Suchergebnisse

When policymakers design programs and policies, they often want to understand why individuals engage in particular behaviors. Collecting survey data about respondents' reasons for their behavior presents important challenges, and there is little methodological research on this topic. We conducted an experiment to investigate the best practices for asking questions about respondents' reasons for their behavior. We embedded a split ballot experiment in a face-to-face survey of 608 entrepreneurs in Ethiopia. Respondents were asked questions about why they did not engage in three business practices (advertising, sharing product storage, and switching suppliers). When asked these questions, respondents were randomly assigned to one of three conditions: close-ended questions, open-ended questions with interviewer probing, and open-ended questions without probing. Respondents endorsed more responses when asked close-ended (versus open-ended) questions. Close-ended responses produced higher rates of socially undesirable responses and fewer "other" responses. Notably, probing had no effect on the number or types of responses given. Our results suggest some best practices for asking respondents questions about reasons for their behavior.

Mobile phone surveys are increasingly prevalent in low- and middle-income countries. The main modes include computer-assisted telephone interviewing (CATI), interactive voice response (IVR), and short message service (SMS, or text messaging). But there is surprisingly little research to guide researchers in selecting the optimal mode for a particular survey. To address this gap, this study compares cross-sectional CATI, IVR, SMS, and face-to-face (FTF) surveys of the general population in Nigeria. We ask four research questions: (1) What are production and response rates to CATI, IVR, SMS, and FTF surveys? (2) How representative (age, gender, education, marital status, literacy, household assets, urbanicity) are CATI, IVR, and SMS respondents relative to FTF respondents? (3) Can IVR and SMS provide an unbiased estimate of voting behavior? If there is bias, to what extent can weights reduce bias? (4) How does the cost and time differ across mobile phone survey modes? We find that FTF had the highest response rate (99%), followed by CATI (15%), IVR (3%) and SMS (0.2%). All mobile phone modes had substantial deficiencies with representativeness: mobile phones underrepresented women, older people, the less educated, and people in rural areas. There were differences in representativeness among mobile phone modes, but differences were relatively small and inconsistent. Both SMS and IVR produced biased estimates of voting relative to official statistics – but SMS was less biased than IVR. Weighting SMS and IVR data for demographic characteristics did not reduce bias. With regard to cost, we find that CATI is the most expensive mobile phone survey mode. For a survey of 3,000 completes, IVR is 43% the cost of CATI, and SMS is 24% the cost of CATI. SMS is significantly less expensive than IVR. We discuss the implications of these results for research and practice.

AbstractAlumni tracking surveys are critical for evaluating and improving youth employment training programmes. However, there is little evidence about how to design these surveys, especially in less developed countries. We conducted short message service and Web surveys of alumni of a South African employment training programme. Short message service surveys returned higher response rates and more representative data than Web surveys, albeit at three times the cost. Combining modes increased data quality but may not be warranted, given the additional cost and complexity. This evidence suggests that training programmes can feasibly collect quality, actionable data on their alumni, even with constrained budgets and staff. Copyright © 2018 John Wiley & Sons, Ltd.

Abstract
Our research evaluates an innovative sampling technique for household surveys called "geosampling" which leverages recent advances in geographic information systems, computer vision algorithms, and satellite imagery. We compare geosampling to the random walk method. We conducted two surveys in Uttar Pradesh, India: one using geosampling (1,026 completes) and another using random walk (939 completes). We compare the two sampling techniques along three dimensions: (a) performance indicators—response rates and contact attempts; (b) sample composition; and (c) components of variance. We help researchers understand the survey contexts for which geosampling and random walk are best suited.