Suchergebnisse

Common regression models are often structurally inconsistent with strategic interaction. We demonstrate that this "strategic misspecification" is really an issue of structural (or functional form) misspecification. The misspecification can be equivalently written as a form of omitted variable bias, where the omitted variables are nonlinear terms arising from the players' expected utility calculations and often from data aggregation. We characterize the extent of the specification error in terms of model parameters and the data and show that typical regressions models can at times give exactly the opposite inferences versus the true strategic data‐generating process. Researchers are recommended to pay closer attention to their theoretical models, the implications of those models concerning their statistical models, and vice versa.

Front Matter -- Introduction and Overview -- A Primer on ARIMA Models -- A Primer on Regression Models -- Rational Distributed Lag Models -- Building Dynamic Regression Models: Model Identification -- Building Dynamic Regression Models: Model Checking, Reformulation and Evaluation -- Intervention Analysis -- Intervention and Outlier Detection and Treatment -- Estimation and Forecasting -- Dynamic Regression Models in a Vector ARMA Framework -- Appendix: Tables -- Data Appendix -- References -- Index -- Wiley Series in Probability and Mathematical Statistics.

We develop a non-dynamic panel smooth transition regression model with fixed individual effects. The model is useful for describing heterogenous panels, with regression coefficients that vary across individuals and over time. Heterogeneity is allowed for by assuming that these coefficients are continuous functions of an observable variable through a bounded function of this variable and fluctuate between a limited number (often two) of extreme regimes. The model can be viewed as a generalization of the threshold panel model of Hansen (1999). We extend the modelling strategy for univariate smooth transition regression models to the panel context. This comprises of model specification based on homogeneity tests, parameter estimation, and diagnostic checking, including tests for parameter constancy and no remaining nonlinearity. The new model is applied to describe firms' investment decisions in the presence of capital market imperfections.