Implementing Causality Tests with Panel Data, with an Example from Localpublic Finance

Abstract

This paper considers estimation and testing of vector autoregression coefficients in panel data, and applies the techniques to analyze the dynamic properties of revenues, expenditures, and grants in a sample of United States municipalities. The model allows for nonstationary individual effects, and is estimated by applying instrumental variables to the quasi-differenced autoregressive equations Q Particular attention is paid to specifying lag lengths and forming convenient test statistics. The empirical results suggest that intertemporal linkages are important to the understanding of state and local behavior. Such linkages are ignored in conventional cross sectional regressions. Also, we present evidence that past grant revenues help to predict current expenditures, but that past expenditures do not help to predict current revenues.