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Related Experiment Video

Updated: Jul 3, 2026

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

Optimal recall length in survey design.

Philip M Clarke¹, Denzil G Fiebig, Ulf-G Gerdtham

¹School of Public Health, The University of Sydney, NSW 2006, Australia. philipc@health.usyd.edu.au

Journal of Health Economics

|August 1, 2008

Summary

Economists use survey data, but recall periods cause errors. This study presents a statistical framework to balance information gain and recall error, optimizing survey design for better economic research.

Area of Science:

Economics
Survey Methodology
Health Services Research

Background:

Self-reported survey data are crucial for economic research.
Recall error in survey data arises from respondents' memory limitations.
Survey designers face a trade-off between recall period length and data accuracy.

Purpose of the Study:

To develop a statistical framework for analyzing the trade-off between recall period length and measurement error in surveys.
To provide a method for estimating optimal recall periods in economic surveys.
To improve the quality of self-reported data used in economic research.

Main Methods:

Utilized a statistical framework to model the relationship between recall period and data accuracy.
Employed hospital utilization data from Sweden's Survey of Living Conditions for illustration.

Related Experiment Videos

Last Updated: Jul 3, 2026

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

A Cross-Disciplinary and Multi-Modal Experimental Design for Studying Near-Real-Time Authentic Examination Experiences

Published on: September 4, 2019

Analyzed the impact of varying recall periods on data quality.

Main Results:

Demonstrated a quantifiable trade-off between the length of the recall period and the extent of recall error.
Showcased the application of the statistical framework using real-world survey data.
Identified optimal recall period lengths based on data characteristics.

Conclusions:

The choice of recall period significantly impacts the reliability of survey data in economic studies.
The proposed statistical framework offers a robust method for optimizing survey design.
Accurate recall period estimation can enhance the validity of economic research findings.