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Education policy reform, local average treatment effect and returns to schooling from instrumental variables in the Philippines

  • Chris Sakellariou

A nationally representative dataset from the Philippines is used to derive returns to schooling estimates from instrumental variables, utilizing a supply-side intervention in the education market capable of generating significant changes in schooling. These estimates apply to a subgroup of, mainly, liquidity constrained individuals, in the spirit of the Local Average Treatment Effect (LATE) literature. Returns to schooling estimates which apply to a subgroup of individuals affected by policy intervention may be more interesting from a policy perspective than the return to the 'average' individual. The findings are consistent with other recent evidence suggesting that the causal effect of education, at least for certain subgroups of individuals, is as big or bigger than what is suggested by OLS estimates.

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Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 38 (2006)
Issue (Month): 4 ()
Pages: 473-481

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Handle: RePEc:taf:applec:v:38:y:2006:i:4:p:473-481
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  1. Kevin J. Denny & Colm P. Harmon, 2000. "Education Policy Reform and the Return to Schooling from Instrumental Variabes," Econometric Society World Congress 2000 Contributed Papers 1422, Econometric Society.
  2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  3. Chris Sakellariou, 2004. "The use of quantile regressions in estimating gender wage differentials: a case study of the Philippines," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 1001-1007.
  4. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2002. "Instrumental variables and GMM: Estimation and testing," United Kingdom Stata Users' Group Meetings 2003 02, Stata Users Group.
  5. Ichino, Andrea & Winter-Ebmer, Rudolf, 1998. "Lower and Upper Bounds of Returns to Schooling: An Exercise in IV estimation with Different Instruments," CEPR Discussion Papers 2007, C.E.P.R. Discussion Papers.
  6. J.D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
  7. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2004. "Evaluating the impact of education on earnings in the UK: models, methods and results from the NCDS," LSE Research Online Documents on Economics 19451, London School of Economics and Political Science, LSE Library.
  8. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc.
  9. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  10. Maluccio, John A., 1998. "Endogeneity of schooling in the wage function," FCND discussion papers 54, International Food Policy Research Institute (IFPRI).
  11. Arjun Bedi & Noel Gaston, 1997. "Returns to endogenous education: the case of Honduras," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 519-528.
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