Attrition and Non-Response in Panel Data: The Case of the Canadian Survey of Labor and Income Dynamics

TL;DR

This study analyzes how attrition and non-response bias affect employment and wage estimates in the Canadian Survey of Labour and Income Dynamics, revealing that attrition is non-random and biases wage estimates upward.

Contribution

It introduces a structural model to quantify the effects of attrition and non-response on employment and wages in panel data, highlighting their non-random nature.

Findings

Attrition is non-random, with less attached and lower-income individuals more likely to drop out.

There is a positive correlation between non-attrition and employment, though small.

Wage estimates are biased upwards due to attrition and non-response.

Abstract

This paper provides an analysis of the effects of attrition and non-response on employment and wages using the Canadian Survey of Labour and Income Dynamics. We consider a structural model composed of three freely correlated equations for nonattrition/response, employment and wages. The model is estimated using microdata from 22,990 individuals who provided sufficient information in the first wave of the 1996-2001 panel. The main findings of the paper are that attrition is not random. Attritors and non-respondents likely are less attached to employment and come from low-income population. The correlation between non-attrition and employment is positive and statistically significant, though small. Also, wage estimates are biased upwards. Observed wages are on average higher than wages that would be observed if all the individuals initially selected in the panel remained in the sample.