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Tracking Weekly State-Level Economic Conditions

Author

Listed:
  • Christiane Baumeister

    (University of Notre Dame; University of Pretoria; NBER; CEPR)

  • Danilo Leiva-Leon

    (Banco de Espana)

  • Eric Sims

    (University of Notre Dame; NBER)

Abstract

In this paper, we develop a novel dataset of weekly economic conditions indices for the 50 U.S. states going back to 1987 based on mixed-frequency dynamic factor models with weekly, monthly, and quarterly variables that cover multiple dimensions of state economies. We show that there is considerable heterogeneity in the length, depth, and timing of business cycles across individual states. We assess the role of states in national recessions and propose an aggregate indicator that allows us to gauge the overall weakness of the U.S. economy. We also illustrate the usefulness of these state-level indices for quantifying the main forces contributing to the economic collapse caused by the COVID-19 pandemic and for evaluating the effectiveness of federal economic policies like the Paycheck Protection Program.

Suggested Citation

  • Christiane Baumeister & Danilo Leiva-Leon & Eric Sims, 2021. "Tracking Weekly State-Level Economic Conditions," Working Papers 202151, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:202151
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    References listed on IDEAS

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    1. Nir Jaimovich & Henry E. Siu, 2020. "Job Polarization and Jobless Recoveries," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 129-147, March.
    2. Christiane Baumeister & Dimitris Korobilis & Thomas K. Lee, 2022. "Energy Markets and Global Economic Conditions," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 828-844, October.
    3. Owyang, Michael T. & Piger, Jeremy & Wall, Howard J., 2008. "A state-level analysis of the Great Moderation," Regional Science and Urban Economics, Elsevier, vol. 38(6), pages 578-589, November.
    4. Christiane Baumeister & Lutz Kilian, 2016. "Lower Oil Prices and the U.S. Economy: Is This Time Different?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
    5. Gerald Carlino & Keith Sill, 2001. "Regional Income Fluctuations: Common Trends And Common Cycles," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 446-456, August.
    6. Theodore M. Crone, 2005. "An Alternative Definition of Economic Regions in the United States Based on Similarities in State Business Cycles," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 617-626, November.
    7. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    8. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    9. Granja, João & Makridis, Christos & Yannelis, Constantine & Zwick, Eric, 2022. "Did the paycheck protection program hit the target?," Journal of Financial Economics, Elsevier, vol. 145(3), pages 725-761.
    10. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2017. "Tracking the Slowdown in Long-Run GDP Growth," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 343-356, May.
    11. Maximo Camacho & Gabriel Perez-Quiros, 2010. "Introducing the euro-sting: Short-term indicator of euro area growth," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 663-694.
    12. Glenn Hubbard & Michael R. Strain, 2020. "Has the Paycheck Protection Program Succeeded?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(3 (Fall)), pages 335-390.
    13. Galbraith, John W. & Tkacz, Greg, 2018. "Nowcasting with payments system data," International Journal of Forecasting, Elsevier, vol. 34(2), pages 366-376.
    14. Francis X. Diebold, 2020. "Real-Time Real Economic Activity:Exiting the Great Recession and Entering the Pandemic Recession," PIER Working Paper Archive 20-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    15. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 935-947, November.
    16. Alexander W. Bartik & Marianne Bertrand & Feng Lin & Jesse Rothstein & Matthew Unrath, 2020. "Measuring the Labor Market at the Onset of the COVID-19 Crisis," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(2 (Summer), pages 239-268;316.
    17. Maximo Camacho & Gabriel Perez‐Quiros & Pilar Poncela, 2015. "Extracting Nonlinear Signals from Several Economic Indicators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1073-1089, November.
    18. Diebold, Francis X & Rudebusch, Glenn D, 1996. "Measuring Business Cycles: A Modern Perspective," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 67-77, February.
    19. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    20. Jushan Bai & Peng Wang, 2015. "Identification and Bayesian Estimation of Dynamic Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 221-240, April.
    21. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    22. Yunjong Eo & Chang-Jin Kim, 2016. "Markov-Switching Models with Evolving Regime-Specific Parameters: Are Postwar Booms or Recessions All Alike?," The Review of Economics and Statistics, MIT Press, vol. 98(5), pages 940-949, December.
    23. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022. "Measuring real activity using a weekly economic index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
    24. Kathryn Koenders & Richard Rogerson, 2005. "Organizational dynamics over the business cycle: a view on jobless recoveries," Review, Federal Reserve Bank of St. Louis, vol. 87(Jul), pages 555-580.
    25. repec:aei:rpaper:1008582843 is not listed on IDEAS
    26. Theodore M. Crone & Alan Clayton-Matthews, 2005. "Consistent Economic Indexes for the 50 States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 593-603, November.
    27. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, April.
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    Cited by:

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    2. Xin Sheng & Rangan Gupta & Wenting Liao & Oguzhan Cepni, 2024. "The Effects of Uncertainty on Economic Conditions across US States: The Role of Climate Risks," Working Papers 202410, University of Pretoria, Department of Economics.
    3. Lyu, Yongjian & Zhang, Xinyu & Cao, Jin & Liu, Jiatao & Yang, Mo, 2024. "Quantitative easing and the spillover effects from the crude oil market to other financial markets: Evidence from QE1 to QE3," Journal of International Money and Finance, Elsevier, vol. 140(C).
    4. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
    5. Emanuele Bacchiocchi & Andrea Bastianin & Graziano Moramarco, 2024. "Macroeconomic Spillovers of Weather Shocks across U.S. States," Working Papers 2024.09, Fondazione Eni Enrico Mattei.
    6. Kohns, David & Potjagailo, Galina, 2023. "Flexible Bayesian MIDAS: time‑variation, group‑shrinkage and sparsity," Bank of England working papers 1025, Bank of England.

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    More about this item

    Keywords

    local economic conditions; government policies; weekly indicators; state economies; cross-state heterogeneity; mixed-frequency dynamic factor model; economic weakness index; Markov-switching; recession probabilities;
    All these keywords.

    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
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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