%0 Journal Article
%T Polynomial Regressions and Nonsense Inference
%A Daniel Ventosa-Santaul¨¤ria
%A Carlos Vladimir Rodr¨ªguez-Caballero
%J Econometrics
%D 2013
%I MDPI AG
%R 10.3390/econometrics1030236
%X Polynomial specifications are widely used, not only in applied economics, but also in epidemiology, physics, political analysis and psychology, just to mention a few examples. In many cases, the data employed to estimate such specifications are time series that may exhibit stochastic nonstationary behavior. We extend Phillips¡¯ results (Phillips, P. Understanding spurious regressions in econometrics. J. Econom. 1986, 33, 311¨C340.) by proving that an inference drawn from polynomial specifications, under stochastic nonstationarity, is misleading unless the variables cointegrate. We use a generalized polynomial specification as a vehicle to study its asymptotic and finite-sample properties. Our results, therefore, lead to a call to be cautious whenever practitioners estimate polynomial regressions.
%K polynomial regression
%K misleading inference
%K integrated processes
%U http://www.mdpi.com/2225-1146/1/3/236