Richard E. Bilsborrow Consultant, MEDHIMS and World Bank University of North Carolina at Chapel Hill Presented at ECE Work Session.

Slides:



Advertisements
Similar presentations
Multiple Indicator Cluster Surveys Survey Design Workshop
Advertisements

Innovation data collection: Methodological procedures & basic forms Regional Workshop on Science, Technology and Innovation (STI) Indicators.
Innovation data collection: Advice from the Oslo Manual South East Asian Regional Workshop on Science, Technology and Innovation Statistics.
Innovation Surveys: Advice from the Oslo Manual South Asian Regional Workshop on Science, Technology and Innovation Statistics Kathmandu,
Innovation Surveys: Advice from the Oslo Manual National training workshop Amman, Jordan October 2010.
An Assessment of the Impact of Two Distinct Survey Design Modifications on Health Insurance Coverage Estimates in a National Health Care Survey Steven.
Innovation Survey in Manufacturing Industry Rizka Rahmaida Presented in: Innovation Session 2011 South East Asian Regional Workshop On Science, Technology,
Using Household Surveys to Study the Economic and Social Implications of Migration: A Methodological Evaluation* Regional Training Workshop on International.
Geographic Oversampling for Race/Ethnicity Using Data from the 2010 Census Presented to WSS Sixia Chen December 3, 2014.
Sample Design (Click icon for audio) Dr. Michael R. Hyman, NMSU.
Dr. Chris L. S. Coryn Spring 2012
Documentation and survey quality. Introduction.
Responding driven sampling Principles of Sampling Session 1.
Stratified Simple Random Sampling (Chapter 5, Textbook, Barnett, V
Linking Data Collection on International Migration in Household Surveys in CIS States Richard E. Bilsborrow University of North Carolina at Chapel Hill.
Session 6 – Sample survey design and implementation G. Cantisani Freelance Expert in Population Data/Statistics UNECE Workshop on Migration Statistics.
Using Household Surveys to Measure International Migration and Remittances in Developing Countries: Examples and Methodological Issues Richard E. Bilsborrow.
Producing migration data using household surveys Experience of the Republic of Moldova UNECE Work Session on Migration Statistics, Geneva, October.
Integrated household based agricultural survey methodology applied in Ethiopia, new developments and comments on the Integrated survey frame work.
Sample Design.
United Nations Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Amman, Jordan,
MEDSTAT Questionnaires for Household Surveys on International Migration Samir Farid Regional Workshop on International Migration Statistics Cairo, 30/6/2009.
The new HBS Chisinau, 26 October Outline 1.How the HBS changed 2.Assessment of data quality 3.Data comparability 4.Conclusions.
Sample Design Establishments Surveys Stuart Brown Research, Design & Evaluation January 2013 STATISTICAL INSTITUTE OF JAMAICA.
Definitions Observation unit Target population Sample Sampled population Sampling unit Sampling frame.
HOUSEHOLD SURVEY PROGRAMME IN UGANDA: PAST EXPERIENCES AND FUTURE PLANS By James Muwonge Uganda Bureau of Statistics OCTOBER, 2009.
Near East Regional Workshop - Linking Population and Housing Censuses with Agricultural Censuses. Amman, Jordan, June 2012 Improving Efficiency.
Multiple Indicator Cluster Surveys Survey Design Workshop Sampling: Overview MICS Survey Design Workshop.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys Bangkok,
Scot Exec Course Nov/Dec 04 Survey design overview Gillian Raab Professor of Applied Statistics Napier University.
International Migration and Remittances in Eastern Europe and Central Asia: Using Household Surveys to Improve Migration Analysis and Policy Responses.
Copyright 2010, The World Bank Group. All Rights Reserved. Business tendency surveys, part 2 1 Business statistics and registers.
CHAPTER 12 DETERMINING THE SAMPLE PLAN. Important Topics of This Chapter Differences between population and sample. Sampling frame and frame error. Developing.
Sampling Methods.
1 Basic requirements for using a household survey to produce good quality migration data Dean H. Judson, Ph.D. Immigration Statistics Staff.
SESSION IV The 2010 round of population censuses: United Nations Recommendations and their implementations African Institute for Economic Development and.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Bangkok,
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis for Arabic Speaking Countries, Amman, Jordan May 2011 Identification.
1. Population and Sampling  Probability Sampling  Non-probability Sampling 2.
5-4-1 Unit 4: Sampling approaches After completing this unit you should be able to: Outline the purpose of sampling Understand key theoretical.
Optimum sampling strategy for National Households In Abu Dhabi (The Household Master Sample 2012) Authors : Mohammed Al Rifai (Ph.D.) Mariam.
SAMPLE DESIGN: WHO WILL BE IN THE SAMPLE ? (CONTINUED) Lu Ann Aday, Ph.D. The University of Texas School of Public Health.
Optimum sampling strategy for National Households In Abu Dhabi (The Household Master Sample 2012) Authors : Mohammed Al Rifai (Ph.D.) Mariam.
Chapter Eleven The entire group of people about whom information is needed; also called the universe or population of interest. The process of obtaining.
Collection of Data on Remittances Experience from the Ghana Living Standards Survey Grace Bediako Ghana Statistical Service.
Questionnaire Design for Linked Surveys of International Migration in the CIS Countries: Issues and Proposed Approach Richard E. Bilsborrow For the World.
Chapter 6: 1 Sampling. Introduction Sampling - the process of selecting observations Often not possible to collect information from all persons or other.
UNFPA/UNECE/NIDI Training programme on international migration, Geneva, 24-28/01/2005 Design of Samples for International Migration Surveys: Methodological.
Household Survey Data on Remittances in Sending Countries Johan A. Mistiaen International Technical meeting on Measuring Remittances Washington DC - January.
United NationsUnited Nations Economic Commission for Europe Statistical Division Measuring Hard-to-Count Migration Populations: Importance, Definitions,
Ëëë.instat.gov.al 17 October 2012 MIGRATION STATISTICS “Albanian specific examples of migration surveys” Ruzhdie Bici.
United Nations Economic Commission for Europe Statistical Division Collecting information on emigration at the census Enrico Bisogno Social and Demographic.
United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis for Arabic Speaking Countries, Amman, Jordan May 2011 Identification.
Towards an improvement of current migration estimates for Italy Domenico Gabrielli, Maria Pia Sorvillo Istat - Italy Joint UNECE-Eurostat Work session.
1 Overview of Economic Statistics in Africa UNECA Andry Andriantseheno Regional Workshop on Basic Economic Statistics Addis-Ababa October 2007.
CASE STUDY: NATIONAL SURVEY OF FAMILY GROWTH Karen E. Davis National Center for Health Statistics Coordinating Center for Health Information and Service.
Probability Sampling. Simple Random Sample (SRS) Stratified Random Sampling Cluster Sampling The only way to ensure a representative sample is to obtain.
SUITLAND WORKING GROUP: Task Force on Improving Migration and Migrant Data Using Household Surveys and Other Sources Eric B. Jensen Population Division.
Sample Design of the National Health Interview Survey (NHIS) Linda Tompkins Data Users Conference July 12, 2006 Centers for Disease Control and Prevention.
Sampling Design and Analysis MTH 494 LECTURE-11 Ossam Chohan Assistant Professor CIIT Abbottabad.
PRESENTED BY- MEENAL SANTANI (039) SWATI LUTHRA (054)
United Nations Economic Commission for Europe Statistical Division Challenges in measuring gender and minorities Govinda Dahal (presented by E.Bisogno)
RESEARCH METHODS Lecture 28. TYPES OF PROBABILITY SAMPLING Requires more work than nonrandom sampling. Researcher must identify sampling elements. Necessary.
United Nations Regional Workshop on the 2010 World Programme on Population and Housing Censuses: Census Evaluation and Post Enumeration Surveys, Addis.
Towards Common Definition and Measurement of Diaspora: Practices and Lessons from South-Eastern Europe, Eastern Europe and Central Asia UNECE/Eurostat.
1 Strategy for mobilizing funds for agricultural census – Tanzania Experience By Lubili Marco Gambamala National Bureau of Statistics 97.7% of smallholder.
The Suitland Working Group: Using Household Surveys to Measure Migration and Migrant Populations Victoria A. Velkoff Assistant Division Chief, Estimates.
RESEARCH METHODS Lecture 28
MED-HIMS: Surveys on Migration
Random sampling Carlo Azzarri IFPRI Datathon APSU, Dhaka
Presentation transcript:

Richard E. Bilsborrow Consultant, MEDHIMS and World Bank University of North Carolina at Chapel Hill Presented at ECE Work Session on Migration Statistics, Geneva, Switz. October 17-19, 2012

Data on individuals who have left (emigrated) from households can be obtained from household members remaining behind (proxy respondents) Limitations in data that can be obtained from proxy respondents In addition, data on whole households who emigrated is usually not available, and normally obtainable only through a survey in the country/ies of destination This indicates a major limitation of a survey (or census) carried out only in a country of origin

 The state of knowledge is weak, partly due to the complexity of the phenomenon (including its definition, involving two countries, etc.) but also to the lack of good data sets and studies  To study the determinants and consequences of migration, survey data are needed on both individuals and households  This requires the use of specialized methods of data collection, including (1) sampling to address the “rare elements” problem and (2) questionnaires that collect retrospective data

 In the country of Origin, goal is to sample (select) households with emigrants and those without emigrants (and possibly those with return migrants as well)  From the latest census or other source, form strata based on the expected prevalence of international migrants  Oversample areas or Primary Sampling Units (PSUs) from strata with higher proportions of households with emigrants at each sampling stage: This means selecting provinces or other PSUs at the first stage using oversampling, then at the second stage for selecting districts, etc., and finally in selecting the last stage area units (Ultimate Area Units or UAUs), such as census sectors or (urban) blocks.  Even highly disproportionate sampling fractions can be used, since that can be adjusted for in the analysis using weights.

Once the final Ultimate Area Units (UAUs) have been selected, in each sample UAU, first conduct a listing or screening operation, to list occupied households and identify those with and without migrants Create separate lists for each type of household of interest, e.g., households with one or more former members who emigrated and did not return in the previous (e.g.) 10 years, those with someone who returned within the previous 10 years, and those without either—non-migrant households. Sample from each list separately, taking high proportions from the lists of households with migrants and return migrants and small proportions of non- migrant households In phase 2, conduct interviews of sample households from both lists

The key is to recognize the need to have data for appropriate comparison groups. I have written 2 books about this for the ILO (1984 and 1997). Ideally, surveys should be conducted in both the country of origin and the main countries of destination. If the survey can be carried out only in the country of origin (e.g., Jordan), it needs to cover households with emigrants (for whom data are obtained from proxy respondents) and households without emigrants. The appropriate comparison groups are (a) emigrants in the former; (b) persons who did not emigrate from both types of households. To study why some persons emigrated and others did not, data on both (a) and (b) and their households (and communities) are pooled to estimate statistical migration functions. To study the consequences of emigration, the same two groups are again compared. To formulate policy recommendations, it is desirable to conduct studies on both the determinants and consequences.

 Thorogood, Jensen and Schachter on Suitland group contributions, on 3 of 7 projects begun following meeting in 2009  Pie (not Psy!)  (Read brief comments on Thorogood & Jensen}  Re. Jason, provides interesting review of a number of hard-to-reach populations who move  Based on questionnaire to 29 Europ countries in 2008  Upcoming conference of ASA

 Some types of hard-to-reach involve issue of purpose of mig and defn, discussed well, but of minor interest to me; see Standing’s Typology in 1984 book of Bilsborrow et al on internal migration—short term, circular, while others so difficult—trafficked, in transit  But is data on transit mig so hard to get in surveys?  Or forced migration? Samir and our MEDSTAT group including UNHCR (Tarek) developed nice screening question, and follow-up questionnaire  In Fig. 1 Jason adds minors; I started working on this for UNICEF in 2007, collapsed, but I think is ongoing?  Says it is “most likely unfeasible to implement surveys to collect data” on hard to reach pops, plus is too costly—but I think we can—or must try!

 To complement what Samir has said, we propose to use specialized sampling techniques appropriate for rare populations, where possible  In first country, there was not adequate frame to make it possible, so a PPES sample was used  But in Jordan, there seemed to be two sources which, while each is inadequate, proved feasible to use when considered together

Job Creation Survey stratification, 2012 Census stratification, 2004 HighMediumLowTotal High Medium Low Total

Stratum Number in stratum, N h Mean proportion internation al migrants Proportionate allocation (1) X (2) Disproportion ate Allocation A Disproportio nate Allocation B (1)(2)(3)(4)(5)(6) High Medium Low Total 89 30

 So let us move forward, in both the MEDHIMS region and CIS States, and surprise the world!