Correcting Nonresponse Bias Using Panel Data on Data Requests and Responses

TL;DR

This paper introduces a method to correct nonresponse bias in surveys by using panel data on data requests and responses as instruments, demonstrated through estimating gender gaps in entrepreneurial intentions.

Contribution

The paper presents a novel approach leveraging panel data on requests and responses to address nonresponse bias without requiring randomized requests.

Findings

Estimated an 18-percentage-point gender gap in entrepreneurial intentions.

Identified a 20-percentage-point intention gap among respondents.

Demonstrated effectiveness with a 15% survey response rate.

Abstract

When subjects who respond to requests for data, such as in surveys or post-treatment follow-up, are not representative of the population as a whole, inferences drawn from the data can be misleading. We show that if subjects' accumulated requests and responses over time are recorded and organized as panel data, requests can be used as instruments to correct for nonresponse bias even if total requests are not randomized between subjects. We demonstrate our method by estimating an 18-percentage-point gender gap in entrepreneurial career intentions using a survey of undergraduates at the University of Wisconsin-Madison with a 15% response rate and a 20-percentage-point intention gap among respondents.