Labor Migration & Social Networks: The Case of Kyrgyzstan

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Labor Migration & Social Networks: The Case of Kyrgyzstan Bakhrom Mirkasimov (co-authors: Tanika Chakraborty & Susan Steiner) Sep 15, 2011 Bishkek, Kyrgyzstan

Introduction This paper investigates how social networks are affected if people migrate in Kyrgyzstan. Usually most (almost all) papers only analyze cases how social networks affect migration decisions in source communities and how migrants form/participate in social networks at destination communities. There is (almost) NO research on social network ties of households and communities (ayil/rayon) left behind due to migration and we hope to fill this gap by directly testing the role of migration and remittances using household surveys in Kyrgyzstan.

Definition Why and how do we define social networks? Social networks are a key source of information and resources, hence influence economic performance. Many economic functions (i.e., employment, informal insurance, access to credit) are fulfilled through social networks. Social networks serve a major role/function ESPECIALLY in low-income country settings due to lack of formal institutions and market mechanisms.

Definition (cont d) We focus on economic benefits of social networks (as opposed to psychological or social benefits). In this paper, measures (proxies) for social networks are the following: Participation in groups (i.e., profsoyuz, religious groups) Provided financial help in the last 12 months Provided non-financial help in the last 12 months (i.e., house repair, prep for celebrations) Lending 2000 Soms if suddenly needed Expenses on ceremonies (i.e., toi/weddings, funerals) 2-3 more proxies will be added in near future

Research Question? What is the effect of migration on social networks at origin? (Does it depend on remittances?) What is the effect of remittances on social networks at origin? Are the effects different/same at the household level and at the community level? 5

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Literature Review: Theory This topic is theoretically ambiguous. Lots of research focus on physical and human capital of households left behind if people migrate. Research is thin when it comes to social capital, inter-household informal exchanges, group participation when people migrate. In theory, migration/remittances could either strengthen or weaken the degree of mutual exchange and reciprocity (insurance) in social networks.

Literature Review: Empirics Gallego & Mendola (2010) look at labor migration and social networks using household survey data from two southern regions in Mozambique and they find that households with successful migrants (receiving remittances or return migration) engage more in community based social networks. Ablezova, Nasritdinov and Rahimov (2008) study the impact of migration on elderly people (grandparentheaded households). Piotrowski (2006) studies the effect of social networks at origin communities on migrant remittances, using panel survey data in Thailand.

The Kyrgyz context Estimations that up to one third of economically active population (labor force) is abroad and this, in turn, will have consequences on the economic and social life in the source communities. Emigration from Kyrgyzstan is almost exclusively motivated by economic reasons 80% come from the densely populated South of the country and migration is an important livelihood strategy In 2009, migrants remitted nearly US$ 1 billion!!!

Data Life in Kyrgyzstan 3-year panel household survey data collected annually by German Institute for Economic Research (DIW Berlin), 2010-2012 Project is funded by Volkswagen Foundation Random three-stage sampling based on 2009 Census, nationally-representative Covers 3000 households, 8160 individuals, 120 communities all over the Kyrgyz Republic Includes information on education, health, migration, remittances, social life, labor market, expenditures, shocks, etc

Descriptive Statistics # of current migrants in the HH: 1.25 HH with current migrants: 12% HH receiving remittances (total): 10% Typical migrant: young, male, working in construction or trade sector in Russia, sends money mainly 4-5 times a year via MTAs (Western Union, Anelik, etc) Remittances are mainly used for consumption (food, electricity, etc)

Summary statistics individual characteristics by migration categories Current Migrants (M-HH) Gender (male) 73% Age in years 28.95 Married 47% Ethnicity (kyrgyz) 68% Russian speaker 56% HH head secondary education (general) 67% HH head university degree 10% Occupation (sector) Construction 43% Trade and repair 24% Occupation (position) Service worker (shop/market sales) 14% Craft and related trades 14% Unskilled worker 63% Student (studying) 2% Seasonal worker (yes) 20% Country of destination: Russia 90% Kazakhstan 6%

Remittance management (individual level-migrants) Frequency: (within the last 12 months) 2-3 times 23% 4-5 times 35% 6-10 times 21% Use Consumption (food, electricity, ) 71% Saving 22% Wedding 25% Way to send Bank account 36% MTA (Western Union, Anelik) 58%

Empirical strategy (1) Estimate a linear probability model (with IV) at the household level Where, is an indicator for participation in network type k (financial help, non-financial help, etc) by HH i in region j is a dummy for migration status of HH i in region j are the vectors of household characteristics (such as demographics, education, household size, etc) is a dummy for community j (comparing migrant vs. non-migrant households within a community/ayil/rayon) is the standard error term

Empirical Strategy (2) Estimate a linear probability model (with IV) at the community level Where, is the fraction of households participating in network type k (financial help, non-financial help, etc) by HH i in region j is the fraction of migrant households in region j are the vectors of community characteristics NOTE: Instrument for migration use geographic factors and community-specific labor market shocks in the 1990s 16

Preliminary Results Migrant households provide less financial help to other households in their community, however, households that receive remittances give more financial help than their counterparts. Other social network variables (group participation, non-financial help, etc) are not statistically significant, meaning that there is seemingly no (statistical) difference in the behavior of migrant and non-migrant households.

Further research Include 2011 Life in Kyrgyzstan Round 2 survey data later this year. Do robustness/sensitivity checks. Clear policy implications: raise the awareness for long-term impacts of migration and remittances on the general welfare of migrant and nonmigrant households and communities left behind in Kyrgyzstan.

Conclusion Migration has affected social network ties of households left behind in Kyrgyzstan. Based on the original 2010 household survey data and my own fieldwork this summer in Kyrgyzstan, we interpret these preliminary results cautiously that participation in social networks (financial, non-financial, expenses on ceremonies, group membership, etc) may be open but not without a cost to remaining household members.

Thank you for your attention!