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Alternative Versions of the RESET Test for Binary Response Index Models: A Comparative Study

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  • Esmeralda A. Ramalho
  • Joaquim J. S. Ramalho

Abstract

Binary response index models may be affected by several forms of misspecification, which range from pure functional form problems (e.g. incorrect specification of the link function, neglected heterogeneity, heteroskedasticity) to various types of sampling issues (e.g. covariate measurement error, response misclassification, endogenous stratification, missing data). In this paper we examine the ability of several versions of the RESET test to detect such misspecifications in an extensive Monte Carlo simulation study. We find that: (i) the best variants of the RESET test are clearly those based on one or two fitted powers of the response index; and (ii) the loss of power resulting from using the RESET instead of a test directed against a specific type of misspecification is very small in many cases.

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 74 (2012)
Issue (Month): 1 (02)
Pages: 107-130

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Handle: RePEc:bla:obuest:v:74:y:2012:i:1:p:107-130

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  1. J M C Santos Silva, 1996. "A Score Test for Non-nested Hypotheses with Applications to Discrete Data Models," Discussion Papers 96-28 ISSN 1350-6722, University College London, Department of Economics.
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Cited by:
  1. Esmeralda Ramalho & Joaquim Ramalho & Jose M.R. Murteira, 2012. "A supremum-type RESET test for binary choice models," Economics Bulletin, AccessEcon, vol. 32(1), pages 905-912.
  2. Tomás del Barrio Casto & William Nilsson & Andrés J. Picazo-Tadeo, 2013. "How wrong can you be, without noticing? Further evidence on speci cation errors in the Conditional Logit," Working Papers 1318, Department of Applied Economics II, Universidad de Valencia.
  3. Esmeralda A. Ramalho & Joaquim J.S. Ramalho & José M.R. Murteira, 2013. "A generalized goodness-of-functional form test for binary and fractional regression models," CEFAGE-UE Working Papers 2013_09, University of Evora, CEFAGE-UE (Portugal).

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