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Identification in Macroeconomics†

Identification in Macroeconomics† AbstractThis paper discusses empirical approaches macroeconomists use to answer questions like: What does monetary policy do? How large are the effects of fiscal stimulus? What caused the Great Recession? Why do some countries grow faster than others? Identification of causal effects plays two roles in this process. In certain cases, progress can be made using the direct approach of identifying plausibly exogenous variation in a policy and using this variation to assess the effect of the policy. However, external validity concerns limit what can be learned in this way. Carefully identified causal effects estimates can also be used as moments in a structural moment matching exercise. We use the term “identified moments” as a short-hand for “estimates of responses to identified structural shocks,” or what applied microeconomists would call “causal effects.” We argue that such identified moments are often powerful diagnostic tools for distinguishing between important classes of models (and thereby learning about the effects of policy). To illustrate these notions we discuss the growing use of cross-sectional evidence in macroeconomics and consider what the best existing evidence is on the effects of monetary policy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Economic Perspectives American Economic Association

Identification in Macroeconomics†

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Publisher
American Economic Association
Copyright
Copyright © 2018 © American Economic Association
ISSN
0895-3309
DOI
10.1257/jep.32.3.59
Publisher site
See Article on Publisher Site

Abstract

AbstractThis paper discusses empirical approaches macroeconomists use to answer questions like: What does monetary policy do? How large are the effects of fiscal stimulus? What caused the Great Recession? Why do some countries grow faster than others? Identification of causal effects plays two roles in this process. In certain cases, progress can be made using the direct approach of identifying plausibly exogenous variation in a policy and using this variation to assess the effect of the policy. However, external validity concerns limit what can be learned in this way. Carefully identified causal effects estimates can also be used as moments in a structural moment matching exercise. We use the term “identified moments” as a short-hand for “estimates of responses to identified structural shocks,” or what applied microeconomists would call “causal effects.” We argue that such identified moments are often powerful diagnostic tools for distinguishing between important classes of models (and thereby learning about the effects of policy). To illustrate these notions we discuss the growing use of cross-sectional evidence in macroeconomics and consider what the best existing evidence is on the effects of monetary policy.

Journal

Journal of Economic PerspectivesAmerican Economic Association

Published: Aug 1, 2018

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