Inference in limited dependent variable models robust to weak identification
AbstractWe propose tests for structural parameters in limited dependent variable models with endogenous explanatory variables. These tests are based upon the generalized minimum distance principle. They are of the correct size regardless of whether the structural parameters are identified and are especially appropriate for models whose moment conditions are non-linear in the parameters. Moreover, they are computationally simple, allowing them to be implemented using a large number of statistical software packages. We compare our tests to Wald tests in a simulation experiment and use them to analyse the female labour supply and the demand for cigarettes. Copyright (C) 2010 The Author(s). The Econometrics Journal (C) 2010 Royal Economic Society
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Bibliographic InfoArticle provided by Royal Economic Society in its journal Econometrics Journal.
Volume (Year): 13 (2010)
Issue (Month): 3 (October)
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Other versions of this item:
- Leandro M. Magnusson, 2008. "Inference in Limited Dependent Variable Models Robust to Weak Identification," Working Papers 0801, Tulane University, Department of Economics, revised Apr 2009.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
- C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
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