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Renewed interest in fiscal policy has increased the use of quantitative models to evaluate policy. Because of modeling uncertainty, it is essential that policy evaluations be robust to alternative assumptions. We find that models currently being used in practice to evaluate fiscal policy stimulus proposals are not robust. Government spending multipliers in an alternative empirically-estimated and widely-cited new Keynesian model are much smaller than in these old Keynesian models; the estimated stimulus is extremely small with GDP and employment effects only one-sixth as large.
In the aftermath of the global financial crisis and great recession, many countries face substantial deficits and growing debts. In the United States, federal government outlays as a ratio to GDP rose substantially from about 19.5 percent before the crisis to over 24 percent after the crisis. In this paper we consider a fiscal consolidation strategy that brings the budget to balance by gradually reducing this spending ratio over time to the level that prevailed prior to the crisis. A crucial issue is the impact of such a consolidation strategy on the economy. We use structural macroeconomic models to estimate this impact focussing primarily on a dynamic stochastic general equilibrium model with price and wage rigidities and adjustment costs. We separate out the impact of reductions in government purchases and transfers, and we allow for a reduction in both distortionary taxes and government debt relative to the baseline of no consolidation. According to the model simulations GDP rises in the short run upon announcement and implementation of this fiscal consolidation strategy and remains higher than the baseline in the long run. We explore the role of the mix of expenditure cuts and tax reductions as well as gradualism in achieving this policy outcome. Finally, we conduct sensitivity studies regarding the type of model used and its parameterization.
In this paper we investigate the comparative properties of empirically-estimated monetary models of the U.S. economy. We make use of a new data base of models designed for such investigations. We focus on three representative models: the Christiano, Eichenbaum, Evans (2005) model, the Smets and Wouters (2007) model, and the Taylor (1993a) model. Although the three models differ in terms of structure, estimation method, sample period, and data vintage, we find surprisingly similar economic impacts of unanticipated changes in the federal funds rate. However, the optimal monetary policy responses to other sources of economic fluctuations are widely different in the different models. We show that simple optimal policy rules that respond to the growth rate of output and smooth the interest rate are not robust. In contrast, policy rules with no interest rate smoothing and no response to the growth rate, as distinct from the level, of output are more robust. Robustness can be improved further by optimizing rules with respect to the average loss across the three models.