On the robustness/replication of econometric analyses from nonlinear models using various commonplace software packages

Abstract

Because replicability is an important part of every scientific endeavor, this research deals with comparing and contrasting parameter estimates, standard errors, and p-values from the estimation of five commonly encountered nonlinear models in applied econometrics. Commonplace software packages indigenous to econometrics and statistics are used, namely EVIEWS 11.0, SAS 9.4, Stata 17, and R 4.1.2 in five replication exercises to determine potential differences, if any, in empirical results. The hypothesis that mainstream software packages generate different empirical results in the estimation of nonlinear models is confirmed for the polynomial distributed lag (PDL) model and the GARCH(1,1) model. For the probit model and the Barten synthetic demand system model, the differences in parameter estimates, standard errors, and p-values are less evident across the four commonly used software packages. For the Tobit model, the respective sets of parameter estimates, standard errors, and p-values are nearly identical across the respective software packages. Economic analysts should not just accept estimation results uncritically, but instead, conduct sensitivity analyses involving the use of at least two software packages. The agricultural economics profession should adopt this recommendation as standard practice.