Data and Code for: How Do Beliefs about the Gender Wage Gap Affect the Demand for Public Policy?

Principal Investigator(s): View help for Principal Investigator(s) Sonja Settele, CEBI and University of Copenhagen

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ado			07/03/2021 06:18:AM
data			07/03/2021 06:22:AM
dofiles			07/03/2021 06:26:AM
output			07/03/2021 06:26:AM
surveys			07/03/2021 06:26:AM
All.log	text/x-log	2.2 MB	07/03/2021 02:18:AM
Read Me.pdf	application/pdf	381.4 KB	07/03/2021 02:18:AM

Project Citation:

Settele, Sonja. Data and Code for: How Do Beliefs about the Gender Wage Gap Affect the Demand for Public Policy? Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-04-22. https://doi.org/10.3886/E134041V1

Project Description

Summary: I conduct a survey experiment to study the relationship between people's beliefs about the size of the gender wage gap and their demand for policies aimed at mitigating it. Beliefs causally affect support for equal pay legislation and affirmative action programs, but cannot account for the polarization in policy views by partisanship and gender. Changes in policy demand seem to be driven by changes in beliefs about discrimination in labor markets and fairness concerns, while self-interest appears less important. I provide evidence that pessimism about the effectiveness of government intervention limits the elasticity of policy demand to perceived wage differentials.

Funding Sources: Goethe University Frankfurt

Scope of Project

JEL Classification:
      C91 Design of Experiments: Laboratory, Individual
      D63 Equity, Justice, Inequality, and Other Normative Criteria and Measurement
      D72 Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      J38 Wages, Compensation, and Labor Costs: Public Policy
      J78 Labor Discrimination: Public Policy

Geographic Coverage: USA

Collection Date(s): 8/2018 – 1/2019

Universe: US residents aged 18-65

Data Type(s): administrative records data; survey data

Methodology

Unit(s) of Observation: individuals

Related Publications

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Published Versions

V1 [2022-04-22]

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Dublin Core

DDI 2.5

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