Measuring Skills in Developing Countries

Working Paper: CEPR ID: DP13271

Authors: Rachid Laajaj; Karen Macours

Abstract: Measures of cognitive, noncognitive, and technical skills are increasingly used to analyze the determinants of skill formation or the role of skills in economic decisions in developing and developed countries. Yet in most cases, these measures have only been validated in high-income countries. This paper tests the reliability and validity of some of the most commonly used skills measures in a rural developing context. A survey experiment with a series of skills measurements was administered to more than 900 farmers in western Kenya, and the same questions were asked again after three weeks to test the reliability of the measures. To test predictive power, the study also collected information on agricultural practices and production during the four following seasons. The results show the cognitive skills measures are reliable and internally consistent, while technical skills are difficult to capture and very noisy. The evidence further suggests that measurement error in noncognitive skills is non-classical, as correlations between questions are driven in part by the answering patterns of the respondents and the phrasing of the questions. Addressing both random and systematic measurement error using common psychometric practices and repeated measures leads to improvements and clearer predictions, but does not address all concerns. We replicate the main parts of the analysis for farmers in Colombia, and obtain similar results. The paper provides a cautionary tale for naïve interpretations of skill measures. It also points to the importance of addressing measurement challenges to establish the relationship of different skills with economic outcomes. Based on these findings, the paper derives guidelines for skill measurement and interpretation in similar contexts.

Keywords: skills measurement; agricultural productivity

JEL Codes: O12; O13; O15


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
Cognitive skills measures (G53)Agricultural productivity (Q11)
Technical skills (J24)Agricultural productivity (Q11)
Noncognitive skills (G53)Agricultural productivity (Q11)
Cognitive skills (G53)Maize yield (Q11)
Cognitive skills (G53)Agricultural outcomes (Q11)
Agricultural outcomes (Q11)Skills formation (J24)
Observable characteristics of farmers (Q12)Skills (J24)

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