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Inference in Limited Dependent Variable Models Robust to Weak Identification

  • Leandro M. Magnusson

    ()

    (Department of Economics, Tulane University)

We propose tests for structural parameters in limited dependent variable models with endogenous explanatory variables using the classical minimum distance framework. These tests have the correct size whether the structural parameters are identified or not. Relating to the current tests, the application of ours is appropriate especially to models whose moment conditions are nonlinear in parameters. Moreover, the computation of ours tests is simple, allowing their implementation in a large number of statistical software packages. We compare our tests with Wald tests by performing simulation experiments. We use our tests to analyze the female labor supply and the demand for cigarette.

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File URL: http://econ.tulane.edu/RePEc/pdf/tul0801.pdf
File Function: First version, 2008
Download Restriction: no

File URL: http://econ.tulane.edu/RePEc/pdf/tul0801r1.pdf
File Function: Revised version, 2009
Download Restriction: no

Paper provided by Tulane University, Department of Economics in its series Working Papers with number 0801.

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Length: 31 pages
Date of creation: Sep 2008
Date of revision: Apr 2009
Handle: RePEc:tul:wpaper:0801
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Web page: http://econ.tulane.edu

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  1. John Mullahy, 1997. "Instrumental-Variable Estimation Of Count Data Models: Applications To Models Of Cigarette Smoking Behavior," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 586-593, November.
  2. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-85, May.
  3. Thomas Mroz, . "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," University of Chicago - Population Research Center 84-8, Chicago - Population Research Center.
  4. Andrews, Donald W.K. & Soares, Gustavo, 2007. "Rank Tests For Instrumental Variables Regression With Weak Instruments," Econometric Theory, Cambridge University Press, vol. 23(06), pages 1033-1082, December.
  5. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  6. Sbordone, Argia M., 2005. "Do expected future marginal costs drive inflation dynamics?," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1183-1197, September.
  7. Blundell, Richard W & Smith, Richard J, 1989. "Estimation in a Class of Simultaneous Equation Limited Dependent Variable Models," Review of Economic Studies, Wiley Blackwell, vol. 56(1), pages 37-57, January.
  8. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-60, November.
  9. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
  10. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
  11. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, vol. 71(4), pages 1027-1048, 07.
  12. Blundell, Richard & MaCurdy, Thomas & Meghir, Costas, 2007. "Labor Supply Models: Unobserved Heterogeneity, Nonparticipation and Dynamics," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 69 Elsevier.
  13. Patrik Buggenberger & Richard Smith, 2003. "Generalized empirical likelihood estimators and tests under partial, weak and strong identification," CeMMAP working papers CWP08/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  14. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
  15. Arellano, M. & Bover, O. & Labeaga, J.M., 1997. "Autoregressive Models with Sample Selectivity for Panel Data," Papers 9706, Centro de Estudios Monetarios Y Financieros-.
  16. Andrew M. Jones & José M. Labeaga, 2003. "Individual heterogeneity and censoring in panel data estimates of tobacco expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(2), pages 157-177.
  17. Kleibergen, Frank, 2007. "Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics," Journal of Econometrics, Elsevier, vol. 139(1), pages 181-216, July.
  18. Olympia Bover & Manuel Arellano, 1997. "Estimating limited dependent variable models from panel data," Investigaciones Economicas, Fundación SEPI, vol. 21(2), pages 141-166, May.
  19. Santos Silva, J M C, 2001. "Influence Diagnostics and Estimation Algorithms for Powell's SCLS," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 55-62, January.
  20. Lee, Myoung-Jae, 1992. "Winsorized Mean Estimator for Censored Regression," Econometric Theory, Cambridge University Press, vol. 8(03), pages 368-382, September.
  21. Frank Kleibergen, 2005. "Testing Parameters in GMM Without Assuming that They Are Identified," Econometrica, Econometric Society, vol. 73(4), pages 1103-1123, 07.
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