There is a wide variety of existing questions, tests or modules to measure such skills. Many instruments have been designed to assess skills in lab conditions, and some standardized instruments have been developed for inclusion in surveys in developed country settings. Increasingly, economists are also trying to include various measures of abilities and personality traits in household surveys conducted in developing countries. But little validation of such instruments has occurred for such contexts.<sup>3</sup> Many questions can be raised about the applicability of some of the existing scales for poor rural populations, given the high level of abstraction of many questions, low levels of education in the respondent population, difficulties of standardization for enumerator-administered tests conducted in the field, and translation challenges.<sup>4</sup> This study aims to test the reliability and validity of several commonly used scales and tests, and highlights both random and systematic measurement error that needs to be accounted for when measuring skills in developing-country field conditions. We do so by analyzing the test-retest reliability and the Cronbach’s alpha to estimate internal consistency of various existing scales. We subsequently use exploratory factor analysis, correction for acquiescence bias, and item response theory (IRT) to reduce some of the observed measurement error, and analyze validity and reliability of the improved constructs.<sup>5</sup> We then study the predictive validity of both the original scales and the improved constructs and analyze the extent to which the skills measured predict agricultural productivity and economic decisions related to the adoption of advanced agricultural practices.<sup>6</sup> This tests the potential role played by these skills in agricultural production, and shows that they might be important omitted variables when not included in the analysis of agricultural decision-making. More generally, understanding the role of skills in agricultural decisions can be key to inform policy interventions that directly aim to improve skills, or the success of which could be conditional on the skills of the target population.

Almund et al. (2011) suggests that different skills and personality traits might help predict different outcomes, with cognitive ability being more important for complex tasks, while

> 3 Measures of risk aversion and time preferences, which have a longer history of use in developing country surveys, have received more scrutiny.

> 4 While there is a literature in psychology regarding the validity of scales across cultures (Benet-Martinez and John, 1998; John, Naumann, and Soto, 2008), these studies typically focus on highly-educated populations in different countries, and often are limited to high or middle income settings.

> 5 While explanatory factor analysis is used elsewhere in the economics literature on skills (Cunha and Heckman, 2010; Heckman, Stixrud and Urzua, 2006), we also build on insights from the psychometrics literature, such as for the corrections for acquiescence bias.

> 6 Following McKenzie (2012), in order to reduce the noise in the outcome variables, the measures of yield and practices are obtained from the average over the four seasons that followed the collection of skills data.

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