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Research ArticleArticle

When Measure Matters

Coresidency, Truncation Bias, and Intergenerational Mobility in Developing Countries

M. Shahe Emran, William Greene and Forhad Shilpi
Journal of Human Resources, July 2018, 53 (3) 589-607; DOI: https://doi.org/10.3368/jhr.53.3.0216-7737R1
M. Shahe Emran
M. Shahe Emran is a researcher at IPD, Columbia University. William Greene is a professor of economics at NYU. Forhad Shilpi is a senior economist at DECRG, World Bank.
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William Greene
M. Shahe Emran is a researcher at IPD, Columbia University. William Greene is a professor of economics at NYU. Forhad Shilpi is a senior economist at DECRG, World Bank.
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Forhad Shilpi
M. Shahe Emran is a researcher at IPD, Columbia University. William Greene is a professor of economics at NYU. Forhad Shilpi is a senior economist at DECRG, World Bank.
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Article Information

vol. 53 no. 3 589-607
DOI 
https://doi.org/10.3368/jhr.53.3.0216-7737R1
Published By 
University of Wisconsin Press
Print ISSN 
0022-166X
Online ISSN 
1548-8004
History 
  • Received February 1, 2016
  • Accepted January 1, 2017
  • Published online June 25, 2018.

ARTICLE VERSIONS

  • Ahead of Print Version (Wednesday, April 19, 2017 - 3:11 PM).
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© 2018 by the Board of Regents of the University of Wisconsin System

Author Information

  1. M. Shahe Emran,
  2. William Greene and
  3. Forhad Shilpi
  1. M. Shahe Emran is a researcher at IPD, Columbia University. William Greene is a professor of economics at NYU. Forhad Shilpi is a senior economist at DECRG, World Bank.
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Journal of Human Resources: 53 (3)
Journal of Human Resources
Vol. 53, Issue 3
1 Jul 2018
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When Measure Matters
M. Shahe Emran, William Greene, Forhad Shilpi
Journal of Human Resources Jul 2018, 53 (3) 589-607; DOI: 10.3368/jhr.53.3.0216-7737R1

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When Measure Matters
M. Shahe Emran, William Greene, Forhad Shilpi
Journal of Human Resources Jul 2018, 53 (3) 589-607; DOI: 10.3368/jhr.53.3.0216-7737R1
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  • Article
    • Abstract
    • I. Introduction
    • II. Related Literature
    • III. Coresidency Restriction and Truncation Bias in a Simple Model
    • IV. Data and Variables
    • V. Empirical Results
    • VI. Conclusions
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Supplemental
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