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Testing for Strong Exogeneity in Proxy-VARS

Author

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  • Martin Bruns

    (School of Economics, University of East Anglia)

  • Sascha A. Keweloh

    (TU Dortmund University)

Abstract

Proxy variables have gained widespread prominence as indispensable tools for identifying structural VAR models. Analogous to instrumental variables, proxies need to be exogenous, i.e. uncorrelated with all non-target shocks. Assessing the exogeneity of proxies has traditionally relied on economic arguments rather than statistical tests. We argue that the economic rational underlying the construction of commonly used proxy variables aligns with a stronger form of exogeneity. Specifically, proxies are typically constructed as variables not containing any information on the expected value of non-target shocks. We show conditions under which this enhanced concept of proxy exogeneity is testable without additional identifying assumptions.

Suggested Citation

  • Martin Bruns & Sascha A. Keweloh, 2023. "Testing for Strong Exogeneity in Proxy-VARS," University of East Anglia School of Economics Working Paper Series 2023-07, School of Economics, University of East Anglia, Norwich, UK..
    • Handle: RePEc:uea:ueaeco:2023-07
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    1. Robin Braun & Ralf Brüggemann, 2017. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2017-07, Department of Economics, University of Konstanz.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Keweloh, Sascha A. & Hetzenecker, Stephan & Seepe, Andre, 2023. "Monetary policy and information shocks in a block-recursive SVAR," Journal of International Money and Finance, Elsevier, vol. 137(C).
    4. Gouriéroux, Christian & Monfort, Alain & Renne, Jean-Paul, 2017. "Statistical inference for independent component analysis: Application to structural VAR models," Journal of Econometrics, Elsevier, vol. 196(1), pages 111-126.
    5. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    6. Christina D. Romer & David H. Romer, 2010. "The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks," American Economic Review, American Economic Association, vol. 100(3), pages 763-801, June.
    7. Giovanni Angelini & Luca Fanelli, 2019. "Exogenous uncertainty and the identification of structural vector autoregressions with external instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 951-971, September.
    8. Giovanni Angelini & Luca Fanelli & Luca Neri, 2024. "Invalid proxies and volatility changes," Papers 2403.08753, arXiv.org, revised Nov 2025.
    9. Guay, Alain, 2021. "Identification of structural vector autoregressions through higher unconditional moments," Journal of Econometrics, Elsevier, vol. 225(1), pages 27-46.
    10. Arthur Lewbel, 1997. "Constructing Instruments for Regressions with Measurement Error when no Additional Data are Available, with an Application to Patents and R&D," Econometrica, Econometric Society, vol. 65(5), pages 1201-1214, September.
    11. Klein, Mathias & Linnemann, Ludger, 2019. "Tax and spending shocks in the open economy: Are the deficits twins?," European Economic Review, Elsevier, vol. 120(C).
    12. Dario Caldara & Christophe Kamps, 2017. "The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(3), pages 1015-1040.
    13. Erickson, Timothy & Whited, Toni M., 2002. "Two-Step Gmm Estimation Of The Errors-In-Variables Model Using High-Order Moments," Econometric Theory, Cambridge University Press, vol. 18(3), pages 776-799, June.
    14. Piotr Zwiernik & Geert Mesters, 2022. "Non-Independent Components Analysis," Working Papers 1358, Barcelona School of Economics.
    15. Mathias Klein & Ludger Linnemann, 2019. "Tax and Spending Shocks in the Open Economy: Are the Deficits Twins?," Discussion Papers of DIW Berlin 1821, DIW Berlin, German Institute for Economic Research.
    16. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    17. Giacomini, Raffaella & Kitagawa, Toru & Read, Matthew, 2022. "Robust Bayesian inference in proxy SVARs," Journal of Econometrics, Elsevier, vol. 228(1), pages 107-126.
    18. Marek Jarociński & Peter Karadi, 2020. "Deconstructing Monetary Policy Surprises—The Role of Information Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(2), pages 1-43, April.
    19. Sascha Alexander Keweloh, 2021. "A Generalized Method of Moments Estimator for Structural Vector Autoregressions Based on Higher Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 772-782, July.
    20. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
    21. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Waggoner, Daniel F., 2021. "Inference in Bayesian Proxy-SVARs," Journal of Econometrics, Elsevier, vol. 225(1), pages 88-106.
    22. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
    23. Bierens, Herman J., 1982. "Consistent model specification tests," Journal of Econometrics, Elsevier, vol. 20(1), pages 105-134, October.
    24. Helmut Lütkepohl & Thore Schlaak, 2022. "Heteroscedastic Proxy Vector Autoregressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1268-1281, June.
    25. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    26. David S. Matteson & Ruey S. Tsay, 2017. "Independent Component Analysis via Distance Covariance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 623-637, April.
    27. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    28. John G. Fernald, 2012. "A quarterly, utilization-adjusted series on total factor productivity," Working Paper Series 2012-19, Federal Reserve Bank of San Francisco.
    29. Thore Schlaak & Malte Rieth & Maximilian Podstawski, 2023. "Monetary policy, external instruments, and heteroskedasticity," Quantitative Economics, Econometric Society, vol. 14(1), pages 161-200, January.
    30. Bruns, Martin & Lütkepohl, Helmut, 2024. "Heteroskedastic proxy vector autoregressions: An identification-robust test for time-varying impulse responses in the presence of multiple proxies," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    31. Sascha A. Keweloh, 2023. "Uncertain Short-Run Restrictions and Statistically Identified Structural Vector Autoregressions," Papers 2303.13281, arXiv.org, revised Apr 2024.
    32. Klein, Mathias & Linnemann, Ludger, 2019. "Tax and spending shocks in the open economy: are the deficits twins?," Working Paper Series 377, Sveriges Riksbank (Central Bank of Sweden).
    33. Mertens, Karel & Ravn, Morten O., 2014. "A reconciliation of SVAR and narrative estimates of tax multipliers," Journal of Monetary Economics, Elsevier, vol. 68(S), pages 1-19.
    34. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3086-3124.
    35. Martin Bruns & Helmut Lütkepohl, 2023. "An Alternative Bootstrap for Proxy Vector Autoregressions," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1857-1882, December.
    36. Diego R. Känzig, 2021. "The Macroeconomic Effects of Oil Supply News: Evidence from OPEC Announcements," American Economic Review, American Economic Association, vol. 111(4), pages 1092-1125, April.
    37. Dario Caldara & Edward Herbst, 2019. "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 157-192, January.
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    4. Jiaming Huang & Luca Neri, 2026. "Beyond Validity: SVAR Identification Through the Proxy Zoo," Papers 2601.11195, arXiv.org.
    5. Juan Michelsen, 2026. "Global Risk Shocks in a Small Open Economy and Their Impact on Monetary Policy Surprises," Berlin School of Economics Discussion Papers 0093, Berlin School of Economics.
    6. Raimondo Pala, 2025. "Identification, estimation and inference in Panel Vector Autoregressions using external instruments," Papers 2511.19372, arXiv.org.

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    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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