Analyzing the Impact of Events Through Surveys: Formalizing Biases and Introducing the Dual Randomized Survey Design

29 Pages Posted: 13 Feb 2024 Last revised: 5 Mar 2024

See all articles by Andrew Bertoli

Andrew Bertoli

IE University

Laura Jakli

Harvard Business School

Henry Pascoe

IE University

Date Written: March 4, 2024

Abstract

Social scientists and public opinion analysts often use survey data to test how important events impact respondent beliefs, attitudes, and preferences. This paper offers a formal analysis of the pre-event/post-event survey approach, including designs that seek to reduce bias using quota sampling, rolling cross-sections, and panels. Our analysis distinguishes between various sources of bias and clarifies the comparative strengths and weaknesses of each approach. We then propose a modified panel design that can reduce bias in cases where asking respondents to complete the same survey twice could impact their responses in Wave 2. This issue is acute when fielding conventional pre-event/post-event panels due to the short time horizon between Waves 1 and 2. Our analysis elucidates important insights that can improve social scientists’ ability to study the causal impact of important events through surveys.

Keywords: Surveys, Causal Inference, Potential Outcomes Framework, Quota Sampling, Rolling Cross-Sections, Panels

Suggested Citation

Bertoli, Andrew and Jakli, Laura and Pascoe, Henry, Analyzing the Impact of Events Through Surveys: Formalizing Biases and Introducing the Dual Randomized Survey Design (March 4, 2024). Available at SSRN: https://ssrn.com/abstract=4707579 or http://dx.doi.org/10.2139/ssrn.4707579

Andrew Bertoli (Contact Author)

IE University ( email )

Calle Cardenal Zuñiga, 12
Office 347
Segovia, 40003
Spain

Laura Jakli

Harvard Business School ( email )

Soldiers Field
271 Morgan
Boston, MA 02163
United States
3309907840 (Phone)

Henry Pascoe

IE University ( email )

Calle Pedro de Valdivia 21
Madrid, Madrid 28006
Spain

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