The determinants of remittance behaviour in CEECs: a case study of Ukrainian labour migrants in the Czech Republic

Transcription

1 The determinants of remittance behaviour in CEECs: a case study of Ukrainian labour migrants in the Czech Republic Wadim Strielkowski, Ondřej Glazar Institute of economic studies, Faculty of social sciences, CU in Prague

2 Outline of the presentation: Czech Science Foundation project on Ukrainian migration and remittances ( ) Ukraine: country profile and outlook of Ukrainian migrations Research questions Data collection methodology Results: 2010 survey vs 2011 survey Discussion of results and main conclusions 2

3 Czech Science Foundation project No. P404/10/0581 Project s title: Migration and development economic, social and socioeconomic impacts of migration on the Czech Republic, as migration target country, and Ukraine, as migration source country (with a specific focus on the analysis of remittances) Project s duration: 3 years ( ). Reasoning for the project: In spite of the fact that there exist several studies about the impact of Ukrainian labor on Czech and Ukrainian economies, a more complex analysis of this impact on both economies (and, as a consequence, on both societies) as well as on the analysis of the use of remittances from the Czech Republic to Ukraine have never been properly conducted. 3

4 Project outline: C Z E C H R E P. U K R A I N E Preliminary research of Ukrainians in Prague (N=5) Pilot longitudinal survey in Prague (N=5) Contacting Ukrainians in Prague for longitudinal survey (N=10) Preliminary research in families in Ukraine (N=5) Contacting families in Ukraine for longitudinal survey (N=10) Contacting families without remittances in Ukraine (N=10) Pilot survey questionnaire (N=100) in Ukraine Contacting 10 Ukrainians (2nd group) for longitudinal survey in Prague Longitudinal survey in Prague (2nd group) Interviews with families (N=20) in Ukraine (1st group) Contacting respondents families in Ukraine (N=10) Contacting families without remittances in Ukraine (N=10) 2nd interview with the 1st group of families (N=20) in Ukraine and 1st interview with 2nd group of families (N=20) in Ukraine Questionnaire survey in Ukraine (100 families with remittances and 100 families without remittances) Conducting the survey questionnaire (N=300) in Prague and surroundings Preparing, conduction and analysing the interviews with the main players of migration policy and practice (N=20) Organizing the conference to present the main outcomes of the project 2nd interview with 2nd group of families (N=20) in Ukraine Timeline ( )

5 Project team: Project Coordinator: Prof. Dušan Drbohlav, Ph.D. Associate Professor Department of Social Geography and Regional Development, Faculty of Science, Charles University in Prague, Albertov 6, Praha 2, , Czech Republic, Phone: drbohlav@natur.cuni.cz Members of research team Prof. Zdeněk Čermák, Ph.D. Prof. Dagmar Dzúrová, Ph.D. Dr. Eva Janská, Ph.D Robert Stojanov, Ph.D. Dr. Wadim Strielkowski, Ph.D. Dita Čermáková Klára Kavanová Lenka Medová 5 GEOMIGRACE research team URL:

6 Country profile: Ukraine Ukraine is a transition economy with various political and socioeconomic problems: Orange revolution (November 2004January 2005) and presidential elections in 2010 (Viktor Yanukovych back at power) Over 6 milion migrants that is more then 13% of the whole Ukrainian population (World Bank, 2006). The top 10 destination countries for Ukrainian migrants are: Russia, U.S., Poland, Israel, Kazakhstan, Moldova, Germany, Belarus, Spain and Canada. Skilled migration: emigration rate of tertiary educated constituted 6% with about 1.1% of physicians trained in the country leaving Ukraine (Docqueir and Marfouk, 2004) 6

7 The map shows the centrality of Ukraine in EurAsianAfrican region. Circles illustrate sending and receiving countries. 7 Source: Düvell (2005)

8 Ukrainian migration in the Czech Republic: Ukrainian migrants constitute the highest share amongst all migrants in the Czech Republic: as of Dec ,339 Ukrainians resided in the Czech Republic: 46,840 permanent residence holders and 77,499 longterm residence holders (Ministry of Interior of the Czech Republic, 2011). Illegal migrants from Ukraine (overstayers, cladestinos, entering on a different or wrong visa): easily around 50,000100,000 people (Drbohlav and Lachmanova, 2008) 8

9 Reasoning for the research topic: The Czech Republic is unambiguously the main net recipient of foreign labour force amongst the postcommunist countries of Central and Eastern Europe (CEECs). Ukraine is the most important source country of foreign labour for the Czech market Ukrainian (labour) migration to the Czech Republic is used as a proxy for all outward Ukrainian migrations Remittance behaviour of Ukrainian migrants in the Czech Republic is used as a proxy for the remittance behaviour in CEECs 9

10 Research questions: What factors determine the remittance behaviour in CEECs? Specific case of Ukrainian labor migrants in the Czech Republic and their families in Ukraine Importance of life cycle characteristics, human capital and household characteristics for remittances Interdependence of above factors and the value of sent remittances What are the differences and similarities between remitting Ukrainian labor migrants and nonmigrants? Are there any differences in remitting behaviour for Ukrainian migrants in the Czech Republic and other countries (e.g. Russia)? 10

11 Ukrainian remittances: Overview of inward and outward remittance flows in Ukraine ( ), in millions of US$ US$ million Inward remittance flows of which * Workers remittances Compensation of employees Migrants transfers 1 2 Outward remittance flows of which Workers remittances 2 Compensation of employees Migrants transfers * 0.7% of GDP in This table reports officially recorded remittances. The true size of remittances, including unrecorded flows through formal and informal channels, is believed to be larger. Source: Development Prospects Group (2006), 11

12 Remitting from Czech Republic to Ukraine in 2010: ikobo * Cost resulting from the % difference between the current interbank exchange rate and the actual exchange rate applied to the remittance transfer; ** includes the fee charged to the sender plus the exchange rate margin. 12 Firm name Leader Moneybookers Checkpoint Unistream MoneyGram Western Union Citybank Ceska Sporitelna CSOB Komercni Banka Bank average MTO average Total average Firm type MTO MTO MTO MTO MTO MTO MTO Bank Bank Bank Bank Fee (in CZK) Exchange rate margin (in %) Source: World Bank (2010), Percent (%) Total cost** CZK Transfer speed Less than 1 hr 35 days Same day Same day Less than 1 hr Less than 1 hr 6 days or more 35 days 6 days or more 35 days 6 days or more Network coverage Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide Nationwide

13 Data collection methodology: 2010 survey Name: 2010 Ukrainian household survey Timing: JulyAugust 2010 Sample: 100 respondents (total sample of 359 individuals (data on 3 and more individuals residing in the same household were obtained in majority of cases). Sample selection technique: snowball sampling Conducted by: specially hired and trained interviewers Conducted in: Zakarpat ye region (oblast) of Western Ukraine. 13

14 Results: 2010 survey (100 surveys, 357 observations) Comparing the survey data against available statistics Survey 2010 Statistical offices Sources Male 48.7% 45.6% State Statistic Committee of Ukraine (est. 2008) Female 51.3% 54.4% State Statistic Committee of Ukraine (est. 2008) Labour force participation 61.1% 64.7% World Bank (2009) Unemployment 1.9% 2.3% National Bank of Ukraine (2007) Married 53.8% Secondary education 54.1% University degree 17.4% Source: own estimations 14

15 Results: 2010 survey (100 surveys, 357 observations) Main characteristics of Ukrainian labour migrants in the Czech Republic 15 Age and over Population 1854 Male Female Level of education Primary Secondary University Marital status Married Single Source: own estimations Total population (survey) 11.2% 20.7% 28.3% 27.7% 12.0% 51.0% 49.0% 28.6% 54.1% 17.4% 54.0% 46.0% Emigrants (survey) 0.0% 3.9% 40.2% 52.0% 3.9% 67.3% 32.7% 9.8% 71.6% 18.6% 75.4% 24.6%

16 Results: 2010 survey (100 surveys, 357 observations) 16 Independent variable Life cycle characteristics Age Female Marital status (females) Marital status (males) Human capital Secondary education University degree Household characteristics Household size Family income Intercept Log likelihood ratio McFadden Rsquared Number of observations Remitting migrant 0,009 0,534** 0,319 0,633*** 0,804*** 0,837*** 0,145 0,730** 1, Probit model: Funkhouser (1992); Durand and Massey (1992); Durand et al. (1996); Massey, Durand, Pren (2011): Pr(Migrant=1) = F(α + β 1 Fem + β 2 Age + β 3 Femm + β 4 Malm + β 5 Sec + β 6 Uni + γ 1 HH + γ 2 Inc Note: * Significant on the 10% level;** Significant on the 5% level; *** Significant on the 1% level

17 Comparing profiles: Ukrainian labour migrants (2010) Characteristics Gender Age I have learnt how to Czech solve problems Republic both on my own and in teams, which proved crucial in my career Male I still cooperate with many of my schoolmates who hold important positions at various companies and universities around the Married world. Marital status Education Income status Remittances Typical Ukrainian labour migrant in the Working age (2554) Completed secondary or higher Lowincome Yes Typical Ukrainian not interested in (labour) migration Male 1524; 54 and over Single Unfinished primary or secondary Middleincome or highincome No Source: own estimations (2010 survey) 17

18 Data collection methodology: 2011 survey Name: 2011 Ukrainian household survey Timing: May 2011 Sample: 161 respondents (total sample of 651 individuals (data on 3 and more individuals residing in the same household were obtained in majority of cases)). Sample selection technique: snowball sampling with gatekeepers Conducted through: secondary schools (using teachers as gatekeepers ) Conducted in: Zakarpat ye region (oblast) of Western Ukraine. 18

19 Spending patterns: 2011 survey How do you usually use cash remittances as a household (please select maximum four most relevant answers and mark them from 1 to 4 with one being the most significant and 4 being the least significant): a) b) c) d) e) f) g) h) i) k) l) m) n) 19 To consume in food? To consume in clothes? To buy a personal car? To by house appliances, furniture? To pay the costs of utilities (gas, water, heating, etc.) Use for building or reconstruction of a house? To buy land? To pay debts? To pay for schooling (e.g. University)? To pay for healthcare? Save? Invest in business? What kind of business? Other (what?): building a house 17% healthcare 3% utilities 4% clothing 37% other 3% food 36% The most important items are: food, clothing, construction (building/reconstructing a house)

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21 Results: 2011 survey (161 surveys, 651 observations) Independent variable Remitting migrant Nonmigrant Total sample Life cycle characteristics Age Female 1.424*** 1.211*** 1.300*** Marital status 1.184*** 1.539*** Human capital Secondary education University degree 0.129* 0.075* 0.346* Household characteristics Household size 0.502*** 0.308* 0.513** Family income Intercept Log likelihood ratio McFadden Rsquared Number of observations Note: * Significant on the 10% level;** Significant on the 5% level; *** Significant on the 1% level

22 Comparing remittees and stayers : Remitting migrants Nonmigrants + Marital status: married*** + Gender: Male*** + Household size: smaller household* + University degree* + Marital status: single*** 22 Note: * Significant on the 10% level;** Significant on the 5% level; *** Significant on the 1% level Total sample

23 Determinants of a Ukrainian remittee: Determinants I have learnt how to Republic solve problems both on my own and in teams, which proved crucial in my career Male, I still married cooperate with many of my schoolmates who hold important positions at various companies and universities around the world. Life cycle characteristics Human capital Household characteristics Remittances Typical Ukrainian remittee in Czech University degree Originating from a smaller household (3 and less people) Yes Typical nonremittee ( stayer ) Female, single Secondary school or unfinished secondary education Originating from a larger household (3 and more people) No Source: own estimations (2011 survey) 23

24 Results: 2011 survey (161 surveys, 258 observations) Independent variable All remitting Remitting CR Remitting Russia Life cycle characteristics Age Female 2.070*** 1.898*** 1.218*** Marital status 1.784*** 2.488*** Human capital Secondary education ** University degree 0.468* 0.074* 0.604* Household characteristics Household size Family income Intercept Log likelihood ratio McFadden Rsquared Number of observations Note: * Significant on the 10% level;** Significant on the 5% level; *** Significant on the 1% level

25 Comparing remittees by countries: Remitting from CR Remitting from Russia + Marital status: married*** + Secondary education* + Gender: Male*** + University degree* 25 Note: * Significant on the 10% level;** Significant on the 5% level; *** Significant on the 1% level + Marital status: married*** All remitting

26 Discussion of results: Factors determining remittance behaviour in case of Ukrainian migrants: life cycle characteristics (gender), human capital (education) and household characteristics (household size) Differences and similarities between remitting Ukrainian labor migrants and nonmigrants: a remitting migrant tends to be married male with a University degree originating from a smaller household, while a typical stayer would be a single female with secondary education or less originating from a larger household (>3 members). Differences in remitting behaviour for Ukrainian migrants in the Czech Republic and other countries (e.g. Russia): both tend to be males, however those remitting from CR tend to be married; importance of secondary degree or less for those remitting from Russia and importance of University degree for both groups 26

27 Main conclusions: It appears that smarter, married males staying/working in CEECs tend to remit back home in order to provide their (smaller) families. The household size factor shows that people in larger household are more likely to stay at home (externalities associated with the costs of migrations and the existence of networks that would compensate for remittances). Policy implications: family reunion programmes, migration policy targeted at qualified labor (from Ukraine and other countries), system of green (or blue) cards. The impact of remittances is yet to be measured both for the target and sending countries. 27

28 Questions and answers: Thank you for your attention! Q&A Contact for the corresponding author: PhDr. Wadim Strielkowski, Ph.D. URL: (s): 28