Returns to Higher Education in Timor-Leste

Returns to Higher Education in Timor-Leste TAKAO OKAMOTO MASTER STUDENT, KOBE UNIVERSITY OCTOBER 14, 2015

2 Outline of the Presentation 1. Background 2. Problem Statement 3. Research Question 4. Objective of the Study 5. Significance 6. Literature Review 7. Methodology 7-1. Hypothesis 7-2. Model 7-3. Data 8. Expected Outcomes 9. Limitation of the Study 10. References

3 1. Background After a long period in which the international development community has placed emphasis on primary education, there is now renewed interest in tertiary education (TE). However, the extent and nature of the impact of TE on development remains unclear. This study seeks to address this question in Timor-Leste in terms of low- and lowermiddle income countries Overall, while there is a large body of literature on TE in low- and lower-middle income countries(llmics), the majority of studies focus on the characteristics of TE systems and institutions, or on the short-term effects of interventions (for example, on policy and funding arrangements). Few studies that sought evidence of the broader impact of TE on development in LLMICs.

4 1.Background PLACE: Southern East Asia Neighbours: Indonesia and Australia LAND: 14,900 km2

5 1.Background POPULATION: About 1140.000 (CENSUS 2010) 60% of the population under 25 years RELIGION: Catholics (90%) MINORITIES : Protestants and Muslims.

5 1.Background ECONOMY Lower-Middle Country (WORLD BANK) GDP: 4,190 million US (2014) GDP(EXCEPT PETROLEUM): 1,767 MILLION US (2014) POVERTY 37.4% of the country's population lives below the international poverty line which means living on less than U.S. $1.25 per day KEY INDUSTRY: Offshore Petroleum

5 1.Background EDUCATION Gross enrolment rate in 2010 from Census 2010 (%) Primary 104.6 Pre-Secondary 74.3 Secondary 61.1 Tertiary (University) 17.6 (13.4) Literacy rate (% of persons 15 and over who can speak, read and write) Tetun 56.1 Portuguese 25.2 Indonesian 45.3 English 14.6 Source: Population Distribution by Administrative Areas Vol2. Population and Housing Census 2010, Ministry of Finance, 2010.

8 2. Problem Statement Wages Average wages are too high relative to productivity (and skills), limiting labor demand. The benefits of high wages in the formal sector accrue to very few and have not helped to overcome inequality. This clearly indicates that only a small fraction of the working age population in Timor-Leste contributes to the high average wage of USD 174. Thus, the distribution of incomes is highly dispersed. High minimum wages do not adequately protect low-income workers. The government reviewed the minimum wage policy in 2012 and set a new minimum wage of USD 115 per month, to be paid 13 times a year.

9 2. Problem Statement Wages High minimum wages would adversely affect employment, with disproportionate consequences for youth and female employment. The high public sector wages and minimum wage are discouraging the development of a strong private sector. The wage and salary bill for civil servants in Timor-Leste is high, relative to other countries in the region; as a percentage of GDP, it is between 25 to 50% higher than countries such as Fiji, Tonga, and Vanuatu; and two to four times higher than countries such as Solomon Islands, Laos and Cambodia. These information raises the question why not all people could pursue higher education if previous studies have shown that higher education provides a higher return.

10 3. Research Question To what extent do the economic incentives for investing in education in Timor-Leste? What are the returns to education in such a setting in Timor-Leste?

11 4. Objective of the Study The over goal of the study is to measure casual effect of education on wages in Timor-Leste. Corresponding to the above stated research question, this study has two objectives. - To examine the rate of return to higher education in Timor-Leste. - To examine the effect of family factors on wages in Timor-Leste.

12 5. Significance of the Study It is important to analyze the education-labor issue through econometric approach Little study has been done on the rate of return to education in Timor-Leste Previous studies on rate of return to education in Timor-Leste including but not and have not shown the relationship between wages and higher education. This study provide empirical evidence on the effects of higher education on wages in Timor-Leste.

13 6. Literature Review Rate of Return to education Conventionally, the return on education is estimated using the Ordinary Least Squares (OLS) adopted from the standard Mincerian equation (Mincer, 1974) as follows: In W i = π 0 X i + β 0 S i + ε i ε i = α i + f i + v i ln W i : Natural logarithm of the wage for individual i S i : Completed years of schooling of individual i X i : Vector of other controls variables ε i : Error term α i : Measure of cognitive ability for individual i f i : Unobserved family-specific wage component v i : Error component reflecting unobserved individual-specific factors and transitory wage shocks.

14 6. Literature Review Rate of Return to education Using household-survey data collected between 1985 and 1998, Schultz (2004) finds higher private wage returns for higher education than for primary education in Ghana, Cote d Ivoire and Kenya. In fact, a number of these studies (for example, Duraisamy 2000, Fasih et al. 2012, Glewwe et al. 2002) indicate that ROR on higher education has trended upward in lowerincome countries in recent years. In many contexts, this is likely to be a result of increased access to primary and secondary education, as such expansion leads to a surplus of individuals with lower levels of education in the labor market.

15 6. Literature Review Rate of Return to education One area of substantial debate within the literature is the question of whether the relationship between education and earnings is concave (meaning that the marginal returns to education are higher for individuals with lower levels of education) or convex (meaning that the returns are lowest for those with the least education). According to the influential body of evidence presented by Psacharopoulos (1994; et al. 1994; with Patrinos 2004), the earnings function is concave in lower-income countries, meaning that returns are higher for lower levels of education. However, more recent evidence from Sub-Saharan Africa, presented by Teal (2011) and Schultz (2004), indicates higher returns for higher levels of education in Africa. Their analyses suggest that primary education is likely to have little impact on income.

16 6. Literature Review Rate of Return to education Most of the reviewed literature indicates that there are high private returns on investment in TE in LLMIC contexts. Using household-survey data collected between 1985 and 1998, Schultz (2004) finds higher private wage returns for higher education than for primary education in Ghana, Cote d Ivoire and Kenya. In fact, a number of these studies (for example, Duraisamy 2000, Fasih et al. 2012) indicate that ROR on higher education has trended upward in lower-income countries in recent years. In many contexts, this is likely to be a result of increased access to primary and secondary education, as such expansion leads to a surplus of individuals with lower levels of education in the labor market.

17 6. Literature Review Rate of Return to education Some of the included studies consider the link between TE and earnings within particular sectors of the economy. Teal (2011) notes that the relationship between earnings and education is complicated by the fact that individuals with identical levels of education can earn a wide range of incomes. This concept is further elaborated through other studies, which consider differential returns to TE for males and females, for employees of the formal and informal sector, for urban and rural workers, and for paid-wage workers versus self-employed individuals (Agesa et al. 2013, Al-Samarrai and Reilly 2008, Deolalika 1993, Duraisamy 2000, Dutta 2006, El-Hamidi 2006, Fasih et al. 2012, Kimenyi et al. 2006, Moock et al.2003).

18 6. Literature Review Previous Timor-Leste s Study Santos(2014) conducted to assess the rate of returns to education in Timor-Leste in terms of post conflict situation. The results show that 1. Higher than proportional earnings premiums were awarded to those that completed technical and vocational training or a post graduate degree. 2. Those with command of the Portuguese language also seem to have a higher wage, controlling for other factors.

19 7. Methodology 7-1. Hypothesis The following hypotheses were formulated based on previous studies, in response to the three research questions. The investment in education is one of forms investments in the long term that will give more advantages (Krueger and Lindahl, 2000). 1. In term of gender, the hypothesis is female has lower wages rather than male or in other words there is discrimination wages between male and female (Deolalikar, 1993). 2. The returns to education hypothesis regarding to area between rural and urban indicated that financial earnings in rural area have been lower rather than in urban areas in Timor-Leste 3. In term of, industrial classification in Timor-Leste, the hypothesis indicated that the highest wages are earned by worker who worked in public sector.

20 7. Methodology 7-2. Model The earnings differentials between men and women may be corrected for differences in levels of educational attainment and work experience using the Mincer model. The Mincerian equation is a widely used function to model earnings based on key determining variables. A typical Mincer equation uses sex, age and educational attainment as determining variables, age being a proxy variable for length of work experience and educational attainment a proxy for years of formal education. The Mincer equation is thus specified here by w = β 0 +β 1 sex + β 2 age + β 3 age 2 + β 4 educ + ε where w is the logarithm of earnings or more precisely net income from paid employment per unit of time, sex : a variable with value 0 for men and 1 for women, age : the age variable, educ : the educational attainment (-1 for primary education to 0 and 1 for second and tertiary education, respectively). The last term ε represents a residual variable with conditional expected value equal to zero.

21 7. Methodology 7-3. Data This research uses the dataset of the Timor-Leste Labour Force Survey 2010 (TLFS 2010), conducted by the National Statistics Directorate (DNE) in collaboration with the Labour Market Information Department of the Secretariat of State for Vocational Training and Employment (SEFOPE) and with technical support provided by the International Labour Organization (ILO). A representative set of 4,665 households was interviewed, with 252,000 people surveyed, from all districts of Timor-Leste.

22 8.Expected Outcomes 1. The sex variable is significant. 2. There will be a statistically significant difference between the earnings of men and women: men receiving on average higher earnings than women. 3. The age variable (age2) will be negative indicating that the relationship between earnings and age was parabolic, i.e. after a certain threshold, the effect of work experience measured in terms of age had diminishing return on earnings.

23 9. Limitation of the Study Literature Review More literature review is necessary Relationships between Labor market and education Higher education in Timor-Leste Methodology Mincerian equation has many critics. Endogenity (Control for unobserved family background)

24 10. References Agesa, R. U., Agesa, J. and Dabalen, A. (2013). Sources of the persistent gender wage gap along the unconditional earnings distribution: Findings from Kenya. Oxford Development Studies, 41 (1): 76 103. Al-Samarrai, S. and Reilly, B. (2008). Education, employment and earnings of secondary school and university leavers in Tanzania: Evidence from a tracer study. The Journal of Development Studies, 44 (2): 258 288. Becker, G.S. (1962). Investment in human capital: A theoretical analysis. Journal of Political Economy, 70 (Suppl.): 9 49. Deolalikar, A. B. (1993). Gender differences in the returns to schooling and in school enrollment rates in Indonesia. The Journal of Human Resources, 28 (4): 899 932. Doan, T. (2011). Labour Market Returns to Higher Education in Vietnam. Duraisamy, P. (2000). Changes in returns to education in India, 1983-94: By gender, agecohort and location. Economic Growth Center Discussion Paper 815. New Haven, C.T.: Yale University. Dutta, P. V. (2006). Returns to education: New evidence for India, 1983-1999. Education Economics, 14 (4): 431-451. El-Hamidi, F. (2006). General or vocational schooling? Evidence on school choice, returns, and sheepskin effects from Egypt 1998. The Journal of Policy Reform, 9 (2): 157 176.

25 10. References Fasih, T., Kingdon, G., Patrinos, H. A., Sakellariou, C. and Soderbom, M. (2012). Heterogeneous returns to education in the labor market. Washington, D.C.: World Bank. Heckman, J., & Li, X. (2004). Selection bias, comparative advantage and heterogeneous returns to education: Evidence from China in 2000. Pacific Economic Review, 9(3), 155-171. Kimenyi, M. S., Mwabu, G. and Manda, D. K. (2006). Human capital externalities and private returns to education in Kenya. Eastern Economic Journal, 32 (3): 493 513. Lall, A.. (2008). Returns to Education in Cambodia: Results from the 2007 Socio-Economic Survey. Asia Competitiveness Institute, LKY School of Public Policy. Mincer, J. (1974). Schooling, experience and earnings. : National Bureau of Economic Research. New York. Moock, P. R., Patrinos, H. A. and Venkataraman, M. (2003). Education and earnings in a transition economy: The case of Vietnam. Economics of Education Review, 22 (5): 503 510. Psacharopoulos, G. and Patrinos, H.A. (2004). Returns to investment in education: A further update. Education Economics, 12(2), pp.111-134. Sakellariou, C. (2008). Demand for Skills, Supply of Skills and Returns to Schooling in Cambodia., Economic Growth Centre, Working Paper No. 2008/05. Santos,R. (2014). Post-Conflict Returns to Education the Case of Timor-Leste, Institute of Development Studies at the University of Sussex. Teal, F. (2011). Higher education and economic development in Africa: A review of channels and interactions. Journal of African Economies, 20, pp.50 79.