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Economic policy uncertainty and unemployment in the United States: A nonlinear approach

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  • Caggiano, Giovanni
  • Castelnuovo, Efrem
  • Figueres, Juan Manuel

Abstract

We model US post-WWII monthly data with a Smooth Transition VAR model and study the effects of an unanticipated increase in economic policy uncertainty on unemployment in recessions and expansions. We find the response of unemployment to be statistically and economically larger in recessions. A state-contingent forecast error variance decomposition analysis confirms that the contribution of EPU shocks to the volatility of unemployment at business cycle frequencies is markedly larger in recessions.

Suggested Citation

  • Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
  • Handle: RePEc:eee:ecolet:v:151:y:2017:i:c:p:31-34
    DOI: 10.1016/j.econlet.2016.12.002
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    References listed on IDEAS

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    1. Nodari, Gabriela, 2014. "Financial regulation policy uncertainty and credit spreads in the US," Journal of Macroeconomics, Elsevier, vol. 41(C), pages 122-132.
    2. repec:taf:jnlbes:v:34:y:2016:i:4:p:574-589 is not listed on IDEAS
    3. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    4. ., 2015. "Income distribution and the business cycle," Chapters,in: The New Economics of Income Distribution, chapter 5, pages 96-122 Edward Elgar Publishing.
    5. Markku Lanne & Henri Nyberg, 2016. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(4), pages 595-603, August.
    6. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1593-1636.
    7. James Morley & Jeremy Piger, 2012. "The Asymmetric Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 208-221, February.
    8. Scott R. Baker & Nicholas Bloom & Brandice Canes-Wrone & Steven J. Davis & Jonathan Rodden, 2014. "Why Has US Policy Uncertainty Risen since 1960?," American Economic Review, American Economic Association, vol. 104(5), pages 56-60, May.
    9. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    10. Fleissig, 2015. "Changes in aggregate food demand over the business cycle," Applied Economics Letters, Taylor & Francis Journals, vol. 22(17), pages 1366-1371, November.
    11. Timo Teräsvirta & Yukai Yang, 2014. "Linearity and Misspecification Tests for Vector Smooth Transition Regression Models," CREATES Research Papers 2014-04, Department of Economics and Business Economics, Aarhus University.
    12. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    13. Matteo Cacciatore, 2015. "Uncertainty and the Business Cycle," 2015 Meeting Papers 1440, Society for Economic Dynamics.
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    Citations

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    Cited by:

    1. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2017. "Economic Policy Uncertainty Spillovers in Booms and Busts," Melbourne Institute Working Paper Series wp2017n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    2. Castelnuovo, Efrem & Tran, Trung Duc, 2017. "Google It Up! A Google Trends-based Uncertainty index for the United States and Australia," Economics Letters, Elsevier, vol. 161(C), pages 149-153.
    3. Athanasios Triantafyllou & Dimitrios Bakas & Marilou Ioakimidis, 2019. "Commodity Price Uncertainty as a Leading Indicator of Economic Activity," Working Paper series 19-03, Rimini Centre for Economic Analysis.
    4. repec:eee:ecolet:v:155:y:2017:i:c:p:121-125 is not listed on IDEAS
    5. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2014. "Uncertainty and Monetary Policy in Good and Bad Times," "Marco Fanno" Working Papers 0188, Dipartimento di Scienze Economiche "Marco Fanno".
    6. MORIKAWA Masayuki, 2017. "Uncertainty over Production Forecasts: An empirical analysis using monthly firm survey data," Discussion papers 17081, Research Institute of Economy, Trade and Industry (RIETI).
    7. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    8. Christian Pierdzioch & Rangan Gupta, 2017. "Uncertainty and Forecasts of U.S. Recessions," Working Papers 201732, University of Pretoria, Department of Economics.
    9. repec:eee:intfin:v:55:y:2018:i:c:p:134-150 is not listed on IDEAS
    10. repec:eee:eecrev:v:100:y:2017:i:c:p:257-272 is not listed on IDEAS
    11. repec:eee:chieco:v:51:y:2018:i:c:p:1-19 is not listed on IDEAS
    12. repec:eee:ecmode:v:72:y:2018:i:c:p:42-53 is not listed on IDEAS
    13. repec:eee:ecofin:v:45:y:2018:i:c:p:245-265 is not listed on IDEAS
    14. Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2017. "Estimating the real effects of uncertainty shocks at the Zero Lower Bound," European Economic Review, Elsevier, vol. 100(C), pages 257-272.
    15. Degiannakis, Stavros & Filis, George & Panagiotakopoulou, Sofia, 2018. "Oil price shocks and uncertainty: How stable is their relationship over time?," Economic Modelling, Elsevier, vol. 72(C), pages 42-53.
    16. 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," Center for European, Governance and Economic Development Research Discussion Papers 358, University of Goettingen, Department of Economics.
    17. Efrem Castelnuovo & Guay Lim, 2018. "What do we know about the macroeconomic effects of fiscal policy? A brief survey of the literature on fiscal multipliers," CAMA Working Papers 2018-59, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    18. repec:eee:jmacro:v:57:y:2018:i:c:p:317-337 is not listed on IDEAS
    19. Kevin Larcher & Jaebeom Kim & Youngju Kim, 2018. "Uncertainty Shocks and Asymmetric Dynamics in Korea: A Nonlinear Approach," Working Papers 2018-12, Economic Research Institute, Bank of Korea.
    20. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    21. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    22. Bao H. NGUYEN & OKIMOTO Tatsuyoshi, 2017. "Asymmetric Reactions of the U.S. Natural Gas Market and Economic Activity," Discussion papers 17102, Research Institute of Economy, Trade and Industry (RIETI).

    More about this item

    Keywords

    Economic policy uncertainty shocks; Unemployment dynamics; Smooth transition vector autoregressions; Recessions; Expansions;

    JEL classification:

    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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