A benefit because probit modeling (and its close cousin logit modeling) can be customized in an endless variety to extract estimates of a particular state from raw data.

Next, we use the probit model to interpret that history via CS-ETI for estimating where we stand currently. Each month in history is referenced as either a 0 (no recession) or 1 (recession).

Geweke, John, Keane, Michael P., Federal Reserve Bank of Minneapolis. Research Department This paper generalizes the normal probit model of dichotomous choice by introducing mixtures of normals ...

I consider an ordered probit model in which some of the observations in one of the categories are missing. The model can be estimated because of a second variable with a similar truncation scheme.

Example 45.3: Probit Model with Likelihood function The data, taken from Lee (1974), consist of patient characteristics and a variable indicating whether cancer remission occured.

A general log likelihood specification is used in the MODEL statement, and the RANDOM statement defines the random effect U to have standard deviation SD and subject variable SUB. The REPLICATE ...

This paper analyzes the link between digitalization and intergenerational occupational mobility in Africa. We use a probit model estimated on a large sample of 28 million individuals aged 14 and ...