Can personality traits be measured and interpreted reliably across the world? While the use of Big Five personality measures is increasingly common across social sciences, their validity outside of western, educated, industrialized, rich, and democratic (WEIRD) populations is unclear. Adopting a comprehensive psychometric approach to analyze 29 face-to-face surveys from 94,751 respondents in 23 low- and middle-income countries, we show that commonly used personality questions generally fail to measure the intended personality traits and show low validity. These findings contrast with the much higher validity of these measures attained in internet surveys of 198,356 self-selected respondents from the same countries. We discuss how systematic response patterns, enumerator interactions, and low education levels can collectively distort personality measures when assessed in large-scale surveys. Our results highlight the risk of misinterpreting Big Five survey data and provide a warning against naïve interpretations of personality traits without evidence of their validity.

We report the results of a randomized experiment testing impacts of subsidies for modern agricultural inputs in rural Mozambique. One-time provision of a voucher for fertilizer and improved seeds leads to substantial increases in fertilizer use, which persist through two subsequent agricultural seasons. Voucher receipt also leads to large, persistent increases in household agricultural production and market sales, per capita consumption, assets, durable good ownership, and housing improvements. Consistent with learning models of the adoption decision, we find positive treatment effects on farmers' estimated returns to the input package. We also document positive cross-household treatment spillovers: one's own fertilizer use rises in the number of social network members receiving vouchers. Our findings are consistent with theoretical models predicting persistence of impacts of temporary technology adoption subsidies, in particular due to learning effects.

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Measures of cognitive, noncognitive, and technical skills are increasingly used in developing country surveys, 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 non-classical. 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. JEL codes: O12, O13, O15The data and programs for full replication are available online at https://www.laajaj.com/research 1 Jack Pfeiffer provided invaluable research assistance and programming skills, field support, tenacity and ideas throughout the project and we gratefully acknowledge all his contributions to this project. provided excellent research assistance. Data collection was organized through IPA Kenya and S.E.I. in Colombia and we acknowledge the excellent field teams for key contributions during piloting and translation and for all efforts during the data collection. We are indebted to Chris Soto for many suggestions and insights from the psychometric literature. This open access article is distributed under the terms of the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0) and is freely available online at: http://jhr.uwpress.org 2 Hence we broadly follow the distinction of Heckman and Kautz (2012) who distinguish between cognitive abilities, personality traits, and other acquired skills. Jones and Kondylis (2018) is a recent example using a measure of acquired agricultural skills, in which measurement error is being discussed as potential reason for lack of impact. 3 Measures of risk aversion and time preferences, which have a longer history of use in developing country surveys, have received more scrutiny. Chuang and Schechter (2015) review the evidence, including their stability over time. 4 While explanatory factor analysis is used elsewhere in the economics literature on skills Heckman, Stixrud and Urzua, 2006), we also build on insights from the psychometrics literature, such as for the corrections for acquiescence bias (the tendency to agree even when statements are contradictory, or "yea-saying"). 5 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.

Short-Term Logic and Limitations of Voucher Coupons In the 1970s and early 1980s, a majority of African countries subsidized and sold fertilizer

Background Epidemiologic surveillance of COVID-19 is essential to collect and analyse data to improve public health decision making during the pandemic. There are few initiatives led by public-private alliances in Colombia and Latin America. The CoVIDA project contributed with RT-PCR tests for SARS-CoV-2 in mild or asymptomatic populations in Bogotá. The present study aimed to determine the factors associated with SARS-CoV-2 infection in working adults. Methods COVID-19 intensified sentinel epidemiological surveillance study, from April 18, 2020, to March 29, 2021. The study included people aged 18 years or older without a history of COVID-19. Two main occupational groups were included: healthcare and essential services workers with high mobility in the city. Social, demographic, and health-related factors were collected via phone survey. Afterwards, the molecular test was conducted to detect SARS-CoV-2 infection. Findings From the 58,638 participants included in the study, 3,310 (5·6%) had a positive result. A positive result was associated with the age group (18-29 years) compared with participants aged 60 or older, participants living with more than three cohabitants, living with a confirmed case, having no affiliation to the health system compared to those with social health security, reporting a very low socioeconomic status compared to those with higher socioeconomic status, and having essential occupations compared to healthcare workers. Interpretation The CoVIDA study showed the importance of intensified epidemiological surveillance to identify groups with increased risk of infection. These groups should be prioritised in the screening, contact tracing, and vaccination strategies to mitigate the pandemic.

Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mechanisms best explain the disproportionate impact of the virus on the poor. Combining an epidemiological model with rich data from Bogotá, Colombia, we show that total infections and inequalities in infections are largely driven by inequalities in the ability to work remotely and in within-home secondary attack rates. Inequalities in isolation behavior are less important but non-negligible, while access to testing and contract-tracing plays practically no role because it is too slow to contain the virus. Interventions that mitigate transmission are often more effective when targeted on socioeconomically disadvantaged groups.