2013•RePEc: Research Papers in EconomicsOpen access

On the Size of Fiscal Multipliers: A Counterfactual Analysis

Jan Kuckuck, Frank Westermann

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Abstract

The Structural Vector Auto-regression (SVAR) approach to estimating fiscal multipliers, following the seminal paper by Blanchard and Perotti (2002), has been widely applied in the literature. In our paper we discuss the interpretation of these estimates and suggest that they are more useful for forecasting purposes than for policy advice. Our key point is that policy instruments often react to each other. We analyze a data set from the US and document that these interactions are economically and statistically significant. Increases in spending have been financed by subsequent increases in taxes. Increases in taxes have been complemented by additional spending cuts in subsequent quarters. In a counterfactual analysis we report fiscal multipliers that abstract from these dynamic responses of policy instruments to each other.

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What this paper is about

The Structural Vector Auto-regression (SVAR) approach to estimating fiscal multipliers, following the seminal paper by Blanchard and Perotti (2002), has been widely applied in the literature. In our paper we discuss the interpretation of these estimates and suggest that they are more useful for forecasting purposes than for policy advice. Our key point is that policy instruments often react to each other. We analyze a data set from the US and document that these interactions are economically and statistically significant. Increases in spending have been financed by subsequent increases in taxes. Increases in taxes have been complemented by additional spending cuts in subsequent quarters. In a counterfactual analysis we report fiscal multipliers that abstract from these dynamic responses of policy instruments to each other.

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Available abstract

The Structural Vector Auto-regression (SVAR) approach to estimating fiscal multipliers, following the seminal paper by Blanchard and Perotti (2002), has been widely applied in the literature. In our paper we discuss the interpretation of these estimates and suggest that they are more useful for forecasting purposes than for policy advice. Our key point is that policy instruments often react to each other. We analyze a data set from the US and document that these interactions are economically and statistically significant. Increases in spending have been financed by subsequent increases in taxes. Increases in taxes have been complemented by additional spending cuts in subsequent quarters. In a counterfactual analysis we report fiscal multipliers that abstract from these dynamic responses of policy instruments to each other.

Key concepts: Counterfactual thinking, Fiscal policy, Economics, Econometrics, Structural vector autoregression, Point (geometry), Set (abstract data type), Advice (programming)

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