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A New Measure of Fit for Equations with Dichotomous Dependent Variables

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  • Estrella, Arturo

Abstract

The econometrics literature contains many alternative measures of goodness of fit, roughly analogous to R-squared, for use with equations with dichotomous dependent variables. There is, however, no consensus as to the measures' relative merits or about which ones should be reported in empirical work. This article proposes a new measure that possesses several useful properties that the other measures lack. The new measure may be interpreted intuitively in a similar way to R-squared in the linear regression context.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 16 (1998)
Issue (Month): 2 (April)
Pages: 198-205

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Handle: RePEc:bes:jnlbes:v:16:y:1998:i:2:p:198-205

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  1. Dhrymes, Phoebus J., 1986. "Limited dependent variables," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 3, chapter 27, pages 1567-1631 Elsevier.
  2. John G. Cragg & Russell S. Uhler, 1970. "The Demand for Automobiles," Canadian Journal of Economics, Canadian Economics Association, vol. 3(3), pages 386-406, August.
  3. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
  4. Estrella, Arturo & Mishkin, Frederic S., 1997. "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European Central Bank," European Economic Review, Elsevier, vol. 41(7), pages 1375-1401, July.
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