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Combining Models for Forecasting and Policy Analysis

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Abstract

Model uncertainty is pervasive. Economists, bloggers, policymakers all have different views of how the world works and what economic policies would make it better. These views are, like it or not, models. Some people spell them out in their entirety, equations and all. Others refuse to use the word altogether, possibly out of fear of being falsified. No model is “right,” of course, but some models are worse than others, and we can have an idea of which is which by comparing their predictions with what actually happened. If you are open-minded, you may actually want to combine models in making forecasts or policy analysis. This post discusses one way to do this, based on a recent paper of ours (Del Negro, Hasegawa, and Schorfheide 2014).

Suggested Citation

  • Marco Del Negro & Raiden B. Hasegawa & Frank Schorfheide, 2015. "Combining Models for Forecasting and Policy Analysis," Liberty Street Economics 20150323, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednls:87017
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    More about this item

    Keywords

    DSGE; model combination; model uncertainty;
    All these keywords.

    JEL classification:

    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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