Long-Run Growth Effect of the Physical Capital-Human Capital Complementarity: An Approach by Time Series Techniques
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- Bu səhifədəki naviqasiya:
- Graph 2. GDP Level-K/H Logistic Curve
- Table 1. Dynamic Impulse-Response of Growth Rates to One Standart Physical Capital-Human Capital Ratio Innovation
- Period Japan Norway Sweden Switzerland United Kingdom United States
10 substitutability toward economic growth while stabilizing around the average in the short-run will lead to K/H complementarity in explaining the economic growth process. The above model can be best expressed by logistic curve which has been put forward in our previous study (Erk, Altan and Ateş, 1998) showing why GDP growth rates alter between developed and developing countries.
In brief, increasing at and increasing rate segment of the logistic curve coincides with the developing countries and the increasing at and the decreasing rate segment represent the developed countries slope of the logistic curve alternative growth rates between developed and developing countries.
In testing the formal model, we have the following assumptions; • Labor human capital is far more important than the labor itself in the production process. • Technological change is a function of physical capital growth. • Human capital measured with Barro-Lee data permits human capital in its broadest definition. • Human capital and physical capital factors show complementarity In a dynamic relationship between GDP growth rate and physical capital-human capital concentration ratio, our formal model is given by the following equation: (7)
t t t t H K L B g L A g ε + + = − ) / )( ( ) ( 1
t A(L) and B(L): lag operator K : physical capital H GDP H K e GDP / 1 + = α K/H
11 4. Findings of the Study Looking at the data used to test the model, we have taken human capital data for Austria, Australia, Canada, France, Germany, Italy, Japan, Norway, Sweden, Switzerland, United Kingdom and the United States human capital data from Barro-Lee data set (1993), physical capital stock data from Nehru-Dharashwar (1993) and GDP data from World Bank International Statistics (1994). Human capital and physical capital stock data has been annual data adjusted for quarterly data looking at the flow nature of accumulation in both. GDP data has been corrected for its base year to be 1990. All calculations had been conducted under TSP software (version 1.0A) to test impulse response functions and variance decompositions. Our hypothesis to be tested assumes that innovations towards K/H concentration ratio will to move to averages, in the short run, showing that key factor explaining GDP growth stand from K/H concentration and other variables have zero growth effect in the long-run. Besides this, we also expect short disturbances in the impulse response functions due to the complementarity property of physical capital stock and human capital stock. In the test of dynamic time series analysis, to determine the stationarity of the data, initially ADF test has been used. In this respect all GDP data showed stationary behavior. Some K/H series also showed stationary behavior, while very limited country data showed non- stationary behavior, corrected by taking the differences. In implementing optimal lags for the model Schwartz Information Criteria has been used. Some non-stationary data has shown second degree cointegration.
12 Table 1. Dynamic Impulse-Response of Growth Rates to One Standart Physical Capital-Human Capital Ratio Innovation
Italy 1 0.000 0.000 0.000 0.000 0.000 0.000 2 0.007 0.460 -0.027 -0.031 0.197 0.323 3 0.121 0.719 0.067 -0.058 0.309 0.310 4 0.046 0.583 0.075 -0.076 0.426 0.197 5 0.029 0.243 0.065 -0.086 0.297 0.041 6 0.057 0.122 0.049 -0.091 0.321 -0.069 7 -0.002 -0.200 0.035 -0.092 0.284 -0.132 8 -0.008 -0.254 0.9025 -0.090 0.154 -0.148 9 -0.012 -0.242 0.017 -0.086 0.068 -0.127 10 -0.035 -0.240 0.012 -0.082 0.026 -0.081 11 -0.025 -0.121 0.008 -0.076 -0.043 -0.026 12 -0.026 -0.042 0.005 -0.071 -0.073 0.023 13 -0.025 -0.001 0.004 -0.065 -0.077 0.055 14 -0.014 0.066 0.002 -0.060
-0.070 0.067 15 -0.012 0.063 0.002 -0.055 -0.051 0.059 16 -0.006 0.055 0.001 -0.050 -0.026 0.040 17 -0.002 0.050 0.001 -0.046 -0.003 0.015 18 -0.002 0.017 0.001 -0.042 0.017 -0.008 19 -0.001 0.004 0.000 -0.038 0.029 -0.023 20 -0.002 -0.006 0.000 -0.035 0.034 -0.030 30 -0.008 0.003 0.000 -0.016 -0.008 0.000 40 -0.008 0.000 0.000 -0.010 0.000 0.002 50 -0.008 0.000 0.000 -0.008 0.000 0.000 60 -0.008 0.000 0.000 -0.007 0.000 0.000
1 0.000 0.000 0.000 0.000 0.000 0.000
2 -0.014 0.211 0.135 0.219 0.235 -0.079
3 0.073 0.069 0.072 -0.037 0.313 0.064 4 -0.021 0.045 0.043 0.180 0.194 -0.170 5 -0.160 0.017 0.025 0.134 0.144 -0.201 6 -0.125 0.006 0.013 0.087 0.119 -0.206 7 -0.133 -0.001 0.006 0.073 0.092 -0.175 8 -0.140 -0.004 0.002 0.044 0.071 -0.114 9 -0.103 -0.006 -0.001 0.025 0.055 -0.059 10 -0.069 -0.007 -0.003 0.014 0.043 -0.012 11 -0.038 -0.008 -0.004 0.005 0.033
0.019 12 -0.003 -0.008 -0.004 0.001 0.026 0.034 13 0.020 -0.008 -0.005 -0.001 0.020 0.036 14 0.036 -0.008 -0.005 -0.002 0.016 0.031 15 0.045 -0.009 -0.005 -0.002 0.012 0.022 16 0.044 -0.009 -0.005 -0.002 0.009
0.012 17 0.038 -0.009 -0.005 -0.001 0.007 0.004 18 0.028 -0.009 -0.005 -0.001 0.006 -0.002 19 0.017 -0.009 -0.005 -0.001 0.004 -0.005 20 0.006 -0.009 -0.006 0.000
0.003 -0.006
30 0.002 -0.009 -0.006 0.000
0.000 0.000
40 -0.001 -0.009 -0.006 0.000 0.000
0.000 50 0.000 -0.009 -0.006 0.000 0.000
0.000 60 0.000 -0.009 -0.006 0.000 0.000
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