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Instrumental Variable Identification of Dynamic Variance Decompositions

Mikkel Plagborg-Møller, Christian K. Wolf

arXiv 2 Nov 2020 · Econometrics · publishedJournal of Political Economy (2022) · 66 citations (OpenAlex)

arXiv:2011.01380 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Macroeconomists increasingly use external sources of exogenous variation for causal inference. However, unless such external instruments (proxies) capture the underlying shock without measurement error, existing methods are silent on the importance of that shock for macroeconomic fluctuations. We show that, in a general moving average model with external instruments, variance decompositions for the instrumented shock are interval-identified, with informative bounds. Various additional restrictions guarantee point identification of both variance and historical decompositions. Unlike SVAR analysis, our methods do not require invertibility. Applied to U.S. data, they give a tight upper bound on the importance of monetary shocks for inflation dynamics.

Citation extraction

51
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97
in-text mentions
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Stock, J. H. & Watson, M. W (2018) Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments1.000115100%
2Leeper, E. M., Walker, T. B., & Yang, S.-C. S (2013) Fiscal Foresight and Information Flows1.00063100%
3Ramey, V. A (2016) Macroeconomic Shocks and Their Propagation1.00053100%
4Gorodnichenko, Y. & Lee, B (2020) Forecast Error Variance Decompositions with Local Projections0.92843100%
5Gertler, M. & Karadi, P (2015) Monetary Policy Surprises, Credit Costs, and Economic Activity0.87482100%
6Mertens, K. & Ravn, M. O (2013) The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States0.84333100%
7Brockwell, P. J. & Davis, R. A (1991) Time Series: Theory and Methods\/ (2nd ed.)0.73732100%
8Forni, M., Gambetti, L., & Sala, L (2019) Structural VARs and noninvertible macroeconomic models0.73732100%
9Imbens, G. W. & Manski, C. F (2004) Confidence Intervals for Partially Identified Parameters0.73732100%
10Kilian, L. & Lütkepohl, H (2017) Structural Vector Autoregressive Analysis0.64441100%

Showing the top 10 of 51 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Structural Analysis of Vector Autoregressive Models0.64422
2Causality versus Serial Correlation: an Asymmetric Portmanteau Test0.64422
3Inference for Local Projections0.40511
42409.095770.40511
5Locally- but not Globally-identified SVARs0.40511