Projecting Policy Effects with Statistical Models
Keywords:
forecasting, policy analysis, statistical models, quantitative modeling, stochastic optimization, identificationAbstract
This paper attempts to briefly discuss the current frontiers in quantitative modeling for forecasting and policy analysis. It does so by summarizing some recent developments in three areas: reduced form forecasting models; theoretical models including elements of stochastic optimization; and identification. In the process, the paper tries to provide some remarks on the direction we seem to be headed.Downloads
References
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Blanchard, O., & Watson, M. (1986). Are business cycles all alike? In R. J. Gordon (Ed.), The American business cycle: Continuity and change (pp. 123–180). University of Chicago Press for the National Bureau of Economic Research.
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Sims, C. A. (1988). A nine-variable forecasting model of the U.S. (Discussion Paper). Institute for Empirical Macroeconomics, University of Minnesota and Federal Reserve Bank of Minneapolis.
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Copyright (c) 1988 Christopher Sims

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