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Causal Inference from Hypothetical Evaluations

Author

Listed:
  • B. Douglas Bernheim
  • Daniel Björkegren
  • Jeffrey Naecker
  • Michael Pollmann

Abstract

We develop methods for estimating the effects of treatments on choices by combining data on real choices with hypothetical responses. Our basic method accounts for potential variation of hypothetical bias across treatment states yet is applicable even when treatment variation in real choice data is absent or limited. Under stated conditions, it also yields consistent estimates in applications with endogenous treatments. For applications that do not satisfy those conditions, we offer variants of the approach that do not require the analyst to identify sources of quasi-experimental variation. We provide formal econometric theory and test the methods in two applications.

Suggested Citation

  • B. Douglas Bernheim & Daniel Björkegren & Jeffrey Naecker & Michael Pollmann, 2021. "Causal Inference from Hypothetical Evaluations," NBER Working Papers 29616, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29616
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    Cited by:

    1. Romuald Meango & Marc Henry & Ismael Mourifie, 2025. "Combining stated and revealed preferences," Papers 2507.13552, arXiv.org, revised Nov 2025.
    2. Romuald Meango, 2023. "Using Probabilistic Stated Preference Analyses to Understand Actual Choices," Papers 2307.13966, arXiv.org.
    3. Ingvild Almås & Orazio Attanasio & Pamela Jervis, 2024. "Presidential Address: Economics and Measurement: New Measures to Model Decision Making," Econometrica, Econometric Society, vol. 92(4), pages 947-978, July.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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