Count data regressions are an important tool for empirical analyses ranging from analyses of patent counts to measures of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis because the Poisson conditional fixed effects maximum...

We study a simple exogeneity test in count data models with possibly endogenous multinomial treatment. The test is based on Two Stage Residual Inclusion (2SRI). Results from a broad Monte Carlo study provide novel evidence on important features of this approach in nonlinear settings. We find...

We develop a general class of factor-analytic models for the analysis of multivariate (truncated) count data. Dependencies in multivariate counts are of interest in many applications, but few approaches have been proposed for their analysis. Our model class allows for a variety of distributions...

Excess zeros are encountered in many empirical count data applications. We provide a new explanation of extra zeros, related to the underlying stochastic process that generates events. The process has two rates, a lower rate until the first event, and a higher one thereafter. We derive the...

Africa's biofuel potential over the last ten years has increasingly attracted foreign investors’ attention. We estimate the determinants of foreign investors land demand for biofuel production in SSA, using Poisson specifications of the gravity model. Our estimates suggest that land...

In this paper, we estimated a gravity model of Russian trade using panel data from Russia and 23 OECD member countries. Our estimation results indicate that foreign direct investment and socio-cultural similarity are determining factors in the trade volume between Russia and these developed...