Family Income and Child Cognitive Development: A Response to Marks

Excerpt

The association between childhood outcomes and family income has gained enormous attention from academics, researchers, and policymakers in recent years because understanding the socioeconomic gradient in child development is important for uncovering the mechanisms through which intergenerational transmission of poverty takes place, as well as for formulating policies to help children reach their full potential. A considerable literature has shown that low income is associated with all domains of child development, including educational attainment (e.g., Dahl and Lochner 2012; Duncan et al. 2014). A recent scientific study by Noble et al. (2015) also found that income is associated with brain surface area; especially for low-income children, small changes in income were associated with larger differences in surface areas. These associations are dominant in areas that are responsible for language, reading, executive functions, and spatial skills. In an attempt to contribute further to this literature, we investigated whether and to what extent income is associated with child cognitive and noncognitive development in our article published earlier in Demography (Khanam and Nghiem 2016; hereafter, KN). KN (2016:608) found that “. . . an increase of log family income by 1 [standard deviation] is associated with an improvement in the PPVT, MR, literacy, and mathematical scores of children by about 0.29, 0.26, 0.23, and 0.24 SD, respectively.” Subsequently, in his commentary published in this issue using the same data set, Marks argued that the income effects produced by KN may be larger than they should be. To that end, in this reply note, we investigate why these two studies using data from the same source reach such different conclusions about the association between income and child cognitive development. We find that the divergence in results in two studies can mainly be explained by differences in (1) treatment of missing data, (2) methodology used, and (3) the control variables used, among other factors. Herein, we discuss elaborately why two studies have found comparatively different results. …