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A practical comparison of the bivariate probit and linear IV estimators

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  • Chiburis, Richard C.
  • Das, Jishnu
  • Lokshin, Michael

Abstract

This paper presents asymptotic theory and Monte-Carlo simulations comparing maximum-likelihood bivariate probit and linear instrumental variables estimators of treatment effects in models with a binary endogenous treatment and binary outcome. The three main contributions of the paper are (a) clarifying the relationship between the Average Treatment Effect obtained in the bivariate probit model and the Local Average Treatment Effect estimated through linear IV; (b) comparing the mean-square error and the actual size and power of tests based on these estimators across a wide range of parameter values relative to the existing literature; and (c) assessing the performance of misspecification tests for bivariate probit models. The authors recommend two changes to common practices: bootstrapped confidence intervals for both estimators, and a score test to check goodness of fit for the bivariate probit model.

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Bibliographic Info

Paper provided by The World Bank in its series Policy Research Working Paper Series with number 5601.

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Date of creation: 01 Mar 2011
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Handle: RePEc:wbk:wbrwps:5601

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Keywords: Scientific Research&Science Parks; Science Education; Statistical&Mathematical Sciences; Econometrics; Educational Technology and Distance Education;

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  1. Joshua Angrist, 1999. "Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice," Working papers 99-31, Massachusetts Institute of Technology (MIT), Department of Economics.
  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. Murphy, Anthony, 2007. "Score tests of normality in bivariate probit models," Economics Letters, Elsevier, vol. 95(3), pages 374-379, June.
  4. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2000. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," NBER Working Papers 7831, National Bureau of Economic Research, Inc.
  5. James J. Heckman, 1977. "Dummy Endogenous Variables in a Simultaneous Equation System," NBER Working Papers 0177, National Bureau of Economic Research, Inc.
  6. Angrist, Joshua D, 2001. "Estimations of Limited Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 27-28, January.
  7. Joshua D. Angrist, 1991. "Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology," NBER Technical Working Papers 0115, National Bureau of Economic Research, Inc.
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Cited by:
  1. Schneider, Hilmar & Uhlendorff, Arne & Zimmermann, Klaus F., 2011. "├ľkonometrie vs. Projektdesign: Lehren aus der Evaluation eines Modellprojekts zur Umsetzung des Workfare-Konzepts," IZA Discussion Papers 5599, Institute for the Study of Labor (IZA).
  2. Andrabi, Tahir & Das, Jishnu & Khwaja, Asim Ijaz, 2013. "Students today, teachers tomorrow: Identifying constraints on the provision of education," Journal of Public Economics, Elsevier, vol. 100(C), pages 1-14.
  3. Tobias Lechtenfeld, 2012. "Why does piped water not reduce diarrhea for children? Evidence from urban Yemen," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 119, Courant Research Centre PEG.
  4. Chang, Hung-Hao, 2013. "Does Food Consumption Away From Home Make You Happier? An Empirical Investigation of the Elderly in Taiwan," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149927, Agricultural and Applied Economics Association.

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