SURVEYING RARE GROUPS: SOME APPLICATIONS FROM RECENT RESEARCH

1. SURVEYING RARE GROUPS: SOME APPLICATIONS FROM RECENT RESEARCH David McKenzie DECRG-FP

2. Surveying Rare Groups With No Sample Frame available • Application 1: Surveying Brazilian-Japanese Households • Application 2: Surveying Male and Female Self-employed in Sri Lanka • Application 3: Surveying Rural-Urban Migrants in Ethiopia.

3. Considerations in Sampling Design • 2 Key Challenges with Constructing Probability Samples for the Study of Migration and Remittances: • Sampling frames for population sub-groups that migrate, send or receive remittances are generally non-existent so they must be constructed; and • These sub-groups are typically “Rare Elements” in the population and is often equivalent to finding a needle in a haystack.

4. Research: The Brazil Nikkei Household Survey • Test 3 Sampling Design Approaches: • Random Disproportionate Stratified Sampling • Snowball Sampling • Aggregation Point Intercept Sampling

5. Research: The Brazil Nikkei Household Survey • Random Disproportionate Stratified Sample • Census-based target clusters identified • Listing conducted in the PPS selected clusters • Households randomly PPS sampled from lists • F2F interviews by Nikkei enumerators • Stratified by geography, migrant status and generational characteristics • Will yield benchmark PS

6. Nikkei Target clusters in the State of Sao Paulo

7. Summary of listing • Listed 22, 539 dwellings • Among these, detected 839 Nikkei households – 528 interviewed in person, 311 by proxy-reporting • Initial phase of interviewing interviewed 247 Nikkei households • Returned and interviewed another 156 (45 long interview, 111 short interview)

8. Research: The Brazil Nikkei Household Survey • Snowball Sample (NPS) • 25 Nikkei Diaspora associations contacted to request “seed” households • 70 seed households identified via 20 Nikkei Diaspora associations • Exhaustive surveying of the referral-chain network identified via the seed households to minimize bias (Heckathorn, 1997, 2002)

9. Intercept point survey • Consulted with local researchers, Nikkei organizations, and Sudameris officers to select broad range of locations which Nikkei community frequents • Chose 9 fixed points, and 6 events • Sports club, metro station in Liberdade neighborhood, two Feiras (Sunday marketplaces), hospital, grocery stores, language school, outside branch of bank. • Japanese film event, large cultural festivals, Japanese food festival, Japanese art exposition, Christmas concert and music festival. • Short questionnaire – 62 questions, 7 minutes.

10. Intercept survey • At each location, 2 interviewers used, one to count number passing through location, one to interview • Interviewers there for 129 total hours over 2 weeks (~8.5 hours/location). • Each person asked how often in past 2 weeks had frequented any of the other locations – used to reweight answers. • Find females and older individuals visit more locations • Individuals more connected to Japan visit more locations – return migrants, 1st or 2nd generation, those who read Japanese newspapers.

11. Results: Connection to Japan

12. Comparison of costs • Total cost per household interviewed: • Stratified survey: US$212 ($2 per dwelling listed; $80 per interview) • Snowball survey: US$100 • Intercept survey: US$30 • Recall survey lengths differ: • Stratified and Snowball: 36-page questionnaire, 1 hour to complete • Intercept: 3-page questionnaire, 7 minutes to complete

13. Application 2: Surveying the Self-employed in Sri Lanka • In the field now • Want survey with 4 groups • Self-employed females • Self-employed males • Wage worker males • Wage worker females • Steps: • Randomly choose 200 GNs • Within each GN, start from 2 random starting points and list 70 households. Count number in each category above

14. Sri Lankan example: • Issue: some GNs (areas) have much higher incidence of self-employment than others – want sampling to reflect this. • Based on listing, set quotas, where sample UP TO quota per GN • E.g. Survey UP TO 10 households with self-employed males. • Get more of sample from areas where more self-employed work Alternative: have fixed quota per GN – but then have lots of your sample who are uncommon.

15. Ethiopia Example • Sampling rural-urban migrants • Adaptive sampling (with Macro international) • Begin with random survey (randomly selected starting point, fixed number of households to skip between selected households, and a ‘random’ walk methodology to guide the team) • Adaptive sampling kicks in when you identify individual of the target population.

16. Adaptive sampling The adaptive methodology only is implemented when contact is made with the target population. When a target household is encountered the team continues conducting surveys in both directions from the first and last household of incidence following the same skip pattern until they have encountered a number of sequential non-incidence households that is one less than the initial cluster size.

17. Example of adaptive sampling. • Example (initial cluster size = 4)

18. Adaptive sampling cont.. The probability of selection of the final cluster is then calculated by the number of initial clusters that could result in the final cluster. This is the final cluster size minus one less than the initial cluster size. In the case above there are 10 possible initial cluster that would bring the same result (13-(4-1)). Therefore, these incidence cases will be weighted to reflect that they are 10 times more likely to be selected than a randomly selected household.