Who is Bearing the Burden? Exploring the Role of Albanian International Migration on Education

1. Who is Bearing the Burden? Exploring the Role of Albanian International Migration on Education Juna Miluka Andrew Dabalen June 10, 2008

2. Motivation • Scale of International Migration • 300,000 individuals left the country between 1991 and 1992 (Carletto et. al., 2004) • Remittances approximately 14% of GDP • Limited Empirical Evidence • Moving Beyond the Role of Remittances

3. Purpose • In light of the ambiguous and multiple effects of migration on human capital, this essay will determine the specific effect that international migration has on school enrollments, educational attainment, and educational expenditures in Albania.

4. Migration in Albania • Main Destinations • Greece and Italy • 300,000 Migrants between 1990-1992 • Factors Influencing Migration • Close Location • Cultural Similarities • Family and Social Networks

5. Effects of Migration • Positive through relaxation of liquidity constraints • Negative through • Direct Substitution of Schooling Today for Migration Tomorrow • The Change in the Expected Future Returns to Education • Disruption of Household Structure

6. Data • 2005 ALSMS • 3640 Households • Sub-sample of Individuals • Ages 6-22 • Ages 14 to 17 • Final Sample 2,446 households • 5004 individuals between 6-22 • 1,403 individuals between 14-17

7. Descriptive Statistics • Lower Enrollment for Migrant HH overall and by Gender • Same for ages 14-17, exception of males • Lower Expenditures for Females in Migrant HH • For Migrant HH • Smaller HH size • Female Headed HH • Less Educated Heads

8. Empirical Model • Instrumental Variable Probit Yi = βMi + δ׳ Xi + μi Yi = 1 if Y*>0 0 otherwise Mi= Xi∏1 + Ii∏2 + vi • Instrumental Variable 2 Step Model P(e=0 | x) = 1- Φ(x γ) log(e) | (x, e>0) ~ Normal (xβ, σ2) • IV Censored Ordered Probit • Instruments Languages Distance to borders Average Number of Shocks

9. Variables • Dependent Variables • Binary Enrollment • Discrete Ordered Educational Attainment • Binary Educational Expenditure • Log of HH Educational Expenditure • Independent Variables • Migration • Human Capital • Wealth • Community and Regional Characteristics

10. Results • IV Probit • Overall Negative Impact • Insignificant Effects for Males • Negative Significant Effect for Females • Negative Significant Effect for Rural Areas • Insignificant Effect for Males • Negative Effect for Females • No Effect on Urban Areas

11. Results • IV Censored Ordered Probit • Negative Impact for 9-11, 12, and 13-15 years of schooling. • Negative Impact for Urban Areas for 9-11, and 12 years of schooling. • Negative for Females for 9-11, 12, and 13-15 years of schooling. • Same for urban females. • Negative Impact for Rural Females for 1-7 Years of schooling.

12. Results • 2 Part Model • No effect on probability of positive educational expenditures • Negative impact on probability of positive educational expenditures for females • Negative effect on educational expenditures for enrolled (no gender differences)

13. Results 14 to 17 year olds • Overall negative impact • No impact on males • Negative impact on females • Negative impact on rural areas • No impact on urban areas • Two Part Model in Accordance with Earlier Findings

14. Explanation of Results • Poorer Conditions for Rural Areas • Increased Female Migration • Changes in the Family Structure • Increased Household Self Owned Businesses • Material Goods sent by Migrants

15. Conclusions • Special Consideration to Diverse Migration Channels • Perverse Incentives • Negative Influence on School Enrollments • More Incentives Devoted to Education • Social Capital • Distance to Schools • Improved Living Conditions of Households