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Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models

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  • Arthur Lewbel

Abstract

This article proposes a new method of obtaining identification in mismeasured regressor models, triangular systems, and simultaneous equation systems. The method may be used in applications where other sources of identification, such as instrumental variables or repeated measurements, are not available. Associated estimators take the form of two-stage least squares or generalized method of moments. Identification comes from a heteroscedastic covariance restriction that is shown to be a feature of many models of endogeneity or mismeasurement. Identification is also obtained for semiparametric partly linear models, and associated estimators are provided. Set identification bounds are derived for cases where point-identifying assumptions fail to hold. An empirical application estimating Engel curves is provided.

Suggested Citation

  • Arthur Lewbel, 2010. "Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 67-80, December.
  • Handle: RePEc:taf:jnlbes:v:30:y:2010:i:1:p:67-80
    DOI: 10.1080/07350015.2012.643126
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    Cited by:

    1. Krauth Brian, 2016. "Bounding a Linear Causal Effect Using Relative Correlation Restrictions," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 117-141, January.
    2. Prono, Todd, 2011. "When A Factor Is Measured with Error: The Role of Conditional Heteroskedasticity in Identifying and Estimating Linear Factor Models," MPRA Paper 33593, University Library of Munich, Germany.
    3. M. Shahe Emran & Forhad Shilpi, 2012. "The extent of the market and stages of agricultural specialization," Canadian Journal of Economics, Canadian Economics Association, vol. 45(3), pages 1125-1153, August.
    4. Inas Kelly & Dhaval Dave & Jody Sindelar & William Gallo, 2014. "The impact of early occupational choice on health behaviors," Review of Economics of the Household, Springer, vol. 12(4), pages 737-770, December.
    5. Todd Prono, 2008. "GARCH-based identification and estimation of triangular systems," Risk and Policy Analysis Unit Working Paper QAU08-4, Federal Reserve Bank of Boston.
    6. Clive R. Belfield & Inas Rashad Kelly, 2012. "The Benefits of Breast Feeding across the Early Years of Childhood," Journal of Human Capital, University of Chicago Press, vol. 6(3), pages 251-277.
    7. Yi Huang & Marco Pagano & Ug Panizza, 2016. "Local Crowding Out in China," CSEF Working Papers 450, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 13 Nov 2017.
    8. Tsunao Okumura, 2011. "Nonparametric Estimation of Labor Supply and Demand Factors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 174-185, January.
    9. Yi Huang & Marco Pagano & Ugo Panizza, 2016. "Public Debt and Private Firm Funding: Evidence from Chinese Cities," IHEID Working Papers 10-2016, Economics Section, The Graduate Institute of International Studies, revised Aug 2016.
    10. Leandro M. Magnusson & Sophocles Mavroeidis, 2014. "Identification Using Stability Restrictions," Econometrica, Econometric Society, vol. 82, pages 1799-1851, September.
    11. Amini, Chiara & Nivorozhkin, Eugene, 2015. "The urban–rural divide in educational outcomes: Evidence from Russia," International Journal of Educational Development, Elsevier, vol. 44(C), pages 118-133.
    12. Alan Fernihough, 2017. "Human capital and the quantity–quality trade-off during the demographic transition," Journal of Economic Growth, Springer, vol. 22(1), pages 35-65, March.
    13. Vouldis, Angelos, 2015. "Credit market disequilibrium in Greece (2003-2011) - a Bayesian approach," Working Paper Series 1805, European Central Bank.
    14. Claudia Buch & Iris Kesternich & Alexander Lipponer & Monika Schnitzer, 2014. "Financial constraints and foreign direct investment: firm-level evidence," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 150(2), pages 393-420, May.
    15. March, Raymond J. & Lyford, Conrad P. & Carpio, Carlos E. & Boonsaeng, Tullaya, 2016. "Do SNAP Recipients Get the Best Prices?," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 236213, Agricultural and Applied Economics Association.

    More about this item

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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