I show a simple back-of-the-envelope method for calculating marginal effects in binary choice and count data models. The approach suggested here focuses attention on marginal effects at different points in the distribution of the dependent variable rather than representative points in the joint...

I show a simple back-of-the-envelope method for calculating marginal effects in binary choice and count data models. The approach suggested here focuses attention on marginal effects at different points in the distribution of the dependent variable rather than representative points in the joint...

Estimation of marginal or partial effects of covariates x on various conditional parameters or functionals is often the main target of applied microeconometric analysis. In the specific context of probit models, estimation of partial effects involving outcome probabilities will often be of...

To test for group differences in growth trajectories in mixed (fixed and random effects) models, researchers frequently interpret the coefficient of Group-by-Time product terms. While this practice is straightforward in linear mixed models, it is less so in generalized linear mixed models. Using...

In non-linear regression models, such as the heteroskedastic probit model, coefficients cannot be interpreted as marginal effects. Marginal effects can be computed as a non-linear combination of the regression coefficients. Standard errors of the marginal effects needed for inference and...

In non-linear regression models, such as the probit model, coefficients cannot be interpreted as marginal effects. The marginal effects are usually non-linear combinations of all regressors and regression coefficients of the model. This paper derives the marginal effects in a probit model with a...

With ever increasing traffic loadings, highway pavement maintenance needs continue to outpace the availability of resources, and transportation agencies seek cost-effective maintenance practices. This study investigated the effectiveness of maintenance treatments in the short-term and the cost...

Bertschek and Lechner (1998) propose several variants of a GMM estimator based on the period specific regression functions for the panel probit model. The analysis is motivated by the complexity of maximum likelihood estimation and the possibly excessive amount of time involved in maximum...

Imagine we have two different samples and are interested in doing semi- or nonparametric regression analysis in each of them, possibly on the same econometric model. In this article we consider the problem of testing whether a specific covariate has different impacts on the regression curve in...