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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.

Gender & Law --- Housing & Human Habitats --- Interviewer Effects --- Justice Surveys --- Labor Policies --- Science Education --- Scientific Research & Science Parks --- Subjective Data --- Survey Methodology --- Timor-Leste

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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.

Attrition --- Housing & Human Habitats --- Panel surveys --- Poverty Reduction --- Science Education --- Scientific Research & Science Parks --- Small Area Estimation Poverty Mapping --- Statistical & Mathematical Sciences --- Survey weights --- Tracking surveys

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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.

Agriculture --- Crops & Crop Management Systems --- Educational Sciences --- Measurement Error --- Poverty Reduction --- Recall --- Regional Economic Development --- Rural Development Knowledge & Information Systems --- Rural Poverty Reduction

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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.

Livestock.

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While self-assessments of welfare have become popular for measuring poverty and estimating welfare effects, the methods can be deceptive given systematic heterogeneity in respondents' scales. Little is known about this problem. This study uses specially-designed surveys in three countries, Tajikistan, Guatemala, and Tanzania, to study scale heterogeneity. Respondents were asked to score stylized vignettes, as well as their own household. Diverse scales are in evidence, casting considerable doubt on the meaning of widely-used summary measures such as subjective poverty rates. Nonetheless, under the identifying assumptions of the study, only small biases are induced in the coefficients on widely-used regressors for subjective poverty and welfare.

Biodiversity --- Economic Theory & Research --- Environment --- Heterogeneity --- Macroeconomics and Economic Growth --- Poverty Lines --- Poverty Reduction --- Rural Poverty Reduction --- Scales --- Subjective Poverty --- Subjective Welfare --- Vignettes