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  • 1
    Online Resource
    Online Resource
    Non-Traditional Crops, Traditional Constraints : Long-Term Welfare Impacts of Export Crop Adoption Among Guatemalan Smallholders (2009)
    Washington, D.C : The World Bank
    Details
    Language: English
    Pages: Online-Ressource (27 p)
    Edition: 2009 World Bank eLibrary
    Parallel Title: Carletto, Calogero Non-Traditional Crops, Traditional Constraints
    Abstract: This study documents the long-term welfare effects of household non-traditional agricultural export (NTX) adoption. The analysis uses a unique panel dataset, which spans the period 1985-2005, and employs difference-in-differences estimation to investigate the long-term impact of non-traditional agricultural export adoption on changes in household consumption status and asset position in the Central Highlands of Guatemala. Given the heterogeneity in adoption patterns, the analysis differentiates the impact estimates based on a classification of households that takes into account the timing and duration of non-traditional agricultural export adoption. The results show that while, on average, welfare levels have improved for all households irrespective of adoption status and duration, the extent of improvement has varied across groups. Long-term adopters exhibit the smallest increase in the lapse of two decades, in spite of some early gains. Conversely, early adopters who withdrew from non-traditional agricultural export production after reaping the benefits of the boom period of the 1980s are found to have fared better and shown greater improvements in durable asset position and housing conditions than any other category
    DOI: 10.1596/1813-9450-5142
    URL: Volltext  (Deutschlandweit zugänglich)
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    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Poverty Imputation in Contexts without Consumption Data : A Revisit with Further Refinements (2021)
    Washington, D.C : The World Bank
    Details
    Language: English
    Pages: 1 Online-Ressource (123 pages)
    Parallel Title: Erscheint auch als Print Version: Dang, Hai-Anh H Poverty Imputation in Contexts without Consumption Data: A Revisit with Further Refinements
    Keywords: Asset Wealth ; Demographic and Health Survey ; Educational Achievement ; Employment ; Household Survey ; Inequality ; Living Standards ; Poverty Lines ; Poverty Measurement ; Poverty Reduction ; Survey-To-Survey Imputation
    Abstract: A key challenge with poverty measurement is that household consumption data are often unavailable or infrequently collected or may be incomparable over time. In a development project setting, it is seldom feasible to collect full consumption data for estimating the poverty impacts. While survey-to-survey imputation is a cost-effective approach to address these gaps, its effective use calls for a combination of both ex-ante design choices and ex-post modeling efforts that are anchored in validated protocols. This paper refines various aspects of existing poverty imputation models using 14 multi-topic household surveys conducted over the past decade in Ethiopia, Malawi, Nigeria, Tanzania, and Vietnam. The analysis reveals that including an additional predictor that captures household utility consumption expenditures-as part of a basic imputation model with household-level demographic and employment variables-provides poverty estimates that are not statistically significantly different from the true poverty rates. In many cases, these estimates even fall within one standard error of the true poverty rates. Adding geospatial variables to the imputation model improves imputation accuracy on a cross-country basis. Bringing in additional community-level predictors (available from survey and census data in Vietnam) related to educational achievement, poverty, and asset wealth can further enhance accuracy. Yet, there is within-country spatial heterogeneity in model performance, with certain models performing well for either urban areas or rural areas only. The paper provides operationally-relevant and cost-saving inputs into the design of future surveys implemented with a poverty imputation objective and suggests directions for future research
    DOI: 10.1596/1813-9450-9838
    URL: Deutschlandweit zugänglich
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    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Mission Impossible? Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys (2017)
    Washington, D.C : The World Bank
    Details
    Language: English
    Pages: 1 Online-Ressource (23 p)
    Series Statement: World Bank E-Library Archive
    Parallel Title: Erscheint auch als Kilic, Talip Mission Impossible? Exploring the Promise of Multiple Imputation for Predicting Missing GPS-Based Land Area Measures in Household Surveys
    Abstract: Research has provided robust evidence for the use of GPS technology to be the scalable gold standard in land area measurement in household surveys. Nonetheless, facing budget constraints, survey agencies often seek to measure with GPS only plots within a given radius of dwelling locations. Subsequently, it is common for significant shares of plots not to be measured, and research has highlighted the selection biases resulting from using incomplete data. This study relies on nationally-representative, multi-topic household survey data from Malawi and Ethiopia that exhibit near-negligible missingness in GPS-based plot areas, and validates the accuracy of a multiple imputation model for predicting missing GPS-based plot areas in household surveys. The analysis (i) randomly creates missingness among plots beyond two operationally relevant distance measures from the dwelling locations; (ii) conducts multiple imputation under each distance scenario for each artificially created data set; and (iii) compares the distributions of the imputed plot-level outcomes, namely, area and agricultural productivity, with the known distributions. In Malawi, multiple imputation can produce imputed yields that are statistically undistinguishable from the true distributions with up to 82 percent missingness in plot areas that are further than 1 kilometer from the dwelling location. The comparable figure in Ethiopia is 56 percent. These rates correspond to overall rates of missingness of 23 percent in Malawi and 13 percent in Ethiopia. The study highlights the promise of multiple imputation for reliably predicting missing GPS-based plot areas, and provides recommendations for optimizing fieldwork activities to capture the minimum required data
    DOI: 10.1596/1813-9450-8138
    URL: Volltext  (Deutschlandweit zugänglich)
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    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Moving up the ladder? : the impact of migration experience on occupational mobility in Albania (2009)
    [Washington, D.C] : World Bank
    Details
    Language: English
    Pages: Online-Ressource
    Edition: 2009 World Bank eLibrary Also available in print
    Series Statement: Policy research working paper 4908
    Parallel Title: Carletto, Calogero Moving up the ladder?
    Keywords: Occupational mobility ; Return migration ; Occupational mobility ; Return migration
    Abstract: "The contribution of return migrants to economic development in source countries can be significant. Overseas savings of returnees may lead to improvements in household welfare and provide liquidity for investments in the face of credit market failures. Labor market experience and skills acquired abroad may also lead migrants to find occupations higher in the skill and remuneration spectrum upon return. This study uses the 2005 Albanian Living Standards Measurement Study Survey and estimates the impact of international migration experience on the occupational mobility of return migrants vis a vis working-age Albanian residents that never migrated. Controlling for the non-random nature of international migration and return, the results show that past migration experience increases the likelihood of upward occupational mobility. Exploring the heterogeneity of impact by host country indicates that the positive effect of past migration experience on upward occupational mobility is driven by past migration experience in Italy and countries further a field, while past migration experience in Greece does not exert any significant impact on mobility outcomes. The results, which are consistent across different sample specifications and outcome variables measuring occupational mobility, hint at the link between migration and human/financial capital formation among migrants and foster optimism concerning the positive effect of return migration on economic development. This insight is particularly important since remittances from permanent migrants, which have fueled the impressive growth performance of the country in the recent era, may taper off in the medium to long term with the decline in out-migration and growing global economic woes. "--World Bank web site
    Note: Includes bibliographical references , Title from PDF file as viewed on 5/7/2009 , Also available in print.
    DOI: 10.1596/1813-9450-4908
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 5
    Online Resource
    Online Resource
    Missing(ness) in Action : Selectivity Bias in GPS-Based Land Area Measurements (2013)
    Washington, D.C : The World Bank
    Details
    Language: English
    Pages: Online-Ressource (31 p)
    Edition: 2013 World Bank eLibrary
    Parallel Title: Kilic, Talip Missing(ness) in Action
    Abstract: Land area is a fundamental component of agricultural statistics, and of analyses undertaken by agricultural economists. While household surveys in developing countries have traditionally relied on farmers' own, potentially error-prone, land area assessments, the availability of affordable and reliable Global Positioning System (GPS) units has made GPS-based area measurement a practical alternative. Nonetheless, in an attempt to reduce costs, keep interview durations within reasonable limits, and avoid the difficulty of asking respondents to accompany interviewers to distant plots, survey implementing agencies typically require interviewers to record GPS-based area measurements only for plots within a given radius of dwelling locations. It is, therefore, common for as much as a third of the sample plots not to be measured, and research has not shed light on the possible selection bias in analyses relying on partial data due to gaps in GPS-based area measures. This paper explores the patterns of missingness in GPS-based plot areas, and investigates their implications for land productivity estimates and the inverse scale-land productivity relationship. Using Multiple Imputation (MI) to predict missing GPS-based plot areas in nationally-representative survey data from Uganda and Tanzania, the paper highlights the potential of MI in reliably simulating the missing data, and confirms the existence of an inverse scale-land productivity relationship, which is strengthened by using the complete, multiply-imputed dataset. The study demonstrates the usefulness of judiciously reconstructed GPS-based areas in alleviating concerns over potential measurement error in farmer-reported areas, and with regards to systematic bias in plot selection for GPS-based area measurement
    DOI: 10.1596/1813-9450-6490
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 6
    Online Resource
    Online Resource
    Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost : Evidence from a Randomized Survey Experiment (2024)
    Washington, D.C : The World Bank
    Details
    Language: English
    Pages: 1 Online-Ressource (78 pages)
    Parallel Title: Erscheint auch als Dang, Hai-Anh Using Survey-to-Survey Imputation to Fill Poverty Data Gaps at a Low Cost: Evidence from a Randomized Survey Experiment
    Keywords: Consumption ; Household Surveys ; Information and Communication Technologies ; Macroeconomics and Economic Growth ; Poverty ; Poverty Diagnostics ; Poverty Reduction ; Survey-To-Survey Imputation
    Abstract: Survey data on household consumption are often unavailable or incomparable over time in many low- and middle-income countries. Based on a unique randomized survey experiment implemented in Tanzania, this study offers new and rigorous evidence demonstrating that survey-to-survey imputation can fill consumption data gaps and provide low-cost and reliable poverty estimates. Basic imputation models featuring utility expenditures, together with a modest set of predictors on demographics, employment, household assets, and housing, yield accurate predictions. Imputation accuracy is robust to varying the survey questionnaire length, the choice of base surveys for estimating the imputation model, different poverty lines, and alternative (quarterly or monthly) Consumer Price Index deflators. The proposed approach to imputation also performs better than multiple imputation and a range of machine learning techniques. In the case of a target survey with modified (shortened or aggregated) food or non-food consumption modules, imputation models including food or non-food consumption as predictors do well only if the distributions of the predictors are standardized vis-a-vis the base survey. For the best-performing models to reach acceptable levels of accuracy, the minimum required sample size should be 1,000 for both the base and target surveys. The discussion expands on the implications of the findings for the design of future surveys
    DOI: 10.1596/1813-9450-10738
    URL: Deutschlandweit zugänglich
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