IDEAS home Printed from https://ideas.repec.org/p/kof/wpskof/18-443.html
   My bibliography  Save this paper

Is it good to be bad or bad to be good?: Assessing the aggregate impact of abnormal weather on consumer spending

Author

Abstract

Although the influence of exceptional weather on individual behaviour has already been acknowledgedin finance, psychology, and marketing, the literature examining weather effects at more aggregate levelis still limited. Further, there is a lot of anecdotal evidence that weather anomalies affect consumerspending and retail business. The main aim of this analysis is to investigate and quantify the effectsof unusual weather in consumer spending at macro-level. Using aggregate retail sales data for Switzer-land, our findings reveal that weather deviations from seasonal norms, especially, unusually high or lowtemperatures in a given month, do cause sizeable intertemporal shifts in consumer spending at countrylevel. Furthermore, the effects of abnormal weather are found to differ across seasons, both with respectto sign and magnitude. In particular, our findings indicate that weather effects manifest mainly throughthe seasons change channel: weather conditions in line with the coming season boost the purchases earlyin the season.

Suggested Citation

  • Boriss Siliverstovs & Anna Sandqvist, 2018. "Is it good to be bad or bad to be good?: Assessing the aggregate impact of abnormal weather on consumer spending," KOF Working papers 18-443, KOF Swiss Economic Institute, ETH Zurich.
  • Handle: RePEc:kof:wpskof:18-443
    DOI: 10.3929/ethz-b-000298425
    as

    Download full text from publisher

    File URL: https://doi.org/10.3929/ethz-b-000298425
    Download Restriction: no

    File URL: https://libkey.io/10.3929/ethz-b-000298425?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Boriss Siliverstovs & Rainald Ötsch & Claudia Kemfert & Carlo Jaeger & Armin Haas & Hans Kremers, 2008. "Climate Change and Modelling of Extreme Temperatures in Switzerland," Discussion Papers of DIW Berlin 840, DIW Berlin, German Institute for Economic Research.
    2. Murray, Kyle B. & Di Muro, Fabrizio & Finn, Adam & Popkowski Leszczyc, Peter, 2010. "The effect of weather on consumer spending," Journal of Retailing and Consumer Services, Elsevier, vol. 17(6), pages 512-520.
    3. Michael Boldin & Jonathan H. Wright, 2015. "Weather-Adjusting Economic Data," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(2 (Fall)), pages 227-278.
    4. Martha Starr-McCluer, 2000. "The effects of weather on retail sales," Finance and Economics Discussion Series 2000-08, Board of Governors of the Federal Reserve System (U.S.).
    5. David F. Hendry & Katarina Juselius, 2001. "Explaining Cointegration Analysis: Part II," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 75-120.
    6. Meghan R. Busse & Devin G. Pope & Jaren C. Pope & Jorge Silva-Risso, 2015. "The Psychological Effect of Weather on Car Purchases," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 371-414.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jean-Louis Bertrand & Xavier Brusset, 2018. "Managing the financial consequences of weather variability," Journal of Asset Management, Palgrave Macmillan, vol. 19(5), pages 301-315, September.
    2. Bertrand, Jean-Louis & Brusset, Xavier & Fortin, Maxime, 2015. "Assessing and hedging the cost of unseasonal weather: Case of the apparel sector," European Journal of Operational Research, Elsevier, vol. 244(1), pages 261-276.
    3. Stefan Lamp, 2023. "Sunspots That Matter: The Effect of Weather on Solar Technology Adoption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 1179-1219, April.
    4. Verstraete, Gylian & Aghezzaf, El-Houssaine & Desmet, Bram, 2019. "A data-driven framework for predicting weather impact on high-volume low-margin retail products," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 169-177.
    5. Martínez-de-Albéniz, Victor & Belkaid, Abdel, 2021. "Here comes the sun: Fashion goods retailing under weather fluctuations," European Journal of Operational Research, Elsevier, vol. 294(3), pages 820-830.
    6. Badorf, Florian & Hoberg, Kai, 2020. "The impact of daily weather on retail sales: An empirical study in brick-and-mortar stores," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    7. Sinha, Rajesh Kumar, 2021. "Subscription and casual customers’ differential sensitivity to meteorological characteristics," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    8. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2021. "Computing Macro-Effects and Welfare Costs of Temperature Volatility: A Structural Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 347-394, August.
    9. Tian, Xin & Cao, Shasha & Song, Yan, 2021. "The impact of weather on consumer behavior and retail performance: Evidence from a convenience store chain in China," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    10. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2019. "Temperature Volatility Risk," Working Papers 2019:05, Department of Economics, University of Venice "Ca' Foscari".
    11. Fan, Ying & Fu, Yuqi & Yang, Zan & Chen, Ming, 2023. "Search Frictions in Rental Markets: Evidence from Urban China," Working Paper Series 23/11, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    12. Tobias Schlager & Emanuel de Bellis & JoAndrea Hoegg, 2020. "How and when weather boosts consumer product valuation," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 695-711, July.
    13. Michele Cascarano & Filippo Natoli, 2023. "Temperatures and search: evidence from the housing market," Temi di discussione (Economic working papers) 1419, Bank of Italy, Economic Research and International Relations Area.
    14. Evgeniya Tonkova, 2017. "Specific Applications of Weather-Based Marketing," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, vol. 1(1), pages 204-209, October.
    15. Chenxi Li & Xueming Luo & Cheng Zhang, 2017. "Sunny, Rainy, and Cloudy with a Chance of Mobile Promotion Effectiveness," Marketing Science, INFORMS, vol. 36(5), pages 762-779, September.
    16. Barbera, Michael & Northey, Gavin & Septianto, Felix & Spanjaard, Daniela, 2018. "Those prices are HOT! How temperature-related visual cues anchor expectations of price and value," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 178-181.
    17. Agarwal, Sumit & Chomsisengphet, Souphala & Meier, Stephan & Zou, Xin, 2020. "In the mood to consume: Effect of sunshine on credit card spending," Journal of Banking & Finance, Elsevier, vol. 121(C).
    18. Clot, Sophie & Grolleau, Gilles & Ibanez, Lisette, 2022. "Projection bias in environmental beliefs and behavioural intentions - An application to solar panels and eco-friendly transport," Energy Policy, Elsevier, vol. 160(C).
    19. Bertrand, Jean-Louis & Brusset, Xavier & Chabot, Miia, 2021. "Protecting franchise chains against weather risk: A design science approach," Journal of Business Research, Elsevier, vol. 125(C), pages 187-200.
    20. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.

    More about this item

    Keywords

    Consumer spending; intertemporal shifts; retail sales; unusual weather;
    All these keywords.

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kof:wpskof:18-443. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/koethch.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.