions, with greater support among women than men. However, the prediction is not supported in sub-Saharan African countries, most likely owing to the nonequilibrium conditions observed in sub-Saharan Africa with respect to life expectancy. The applicability of the model to understanding HIV/AIDS risk behaviors is discussed.

DOI:10.1007/s12110-010-9087-z (Full Text)

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