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Instrument Choice and the Returns to Education: New Evidence from Vietnam Author info | Abstract | Publisher info | Download info | Related research | Statistics Jean-Louis Arcand (CERDI-CNRS, University of Auvergne & European Development Network)
Béatrice d'Hombres (CERDI-CNRS, University of Auvergne & University of Padua)
Paul Gyselinck (CERDI-CNRS, University of Auvergne)
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This paper focuses on instrument choice while consistently estimating the returns to education in Vietnam. Using data culled from the 2 rounds of the Vietnam Living Standards Survey (VLSS), we explore different sets of exogenous instruments that rely on demand and supply side sources of variation in schooling as well as the matrix of instruments proposed by Hausman and Taylor (1981). Instrument validity tests suggest that many variables do not satisfy the necessary conditions allowing them to be used as instruments. As in several studies, we find that IV estimates of the returns to education are substantially higher than the corresponding OLS estimate. We show how the Hausman-Taylor matrix of instruments, when combined with other instruments, may be a useful way of consistently estimating an average return to education rather than a local average treatment effect (Angrist, 1994).
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Paper provided by EconWPA in its series Labor and Demography with number
0510011.
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Length: 22 pages
Date of creation: 11 Oct 2005Date of revision:
Handle: RePEc:wpa:wuwpla:0510011Note: Type of Document - pdf; pages: 22Contact details of provider: Web page: http://129.3.20.41
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Keywords: ate of return ; instrumental variables procedures ; Instrument choice ; Hausman-Taylor estimator ; Hahn-Hausman test ; Vietnam ; Other versions of this item:
Find related papers by JEL classification: J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials I21 - Health, Education, and Welfare - - Education - - - Analysis of Education C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
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