Abstract
Intergenerational mobility is often studied using survey data. In such settings, selective unit or item non-response may bias estimates. Linking Dutch survey data to administrative income data allows us to examine whether selective responses bias the estimated relationship between parental income and children’s mathematics and language test scores in grades 6 and 9. We find that the estimates of these relationships are biased downward due to parental unit non-response, while they are biased upwards due to item non-response. In the analyses of both unit and item non-response, the point estimates for language and mathematics test scores point in the same direction but only one of the two relationships is significant. These findings suggest that estimates of intergenerational mobility based on survey data need to be interpreted with caution because they may be biased by selective non-response. The direction of such bias is difficult to predict a priori. Bias due to unit and item non-response may work in opposing directions and may differ across outcomes.
Highlights
The relationship between parental income and children’s schooling outcomes is often estimated using survey data.1 A potentially important issue in the literature on intergenerational mobility is that survey response is potentially not random
In the analyses of both unit and item non-response, the point estimates for language and mathematics test scores point in the same direction but only one of the two relationships is significant
That unit non-response at the household level attenuates the intergenerational relationship
Summary
The relationship between parental income and children’s schooling outcomes is often estimated using survey data (see, e.g., Blau 1999; Chevalier et al 2013; Plug and Vijverberg 2005). A potentially important issue in the literature on intergenerational mobility is that survey response is potentially not random. We examine whether survey-based estimates of the relationship between household income and children’s performance in school are biased because of selective non-response. Observing non-responding households using administrative information enables us to directly assess whether response rates are selective and whether the relationship between parental income and child school performance is biased. The contribution of our study is to identify and assess the magnitude of unit and item non-response bias in the context of the intergenerational relationship between parental income and children’s schooling. 10 In this wave of the data, we observe that at least one parent from each school completed the survey This supports our claim of institutional unit non-response based on observing a zero response rate at the school level. They identify non-filing of tax returns as a major reason for this incomplete link
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