Instrumental Variables Quantile Regression for Panel Data with Measurement Errors

Antonio Galvao () and Montes-Rojas, Gabriel ()
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Antonio Galvao: galvao@illinois.edu
Montes-Rojas, Gabriel: Department of Economics, City University, London, http://www.city.ac.uk/economics/staff/montes-rojas/index.html

No 09/06, City University Economics Discussion Papers from Department of Economics, City University, London

Abstract: This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T->0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables, which induces endogeneity and as a result bias in the model. We derive an approximation to the bias in the quantile regression fixed effects estimator in the presence of measurement error and show its connection to similar effects in standard least squares models. Monte Carlo simulations are conducted to evaluate the finite sample properties of the estimator in terms of bias and root mean squared error. Finally, the methods are applied to a model of firm investment. The results show interesting heterogeneity in the Tobin’s q and cash flow sensitivities of investment. In both cases, the sensitivities are monotonically increasing along the quantiles.

Keywords: Quantile Regression; Panel Data; Measurement Errors; Instrumental Variables (search for similar items in EconPapers)
JEL-codes: C14 C23 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2009-03
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Persistent link: http://EconPapers.repec.org/RePEc:cty:dpaper:0906

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