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The Effects of COVID-19 Policies on Consumer Spending in Norway

Author

Listed:
  • Fenella Carpena

    (Oslo Business School, Oslo Metropolitan University)

  • Laurens Swinkels

    (Erasmus University Rotterdam (EUR); Robeco Asset Management)

  • Dan Zhang

    (Oslo Business School, Oslo Metropolitan University)

Abstract

This paper examines the effect of COVID-19 policies on consumer spending using bank card transaction data from Norway. Taking advantage of variation in COVID-19 policies over time and across space in the four largest municipalities in the country, we investigate the heterogeneity of effects of policies in their number and type. First, we document that the number of restrictions is negatively correlated with spending and exhibits decreasing marginal effects. Second, restrictions do not affect all types of spending equally: restrictions tend to have larger impacts on the sector in which it is targeted. Finally, we find evidence from a difference-in-differences estimation that supports a causal interpretation of our results.

Suggested Citation

  • Fenella Carpena & Laurens Swinkels & Dan Zhang, 2023. "The Effects of COVID-19 Policies on Consumer Spending in Norway," Working Papers 202302, Oslo Metropolitan University, Oslo Business School.
    • Handle: RePEc:oml:wpaper:202302
    DOI: 10.2139/ssrn.4497685
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    References listed on IDEAS

    as
    1. Akerman, Anders & Ekholm, Karolina & Persson, Torsten & Nordström Skans, Oskar, 2022. "Sweden's COVID-19 Recession: How Foreign and Domestic Infections Struck against Firms and Workers," IZA Discussion Papers 15408, Institute of Labor Economics (IZA).
    2. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    3. Goodman-Bacon, Andrew & Marcus, Jan, 2020. "Using Difference-in-Differences to Identify Causal Effects of COVID-19 Policies," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14(2), pages 153-158.
    4. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    5. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    6. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    7. Natalie Cox & Peter Ganong & Pascal Noel & Joseph Vavra & Arlene Wong & Diana Farrell & Fiona Greig & Erica Deadman, 2020. "Initial Impacts of the Pandemic on Consumer Behavior: Evidence from Linked Income, Spending, and Savings Data," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(2 (Summer), pages 35-82.
    8. Scott R Baker & Robert A Farrokhnia & Steffen Meyer & Michaela Pagel & Constantine Yannelis & Jeffrey Pontiff, 0. "How Does Household Spending Respond to an Epidemic? Consumption during the 2020 COVID-19 Pandemic," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 834-862.
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    More about this item

    Keywords

    Expenditure; Consumption; COVID-19; pandemic;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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