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Tracking Weekly State-Level Economic Conditions

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  • Christiane Baumeister
  • Danilo Leiva-León
  • Eric R. Sims

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-León & Eric R. Sims, 2021. "Tracking Weekly State-Level Economic Conditions," NBER Working Papers 29003, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29003
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    References listed on IDEAS

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    2. Emanuele Bacchiocchi & Andrea Bastianin & Graziano Moramarco, 2024. "Macroeconomic Spillovers of Weather Shocks across U.S. States," Working Papers 2024.09, Fondazione Eni Enrico Mattei.
    3. Sheng, Xin & Marfatia, Hardik A. & Gupta, Rangan & Ji, Qiang, 2023. "The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. 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.
    5. Rueben Ellul & Germano Ruisi, 2022. "Nowcasting the Maltese economy with a dynamic factor model," CBM Working Papers WP/02/2022, Central Bank of Malta.
    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

    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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