Unexpected Event during Survey Design: Promise and Pitfalls for Causal Inference

Jordi Muñoz*, Albert Falcó-Gimeno, Enrique Hernández

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

76 Citations (Scopus)


An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper, we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Survey Design. In particular, we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey, we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens' satisfaction with their national government.

Original languageAmerican English
Pages (from-to)186-206
Number of pages21
JournalPolitical Analysis
Issue number2
Publication statusPublished - 1 Apr 2020


  • causal inference
  • natural experiments
  • survey design


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