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A machine learning approach to identifying different types of uncertainty

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  • Saltzman, Bennett
  • Yung, Julieta

Abstract

We implement natural language processing techniques to extract uncertainty measures from Federal Reserve Beige Books between 1970 and 2018. Business and economic related uncertainty is associated with future weakness in output, higher unemployment, and elevated term premia. On the other hand, political and government uncertainty, while high during recent times, has no statistically significant impact on the economy.

Suggested Citation

  • Saltzman, Bennett & Yung, Julieta, 2018. "A machine learning approach to identifying different types of uncertainty," Economics Letters, Elsevier, vol. 171(C), pages 58-62.
    • Handle: RePEc:eee:ecolet:v:171:y:2018:i:c:p:58-62
    DOI: 10.1016/j.econlet.2018.07.003
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    Cited by:

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    2. Li, Wanli & Su, Yueying & Wang, Kaixiu, 2022. "How does economic policy uncertainty affect cross-border M&A: Evidence from Chinese firms," Emerging Markets Review, Elsevier, vol. 52(C).
    3. Xie, Fangzhou, 2020. "Wasserstein Index Generation Model: Automatic generation of time-series index with application to Economic Policy Uncertainty," Economics Letters, Elsevier, vol. 186(C).
    4. Bhanu Pratap & Nalin Priyaranjan, 2023. "Macroeconomic effects of uncertainty: a Google trends-based analysis for India," Empirical Economics, Springer, vol. 65(4), pages 1599-1625, October.
    5. Azqueta-Gavaldón, Andrés, 2020. "Causal inference between cryptocurrency narratives and prices: Evidence from a complex dynamic ecosystem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    6. Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.
    7. Hammoudeh, Shawkat & Uddin, Gazi Salah & Sousa, Ricardo M. & Wadström, Christoffer & Sharmi, Rubaiya Zaman, 2022. "Do pandemic, trade policy and world uncertainties affect oil price returns?," Resources Policy, Elsevier, vol. 77(C).
    8. Costantini, Mauro & Sousa, Ricardo M., 2022. "What uncertainty does to euro area sovereign bond markets: Flight to safety and flight to quality," Journal of International Money and Finance, Elsevier, vol. 122(C).
    9. Śmiech, Sławomir & Papież, Monika & Dąbrowski, Marek A., 2019. "How important are different aspects of uncertainty in driving industrial production in the CEE countries?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 252-266.
    10. Svetlana Kresova & Sebastian Hess, 2022. "Identifying the Determinants of Regional Raw Milk Prices in Russia Using Machine Learning," Agriculture, MDPI, vol. 12(7), pages 1-18, July.
    11. Azqueta-Gavaldon, Andres, 2023. "Political referenda and investment: Evidence from Scotland," European Journal of Political Economy, Elsevier, vol. 80(C).
    12. Vu M. Ngo & Toan L. D. Huynh & Phuc V. Nguyen & Huan H. Nguyen, 2022. "Public sentiment towards economic sanctions in the Russia–Ukraine war," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(5), pages 564-573, November.
    13. Azqueta-Gavaldón, Andrés & Hirschbühl, Dominik & Onorante, Luca & Saiz, Lorena, 2023. "Sources of Economic Policy Uncertainty in the euro area," European Economic Review, Elsevier, vol. 152(C).
    14. Amrendra Pandey & Jagadish Shettigar & Amarnath Bose, 2021. "Evaluation of the Inflation Forecasting Process of the Reserve Bank of India: A Text Analysis Approach," SAGE Open, , vol. 11(3), pages 21582440211, July.
    15. Kyoto Yono & Hiroki Sakaji & Hiroyasu Matsushima & Takashi Shimada & Kiyoshi Izumi, 2020. "Construction of Macroeconomic Uncertainty Indices for Financial Market Analysis Using a Supervised Topic Model," JRFM, MDPI, vol. 13(4), pages 1-18, April.
    16. Wang, Hanjie & Feil, Jan-Henning & Yu, Xiaohua, 2023. "Let the data speak about the cut-off values for multidimensional index: Classification of human development index with machine learning," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    17. Thomas E. Koker & Dimitrios Koutmos, 2020. "Cryptocurrency Trading Using Machine Learning," JRFM, MDPI, vol. 13(8), pages 1-7, August.

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    More about this item

    Keywords

    Natural language processing; VAR; Federal Reserve Beige Books;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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