outcome measure, child performance on the _Test de Vocabulario en Imágenes Peabody_ (TVIP). In all five countries, we observe socioeconomic gradients in cognitive development (albeit of different magnitudes), which suggests that this pattern is not idiosyncratic, country-specific, or a result of data mining. Moreover, in the rural areas of all five countries, and in the urban areas of Chile and Colombia the distribution of socioeconomic status in the surveys we use is broadly similar to the distribution of socioeconomic status in nationally-representative household surveys, further suggesting that the results we report have external validity, at least in rural areas.<sup>2</sup> Second, we show that our findings are robust to different ways of defining socioeconomic status, to different ways of standardizing outcomes, and to selective non-response on our measure of cognitive development. Finally, in three countries (Ecuador, Nicaragua, and Peru) we exploit the longitudinal structure of the data to analyze how deficits in receptive language ability observed at young ages evolve as children enter the early school years.

# **2. Data and setting**

We begin by describing the surveys that we use for our analysis in Table 1. The table shows that the surveys we use vary in sample sizes and coverage. The largest samples are found in the survey for Chile (approximately 5,400 children) and the smallest in Nicaragua and Peru (between 1,800 and 1,900 children each). The Nicaraguan survey only sampled children in rural areas, while the data for Chile, Colombia, Ecuador and Peru covered both urban and rural areas. The age range of children in the surveys also varies. The test of child cognitive development we use, discussed in more detail below, is designed to be applied to children 30 months and older, and in most of our analysis we limit the sample to children ages 36-71 months of age. In practice, however, the oldest children in Chile are 57 months of age, while the youngest children in Peru are 53 months of age.

Table 1 also shows that in three of the countries we analyze, Ecuador, Nicaragua, and Peru, there is a panel component in the data. In Peru, there are two waves of this panel, separated by approximately three years; in Nicaragua, there are three rounds of data collected over a four-year period; in Ecuador, finally, there are four rounds of data collected over a seven-year period.

> 2 To make this comparison, we use nationally-representative household surveys in each of the five countries, restrict the list of assets and dwelling characteristics to those that are common to both the nationally-representative survey and the survey that was the basis for our analysis of the TVIP scores, and calculate wealth indices in the nationally-representative surveys, separately for urban and rural areas. We then re-calculate a wealth index in the surveys that we use to analyze the TVIP scores, giving each of the assets and dwelling characteristics the same weight that they receive in the calculation of the first principal component in the nationally-representative survey. Finally, we graph kernel densities of the distribution of wealth in both surveys (See Appendix Figure 1).

3