In the current literature, fiscal policy is usually characterized by a singleequation rule, in which primary surplus is generally de ned as a function of lagged government debt and other controlled variables. To apply Ordinary Least Squares (OLS) method on the single-equation rule has been one of the common approaches to identify scal policy behavior. From the rational expectations general equilibrium perspective, this paper illustrates that lagged government debt is generally endogenous and the OLS approach suers from simultaneity bias. Consequently, the OLS-based identi cation of scal policy behavior is unreliable. As a solution, we apply the Generalized Method of Moments (GMM) for estimation and inference. Monte Carlo experiments demonstrate that GMM provides more reliable results than OLS in terms of accuracy of the estimator, size and power. In short, people should be cautious of the existing OLS-based identi cation results of scal policy behavior and the empirical researchers should not consider OLS regression as a reliable tool when trying to identify scal policy behavior in the future.
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Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number
2008-026.
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Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation E63 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization
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