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329 records from EconBiz based on author Name
1. Assessing Uganda's progressive refugee policy in the era of COVID-19 : introduction to the special issue
D'Errico, Marco; Winters, Paul; Romano, Donato;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
2. Economic integration between refugee settlements and host communities
Oliver, Lauren; D'Errico, Marco; Winters, Paul;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
3. Transfers as a means to mitigate COVID-19 impacts on food security : evidence from refugee and host communities Uganda
D'Errico, Marco; Jumbe, Ellestina; Oliver, Lauren; Pietrelli, Rebecca; Staffieri, Irene; Winters, Paul;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
4. How close is close? : assessing Uganda’s progressive refugee policy in the era of COVID-19 : special issue
D'Errico, Marco; Winters, Paul; Romano, Donato; Oliver, Lauren; Malevolti, Giulia; Mastrorillo, Marina; Scognamillo, Antonio; Ignaciuk, Adriana M.; Jumbe, Ellestina; Pietrelli, Rebecca; Staffieri, Irene; Squarcina, Margherita;2024
Type: Aufsatzsammlung; Beiträge
Availability: Link
5. Digital Training for Micro-Entrepreneurs
abstractPrevious literature shows minor impacts of in-person business training in developing countries, but few papers study the effectiveness of digital training. A research partnership with a multinational company operating in the food sector of Guatemala enables the randomized evaluation of a digital training program involving the franchise store owners of one of its retail chains. The training program combined a mobile app offering access to reproducible video capsules and virtual one-on-one consulting meetings. The results of the randomized evaluation reveal significant impacts on knowledge, business practices, sales, and profits. An examination of the mechanisms underlying these results reveals that consulting meetings are crucial in inducing engagement with the app's content. Program flexibility, internet access, and initial sales are also crucial determinants of training effectiveness
Estefan, Alejandro; Improta, Martina; Ordoñez, Romina; Winters, Paul;2023
Availability: Link
6. Decomposing the impacts of an agricultural value chain development project by ethnicity and gender in Nepal
Songsermsawas, Tisorn; Kafle, Kashi; Winters, Paul;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
7. Explaining Gender Differentials in Agricultural Production in Nigeria
abstractThis paper uses data from the General Household Survey Panel 2010/11 to analyze differences in agricultural productivity across male and female plot managers in Nigeria. The analysis utilizes the Oaxaca-Blinder decomposition method, which allows for decomposing the unconditional gender gap into (i) the portion caused by observable differences in the factors of production (endowment effect) and (ii) the unexplained portion caused by differences in returns to the same observed factors of production (structural effect). The analysis is conducted separately for the North and South regions, excluding the west of the country. The findings show that in the North, women produce 28 percent less than men after controlling for observed factors of production, while there are no significant gender differences in the South. In the decomposition results, the structural effect in the North is larger than the endowment at the mean. Although women in the North have access to less productive resources than men, the results indicate that even if given the same level of inputs, significant differences still emerge. However for the South, the decomposition results show that the endowment effect is more important than the structural effect. Access to resources explains most of the gender gap in the South and if women are given the same level of inputs as men, the gap will be minimal. The difference in the results for the North and South suggests that policy should vary by region
Oseni, Gbemisola; Corral, Paul; Goldstein, Markus P.; Winters, Paul; Corral Rodas, Paul Andres; Siwatu, Gbemisola Oseni; Winters, Paul;2020
Availability: Link
8. Decentralized Beneficiary Targeting in Large-Scale Development Programs : Insights from the Malawi Farm Input Subsidy Program
abstractThis paper contributes to the long-standing debate on the merits of decentralized beneficiary targeting in the administration of development programs, focusing on the large-scale Malawi Farm Input Subsidy Program. Nationally-representative household survey data are used to systematically analyze the decentralized targeting performance of the program during the 2009-2010 agricultural season. The analysis begins with a standard targeting assessment based on the rates of program participation and the benefit amounts among the eligible and non-eligible populations, and provides decompositions of the national targeting performance into the inter-district, intra-district inter-community, and intra-district intra-community components. This approach identifies the relative contributions of targeting at each level. The results show that the Farm Input Subsidy Program is not poverty targeted and that the national government, districts, and communities are nearly uniform in their failure to target the poor, with any minimal targeting (or mis-targeting) overwhelmingly materializing at the community level. The findings are robust to the choice of the eligibility indicator and the decomposition method. The multivariate analysis of household program participation reinforces these results and reveals that the relatively well-off, rather than the poor or the wealthiest, and the locally well-connected have a higher likelihood of program participation and, on average, receive a greater number of input coupons. Since a key program objective is to increase food security and income among resource-poor farmers, the lack of targeting is a concern and should underlie considerations of alternative targeting approaches that, in part or completely, rely on proxy means tests at the local level
Kilic, Talip; Whitney, Edward; Winters, Paul; Whitney, Edward Matthew; Winters, Paul;2020
Availability: Link
9. From Guesstimates to Gpstimates : Land Area Measurement and Implications for Agricultural Analysis
abstractLand area measurement is a fundamental component of agricultural statistics and analysis. Yet, commonly employed self-reported land area measures used in most analysis are not only potentially measured with error, but these errors may be correlated with agricultural outcomes. Measures employing Global Positioning Systems, on the other hand, while not perfect especially on smaller plots, are likely to provide more precise measures and errors less correlated with agricultural outcomes. This paper uses data from four African countries to compare the use of self-reported and Global Positioning Systems land measures to (1) examine the differences between the measures, (2) identify the sources of the differences, and (3) assess the implications of the different measures on agricultural analysis focusing on the inverse productivity relationship. The results indicate that self-reported land areas systematically differ from Global Positioning Systems land measures and that this difference leads to potentially biased estimates of the relationship between land and productivity
Carletto, Calogero; Gourlay, Sydney; Winters, Paul; Carletto, Calogero; Winters, Paul;2020
Availability: Link
10. Poverty Prediction and Targeting Over Time and Space : Evidence from Nigeria
abstractUnderstanding poverty dynamics is crucial to target and tailor economic policies in developing countries like Nigeria – a country at the risk of hosting about a quarter of all people living in poverty worldwide. To facilitate the targeting of poverty-reducing interventions, we build a nationally representative panel dataset with more than a hundred covariates and apply econometric and machine learning tools to predict and examine factors associated with static, transient, and persistent poverty status of Nigerian households. Results show that demographic, asset holdings, access to infrastructure, and housing indicators can predict poverty accurately in 80% of cases
Hossain, Marup; Jäckering, Lisa; Mullally, Conner; Winters, Paul;2022
Availability: Link Link