The impacts of human capital on economic growth in red river delta’s provinces

56 THE IMPACTS OF HUMAN CAPITAL ON ECONOMIC GROWTH IN RED RIVER DELTA’S PROVINCES Vu Thi Tuyet Mai 1 maivu@neu.edu.vn Dong Thi Yen Phuong 2 phuongphon.1412@gmail.com Abstract: This research paper aims to measure the impacts of human capital on economic growth in Red River Delta by using regression model. The research focuses on identifying the human capital on the framework theory on growth models and examining the economic roles of the human capital regarding the representative parameters. The research shows that human capital has significant roles in economic growth in Red River Delta‟s provinces. In addition, the statistical test shows that the impacts of human capital are varied according to the GDP levels. From a policy perspective, the results urge Vietnam particularly the Red River Delta‟s provinces to have appropriate and focal policies for enhancing the quality of human capital. Keywords: Economic growth model, Economic development, Economic growth, Human capital. 1. Introduction Economic growth is an important goal for the most nations. It is a necessary condition for development of a country and for modern economic restructuring and creating a foundation of human development. At each stage of development, the growth pattern is marked by different emphases. Vietnam has recorded remarkable achievements on the development. From the backward agricultural country in which a large rural population accounting for almost 80% of the total population is engaged in agriculture, Vietnam has gradually built up its facilities and technologies to accelerate industrialization and modernization. From 2001 to now, Vietnam's economic growth rate has continually maintained at a relatively high level compared to the region and the world. In addition, it can be seen that there are the suitable changes of economic structure and steady increase of human development index (HDI) in Vietnam over the past 20 years. The economic growth had achieved the significant rate of 7.51% per year around the period 5 years (2001-2005). This rate had been declined rapidly to 5.88% per year (2011-2015). In addition, Vietnam 1 Assoc. Prof, Dr. Vu Thi Tuyet Mai, Senior Lecturer, Planning and Development Department, National Economics University, Vietnam. 2 Dong Thi Yen Phuong, Student, Planning and Development Department, National Economics University, Vietnam. 57 is facing high risk of middle-income trap due to the slow rise of a per capita income in recent years despite becoming a low-income country since 2008. To struggle with these challenges, Vietnam needs to have an appropriate growth model and a proper development orientation for sustainable development. There are three factors which were often analyzed to explain economic growth, including capital, labor, and TFP. With regards to Vietnam, its growth achievements are mainly due to the accumulation of capital over the past 30 years. However, this economic growth is no longer appropriate as the result of the ineffectiveness of capital. In globalization, the physical capital still plays a crucial role but not much as in the past while the role of intangible capital, especially human capital, is growing. The intangible capital is a very necessary source of capital for companies as it is included in their value. Human capital plays an increasingly important role in the process of economic development: (1) it includes the skills created by education and training so that human capital is a factor in the production process combined with tangible capital and raw (unskilled) labor to create products; (2) it is the knowledge to create creativity, a fundamental element of economic development (Mincer, 1989). In addition, some studies provided human capital as an input to analyze economic growth and showed its positive effects like visible capital with a higher level. However, if the investment in human capital is not good, it will cause negative impacts which lead to reduce the growth. By approaching the GDP from the total income of the population, Borjas and George (2005) showed the positive effect of education on income. Waines (1963) argued that despite the plenty of resources, the lack of highly qualified labor force leads to slow development in developing countries. Thus, Vietnam needs to shift to a technology-based growth model and focus on developing human capital as a result of the higher efficiency of human capital than the physical one. In Vietnam, there are also a number of studies on human capital from different perspectives, stages, and circumstances. In particular, the most recent significant study on the role of human capital in Vietnam's economic growth is "Factors affecting the economic growth of Vietnam's provinces and cities in the period of 2000 - 2006 " of Tran Tho Dat. This study suggests that there were different impacts of human capital on the economic growth of each region. In the South East and South Central, human capital played an active role in regional economic growth. In contrast, there was a negative effect at Red River Delta between 2000 and 2006. The results show that in the Red River Delta, where high qualified labor are trained, human capital has not had a key role. However, is that true for the Red River Delta at the present? As an important region in Vietnam, should Red River Delta's provinces change the growth model to contribute to the overall growth of Vietnam? In order to answer those questions, the study will examine the impact of human capital on the economic growth of the provinces at Red River Delta from 2011 to 2015. 2. Research Methods The study uses expanded Cobb-Douglas function to measure the role of human capital as well as other factors related to economic growth in the Red River Delta region 2011-2015. 58 With Z it = ( FI it , GnR it , Pr it ) Where i is the number of provinces (cities), t is the number of years, A is technological factor, Y is economic growth rate (using GDP value), K is physical capital, H is human capital, L is number of employees, Z is a set of variables contributing to output (including FI: Openness index, GnR: net non-agricultural sector income, Pr: poverty rate) and Uit is error term, indicating the effect of ignored variables Besides, α, β, γ, and θ are the coefficients for the effects of exogenous variables. For the analysis of array data, there are three main regression models: Pooled-OLS model, fixed-effects model (FEM) and random-effects model (REM). Pooled - OLS model : Y it = α 1 + β 1 X 1it + ... + β k X kit + U it Where Y it: is the dependent variable of i in period t, X kit is the independent variable of i in period t, α is an intercept and β k is the coefficient of X. The model assumes that the intercept and the slope coefficient are stable over time. In addition, independent variables must be exogenous variables that are independent of the past, present, and future values of the random error. Therefore, this model can lead to phenomena such as multicollinearity and autocorrelation that reduce the accuracy of the regression results. Considering the correlation among independent variables, if the pair of independent variables has a correlation coefficient more than 0.8, the model has a serious autocorrelation. Also if there exist one or more linear relationships among some of the variables, the model will get multicollinearity. In order to solve these defections, fixed effects model (FEM) or random effects model (REM) are used. Fixed effects model (FEM): Y it = Ci + β * X it + U it Where Y it: is the dependent variable of i in period t, X it is the independent in period t, Ci : the intercept for each unit of study and β is the slope coefficient of the variable X This model assumes the intercept Ci is different from each unit of study, but it was maintained over time. This assumption helps to find out the spatial effects of the data on the regression results, because of the particular characteristics. Random-effects model (REM): This model has the same starting point as the fixed- effects model (FEM) but instead of considering Ci as fixed, this model assumes that it is a variable random with the average value of C1 and the intercept Ci is calculated: Ci = C1 + εi where i = 1, 2, 3 ... n Where ε i is the random error term with a mean value of 0 and the variance is ζε 2 . Therefore, the model is Y = C + β it X it + εi + U it To examine whether the random-effects model is appropriate, the Hausman test is conducted. This test helps answer the question of whether there is a correlation between 59 the independent variables and the random factors of each unit in the model. If there is a correlation, the fixed effects model (FEM) will be chosen and vice versa. In case there is a correlation between U it and independent variable, fixed-effects model will be used. In this study, random-effects model is used to examine the impact of human capital on economic growth, based on statistics in the Red River Delta from 2011 to 2015. 3. Research results 3.1. The economic role of human capital Research indicates that three criteria for measuring human capital, including expenditure on education (EC), life expectancy (LE) and mean years of schooling (of adults) (S) have positive impacts on economic growth of the Red River Delta provinces (Table 1, 2 & 3). In particular, the influence of education expenditure (EC) on economic growth has a coefficient 0.161 (Table 1). The coefficient of life expectancy (LE) is 3.510 (Table 2) and of mean years of schooling is 1.420 (Table 3). The physical capital, labor force, non-agricultural income and trade openness have positive impacts on growth, while the rate of poverty is counterproductive. Table 1: Pooled-OLS regression with human capital measured by expenditure on education (EC) Dependent variable: LnY Coefficient P - value LnK 0.442 0,069 LnL 0.325 0.196 LnEC 0.161 0.445 FI 0.009 0.020 GnR 1,85e-09 0.589 Pr - 0.029 0.263 Source: STATA 12 results of the research team Table 2: Pooled-OLS regression with human capital measured by life expectancy (LE) Dependent variable: LnY Coefficient P - value LnK 0.445 0.070 LnL 0.421 0.040 LnLE 3.510 0.605 FI 0.009 0.022 GnR 2.15e-09 0.529 Pr -0.033 0.222 Source: STATA 12 results of the research team 60 Table 3: Pooled-OLS regression with human capital measured by mean years of schooling in the workforce (S) Dependent variable: LnY Coefficient P - value LnK 0.278 0.245 LnL 0.423 0.027 LnS 1.420 0.036 FI 0.011 0.008 GnR 4.08e-09 0.221 Pr -0.04 0.023 Source: STATA 12 results of the research team Of all three regression models with 3 criteria for measures, the conclusions about the coefficient of estimation are quite consistent. Measured by education expenditure and life expectancy, the human capital represents a positive impact on economic growth in the Red River Delta (the coefficients are 0.199 and 3.107). Whereas mean years of schooling of the workforce and trade openness variables are not reliable enough to conclude. In addition, the results show that while physical capital, labor and net revenue of the non- agricultural sector increase, the economic growth rises; however, the increase in poverty rate has the opposite effect. 3.2 Human capital and economic growth in the Red River Delta Table 4 summarizes the results of the regressions of human capital based on 3 criteria for measures: education expenditure, life expectancy and mean years of schooling in the Red River Delta. Table 4: Random-effects regression (REM) without FI Dependent variable lnY Các thước đo vốn con người Expenditure on education (lnEC) Life expectancy (lnLE) Mean years of schooling (lnS) Independent variable Coefficient Coefficient Coefficient Constant 4.606 -9.433 4.619 lnK 0.272 0.280 0.276 lnL 0.417 0.625 0.632 lnH 0.191 3.205 -0.176 GnR 1.32e-09 1.81e-09 2.14e-09 Pr -0.010 -0.017 - 0.024 Prob > F 0.000 0.000 0.000 Adjusted R-squared 0.8216 0.8171 0.8178 Source: STATA 12 results of the research team 61 In the Red River Delta provinces, 1% increase in expenditure on education in the local budget will make the province's income raise by 0.191% /year with constant conditions. According to actual data, Hung Yen province had the GDP of 2013 at 32,377,375 million VND and education expenditure was 1,234,286 million VND. In 2014, expenditure on education was 1.336.837 million VND, that increased (1336837-1234286) / 1234286 * 100 = 5.8179%. As the above result of regression, GDP in 2014 of Hung Yen would increase by 5.8179 * 0.191% = 1.092%. And in fact, the GDP results of Hung Yen in 2014 reached 34.741.584 million VND, an increase by 1.07302% as compared with 2013. When human capital is measured by expenditure on education, the human capital effect is about 0.191%. This result is quite high with provinces having a low percentage of education expenditure compared to local budgets which is a fact in the Red River Delta provinces, where the share of education expenditure in local budgets is only around 13- 15%, the highest is only up to 20%. The result of life expectancy variable is also quite positive. The coefficient 3.205 indicates that 1% increase in life expectancy makes the local income raises by 3.205% per year (constant conditions). For instance, in 2011, the life expectancy in Hai Duong was 74.1 years while the GDP reached 45,32,000 million VND. Then the life expectancy is 74.446 years until 2012, an increase by (74.446-74.1) / 74.1) * 100 = 0.4676%. According to the regression, the GDP in 2012 of Hai Duong would increase to 0.4676 * 3.205% = 1.4985% and in fact, in 2012, the real statistic was 47,440,000 million VND. This result state that population health has a significant impact on the formation of human capital in each individual. It also shows that local public health concerns are one of the factors contributing to the improvement of the province's human capital as well as the positive effect on ecomomy growth. 4. Conclusions and recommendations By using a random-effects model, based on statistics in Red River Delta provinces, the reseach gets positive and significant results of human capital. On the one hand, the results of research emphasize the positive and theoretical relationship between human capital and economic growth. It also points out this actual impact in case of Red River Delta provinces over period 2011 to 2015 as well as the different influences among regions. From policies perspective, the results urge Vietnam particularly the Red River Delta provinces to have appropriate and focal policies for enhancing the quality of human capital: Regarding expenditure on education, it is really essential to improve its efficiency in all provinces. Despite the increase in education expenditure, its impact on economic growth is the smallest of the three criteria for measuring human capital. As to invest more effectively, it is necessary to focus on renovating and modernizing training programs together with teaching methods. Each province also needs to pay attention to invest in teaching equipment and facilities more suitably. Besides, monitoring local budget should be implemented usually. 62 For life expectancy, improving the quality of health care need to be concerned to enhance the health of the population. Socialization of health care that let citizen directly participate in the monitoring process has been identified as a good solution to increase the efficiency of the public sector. As a high educational and high living standards area in the whole country, Red River Delta should completely utilize this solution. In addition, each province needs to invest in medical equipment and facilities, apply achievements of technology and implement policies to support, ensure the health care for the labor force. Finally, to extend mean years of schooling, education for children of school age needs to be renovated. As children are the future workforce, who contribute decisively to the economic growth, investment in childhood education is the best way to get a long-term impact. Besides, technology must become the top priority even in education and training. The structure of training in Vietnam in general and the Red River Delta in particular still exist many shortcomings when the intellectual force with well training becomes more and more unemployed. It is time to restructure the education and training structure with more effective policies from government and provinces. References 1. Anderson. CA. and M. sJ. Bowden. (1965). Education and Economic Development. Chicago: Aldine Publish Co. 2. Asghar. N.. Awan. A.. & Rehman. H. (2012). Human capital and economic growth in Pakistan: A cointegration and causality analysis. International Journal of Economics and Finance. 4 (4). 135-147. 3. Barro. RJ (1991). Economic growth in a cross section of countries. Quarterly Journal of Economics. 106. 407-443. 4. Barro. R.. & Lee. JW (1997). Determinants of schooling quality. Unpublished manuscript. Harvard University. 5. Bauer. PT. (1957). The Economics of Underdevelopment Coutries. Chicago: University of Chicago Press. 6. Becker. Gary S. (1975). Human Capital: A Theoretical and Empirical Analysis. with Special Reference to Education (2nd ed.). Chicago: University of Chicago Press. 7. Cairncross. A. K. (1963). Factors in Economic Development. New York: Frederick A. Prager. 8. Cobb. CW. & Douglas. PH (1928). A theory of production. American Economic Review. 18 (1). 139-165. 9. Commonwealth Secretariat. (1993). Foundation for the Future - Human Resource Development (Report of the Commonwealth Working Group on Human Resource Development Strategies) . London. 10. Coulombe. S. & Tremblay. JA (2001). Human capital and convergence in Canada. Journal of Economic Studies. 28 (3). 154-180. 11. Dinh Phi Tiger & Duc Hoang. (2014). The impact of human capital on the economic growth of the Mekong Delta. Journal of Economic Development. 27 (2). 02-16. 63 12. Goode. RB (May. 1959). Add to the Stock of Physical and Human Capital. American Economic Review. XLIX. No. 2. 147-155. 13. Goode. RB (May. 1959). Add to the Stock of Physical and Human Capital. American Economic Review. XLIX. No. 2. 147-155. 14. Gujarati. D. (2004). Basic Econometrics 4th ed.. New York: McGraw Hill 15. Ha Thi Thieu Dao & Nguyen Dang Khoa. (2014). The role of human capital for economic growth in the South Central Coast. Journal of Economic Development. 283. 3-19. 16. Harbison. FH (May. 1962). Human Resources Development Planning. International Labor Review. Vol. 85. 2-5. 17. Hausman. AJ (1978). Specification Tests in Econometrics. Econometrica. 46 (6). 1251-1271 18. Ilarbison. F.. and CA Myers. (1963). Education. Manpower and Economic Growth. New York: McGraw-Hill. 19. Kendrick. SW (1956). Productivity Trends: Capital and Labor. Review of Eonomics and Statistics. XXXVIII. No. 3. 248-257. 20. Lau. LJ. Jamison. DT. Liu. SC & Rivkin. S. (1993). Education and economic growth: some cross-sectional evidence from Brazil. Journal of Development. 41. 45-70 21. Liu. C.. & Armer. JM (1993). Education effect on economic growth in Taiwan. Comparative Education Review. 47. 304-321 22. Low Linda. Toh Mun Heng and Soon Teck Wong. (1991). Economics of Education and Manpower Development Issues & Policies In Singapore McGraw Hill. Singapore. 23. Lucas. RE (1988). On the mechanics of economic development. Journal of Monetary Economics. 22. 3-42. 24. Martin. MG & Herranz. AA (2004). Human capital and economic growth in Spanish regions. International A dvances in Economic Research. 10 (4). 257-264. 25. Mincer. J. (1974). Schooling. experience and earnings . New York: Columbia University Press. 26. Mulligan. CB. & Sala-i-Martin. X. (2000). Measuring aggregate human capital. Journal of Economic Growth. 5 (3). 215-252. 27. Ng. YC. & Leung. C. M (2004). Regional economic performance in China: A panel data estimation. RBC Papers on China. Hong Kong Baptist University. 28. Nguyen Thi Tue Anh. (2006). Impact of FDI on economic growth in Vietnam. Sida Project 29. OECD. (2001). The well-being of nations: The role of human and social capital. OECD Publishing. Paris. 30. Romer. PM (1986). Increasing returns and long run growth. Journal of Political Economy. 94. 1002-1037. 31. Romer. PM (1990). Human capital and growth: Theory and evidence. Carnegie Rochester Conference Series on Public Policy. 32. 251-286. 32. Schultz. TP (1961). Investment in human capital. American Economic Review. 51. 1-17. 64 33. Schultz. TW. (1963). The Economic Value of Education. New York: Columbia University Press. 34. Siswantoro. D.. & Tien. M. (2012). Analysis of the impact of growth and poverty in Indonesia: Applying the heterogeneous regression. Chinese Business Review. 11 (7). 620-626. 35. Dinh Thanh & Nguyen Minh Tien. (2014). The impact of FDI on local economic growth in Vietnam. Economic Development Review. HCMC University of Economics. HCM. 283. 21-41. 36. Tran Tho Dat. (2011). Human capital role in growth models. Journal of Economic Research. 393. 3-10. 37. Yonemura. Akio ed. (2007). Universalization of Primary Education in the Historical and Developmental Perspective. Chiba. Japan: Institute of Developing Economies.