Browsing by Autor "Rachid Laajaj"

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Factors Associated with SARS-CoV-2 Infection in Bogotá, Colombia: Results from a Large Epidemiological Surveillance Study
(RELX Group (Netherlands), 2021) Andrea Ramírez Varela; Luis Jorge Hernández Flórez; Guillermo Tamayo Cabeza; Sandra Contreras‐Arrieta; Silvia Restrepo; Rachid Laajaj; Giancarlo Buitrago; Paola Rueda‐Guevara; Yuldor Caballero Diaz; Martha J. Vives
Measuring Skills in Developing Countries
(2017) Rachid Laajaj; Karen Macours
Measures of cognitive, noncognitive, and technical skills are increasingly used in development economics to analyze the determinants of skill formation, the role of skills in economic decisions, or simply because they are potential confounders. 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 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. 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.
Measuring Skills in Developing Countries
(Johns Hopkins University, 2012) Rachid Laajaj; Karen Macours
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.
Measuring Skills in Developing Countries
(University of Wisconsin Press, 2019) Rachid Laajaj; Karen Macours
Measures of cognitive, noncognitive, and technical skills are increasingly used in surveys in developing countries, but have mostly been validated in high-income countries. We use a survey experiment in Western Kenya to test the reliability and validity of commonly used skills measures. Cognitive skills measures are found to be reliable and internally consistent, technical skills are very noisy, and measurement error in noncognitive skills is found to be nonclassical. Addressing both random and systematic measurement error using common psychometric practices and repeated measures leads to some improvements and clearer predictions, though concerns remain. These findings hold for a replication in Colombia.
Reconciling yield gains in agronomic trials with returns under African smallholder conditions
(Federal Reserve Bank of St. Louis, 2012) Rachid Laajaj; Karen Macours; Cargele Masso; Moses Thuita; Bernard Vanlauwe
Increased adoption of improved agricultural technologies is considered an essential step to address global poverty and hunger, and agronomic trials suggest intensification in developing countries could result in large yield gains. Yet the promise of new technologies does not always carry over from trials to real-life conditions, and diffusion of many technologies remains limited. We show how parcel and farmer selection, together with behavioural responses in agronomic trials, can explain why yield gain estimates from trials may differ from the yield gains of smallholders using the same inputs under real-life conditions. We provide quantitative evidence by exploiting variation in farmer selection and detailed data collection from research trials in Western Kenya on which large yield increments were observed from improved input packages for maize and soybean. After adjusting for selection, behavioural responses, and other corrections, estimates of yield gains fall to being not significantly different from zero for the input package tested on one of the crops (soybean), but remain high for the other (maize). These results suggest that testing new agricultural technologies in real-world conditions and without researcher interference early in the agricultural research and development process might help with identifying which innovations are more likely to be taken up at scale.