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How Researchers’ Analytical Decisions Impact Brand Price Elasticity Estimates: Insights from A Many-Analyst Study

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Price elasticities are central empirical measures in marketing, informing pricing, promotion planning, or evaluations of consumer responsiveness. Yet estimates may depend not only on brands, categories, and markets but also on the analytical decisions researchers make in transforming raw purchase data into elasticities. We use a many-analyst design in which 156 independent research teams (RTs) estimate brand price elasticities for 68 meat-substitute country-brand combinations from the same dataset. Each team retained discretion over its analytical approach, including choices concerning modeling, aggregation, fixed effects, control variables, and endogeneity correction. Results show substantial heterogeneity in both choices and estimates. Across 10,415 brand price elasticity estimates, the average is -0.61. However, the variation across the 156 RTs is considerable: the average brand price elasticity per RT ranges from -7.3 to +3.1, with a standard deviation of 0.84. Choices related to time aggregation, fixed effects, time controls, and marketing-mix covariates explain the largest share of variation in reported estimates. Because analytical choices occur in configurations rather than in isolation, we cluster RTs and reveal distinct analytical pathways associated with different patterns of estimates. Our findings contribute to elasticity research by identifying modeling decisions that warrant particular scrutiny and to the open science debate by supporting the call for greater transparency about analytical decisions.

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Les sujets associés

Consumer Market Behavior and PricingCustomer churn and segmentationEconomics of Agriculture and Food Markets

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