Using Heterogeneous Choice Models to Compare Logit and Probit Coefficients Across Groups

Using Heterogeneous Choice Models To Compare Logit and Probit Coefficients Across Groups

Confounded coefficients: Accurately comparing logit and probit coefficients across groups

The logit and probit models are critical parts of the management researcher's analytical arsenal. We often want to know if a covariate has the same effect for different groups, e.g., foreign and domestic firms. Unfortunately, many attempts to compare the effect of covariates across groups make the unwarranted assumption that each group has the same residual variation. If this is not the case, c...

Probit and nested logit models based on fuzzy measure

Inspired by the interactive discrete choice logit models [Aggarwal, 2019], this paper presents the advanced families of discrete choice models, such as nested logit, mixed logit, and probit models to consider the interaction among the attributes. Besides the DM's attitudinal character is also taken into consideration in the computation of choice probabilities. The proposed choice models make us...

Comparing Regression Coefficients Between Models using Logit and Probit: A New Method

Logit and probit models are widely used in empirical sociological research. However, the widespread practice of comparing the coefficients of a given variable across differently specified models does not warrant the same interpretation in logits and probits as in linear regression. Unlike in linear models, the change in the coefficient of the variable of interest cannot be straightforwardly att...

Relaxing the IIA Assumption in Locational Choice Models: A Comparison Between Conditional Logit, Mixed Logit, and Multinomial Probit Models∗

This paper estimates a locational choice model to assess the demand for local public services, using a data set where individuals chooses between 26 municipalities within a local labor market. We assess the importance of the IIA assumption by comparing the predictions of three difference models; the conditional logit (CL) model, the mixed logit (MXL) model, and the multinomial probit (MNP) mode...