Abstract1 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 nationallyrepresentative survey. Finally, we graph kernel densities of the distribution of wealth in both surveys (See Online Appendix Figure 1). 2 Some examples include Schady (2011), who shows that children with low levels of TVIP scores before they enter school are more likely to repeat school grades and have lower scores on tests of math and reading in primary school in Ecuador; Case and Paxson (2008), who show that low performance on the PPVT at early ages predicts wages in adulthood in the United States; and Cunha and Heckman (2007) who use the National Longitudinal Survey of Youth (NLSY) to show that, by age 3 years, there is a difference of approximately 1.2 standard deviations in PPVT scores between children in the top and bottom quartiles of the distribution of permanent income in the United States, and that this difference is largely unchanged until at least 14 years of age. More generally, there is a large literature that shows that vocabulary size in kindergarten and earlier predicts reading comprehension throughout school and into early adulthood (see the discussion in Powell and Diamond 2012, and the references therein). 3 These calculations give equal weight to each month of age, thereby standardizing for possible differences across samples in the age distributions of children. The t-statistics adjust for the possible correlation of errors at the level of communities or census tract in Colombia, Ecuador, Nicaragua, and Peru, and at the state level in Chile. 4 We thank an anonymous referee for pointing this out to us.5 In Peru, the TVIP was translated into Quechua, an indigenous language spoken primarily in rural areas of the highlands, and children were given the option of taking the test in Spanish or Quechua. Twenty-two percent of children in rural areas, but only 0.1 percent of children in urban areas, chose to take the test in Quechua. Because children in households that speak Quechua or another indigenous language may have more limited vocabularies in any given language, and because the likelihood of being a non-Spanish speaker is correlated with household wealth, we exclude children with mothers who report they speak a language other than Spanish in Peru (56 percent and 17 percent in rural and urban areas, respectively) and Ecuador (2 percent in both urban and rural areas). 6 The TVIP has been standardized by the test developers on samples ...

Research from the United States shows that gaps in early cognitive and non-cognitive ability appear early in the life cycle. Little is known about this important question for developing countries. This paper provides new evidence of sharp differences in cognitive development by socioeconomic status in early childhood for five Latin American countries. To help with comparability, we use the same measure of receptive language ability for all five countries. We find important differences in development in early childhood across countries, and steep socioeconomic gradients within every country. For the three countries where we can follow children over time, there are few substantive changes in scores once children enter school. Our results 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.

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