Effects of mixing modes on nonresponse and measurement error in an economic panel survey

Abstract Numerous panel surveys around the world use multiple modes of data collection to recruit and interview respondents. Previous studies have shown that mixed-mode data collection can improve response rates, reduce nonresponse bias, and reduce survey costs. However, these advantages come at the expense of potential measurement differences between modes. A major challenge in survey research is disentangling measurement error biases from nonresponse biases in order to study how mixing modes affects the development of both error sources over time. In this article, we use linked administrative data to disentangle both nonresponse and measurement error biases in the long-running mixed-mode economic panel study “Labour Market and Social Security” (PASS). Through this study design we answer the question of whether mixing modes reduces nonresponse and measurement error biases compared to a single-mode design. In short, we find that mixing modes reduces nonresponse bias for most variables, particularly in later waves, with only small effects on measurement error bias. The total bias and mean-squared error are both reduced under the mixed-mode design compared to the counterfactual single-mode design, which is a reassuring finding for mixed-mode economic panel surveys.