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Depression econometrics: a FAVAR model of monetary policy during the Great Depression

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  • Ahmadi, Pooyan Amir
  • Ritschl, Albrecht

Abstract

The prominent role of monetary policy in the U.S. interwar depression has been conventional wisdom since Friedman and Schwartz [1963]. This paper presents evidence on both the surprise and the systematic components of monetary policy between 1929 and 1933. Doubts surrounding GDP estimates for the 1920s would call into question conventional VAR techniques. We therefore adopt the FAVAR methodology of Bernanke, Boivin, and Eliasz [2005], aggregating a large number of time series into a few factors and inserting these into a monetary policy VAR. We work in a Bayesian framework and apply MCMC methods to obtain the posteriors. Employing the generalized sign restriction approach toward identification of Amir Ahmadi and Uhlig [2008], we find the effects of monetary policy shocks to have been moderate. To analyze the systematic policy component, we back out the monetary policy reaction function and its response to aggregate supply and demand shocks. Results broadly confirm the Friedman/Schwartz view about restrictive monetary policy, but indicate only moderate effects. We further analyze systematic policy through conditional forecasts of key time series at critical junctures, taken with and without the policy instrument. Effects are again quite moderate. Our results caution against a predominantly monetary interpretation of the Great Depression.

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  • Ahmadi, Pooyan Amir & Ritschl, Albrecht, 2009. "Depression econometrics: a FAVAR model of monetary policy during the Great Depression," Economic History Working Papers 27878, London School of Economics and Political Science, Department of Economic History.
  • Handle: RePEc:ehl:wpaper:27878
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    Cited by:

    1. Fuentes-Albero, Cristina & Melosi, Leonardo, 2013. "Methods for computing marginal data densities from the Gibbs output," Journal of Econometrics, Elsevier, vol. 175(2), pages 132-141.
    2. Harald Uhlig & Pooyan Amir Ahmadi, 2012. "Measuring The Dynamic Effects Of Monetary Policy Shocks: A Bayesian Favar Approach With Sign Restriction," 2012 Meeting Papers 1060, Society for Economic Dynamics.
    3. Amir Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2014. "Drifts, Volatilities and Impulse Responses Over the Last Century," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100562, Verein für Socialpolitik / German Economic Association.
    4. Ritschl, Albrecht & Sarferaz, Samad, 2009. "Crisis? What Crisis? Currency vs. Banking in the Financial Crisis of 1931," CEPR Discussion Papers 7610, C.E.P.R. Discussion Papers.
    5. Herwartz, Helmut & Rohloff, Hannes, 2018. "Less bang for the buck? Assessing the role of inflation uncertainty for U.S. monetary policy transmission in a data rich environment," University of Göttingen Working Papers in Economics 358, University of Goettingen, Department of Economics.
    6. Pavon-Prado, David, 2019. "Have we been measuring monetary policy correctly? Analysing the Federal Reserve’s policies over the last century," IFCS - Working Papers in Economic History.WH 28342, Universidad Carlos III de Madrid. Instituto Figuerola.
    7. Helmut Lütkepohl, 2014. "Structural Vector Autoregressive Analysis in a Data Rich Environment: A Survey," Discussion Papers of DIW Berlin 1351, DIW Berlin, German Institute for Economic Research.
    8. Klein, Alexander & Otsuy, Keisuke, 2013. "Efficiency, Distortions and Factor Utilization during the Interwar Period," CAGE Online Working Paper Series 147, Competitive Advantage in the Global Economy (CAGE).
    9. Pooyan Amir-Ahmadi & Gustavo S. Cortes & Marc D. Weidenmier, 2020. "Regional Monetary Policies and the Great Depression," NBER Working Papers 26695, National Bureau of Economic Research, Inc.
    10. Dedu, Vasile & Stoica, Tiberiu, 2014. "The Impact of Monetaru Policy on the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 71-86, June.
    11. Pooyan Amir Ahmadi & Harald Uhlig, 2015. "Sign Restrictions in Bayesian FaVARs with an Application to Monetary Policy Shocks," NBER Working Papers 21738, National Bureau of Economic Research, Inc.
    12. Alex Klein & Keisuke Otsu, 2013. "Efficiency, Distortions and Factor Utilization during the Interwar Period," Studies in Economics 1317, School of Economics, University of Kent.
    13. Jalali-Naini , Ahmad. R. & Hemati , Maryam, 2012. "The Effect of Monetary Shocks on Disaggregated Prices in a Data Rich Environment: a Bayesian FAVAR Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 6(4), pages 27-60, July.
    14. Pooyan Amir‐Ahmadi & Christian Matthes & Mu‐Chun Wang, 2016. "Drifts and volatilities under measurement error: Assessing monetary policy shocks over the last century," Quantitative Economics, Econometric Society, vol. 7(2), pages 591-611, July.
    15. Karau, Sören, 2020. "Buried in the vaults of central banks: Monetary gold hoarding and the slide into the Great Depression," Discussion Papers 63/2020, Deutsche Bundesbank.
    16. Anthony Orlando, 2018. "Asset Markets, Credit Markets, and Inequality: Distributional Changes in Housing, 1970-2016," ERES eres2018_182, European Real Estate Society (ERES).

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    JEL classification:

    • N0 - Economic History - - General
    • F3 - International Economics - - International Finance
    • G3 - Financial Economics - - Corporate Finance and Governance
    • J1 - Labor and Demographic Economics - - Demographic Economics

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