<i>Schumpeter Lecture 2025</i> : The New Causal Macroeconomics of Surveys and Experiments

Abstract We discuss how randomized control trials (RCTs) can be used to study the causal effects of expectations on the decisions of households, firms, and other economic agents. Specifically, information provision in RCTs can create exogenous variation in the beliefs of survey participants and thus can address a key identification challenge that has plagued research efforts focused on understanding the role of expectations in shaping economic decisions. When linked to either external information on their actions or subsequent survey waves that measure their ex-post decisions, RCTs can provide clear causal identification of the passthrough from expectations to decisions. We review recent evidence using this strategy and discuss potential challenges associated with this approach.

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Publication Details

Journal
Journal of the European Economic Association
Published
2025-11-19
DOI
https://doi.org/10.1093/jeea/jvaf050
Primary Topic
Advanced Causal Inference Techniques
Type
article
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article

Schumpeter Lecture 2025 : The New Causal Macroeconomics of Surveys and Experiments

Yuriy Gorodnichenko, Olivier Coibion
Journal of the European Economic Association
Advanced Causal Inference Techniques
article

Schumpeter Lecture 2025 : The New Causal Macroeconomics of Surveys and Experiments

Yuriy Gorodnichenko, Olivier Coibion
article en

Abstract

Abstract We discuss how randomized control trials (RCTs) can be used to study the causal effects of expectations on the decisions of households, firms, and other economic agents. Specifically, information provision in RCTs can create exogenous variation in the beliefs of survey participants and thus can address a key identification challenge that has plagued research efforts focused on understanding the role of expectations in shaping economic decisions. When linked to either external information on their actions or subsequent survey waves that measure their ex-post decisions, RCTs can provide clear causal identification of the passthrough from expectations to decisions. We review recent evidence using this strategy and discuss potential challenges associated with this approach.

Journal of the European Economic AssociationVol. 24(1)
Berkeley College (US), NanoMedical Systems (United States) (US), The University of Texas at Austin (US), University of California, Berkeley (US)
Openalex Percentile: Top 67%
Advanced Causal Inference Techniques
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