Long-Term Impacts of Migration Survey 2013-14
New Zealand, Tonga, 2013 - 2014
Get Microdata
Reference ID
WLD_2013_LTIMS_v01_M
Producer(s)
David McKenzie
Collection(s)
Metadata
Created on
May 29, 2018
Last modified
May 24, 2021
Page views
74100
Downloads
1573
Identification
Survey ID Number
WLD_2013_LTIMS_v01_M
Title
Long-Term Impacts of Migration Survey 2013-14
Country/Economy
| Name | Country code |
|---|---|
| New Zealand | NZL |
| Tonga | TON |
Study type
Other Household Survey
Abstract
These data consist of a long-term follow-up of applicants to a migration visa lottery. Tongan households were surveyed as migrants in New Zealand, or non-migrants in Tonga. It was used to examine the long-term impacts of international migration by comparing immigrants who had successful ballot entries in a migration lottery program, and first moved almost a decade ago, with people who had unsuccessful entries into those same ballots. It was additionally used to study how migrating from a poor country to a rich country affects economic beliefs, preference parameters, and household decision-making efficiency. In a ten-year follow-up survey of applicants to a migration lottery program we elicit risk and time preferences and pro-market beliefs for the migrants and the unsuccessful applicants. The successful and the unsuccessful applicants are each linked to closest relative households, who would stay in the home country if the applicant moved, to play lab-in-the-field games that measure intra-family trust and the efficiency of intra-family decision-making.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Data are collected at both the individual and household level
Coverage
Geographic Coverage
The survey covers Tongans who applied to the 2002-05 Pacific Access Category migration visa program, along with linked households of their family members. This involved surveying in both New Zealand and Tonga (along with a small number of surveys of movers to third countries).
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| David McKenzie | World Bank |
Producers
| Name | Affiliation | Role |
|---|---|---|
| John Gibson | University of Waikato | jkgibson@waikato.ac.nz |
| Halahingano Rohorua | University of Waikato | hala@waikato.ac.nz |
| Steven Stillman | Free University of Bozen-Bolzano | steven.stillman@unibz.it |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Marsden Fund | Funder | |
| World Bank Research Support Budget | RSB | Funder |
Sampling
Sampling Procedure
Our population of interest consists of entrants to the 2002 to 2005 PAC migration lotteries. There were a total of 4,696 principal applicants of whom 367 were randomly selected as ballot winners (figure 2). Official records provided by the New Zealand immigration authorities in late 2012 show that 307 of these winners (84%) had residency applications approved and had ever migrated to New Zealand. The remaining 60 ballot winners did not migrate and are thus non-compliers to the treatment of migration.
Our main survey involved an extensive face-to-face interview, which also collected anthropometrics, blood pressure, peak lung flow, and included lab-in-the-field games. Of the 307 principal applicants ever migrating to New Zealand, 133 completed the full survey between late 2013 and the end of 2014. In order to bolster our sample size, in early 2015 we fielded a shortened survey that did not include health measurements or the lab-in-field games. This was mainly done as a telephone interview and was designed to reach those who had on-migrated beyond New Zealand or were located in parts of New Zealand that were impractical for face-to-face interviewing, although we also learned, through snowball effects, of more migrants in our face-to-face survey area and gave them the short survey as well. Overall, 61 additional ballot winners who had ever migrated to New Zealand were given the short survey, including 11 who had now on-migrated to Australia (ten) and the UK (one). In total, we were able to survey 194 households with principal applicants who ever migrated to New Zealand after winning the ballot.
We had even less information available for the ballot losers and non-compliers since these individuals had not filled out residency applications. We therefore used the same surveying approach for these groups as we had in our previous survey, which was to sample from the same villages in Tonga from which our migrants originated. Out of 4329 ballot losers, 143 were administered the long form survey and 39 the short survey (of which nine had subsequently moved to New Zealand through alternative pathways, including by winning a later round of the PAC lottery). Finances limited us to this relatively small sample, but, based on our previous research, we judged that it would give us enough power to measure economically significant impacts. An advantage of surveying from the same origin villages is that we can implicitly control for any unobserved characteristics that vary spatially in Tonga. Finally, we have a small sample of nine non-compliers; six who received the long survey and three the short survey. This is out of a population of 60 non-compliers, which hence made it difficult to find many individuals in this group.
Our main survey involved an extensive face-to-face interview, which also collected anthropometrics, blood pressure, peak lung flow, and included lab-in-the-field games. Of the 307 principal applicants ever migrating to New Zealand, 133 completed the full survey between late 2013 and the end of 2014. In order to bolster our sample size, in early 2015 we fielded a shortened survey that did not include health measurements or the lab-in-field games. This was mainly done as a telephone interview and was designed to reach those who had on-migrated beyond New Zealand or were located in parts of New Zealand that were impractical for face-to-face interviewing, although we also learned, through snowball effects, of more migrants in our face-to-face survey area and gave them the short survey as well. Overall, 61 additional ballot winners who had ever migrated to New Zealand were given the short survey, including 11 who had now on-migrated to Australia (ten) and the UK (one). In total, we were able to survey 194 households with principal applicants who ever migrated to New Zealand after winning the ballot.
We had even less information available for the ballot losers and non-compliers since these individuals had not filled out residency applications. We therefore used the same surveying approach for these groups as we had in our previous survey, which was to sample from the same villages in Tonga from which our migrants originated. Out of 4329 ballot losers, 143 were administered the long form survey and 39 the short survey (of which nine had subsequently moved to New Zealand through alternative pathways, including by winning a later round of the PAC lottery). Finances limited us to this relatively small sample, but, based on our previous research, we judged that it would give us enough power to measure economically significant impacts. An advantage of surveying from the same origin villages is that we can implicitly control for any unobserved characteristics that vary spatially in Tonga. Finally, we have a small sample of nine non-compliers; six who received the long survey and three the short survey. This is out of a population of 60 non-compliers, which hence made it difficult to find many individuals in this group.
Weighting
In our main results, we weight the ballot winner sample to reflect the population proportions of ever migrating to New Zealand versus non-compliers. This is necessary because we effectively have a choice based sample, although our previous research suggests that there is no selection among the non-compliers, and, hence, they can effectively be excluded from the sample (McKenzie et al. 2010). We also examine robustness, using two other weighting schemes. The first uses a snapshot of data from late 2012 on crossborder movements coming from passport scans, which revealed that 265 of the 307 ever-migrating ballot winners were in New Zealand at that point in time. This set of weights allows for the possibility that we found it harder to track individuals who had left New Zealand and so puts more weight on the ballot winners in our survey who were found outside New Zealand. The second alternative weighting scheme allows for the possibility that on-movement among the ballot losers is higher than our sample suggests.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2013-07 | 2014-09 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
See research papers for more detail
Questionnaires
Questionnaires
Four separate questionnaires were administered:
- a survey for migrant households in New Zealand
- a survey for non-migrant households in Tonga
- a survey of linked partner households
- a short survey
- a survey for migrant households in New Zealand
- a survey for non-migrant households in Tonga
- a survey of linked partner households
- a short survey
Data Processing
Other Processing
Replication code (Stata do files) and data are available for download for the two research papers:
The Long-Term Impact of International Migration on Economic Decision-Making:Evidence from a Migration Lottery and Lab-in-the-Field Experiments
The Long-Term Impacts of International Migration: Evidence from a Lottery
Go to 'Get Microdata' > WLD_2013_LTIMS_v01_M_ReplicationFiles.zip
The Long-Term Impact of International Migration on Economic Decision-Making:Evidence from a Migration Lottery and Lab-in-the-Field Experiments
The Long-Term Impacts of International Migration: Evidence from a Lottery
Go to 'Get Microdata' > WLD_2013_LTIMS_v01_M_ReplicationFiles.zip
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| David McKenzie | World Bank | dmckenzie@worldbank.org |
Confidentiality
Data have been anonymized by removing all identifying information
Citation requirements
Gibson, John, David McKenzie, Halahingano Rohorua and Steven Stillman (2018) “The long-term impacts of international migration: Evidence from a lottery”, World Bank Economic Review 32(1): 127-47. Ref: WLD_2013_LTIMS_v01_M. Downloaded from [url] on [date].
Metadata production
DDI Document ID
DDI_WLD_2013_LTIMS_v02_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2018-05-10
DDI Document version
DDI Document - Version 02 - (05/24/21)
This version is identical to DDI_WLD_2013_LTIMS_v01_M_WB but country field has been updated to capture all the countries covered by survey.
Version 01 (May 2018)
This version is identical to DDI_WLD_2013_LTIMS_v01_M_WB but country field has been updated to capture all the countries covered by survey.
Version 01 (May 2018)