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  • 1
    Language: English
    Pages: 1 Online-Ressource (33 p)
    Series Statement: World Bank E-Library Archive
    Parallel Title: Erscheint auch als Himelein, Kristen Second-Stage Sampling for Conflict Areas: Methods and Implications
    Abstract: The collection of survey data from war zones or other unstable security situations is vulnerable to error because conflict often limits the implementation options. Although there are elevated risks throughout the process, this paper focuses specifically on challenges to frame construction and sample selection. The paper uses simulations based on data from the Mogadishu High Frequency Survey Pilot to examine the implications of the choice of second-stage selection methodology on bias and variance. Among the other findings, the simulations show the bias introduced by a random walk design leads to the underestimation of the poverty headcount by more than 10 percent. The paper also discusses the experience of the authors in the time required and technical complexity of the associated back-office preparation work and weight calculations for each method. Finally, as the simulations assume perfect implementation of the design, the paper also discusses practicality, including the ease of implementation and options for remote verification, and outlines areas for future research and pilot testing
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 2
    Language: English
    Pages: 1 Online-Ressource (26 p)
    Series Statement: World Bank E-Library Archive
    Parallel Title: Erscheint auch als Himelein, Kristen Interviewer Effects in Subjective Survey Questions
    Abstract: There is an inherent tension between traditional norms and survey protocols for quantitative data collected in the developing world. Unexpected interactions between the interviewer and respondent can lead to interviewer effects in the data, particularly in the case of subjective or sensitive questions. This paper makes use of a unique data set available from Timor-Leste containing subjective and objective questions to study these effects. In addition to their age and gender, data were collected from the interviewers regarding their opinions on the subjective questions prior to fieldwork. Fixed effects and mixed effects logit models are used to examine the main effects and interactions between interviewer and respondent characteristics. More objective measures serve as a pseudo control group. The paper finds interviewer effects in the both subjective and objective data, but the magnitude is considerably stronger for subjective questions. The paper also finds that female respondents are more susceptible to influence based on the interviewer's beliefs. Despite methodological shortcomings, the study highlights the need to consider more fully the impact of traditional cultural norms when conducting quantitative surveys in the developing world on topics that are outside the standard objective questions
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 3
    Language: English
    Pages: Online-Ressource (14 p)
    Edition: 2013 World Bank eLibrary
    Parallel Title: Himelein, Kristen Weight Calculations for Panel Surveys with Sub-Sampling and Split-Off Tracking
    Abstract: The Living Standards Measurement Study-Integrated Surveys on Agriculture project collects agricultural and livelihood data in seven countries in Sub-Saharan Africa. In order to maintain representativeness as much as possible over multiple rounds of data collection, a sub-sample of households are selected to have members that have left the household tracked and interviewed in their new location with their new household members. Since the sub-sampling occurs at the level of the household but tracking occurs at the level of the individual, a number of issues arise with the correct calculation for the sub-sampling and attrition corrections. This paper is based on the panel weight calculations for the initial rounds of the Integrated Surveys on Agriculture surveys in Uganda and Tanzania, and describes the methodology used for calculating the weight components related to sub-sampling, tracking, and attrition, as well as the criteria used for trimming and post-stratification. It also addresses complications resulting from members previously classified as having attrited from the sample returning in later rounds
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  • 4
    Language: English
    Pages: Online-Ressource (25 p)
    Edition: 2013 World Bank eLibrary
    Parallel Title: Himelein, Kristen The Use of Random Geographic Cluster Sampling to Survey Pastoralists
    Abstract: Livestock are an important component of rural livelihoods in developing countries, but data about this source of income and wealth are difficult to collect because of the nomadic and semi-nomadic nature of many pastoralist populations. Most household surveys exclude those without permanent dwellings, leading to undercoverage. This study explores the use of a random geographic cluster sample as an alternative to the household-based sample. In this design, points are randomly selected and all eligible respondents found inside circles drawn around the selected points are interviewed. This approach should eliminate undercoverage of mobile populations. The results of a random geographic cluster sample survey are presented with a total sample size of 784 households to measure livestock ownership in the Afar region of Ethiopia in 2012. The paper explores the data quality of the random geographic cluster sample relative to a recent household survey and discusses the implementation challenges
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  • 5
    Language: English
    Pages: Online-Ressource (29 p)
    Edition: 2011 World Bank eLibrary
    Parallel Title: Beegle, Kathleen Reliability of Recall in Agricultural Data
    Abstract: Despite the importance of agriculture to economic development, and a vast accompanying literature on the subject, little research has been done on the quality of the underlying data. Due to survey logistics, agricultural data are usually collected by asking respondents to recall the details of events occurring during past agricultural seasons that took place a number of months prior to the interview. This gap can lead to recall bias in reported data on agricultural activities. The problem is further complicated when interviews are conducted over the course of several months, thus leading to recall of variable length. To test for such recall bias, the length of time between harvest and interview is examined for three African countries with respect to several common agricultural input and harvest measures. The analysis shows little evidence of recall bias impacting data quality. There is some indication that more salient events are less subject to recall decay. Overall, the results allay some concerns about the quality of some types of agricultural data collected through recall over lengthy periods
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  • 6
    Online Resource
    Online Resource
    Washington, D.C : The World Bank
    Language: English
    Pages: 1 Online-Ressource (57 pages)
    Parallel Title: Erscheint auch als Print Version: Corral, Paul A Map of the Poor or a Poor Map?
    Abstract: This paper evaluates the performance of different small area estimation methods using model and design-based simulation experiments. Design-based simulation experiments are carried out using the Mexican Intra Censal survey as a census of roughly 3.9 million households from which 500 samples are drawn using a two-stage selection procedure similar to that of Living Standards Measurement Study surveys. Several unit-level methods are considered as well as a method that combines unit and area level information, which has been proposed as an alternative when the available census data is outdated. The findings show the importance of selecting a proper model and data transformation so that the model assumptions hold. A proper data transformation can lead to a considerable improvement in mean squared errors. The results from design-based validation show that all small area estimation methods represent an improvement, in terms of mean squared errors, over direct estimates. However, methods that model unit level welfare using only area level information suffer from considerable bias. Because the magnitude and direction of the bias are unknown ex ante, methods that rely only on aggregated covariates should be used with caution, but they may be an alternative to traditional area level models when these are not applicable
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  • 7
    Language: English
    Pages: Online-Ressource (27 p)
    Edition: 2014 World Bank eLibrary
    Parallel Title: Dabalen, Andrew Estimating Poverty in the Absence of Consumption Data
    Abstract: In much of the developing world, the demand for high frequency quality household data for poverty monitoring and program design far outstrips the capacity of the statistics bureau to provide such data. In these environments, all available data sources must be leveraged. Most surveys, however, do not collect the detailed consumption data necessary to construct aggregates and poverty lines to measure poverty directly. This paper benefits from a shared listing exercise for two large-scale national household surveys conducted in Liberia in 2007 to explore alternative methodologies to estimate poverty indirectly. The first is an asset-based model that is commonly used in Demographic and Health Surveys. The second is a survey-to-survey imputation that makes use of small area estimation techniques. In addition to a standard base model, separate models are estimated for urban and rural areas and an expanded model that includes climatic variables. Special attention is paid to the inclusion of cell phones, with implications for other assets whose cost and availability may be changing rapidly. The results demonstrate substantial limitations with asset-based indexes, but also leave questions as to the accuracy and stability of imputation models
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  • 8
    Language: English
    Pages: Online-Ressource
    Edition: 2009 World Bank eLibrary Also available in print
    Series Statement: Policy research working paper 4904
    Parallel Title: Beegle, Kathleen Frame-of-reference bias in subjective welfare regressions
    Keywords: Household surveys ; Household surveys
    Abstract: "Past research has found that subjective questions about an individuals' economic status do not correspond closely to measures of economic welfare based on household income or consumption. Survey respondents undoubtedly hold diverse ideas about what it means to be "poor" or "rich." Further, this heterogeneity may be correlated with other characteristics, including welfare, leading to frame-of-reference bias. To test for this bias, vignettes were added to a nationally representative survey of Tajikistan, in which survey respondents rank the economic status of the theoretical vignette households, as well as their own. The vignette rankings are used to reveal the respondent's own scale. The findings indicate that respondents hold diverse scales in assessing their welfare, but that there is little bias in either the economic gradient of subjective welfare or most other coefficients on covariates of interest. These results provide a firmer foundation for standard survey methods and regression specifications for subjective welfare data. "--World Bank web site
    Note: Includes bibliographical references , Title from PDF file as viewed on 5/7/2009 , Also available in print.
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  • 9
    Language: English
    Pages: 1 Online-Ressource (34 pages)
    Parallel Title: Erscheint auch als Himelein, Kristen Implications of Choice of Second Stage Selection Method on Sampling Error and Non-Sampling Error: Evidence from an IDP Camp in South Sudan
    Keywords: Cross-Sectional Household Survey ; Displacement ; Economic Theory and Research ; Estimation ; Household Survey Design ; Macroeconomics and Economic Growth ; Microeconomic Data ; Poverty Reduction ; Social Development ; Survey and Sampling Methods ; Voluntary and Involuntary Resettlement
    Abstract: The most common sampling approach for cross-sectional household surveys in the developing world is a stratified two-stage design, where the first stage is usually a sample from a census-based area frame, and the second stage is a random sample of households from each of the areas selected in the first stage. To overcome the problem of outdated census frame information, it is common to conduct a household listing operation within these areas. However, these listing operations come with severe implications for survey costs, timeframe, as well as quality. To avoid such second-stage operations, some surveys choose alternate approaches for their second-stage operation. This paper compares five of these approaches, namely, satellite mapping, segmentation, grid square, the north method, and random walk, through simulations based on a census conducted in a refugee camp in South Sudan. The paper compares the simulated approach with the estimates derived from the actual experiment and finds that all the resulting estimates are biased. Nevertheless, in addition to their practical challenges, the satellite mapping, segmentation, and grid square approaches exhibit the smallest bias. Although random walk shows the worst performance in the simulations, it regains ground in its implementation, especially vis-a-vis the north method, where implementation adds most significantly to its bias. In conclusion, most probability-based methods perform better than non-probability methods like random walk and are therefore preferrable when no traditional household listing can take place. Although it is important to consider the theoretical properties of sampling approaches, implementation is at least as important. Training, implementation modalities, and monitoring of compliance are key factors in the overall performance
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  • 10
    Language: English
    Pages: 1 Online-Ressource (circa 27 Seiten) , Illustrationen
    Series Statement: Policy research working paper 8972
    Series Statement: World Bank E-Library Archive
    Series Statement: Policy research working paper
    Parallel Title: Erscheint auch als Qader, Sarchil A Novel Approach to the Automatic Designation of Predefined Census Enumeration Areas and Population Sampling Frames: A Case Study in Somalia
    Keywords: Graue Literatur
    Abstract: Enumeration areas are the operational geographic units for the collection, dissemination, and analysis of census data and are often used as a national sampling frame for various types of surveys. Traditionally, enumeration areas are created by manually digitizing small geographic units on high-resolution satellite imagery or physically walking the boundaries of units, both of which are highly time, cost, and labor intensive. In addition, creating enumeration areas requires considering the size of the population and area within each unit. This is an optimization problem that can best be solved by a computer. This paper, for the first time, produces an automatic designation of predefined census enumeration areas based on high-resolution gridded population and settlement data sets and using publicly available natural and administrative boundaries. This automated approach is compared with manually digitized enumeration areas that were created in urban areas in Mogadishu and Hargeisa for the United Nations Population Estimation Survey for Somalia in 2014. The automatically generated enumeration areas are consistent with standard enumeration areas, including having identifiable boundaries to field teams on the ground, and appropriate sizing and population for coverage by an enumerator. Furthermore, the automated urban enumeration areas have no gaps. The paper extends this work to rural Somalia, for which no records exist of previous enumeration area demarcations. This work shows the time, labor, and cost-saving value of automated enumeration area delineation and points to the potential for broadly available tools that are suitable for low-income and data-poor settings but applicable to potentially wider contexts
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