A Comparison Between Multinomial Logit and Probit Models

Abstract

Although the estimation of flexible multinomial discrete choice models generally needs the incorporation of simulation methods, their application is recently common in environmental and resource economics such as in many other economic disciplines (e.g. transportation economics). Based on a firm level data set of the German manufacturing sector, this paper examines determinants of environmental innovations by comparing the estimation results in flexible multinomial probit models and restrictive multinomial logit and independent probit models. The analysis of the two latter models implies that some specific environmental organizational measures, technological opportunities, and market pull factors have a significantly positive effect on both environmental product and process innovations. Taking this into consideration, the flexible multinomial probit model analysis provides few new insights since the simulated maximum likelihood estimations are rather unreliable as a consequence of the sole inclusion of firm-specific characteristics as explanatory variables. In this respect, the incorporation of simulation methods into the maximum likelihood estimations is not crucial since the problems do not decrease if the number of random draws in the considered Geweke-Hajivassiliou-Keane simulator rises. Furthermore, the difficulties grow if the number of choice alternatives increases. It can therefore be concluded that the applicability of these flexible multinomial discrete choice models without the incorporation of choice-specific attributes as explanatory variables is rather limited in practice.