Frontiers: Estimating the Long-Term Impact of Major Events on Consumption Patterns: Evidence from COVID-19

Shin Oblander () and Daniel Minh McCarthy ()
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Shin Oblander: Marketing, Columbia University, New York, New York 10027
Daniel Minh McCarthy: Marketing, Emory University, Atlanta, Georgia 30322

Marketing Science, 2023, vol. 42, issue 5, 839-852

Abstract: We propose a general and flexible methodology for inferring the time-varying effects of a discrete event on consumer behavior. Our method enables analysis of events that span the target population being analyzed, where there is no contemporaneous “control group” and/or it is not possible to measure treatment status, by comparing the purchasing behavior of cohorts acquired at different times. Our method applies nonparametric age-period-cohort models, commonly used in sociology but with limited adoption in marketing, in conjunction with a predictive model of the counterfactual no-event baseline (i.e., an event study model). We use this method to infer how the COVID-19 pandemic affected 12 online and offline consumption categories. Our results suggest that the pandemic initially drove significant spending lifts at e-commerce businesses at the expense of brick-and-mortar alternatives. After two years, however, these changes have largely reverted. We observe significant heterogeneity across categories, with more persistent changes in subscription-based categories and more transient changes in categories based on discretionary purchases, especially those of durable goods.

Keywords: customer relationship management; COVID-19; age-period-cohort model; persistence; causal inference; forecasting (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:42:y:2023:i:5:p:839-852

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