The Research on Human Capital and Economic Development of Reservoir Area
--Based on the Empirical Study of Yunyang
Zhuo Ren1, Jia-jun He2
1
The College of Economy and Management, Wuhan University, Wuhan, P.R.China.
The Yangtze River Engineering Supervision and Consultation Co., LTD, Wuhan, P.R.China.
(syrenzhuo@hotmail.com)
2
Abstract - By doing so, the paper tried to investigate the
relationship between human capital and economy
development in Yunyang reservoir area from the
perspective of human capital. A composite evaluation
indicator system of human capital for Yunyang is formed on
the basis of previous research, according to which the
regional human capital evaluation model and human capital
index (H) is obtained by factor analysis and regression
analysis. Furthermore, a mathematical model is built
through correlation Analysis between H (as well as three key
elements) and the regional per capita GDP, which make it
possible to provide quantitative advices on the policy
decision-making with respect to the effect of human capital
investment on economic development in Yunyang reservoir.
Keywords - Regional human capital composite index;
Economy development; Evaluation model; Empirical Study
I. INDICATOR SELECTION AND CALCULATION
OF REGIONAL HUMAN CAPITAL COMPOSITE
EVALUATION SYSTEM
Taking the features of Yunyang reservoir in Three
Gorges Project into account, indicators from the aspects of
formal education, vocational training, health care and
social security are selected according to the principle of
data accuracy and availability. The final list of composite
evaluation indicator system is presented in table 1.
According to the accessible data in hand, there are
missing values in college and above proportion in total
population, health expenditure, Social Security
expenditure and pension and social assistance expenditure,
which requires curve fitting for the missing data in the first
place.
A regression analysis (t=1 to t=17) of curve fit for the
entire period was applied on the data from 1992 to 2008.
The curve fitting models are analyzed by SPSS17.0 and
the best fit models are selected by the value of R2,
independent variable t-test, F-test value and p(sig) ①,②.
①
The data and specific process can be obtained by contacting
II. THE REGIONAL HUMAN CAPITAL COMPOSITE
INDEX OF YUNYANG RESERVOIR AREA
A. Factor Analysis on Regional Human Capital
The calculation results from SPSS17.0 showed that
the KMO value of indicator samples is 0.665, the Approx
Chi-Square of Bartlett test is 257.918, and the significance
probability of  is 0.000 (less than 1%), which means
that the data is statistically correlated. The rotated
component matrix is presented in table 2.
In the table 2, the common factor X1 is defined as
“population quality, medical technology and social
security”, which is also called “Human Capital Quality”;
the common factor X2, which is positively affected by
health expenditure proportion in GDP and education fund
proportion in GDP, is defined as “government human
capital investment”; the common factor X3 is defined as
“education and health service quality” which includes
“doctors per 10000 persons, hospital beds per 10000
persons, teacher to student ratio of middle school and
teacher to student ratio of primary school”.
In factors, the common factor X1 makes the greatest
contribution to H, which is 46.349%, while the
contribution from X2 and X3 is 22.453％ and 18.545％
respectively. As a result, it is the improvement of medical
technology and social security that is essential for the
improvement of human capital in Yunyang reservoir.
Increasing investment on medical and health services and
education, as well as improving health services and
education quality are also required accordingly.
2
B. Calculation of Regional Human Capital Composite
Index (H)
The factor score function of the initial variables on
the common factors of human capital in Yunyang
reservoir area is also conducted.
The score functions of the three principal components
are as follows:
X1=-0.049*H13+0.203*H15+0.146*H19-0.020*H33-0.14
8* H34+0.162*H35+0.228*H40；
（1）
X2=0.384*H11+0.396*H30；
（2）
the author.
②
“Social security expenditure ”has no statistical significance,
so we considered replacing the indicator.
X3=0.011*H31+0.255*H32+0.118*H17+0.070*H18（3
）
TABLE I
THE REGIONAL HUMAN CAPITAL COMPOSITE EVALUATION INDICATOR SYSTEM
Level Ⅰindicators
Level Ⅱindicators
Level ⅢIndicators
Unit
Education Expenses Proportion in GDP
college and above proportion in total population
College students (specialist included) proportion
in total population
Education（H1）
high school students proportion in total population
teacher to student ratio of high school
teacher to student ratio of secondary school
teacher to student ratio of junior high school
teacher to student ratio of primary school
vocational education fund proportion in GDP
Regional Human Capital
Composite Evaluation Indicator
System
emigrant vocational education fund proportion
in immigration investment
vocational training
（H2）
%
trainee proportion in labor force
health expenditure proportion in GDP
doctors per 10000 persons
hospital beds per 10000 persons
Health（H3）
health professionals proportion in medical staff
practicing (assistant) doctors proportion in medical staff
registered nurses proportion in medical staff
Social Security expenditure proportion in GDP
Social Security（H4）
pension and social assistance expenditure proportion in GDP
endowment insurance proportion in total population
basic medical insurance proportion in total population
TABLE II
THE ROTATED COMPONENT MATRIXES
Component
X1
X2
education fund proportion in GDP
0.364
0.797
X3
college and above proportion in total population
0.467
0.742
middle school students proportion in total population
0.968
0.227
students admitted to university proportion in high school students
0.847
0.481
0.159
health expenditure proportion in GDP
-0.129
0.867
0.397
doctors per 10000 persons
-0.778
-0.262
0.134
hospital beds per 10000 persons
0.179
0.637
0.685
health professionals proportion in medical staff
0.481
0.111
-0.683
practicing (assistant) doctors proportion in medical staff
0.03
-0.111
-0.913
registered nurses proportion in medical staff
0.919
0.351
pension and social assistance expenditure proportion in GDP
0.937
0.114
Teacher-student ratio of middle school
-0.862
0.436
Teacher-student ratio of primary school
-0.818
Scores of the three common factors are calculated
according to the score functions, and the composite score
of regional human capital are also obtained by weighting
calculation on the common factor scores.
The weight of each factor can be calculated by the
following formula:
Xn 
0.485
A. Econometric Model of Regional Human Capital and
Economic Development
Based on the regression analysis on per capita GDP
and human capital, we chose H as the independent
variable and per capita GDP of Yunyang as dependent
variable to establish the econometric model.
A linear regression of regional human capital to per
capita GDP is conducted by “enter regression” method
provided in SPSS17.0 with data obtained from the
previous analysis. The regression result is:
factor var iance contributi on rate
 100％
cumulative contributi on rate
（4）
According to the formula and the data, the weights of
X1, X2 and X3 are 53.06%, 25.71% and 21.23%
respectively. As follows is the calculation formula of
Regional Human Capital Composite Index of Yunyang
reservoir area:
H＝0.5306 *X1+0.2571* X2+0.2123* X3
0.24
Y＝-2903.951＋101.953H
R2=0.696, F = 34.285, P=0.0001;
The F-test and p-value indicates that the regression
model is statistically significant. According to the model,
the regional per capita GDP increases by 101.95 Yuan for
1 unit increase in H. 69.6％ of the changes of per capita
GDP can be explained by H, which has a significant effect
on per capita GDP.
（5）
Z score standardization (Z=(X-X')/S) is used to
standardize the common factors: X stands for the initial
score, X' stands for average of initial scores and S stands
for the standard deviation of initial scores. What’s more,
the analysis process required Z score to be converted into
T score (H): The average of the normalized Z score is 50
and the standard deviation is 10, so T=10Z+50.
As an increasing function, the value interval of
Regional human capital composite index (H) is (0, 100): H
= 0 represents the minimum stock of human capital, while
H = 100 represents the maximum stock of human capital.
B. Relationship Analysis between Regional Human
Capital Elements and Economic Development
Previous data analysis demonstrated that the main
elements that affected the regional human capital level of
Yunyang reservoir are X1, X2 and X3 in order of
decreasing importance.
The econometric model is thus established with the
three elements as independent variable and per capita
GDP of Yunyang as dependent variable. Using backward
regression provided in SPSS17.0, we converted the three
indicators of regional human capital into T score and
carried out a linear regression to per capita GDP, the result
of which is presented in table 3.
III. YUNYANG RESERVOIR HUMAN CAPITAL
ECONOMIC GROWTH RELATIONAL MODEL
TABLE III
THE ANALYSIS ON THE RELATIONSHIP BETWEEN REGIONAL HUMAN CAPITAL ELEMENTS AND ECONOMIC DEVELOPMENT
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.928a
.860
.828
506.90988
Coefficients
a
Model
1
Unstandardized Coefficients
B
Std. Error
Standardized Coefficients
Beta
t
Sig.
(Constant)
-2721.708
781.710
-3.482
.004
TX1③
103.859
15.367
.850
6.758
.000
TX2
40.826
16.706
.334
2.444
.030
TX3
-46.377
15.611
-.379
-2.971
.011
a. Dependent Variable: per capita GDP
③
（6）
TX1stants for the value of X1 that has been T- score converted, so does TX2 and TX3.
The model function can be obtained accordingly:
Y＝－2721.708＋103.859TX1＋40.826T X2－46.377T
X3＋ε
（7）
R2=0.86, adjusted R2=0.828, F statistic is 26.67;
Therefore the model passed the significance test, so are
X1, X2 and X3, which means that the components of
human capital all have significant correlation with
regional economic development.
According to the model, per capita GDP increases by
103.86 Yuan for 1 unit increase of TX1 (population
Quality, medical technology and social security level);
increases by 40.83 Yuan for 1 unit increase of TX2 (level
of Government investment on human capital); decreases
by 46.37 Yuan for 1 unit increase of TX3 (education and
③
health service quality) .
IV. CONCLUSIONS AND POLICY SUGGESTIONS
The study used 17-year macro statistical data of
Yunyang reservoir to establish a regional human capital
econometric model and obtained the regional human
capital composite index H and what’s more, the
econometric model on H (as well as three elements) and
regional per capita GDP.
The evaluation model on regional human capital
presented in the paper is predictive to the change of human
capital stock. According to the H-function equation,
Yunyang reservoir should put most attention on raising
medical technology and social security level, increasing
investment on medical, health services and education, and
improving health services and education quality to
improve the human capital level.
According to the econometric model on H and the
regional per capita GDP, when H increases by 1 unit, the
regional per capita GDP increases by 101.95 Yuan.
According to the econometric model on H elements and
per capita GDP, when TX1 (population Quality, medical
technology and social security level) increases by 1 unit,
per capita GDP increases by 103.86 Yuan; when TX2
(level of Government investment on human capital)
increases by 1 unit, per capita GDP increases by 40.83
Yuan; when TX3 (education and health service quality)
increases by 1 unit, per capita GDP decreases by 46.37
Yuan. In combination with the H evaluation model, the
conclusions provide useful perspectives for the
immigration investment policy decision-making.
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