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Complementarity and Macroeconomic Uncertainty

Author

Listed:
  • Tyler Atkinson

    (Federal Reserve Bank of Dallas)

  • Michael Plante

    (Federal Reserve Bank of Dallas)

  • Alexander Richter

    (Federal Reserve Bank of Dallas)

  • Nathaniel Throckmorton

    (University of William and Mary)

Abstract

Macroeconomic uncertainty regularly fluctuates in the data. Theory suggests complementarity between capital and labor inputs in production can generate time-varying endogenous uncertainty because the concavity in the production function influences how output responds to productivity shocks in different states of the economy. This paper examines whether complementarity is a quantitatively significant source of time-varying endogenous uncertainty by estimating a nonlinear real business cycle model with a constant elasticity of substitution production function and exogenous volatility shocks. When matching labor share and uncertainty moments, we find at most 16% of the volatility of uncertainty is endogenous. An estimated model without exogenous volatility shocks can endogenously generate all of the empirical variation in uncertainty, but only at the expense of significantly overstating the volatility of the labor share. (Copyright: Elsevier)

Suggested Citation

  • Tyler Atkinson & Michael Plante & Alexander Richter & Nathaniel Throckmorton, 2022. "Complementarity and Macroeconomic Uncertainty," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 225-243, April.
  • Handle: RePEc:red:issued:21-53
    DOI: 10.1016/j.red.2021.03.003
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    as
    1. Miguel A León-Ledesma & Mathan Satchi, 2019. "Appropriate Technology and Balanced Growth," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(2), pages 807-835.
    2. Zhiguo He & Arvind Krishnamurthy, 2019. "A Macroeconomic Framework for Quantifying Systemic Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(4), pages 1-37, October.
    3. Haroon Mumtaz & Francesco Zanetti, 2013. "The Impact of the Volatility of Monetary Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 535-558, June.
    4. Cosmin Ilut & Matthias Kehrig & Martin Schneider, 2018. "Slow to Hire, Quick to Fire: Employment Dynamics with Asymmetric Responses to News," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 2011-2071.
    5. Jesus Fernandez-Villaverde & Pablo Guerron-Quintana & Juan F. Rubio-Ramirez & Martin Uribe, 2011. "Risk Matters: The Real Effects of Volatility Shocks," American Economic Review, American Economic Association, vol. 101(6), pages 2530-2561, October.
    6. Saijo, Hikaru, 2017. "The uncertainty multiplier and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 1-25.
    7. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    8. Francois Gourio, 2013. "Financial Distress and Endogenous Uncertainty," 2013 Meeting Papers 108, Society for Economic Dynamics.
    9. Ezra Oberfield & Devesh Raval, 2021. "Micro Data and Macro Technology," Econometrica, Econometric Society, vol. 89(2), pages 703-732, March.
    10. 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.
    11. Karen Kopecky & Richard Suen, 2010. "Finite State Markov-chain Approximations to Highly Persistent Processes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(3), pages 701-714, July.
    12. Raj Chetty & Adam Guren & Day Manoli & Andrea Weber, 2013. "Does Indivisible Labor Explain the Difference between Micro and Macro Elasticities? A Meta-Analysis of Extensive Margin Elasticities," NBER Macroeconomics Annual, University of Chicago Press, vol. 27(1), pages 1-56.
    13. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    14. Jesús Fernández-Villaverde & Pablo Guerrón-Quintana & Keith Kuester & Juan Rubio-Ramírez, 2015. "Fiscal Volatility Shocks and Economic Activity," American Economic Review, American Economic Association, vol. 105(11), pages 3352-3384, November.
    15. 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.
    16. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    17. Alexander Richter & Nathaniel Throckmorton & Todd Walker, 2014. "Accuracy, Speed and Robustness of Policy Function Iteration," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 445-476, December.
    18. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    19. Kyle Jurado & Sydney C. Ludvigson & Serena Ng, 2015. "Measuring Uncertainty," American Economic Review, American Economic Association, vol. 105(3), pages 1177-1216, March.
    20. Straub, Ludwig & Ulbricht, Robert, 2015. "Endogenous Uncertainty and Credit Crunches," TSE Working Papers 15-604, Toulouse School of Economics (TSE), revised Dec 2017.
    21. Fabio Canova & David Lopez-Salido & Claudio Michelacci, 2010. "The effects of technology shocks on hours and output: a robustness analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 755-773.
    22. Coleman, Wilbur John, II, 1991. "Equilibrium in a Production Economy with an Income Tax," Econometrica, Econometric Society, vol. 59(4), pages 1091-1104, July.
    23. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    24. Rainer Klump & Peter McAdam & Alpo Willman, 2012. "The Normalized Ces Production Function: Theory And Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 26(5), pages 769-799, December.
    25. Cristina Arellano & Yan Bai & Patrick J. Kehoe, 2019. "Financial Frictions and Fluctuations in Volatility," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 2049-2103.
    26. Born, Benjamin & Pfeifer, Johannes, 2014. "Policy risk and the business cycle," Journal of Monetary Economics, Elsevier, vol. 68(C), pages 68-85.
    27. Sebastian Gechert & Thomas Havranek & Zuzana Irsova & Dominika Kolcunova, 2019. "Death to the Cobb-Douglas Production Function," FMM Working Paper 51-2019, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    28. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
    29. Eggertsson, Gauti B. & Singh, Sanjay R., 2019. "Log-linear approximation versus an exact solution at the ZLB in the New Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 21-43.
    30. Markus K. Brunnermeier & Yuliy Sannikov, 2014. "A Macroeconomic Model with a Financial Sector," American Economic Review, American Economic Association, vol. 104(2), pages 379-421, February.
    31. Miguel A. León-Ledesma & Peter McAdam & Alpo Willman, 2010. "Identifying the Elasticity of Substitution with Biased Technical Change," American Economic Review, American Economic Association, vol. 100(4), pages 1330-1357, September.
    32. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    33. Lawrence J. Christiano & Michele Boldrin & Jonas D. M. Fisher, 2001. "Habit Persistence, Asset Returns, and the Business Cycle," American Economic Review, American Economic Association, vol. 91(1), pages 149-166, March.
    34. Straub, Ludwig & Ulbricht, Robert, 2019. "Endogenous second moments: A unified approach to fluctuations in risk, dispersion, and uncertainty," Journal of Economic Theory, Elsevier, vol. 183(C), pages 625-660.
    35. Ruge-Murcia, Francisco, 2012. "Estimating nonlinear DSGE models by the simulated method of moments: With an application to business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 36(6), pages 914-938.
    36. Rotemberg, Julio J, 1982. "Sticky Prices in the United States," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1187-1211, December.
    37. Cantore, Cristiano & Levine, Paul & Pearlman, Joseph & Yang, Bo, 2015. "CES technology and business cycle fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 133-151.
    38. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May.
    39. Enrique G. Mendoza, 2010. "Sudden Stops, Financial Crises, and Leverage," American Economic Review, American Economic Association, vol. 100(5), pages 1941-1966, December.
    40. Joachim Hubmer, 2019. "The Race Between Preferences and Technology," 2019 Meeting Papers 1430, Society for Economic Dynamics.
    41. Ireland, Peter N., 1997. "A small, structural, quarterly model for monetary policy evaluation," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 83-108, December.
    42. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    43. repec:mcb:jmoncb:v:45:y:2013:i::p:535-558 is not listed on IDEAS
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    Cited by:

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    2. Joshua Bernstein & Michael D. Plante & Alexander W. Richter & Nathaniel A. Throckmorton, 2021. "Countercyclical Fluctuations in Uncertainty are Endogenous," Working Papers 2109, Federal Reserve Bank of Dallas.

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    More about this item

    Keywords

    State-Dependence; Stochastic Volatility; CES Production; Endogenous Uncertainty;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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