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Specification tests in ordered logit and probit models

Andrew Weiss

Open publisher page 30 citations

Abstract

In this paper, I study the application of various specification tests to ordered logit and probit models with heteroskedastic errors, with the primary focus on the ordered probit model. The tests are Lagrange multiplier tests, information matrix tests, and chi-squared goodness of fit tests. The alternatives are omitted variables in the regression equation, omitted varaibles in the equation describing the heteroskedasticity, and non-logistic/non-normal errors. The alternative error distributions include a generalized logistic distribution in the ordered logit model and the Pearson family in the ordered.

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What this paper is about

In this paper, I study the application of various specification tests to ordered logit and probit models with heteroskedastic errors, with the primary focus on the ordered probit model. The tests are Lagrange multiplier tests, information matrix tests, and chi-squared goodness of fit tests. The alternatives are omitted variables in the regression equation, omitted varaibles in the equation describing the heteroskedasticity, and non-logistic/non-normal errors. The alternative error distributions include a generalized logistic distribution in the ordered logit model and the Pearson family in the ordered.

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Available abstract

In this paper, I study the application of various specification tests to ordered logit and probit models with heteroskedastic errors, with the primary focus on the ordered probit model. The tests are Lagrange multiplier tests, information matrix tests, and chi-squared goodness of fit tests. The alternatives are omitted variables in the regression equation, omitted varaibles in the equation describing the heteroskedasticity, and non-logistic/non-normal errors. The alternative error distributions include a generalized logistic distribution in the ordered logit model and the Pearson family in the ordered.

Key concepts: Heteroscedasticity, Ordered probit, Logit, Logistic regression, Econometrics, Probit, Mathematics, Goodness of fit

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