A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data models it is known that the selection of the link function may have an impact on the model estimates. In particular, the selection of the probit link implies an assumption that model error terms are normally distributed and...

This paper estimates ordered logit and probit regression models for bank ratings which also include a country index to capture country-specific variation. The empirical findings provide support to the hypothesis that the individual international bank ratings assigned by Fitch Ratings are underpinned by fundamental quantitative financial analyses. Also, there is strong evidence of a country effe...

Researchers typically analyze time-series–cross-section data with a binary dependent variable (BTSCS) using ordinary logit or probit. However, BTSCS observations are likely to violate the independence assumption of the ordinary logit or probit statistical model. It is well known that if the observations are temporally related that the results of an ordinary logit or probit analysis may be misle...

This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy function, the resulting choice probabilities in the rational inattention model take the multinomial logit form. By exploiting convex-analytic properties of the discrete choice model, we show ...

Abstract. This paper explains why computing the marginal effect of a change in two variables is more complicated in nonlinear models than in linear models. The command inteff computes the correct marginal effect of a change in two interacted variables for a logit or probit model, as well as the correct standard errors. The inteff command graphs the interaction effect and saves the results to al...

Employing a probit, logit and gompit model this paper demonstrates that small firm development, represented by a group of structural, behavioral and performance variables determines regional location in Poland. The paper uses original data that samples the small firm stratum in two contrasting regions, Pomorskie and Lubelskie. The following variables were shown to be significantly correlated wi...

Ordered discrete dependent variable models such as ordered probit and ordered logit are frequently used across the social sciences to study outcomes including health status, happiness, wealth and educational attainment. Unlike in the case of OLS, unaccounted for heteroskedasticity in these models can lead to biased parameter estimates. This paper introduces the oglmx package for the R statistic...

Fires in forest areas are considered an important threat to the Andean Region and the Amazon rainforest. In Colombia, fire is used to expand the agricultural frontier (including illicit crops) which results in deforestation. Given the importance of avoiding deforestation and to control coca expansion, this paper aims to: 1) understand the relationship between fires and deforestation, coca and d...

Social scientists, particularly political scientists, frequently use ordinal survey items as dependent variables in models of political attitudes. Commonly, normal-theory modeling strategies like ordinary least squares regression are applied to these items. Additionally, workers also make frequent use of the proportional odds (ordinal logit) model or cumulative probit model when working with su...