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What is Probit

Applied Econometric Analysis: Emerging Research and Opportunities
Just like the logit, probit also translates the values of the independent variables to range '0' to '1' and uses the standard normal distribution function. Thus, the error term is standard normal distribution. Probit has almost similar results as logit.
Published in Chapter:
Categorical Dependent Variables Estimations With Some Empirical Applications
Alhassan Abdul-Wakeel Karakara (University of Cape Coast, Ghana) and Evans S. C. Osabuohien (Covenant University, Nigeria)
Copyright: © 2020 |Pages: 26
DOI: 10.4018/978-1-7998-1093-3.ch008
Abstract
Microeconomic datasets are usually large, mainly survey data. These data are samples of hundreds of respondents or group of respondents (e.g., households). The distributions of such data are mostly not normal because some responses/variables are discrete. Handling such datasets poses some problems of summarizing/reporting the important features of the data in estimations. This study concentrates on how to handle categorical variables in estimation/reporting based on theoretical and empirical knacks. This study used Ghana Demographic and Health Survey data for 2014 for illustration and elaborates on how to interpret results of binary and multinomial outcome regressions. Comparison is made on the different binary models, and binary logit is found to be weighted over the other binary models. Multinomial logistic model is best handled when the odds of one outcome versus the other outcome are independent of other outcome alternatives as verified by the Independent of Irrelevant Alternatives (IIA). Conclusions and suggestions for handling categorical models are discussed in the study.
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Digital Technologies in Italian Cultural Institutions
A probit model is a statistical method to perform regression for binary outcome variables (0, 1). The probit model estimates the probability a value will fall into one of the two possible binary (i.e. unit) outcomes.
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