Inference in Limited Dependent Variable Models Robust to Weak Identification

Leandro Magnusson

No 801, Working Papers from Tulane University, Department of Economics

Abstract: 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.

Keywords: weak identification; minimum chi-square estimation; hypothesis testing; limited dependent variable models (search for similar items in EconPapers)
JEL-codes: C12 C30 C34 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2008-09, Revised 2009-04
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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http://repec.tulane.edu/RePEc/pdf/tul0801.pdf First version, 2008 (application/pdf)
http://repec.tulane.edu/RePEc/pdf/tul0801r1.pdf Revised version, 2009 (application/pdf)

Related works:
Journal Article: Inference in limited dependent variable models robust to weak identification (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:tul:wpaper:0801

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