Correlação espúria em modelos de painel: uma análise do desmatamento na Amazônia

Abstract

This paper analyzes the effects of individual-specific size factors in a dynamic panel regression model. Theory and simulation show that a size factor, with a long-tailed distribution or a time-varying property, may cause spurious stochastics. If a pair of panel variables depends on size in some way, then they appear to find a strong relationship, if the size variable is not used in the regression, even if the variables are otherwise independent. Moreover, forecasts based on models that have omitted size- factors are affected seriously by the property of the size- factors. A pooling regression with very short time-series appears to fit well in sample, but forecasts poorly out-of-sample if the neglected individual-specific size factor has a long-tailed distribution. Using these results, we apply a dynamic panel model to Amazon data. Predicted deforestation is much lesser than previous studies after accounting for spurious stochastics.