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Advisor(s)
Abstract(s)
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 article 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.
Description
Keywords
Binary Responses Index Models Monte Carlo Analysis
Pedagogical Context
Citation
Ramalho, Esmeralda A. and Joaquim J.S. Ramalho. (2011). “Alternative versions of the reset test for binary response index models: a comparative study”. Oxford Bulletin Of Economics And Statistics, Vol. 74, No. 1: pp. 107-130. (Search PDF in 2023).
Publisher
John Wiley & Sons Ltd. | Department of Economics, University of Oxford