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Empirical Analysis on Higher Education Affecting Regional Economic Development: A Case of Jiangxi Province YIN Yahong School of Finance and Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangsu, P.R.China, 330013 [email protected] Abstract: The relation between higher education and regional economy is always the key subject of research on higher education in each country. It will be helpful for higher education and regional economy to close unify, and enable higher education to promote the development of regional economy. This paper analyzes it taking Jiangxi province for example by using empirical means of Augment Dickey-Fuller (ADF) test, co-integration test, Granger causality test and error correction model test, etc. The result of test indicates that higher education is advantageous to economic growth in Jiangxi, but the brain drain restricts this function. Therefore, the local government should take preferential measure to attract domestic and foreign brain and the fund to flow in Jiangxi, and strengthen the effective interaction between higher education and local economy. Keywords: Regional Economy, Higher Education, Jiangxi 1 Introduction Putting education first is a long-range program. Rejuvenating our country through science, technology and education has been the basic national policy. The competition among nations is mainly the economical competition, and is also the competition in the developmental level of productive forces. In a word, it is still the competition in brain, but the brain raised must rely on education. Nowadays, overall national strength and international competitiveness in a country will more and more lie on the development of education and the level of knowledge innovation. Therefore, higher education plays an important role in developing economy. The research on relation between higher Education and economic development has always received attention from many domestic scholars. For example, Che Honghua (2003) studied higher education having a positive effect on regional economy by input-output model. Wang Shoufa (2005) analyzed that higher education made contribution to economic development and thought that higher education positively promoted economic growth in China. Yao Yilong and Lin Xiangli (2005) explained that education had a positive effect on economy of various countries using the correlative data between higher education and economic growth coming from China, USA, UK, Japan etc. Simultaneously, they confirmed that between education and output had bidirectional causal relation. The above scholars mainly studied the relation between higher education and national or regional economy, but there were few about higher education affecting the development of provincial economy. Therefore, this paper analyzes higher education affecting the development of regional economy taking Jiangxi province for example. 2 Promotion of Higher Education on Regional Economy in Terms of Theory 2.1 Higher education provides luxuriant human capital for regional economic development 2.1.1 Higher education providing high-quality labor force for regional economic development The high-quality labor force is essential to regional economic development. In knowledge economy conditions, it is human capital and technological advancement to promote economic growth. And human capital is the essential factor to technological advancement. Without human capital, there is not technology advancement at all. However, human capital and technological advancement close relate to higher education. This means that higher education has been the driving force to promote regional 121 economic development. Firstly, high-quality labor force can make good use of existing resources. Secondly, high-quality labor force enables using other resources to overcome certain scarce resources. Finally, high-quality labor force itself is substitute for natural resource and material capital, knowledge-intensive production is an evident proof. To successfully realize the modern economic growth, education, especially higher education should be strengthen. Only this way, can quality of science and technology of laborer be improved, and limited resources are effectively used so as to realize rich labor force substituting for scarce natural and social resources. 2.1.2 Higher education is advantageous to controlling regional population growth It is well known that there is strategic meaning in controlling population growth to regional economic development; education plays an importance role in controlling population growth. It is obvious that education has an effect on fertility rate. Parents' education background directly affects fertility rate. The higher parents' education background is, the lower the fertility rate is. Contrariwise, the lower parents' education background is, the higher fertility rate is. Education affecting fertility rate has become the important factor which restricts the balance of regional economic development in China to a certain extent. Generally, the more education develops in an area, the higher the quality of labor force is, and the lower fertility rate is. Correspondingly, economic development is also higher. Accordingly, with the development of education, especially higher education, a lower fertility rate will come forth. This will has huge positive effect on regional economic development. 2.2 Higher education impels technological innovation and transforms it into productivity so as to promote regional economic development From a global perspective, high-tech industrial park is established in university centralized area and the high-tech production is vigorously developed, which is principal means to economic development, such as Standford scientific industry park (Silicon Valley) in USA, Boston industrial park, Tsukuba-Agency of industrial science and technology centre in Japan, TAEDOK science and technology centre in South Korea, and so on. Up to 2008, there are 54 state-level economic development zones in China. All of state-level economic development zones depended on local institutes of higher learning or scientific research institute. They powerfully promoted local economic development. In 2008, 54 state-level economic development zone's GDP increased to 1531.5 RMB billion yuan from 462 RMB billion yuan in 2003. These approximately accounted for 3.5 percent of total GDP in the whole. Guangzhou is 114 RMB billion yuan, Tianjin is 106.6 RMB billion yuan, Suzhou industrial park is 100.2 RMB billion yuan, respectively. Therefore, the enterprise in cooperation with university is helpful to education productivity quickly transforming enterprise productivity so as to bring about great economic efficiency. It is advantageous to the common development of education and regional economy. 2.3 Consumption of higher education is the new economic growth source of regional economic development Consumption of higher education drives the development of real estate industry, business, catering which lie to around universities. This expenditure may promote the development of local economy to a certain extent. Moreover, with the expansion of ordinary institutions of higher learning scale, each university is short of hardware facility, especially schoolhouse. Therefore, investment in infrastructure should be increased. Without a doubt, all of these will make positive contribution to local economic development so as to promote regional economic development. 3 Empirical Analyses on Higher Education Affecting the Development of Regional Economy: A Case of Jiangxi Province 3.1 Basic model and data descriptions New theory of economic growth thought that the primary factors which influenced economic growth had material capital, human capital and technological innovation. Simultaneously, it also hypothesized technology advancement was endogenous. Therefore, this paper is taken students enrollment of higher education (Xs) and expenditure of education (Xf) as the index of higher education in Jiangxi to represent 122 the investment of human capital, and investment in fixed assets (Xt) as the investment of material capital. GDP of Jiangxi is taken as the index of economic growth in Jiangxi. The analysis uses data from the period 1980 to 2007. All variables are in log-linear form to avoid heteroscedasticy. The whole data obtains from bureau of statistics of Jiangxi database. Data analysis software uses EViews 5.1. Consequently, we can express the model as follows: LnGDP= β0 + β1 LnXs+ β 2 LnXf + β3 LnXt + ε Where ε is other factors, βi is coefficient estimated. 3.2 Empirical analysis 3.2.1 Unit root test Generally, the false regression should occur if we use time series variables which are instable to carry on regression. Therefore, we should have unit root test to ensure the stationary of each variable at first. In this paper the Augment Dickey-Fuller (ADF) test is used to determine whether the individual variable has unit root. The results of the unit root test are given in table 1. According to the result from table 1, all of variables in level can not refuse the null hypothesis that they have a unit root, which indicates they are non-stationary series, but all the second difference of them are stationary series at 1% or 10% significance level(except LnXt) . That is all the variables are I (2) except that LnXt is I(1). , Variable LnGDP ∆LnGDP -1 Ln Xs () ( ) ∆Ln Xs − 1 Ln x f ( ) ∆Ln x f − 1 Ln x t ∆Ln xt Table 1 Unit Root Test Result, 1980-2007 Testing ADF 1% Critical value 5% Critical value -2.7148 (C,T,2) -4.3561 -3.5950 -3.7495(C,0,3)* -4.3743 -3.6032 -1.5021(C,T,2) -4.3743 -3.6032 -3.7495(C,0,5)* * -2.6243 -1.9498 -4.3943 -3.6122 -1.3188 C,T,2) -7.9545(C,0,3)* * -4.4164 -3.6220 10% Critical value -3.2335 -3.2380 -3.2380 -1.6204 -3.2431 -3.2486 -2.0764(C,T,3) -4.6920(C,0,2)* * -3.2335 -3.2335 ( -4.3561 -4.3561 -3.5950 -3.5950 Note: ** stands for rejecting unit root at 1% significance level; * 10% significance level. ∆ stands for the difference. Three characters in parentheses express intercept, trend, and lag length in the second row, respectively. 0 stands for no trend. 3.2.2 Co-integration test To determine if linear combination of all non-stationary variable have long-run equilibrium relation (co-integration relation), we usually use Johansen co-integration test. The test results are displayed in table 2. Table 2 Johansen Co-integration Test Result Eigenvalue Trace Statistic 5% Critical Value Hypothesized 0.653167 55.14244 47.85613 None * 0.527797 28.66966 29.79707 At most 1 0.316345 9.911006 15.49471 At most 2 0.016008 0.403444 3.841466 At most 3 Note Observed series have intercept but no trend, and lags interval (1, 2). * denotes rejection of the hypothesis at the 0.05 level. : ﹥ According to the result from table 2, 55.14244 47.85613 indicates that linear combination of all non-stationary variable have long-run equilibrium relation, namely trace test indicates 1 co-integrating equation at the 0.05 level. 3.2.3 Granger causality test Although there is long-run equilibrium relation between these variables, we should test it using Granger 123 Causality Test if the causation exists between independent variable and dependent variable. The test results are displayed in table 3. Null Hypothesis B A Table 3 Granger Causality Test A does not Granger Cause B B does not Granger Cause A Ln Xs Ln x t Ln x f Ln Xs Ln x f LnGDP 0.04673 0.04745 0.03026 0.88198 0.06608 Note: Lag length of the causality test between LnGDP and LnXs is 6, LnXf is5, and LnXt is 3. Ln x t 0.05676 、 According to the test result from table 3, we find that (1)LnGDP does not Granger Cause LnXs LnXf and LnXt are rejected because the possibility is very low (not surpass 5%), which means LnGDP is the factor affecting these variables. Namely, economic growth leads the expansion of higher education and the increase of expenditure of higher education as well as investment in fixed assets in Jiangxi. (2) LnXf and LnXt does not Granger Cause LnGDP are rejected because the possibility is very low (not surpass 10%), but LnXs does not Granger Cause LnGDP is accepted, which shows that LnXf and LnXt are the factors affecting LnGDP (except LnXs). This indicates that increase of expenditure of higher education and the expansion of investment scale in fixed assets promote economic growth in Jiangxi, but the expansion of scale in higher education which is taken students enrollment of higher education as the index of higher education does not notably promote economic growth in Jiangxi. The reason is possibly the brain drain, namely most parts of high quality brain trained up by higher education of Jiangxi flow to other areas and do not make corresponding contribution to Jiangxi's economic growth. 3.2.4 Regression analysis Since there is long-run equilibrium relation among these variables and the causation exists between independent variable (except LnXs) and dependent variable, we should carry on regression in OLS on the basis of the model. Estimated result of model is as follows: LnGDP =1.077613 + 1.181455 LnXf + 0.448352 LnXt (10.10567) (-2.01146) (5.963905) ** * **① R =0.852946, R =0.912389, S. E. of regression=0.076614, Durbin-Watson stat=2.05186, F-statistic=72.50623. From the test result, we find that each variable passes t-test. S. E. of regression is 0.076614 and F =72.50623 F0.01 (2, 25) =5.61 indicate that the regression equation is significant at 1% significance level. R 2 =0.958493 and R 2 =0.952389 mean that the model is very good at the fitted. D.W. is 2.05186. It indicates that residual of regression model does not exist autocorrelation because of 1.560=du d du=2.46 at 1% significance level when n =28 k′ =2. Moreover, we carry on unit root test to the residual of estimated model. The test results are displayed in table 4. According to the test result from table 4, we find that the residual of estimated model is stationary serial because it does not exist in unit root at the level so that long-run equilibrium relation among these variables is confirmed. 2 2 ﹥ 4- , ﹤﹤ Table 4 Unit Root Test Result of the Residual of Estimated Equation Testing ADF 1%Critical value 5%Critical value 10%Critical value -14.720 -3.699871 -2.976263 -2.627420 C,0,2 *** Note: *** denotes that testing ADF is significant at 1% significance level. serial Resid01 ( ) In terms of the above analysis, we can find that each variable has significant effect on economic growth of Jiangxi because all variables pass t-test and estimated coefficient are statistically significant, namely, the expenditure of higher education and the investment in fixed assets have a positive effect on economic growth of Jiangxi. We can further find that if total expenditure of higher education increases by 1 percent, GDP in Jiangxi would increase by 1.1815 percent. If total investment in fixed assets rises by 1 percent, GDP in Jiangxi would increase by 0.4484 percent. However, the effect that the expenditure 124 of higher education promotes economic growth of Jiangxi is bigger than that of investment in fixed assets' (1.181455>0.448352). 3.2.5 Error correction model test The above analysis indicates that long-run equilibrium relation among these variables exists, but that the long-run relation can maintain is on the basis of continuously dynamic adjusting in short-run. Thus, to study higher education in Jiangxi how to affect economic growth of Jiangxi, we should set up error correction model which can reflect its adjusting in short-term. The test results are given as follows. ∆LnGDP =0.118859 + 0.171116 ∆LnXf -0.098314 ∆LnX t - 0.99163 EC (-1) ② (2.288477) (0.282928) (-0.210121) (-10.48331)* S. E. of regression=0.11349 Durbin-Watson stat=1.971435 R 2 =0.858083 R 2 =0.869572 F-statistic=46.35538. From the test result, we find that t-statistics in the error correction term, namely EC (-1) is significant, which suggests a stable short-run property of the data exists. The error in each time period converges to its long-run relation. , , , , 4 Conclusion Based on the above analysis, we can come to the conclusion that (1) there is long-run equilibrium relation between the development of higher education and economic growth in Jiangxi. In the long-run, the development of higher education which is taken expenditure of education as the index of higher education promotes economic growth. However, the development of higher education which is taken students enrollment as the index of higher education does not promote economic growth. The reason is possibly the brain drain, namely most parts of high quality brain trained up by higher education of Jiangxi flow to other areas and do not make corresponding contribution to Jiangxi's economic growth. (2) The effect that the expenditure of higher education promotes economic growth of Jiangxi is bigger than that of investment in fixed assets'. Therefore, to make a better use of higher education to serve economic development in Jiangxi and retain the high quality brain trained up by higher education of Jiangxi to serve local economic development, the local government should take preferential measure to attract domestic and foreign brain and fund to flow in Jiangxi, and strengthen the effective interaction between higher education and local economy. Acknowledgement: Research Fund of Education Sciences of Jiangxi 11th Five-Year Planning of 2008, No. 08ZD005. Research Fund of Education Sciences of Jiangxi 11th Five-Year Planning of 2006, No. 06ZD59. References [1]. Che Honghua. Research on Higher Education Driving Regional economy. Dongbei University of Finance and Economics, Master Dissertation, 2003:24 29(in Chinese) [2]. Yao Yilong, Lin Xiangli. Contribution of Education on Economic Growth: International Comparison Based on the multivariable VAR Model. World Economy, 10(2005), p26 31(in Chinese) [3]. Wang Shoufa. Research on the Contribution of Higher Education to the economic Development. Hunan University, Doctoral Dissertation, 2005:77 82(in Chinese) ~ ~ ① ② Note: The t values are in parentheses. **indicates significance at 1% significance level; *5% significance level. The t values are in parentheses. * indicates significance at 1% significance level. 125 ~