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The effectiveness of central bank purchases of long-term treasury securities: A neural network approach

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  • Tänzer, Alina

Abstract

Central bank intervention in the form of quantitative easing (QE) during times of low interest rates is a controversial topic. This paper introduces a novel approach to study the effectiveness of such unconventional measures. Using U.S. data on six key financial and macroeconomic variables between 1990 and 2015, the economy is estimated by artificial neural networks. Historical counterfactual analyses show that real effects are less pronounced than yield effects. Disentangling the effects of the individual asset purchase programs, impulse response functions provide evidence for QE being less effective the more the crisis is overcome. The peak effects of all QE interventions during the Financial Crisis only amounts to 1.3 pp for GDP growth and 0.6 pp for inflation respectively. Hence, the time as well as the volume of the interventions should be deliberated.

Suggested Citation

  • Tänzer, Alina, 2024. "The effectiveness of central bank purchases of long-term treasury securities: A neural network approach," IMFS Working Paper Series 204, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    • Handle: RePEc:zbw:imfswp:295732
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    References listed on IDEAS

    as
    1. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Is the Phillips Curve Alive and Well after All? Inflation Expectations and the Missing Disinflation," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 197-232, January.
    2. Blanchard, Oliver & Cerutti, Eugenio & SUmmers, Lawrence, 2015. "Inflation and Activity - Two Explorations and Their Monetary Policy Implications," Working Paper Series 15-070, Harvard University, John F. Kennedy School of Government.
    3. Eric T. Swanson, 2011. "Let's Twist Again: A High-Frequency Event-study Analysis of Operation Twist and Its Implications for QE2," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 42(1 (Spring), pages 151-207.
    4. Dolado, Juan J. & Maria-Dolores, Ramon & Naveira, Manuel, 2005. "Are monetary-policy reaction functions asymmetric?: The role of nonlinearity in the Phillips curve," European Economic Review, Elsevier, vol. 49(2), pages 485-503, February.
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    More about this item

    Keywords

    Artificial Intelligence; Machine Learning; Neural Networks; Forecasting and Simulation: Models and Applications; Financial Markets and the Macroeconomy; Monetary Policy; Central Banks and Their Policies;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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