China component in international income inequality: based on method of controlling economic factors MS 379 China component in international income inequality: based on method of controlling economic factors Abstracts: The contribution of China is the main engine for decline of international income inequality in 1980 s and 1990 s. It is over 100 percent some years. By applying the method of controlling economic factors, it is revealed that though economic growth is the major reason of change of China component, and population is the minor, but it is important. The contribution of population growth to change of China component fluctuates between 32% and 42.7% in 1980 and 1990 s, and that of economic growth does between 57.3% and 68%.Therefore, economic growth of China is the main reason, but population growth also plays an important role for decreasing of international income inequality. Keywords: China Component; Economic Factors; International Income inequality; Population Factors Address for correspondence: Jiang Zhiyong, Room 1404, 13 Xinchengnan Street, Tianhedong Road, Guangzhou 510620, China. Phone: +86 136 6711 0181; E-Mail: hijiangzhiyong@163.com.
Introduction Global income inequality includes world income inequality and international income inequality (Milanovic 2002a; Bourguignon & Morrisson, 2002). World income inequality focuses on the income gap between the persons as world citizen, however international income inequality on the income gap between countries. Almost all researches on international income inequality get the same results that it shows a decreasing trend in 1980 s and 1990 s (Milanovic 2004, 2001a; Melchior et al. 2000; Firebaugh 1999; Theil 1996), and that is not the same as results about world income inequality, in other words, whether world income inequality decreases or rises in 1980 s and 1990 s is till a problem (Milanovic 2002b; Sala-i-Martin 2002a, 2002b; Dowrich & Akmal 2001; Wade 2001; Unite Nation Development Program 1999). China is mainly responsible for decline of international income inequality. Researches have shown (Sala-i-Martin 2002a, 2002b; Melchior et al. 2000; Schultz 1998) that when China is included, international income inequality slides down in 1980 s and 1990 s, but when China is excluded, it shows an increasing trend or no trend (Figure 1, Table 2). The reason is that there has been a fast economic growth in China since 1978,the gap between China and other industrialized countries has been narrowed, and also since China is the most populous country, there are more people with the higher per capita GDP in the world, and consequently international income inequality decreases. Though these researches have found the importance of China for decline of international income inequality, they do not analyze that quantitatively, and do not analyze the contribution of economic growth and population growth of China to the decline of international income inequality. Figure 1 about here 1
Milanovic (2002a, 2004) has analyzed the contribution of China to the change of international income inequality between 1980 and 1998 quantitatively, and found that international income inequality decreases 3.6 Gini points from 1980 to 1998, however Chinese component decreases 5.4 Gini points, and so the change of China component can explain the change of international income inequality fully. But he did not analyze China s contribution from 1978 successively. China economic reform began since 1978, and has had a fast economic growth since 1978. And also successive analysis is necessary condition to understand the importance of China for decline of international income inequality. Schults (1998) decompose the change of international income inequality into two elements: change of economic factors and that of population factors by using the method of controlling the population factors, and finds that the change of population factors, or population growth is not the main reason of change of international income inequality. Milanovic (2002a, 2004) also take advantage of method of controlling population factors to analyze the contribution of triangle countries - USA, China and India - to the change of international income inequality, but does not analyze the contribution of China independently. He finds that the change of triangle component from 1965 to 1980 contributes 104.2% to change of international income inequality, change of economic factors contributes 60.4% and change of population factors does 39.6% to change of triangle component. But the change of triangle component from 1965 to 1998 only contributes 10.9% to that of international income inequality. The structure of the paper is like the following. Section 2 presents the properties of data and methodology. By applying method of controlling economic factors, section 3 analyzes the contribution of change of China component to change of international income inequality, and contribution of economic factors and population factors to change of China component. Section 4 analyzes further. Section 5 gives 2
the conclusion. Data and Methodology The data is taken from PWT (Penn World Table Version 6.1, Heston et al. 2002). This database provides the population and per capita GDP data of most the countries in the world. The population data comes from POP variable in PWT. Considering that analysis of international income inequality concerns with comparison of income between countries (Summers & Heston 1991), the per capita GDP data comes from the RGDP variable in 1996 international price, that is, Purchase Power Parity adjusted per capita GDP in PWT. With development of empirical and theoretical research of inequality, economists have constructed many inequality measures, for example, variance of logarithm of income, Gini index, Generalized Entropy index (Cowell 1995; Cowell & Kuga 1981a, 1981b; Cowell 1977; Theil 1967), Atkinson index (Atkinson 1970). Because of the decomposed properties of Gini index, it is taken as the measure of international income inequality in this analysis. The component related to China in Gini index is taken as the measure of China component. Assume international income distribution is discrete, (x 1m, p 1m), (x 2m, p 2m) (x nm, p nm), x 1m,x 2m x nm are the per capita GDP of n countries respectively, and p 1m,p 2m p nm are the population proportion of n countries respectively to the world population. Let Gm denote the international income inequality of m year expressed by Gini index, then n n j= 1 k= 1 xjm xkm pjm pkm G = (1) m 2 n i = 1 x im p im It can be decomposed into the sum of component of all countries, Gjm, that is 1 n n k = 1 xjm xkm pjm pkm 1 n G = ( ) = G m 2 j = 1 n 2 j 1 jm i 1 x im p im = = (2) 3
Here n k= 1 xjm xkm pjm pkm G =,x jm jm and p jm are per capita GDP and population proportion of n i = 1 x p im im j th country. Let Gcm denote China component. The ratio of change of China component to change of international income inequality between 1978 and m year is the contribution of change of China component to change of international income inequality, denoted by Rcm, then R = G / G = ( G G )/( G G ) (3) cm cm m c1978 cm 1978 m G = G G Here cm c1978 cm G = G G is change of China component, m 1978 m is change of international income inequality. This ratio reflects the contribution of China to change of international income inequality. There are two methods to decompose the change of China component, one is controlling economic factors, and the other is controlling population factors. The method of controlling economic factors is based on the per capita GDP structure of the world in 1978, and it is used in this analysis. Gini index with per capita GDP in 1978 and population proportion of m year is taken as measure of international income inequality with controlling economic factors of m year, denoted by GPm, then n n j= 1 k= 1 xj1978 xk1978 pjmpkm GP = (4) m 2 n i = 1 x i1978 p im It can also be decomposed into the sum of component of all countries. The component related China in this Gini index is the measure of China component with controlling economic factors, or the measure of population factors, denoted by GPcm, then n j= 1 xc1978 xj1978 pcmpjm GP = (5) cm n i = 1 x p i1978 im Here x cm and p cm are per capita GDP and population proportion of China. 4
The change of China component is composed of change of population factors and change of economic factors. Let ΔGPcm denote change of population factors between 1978 and m year, then GP cm = GP c1978 GP cm. The change of economic factors between 1978 and m year is equal to the change of China component minus the change of population factors, denoted by ΔGEcm, then GE = G GP. cm cm cm The ratio of change of population factors to change of China component is the contribution of change of population factors to change of China component, or the contribution of population growth to change of China component, denoted by RPcm, then RP = GP / G (6) cm cm cm The ratio of change of economic factors to change of China component is the contribution of change of economic factors to change of China component, or the contribution of economic growth to change of China component, denoted by REcm, then RE = GE / G (7) cm cm cm The ratio of change of population factors to change of international income inequality is the contribution of change of population factors to change of international income inequality, denoted by SPcm, then SP = GP / G (8) cm cm m The ratio of change of economic factors to change of international income inequality is the contribution of change of economic factors to change of international income inequality, denoted by SEcm, then SE = GE / G (9) cm cm m China Component, Population Factors and Economic Factors 5
It can be seen from Figure 1 that when china is included, international income inequality decreases in 1980 and 1990 s, but when China is excluded, it show an increasing trend. This phenomenon gives intuition that China component can explain the change of international income inequality partially or fully. The empirical analysis below proves that intuition. The international income inequality in 1978, Gm, is 0.594, 1980, 0.59, and 2000, 0.534. The change of international income inequality between 1978 and 1980, ΔGm, is 0.4 percentage point, and then, it become larger and larger, and it is 6 percentage point from 1978 to 2000 (Table 1). The China component in 1978, Gcm, is 0.209,1980, 0.202, and 2000, 0.161. The change of China component from 1978 to 1980, ΔGcm, is 0.7 percentage point, and then it becomes larger and larger, and it is 4.8 percentage from 1978 to 2000. The contribution of change of China component to change of international income inequality, Rcm, is 145.3%, in 1980, and fluctuates from 82% to 145% in 1980 s, and decreases in 1990 s, and is 79% in 2000. It reaches to 289.2% in 1979 (Figure 2). Figure 2 about here Thus, China component is the main engine for decline of international income inequality in 1980 s and 1990 s, and the contribution of China to change of international income inequality is above 100% some year. The reason for the contribution over 100% is that the income gap between industrialized countries and poor countries in Africa and Latin America becomes larger, and that cancels out parts of contribution of China to international income inequality. The change of China component can be decomposed into the change of population factors and the change of economic factors. By applying method of controlling economic factors, it can be got from the analysis below that though the change of population factors is minor reason of change of China 6
component and the change of economic factors is the major, the change of population factors is important. The population factors in 1978, GPcm, is 0.209, 1980, 0.207, and 2000, 0.192. The change of population factors from 1978 to 1980, ΔGPcm, is 0.2 percentage point, and then, it become larger and larger, and it is 1.7 percentage point from 1978 to 2000. The contribution of change of population factors to change of China component, RPcm, is 36. 4% in 1980, and it fluctuate from 32% to 42.7% in 1980 s and 1990 s, and it is 35.3% in 2000 (Figure 3). Figure 3 about here The change of economic factors from 1978 to 1980, ΔGEcm, is 0.4 percentage point, and then, it become larger and larger, and it is 3.1 percentage point from 1978 to 2000. The contribution of change of economic factors to change of China component, REcm, is 63. 6%, and it fluctuate from 57.3% to 68% in 1980 s and 1990 s, and it is 64.7% in 2000 (Figure 4). Figure 4 about here Though population factors is the minor reason for change of China component and economic factors is the major, but it is an important, in other words, the population growth plays an important role for decline of international income inequality. Let analyze that below The contribution of change of population factors to change of international income inequality, SPcm, fluctuates between 26.3% and 61.9% in 1980 s, and shows a decreasing trend in 1990 s, and it is 27.9% in 2000. The contribution of change of economic factors to change of international income inequality, SEcm, fluctuates between 55.7% and 92.5% in 1980 s, and shows a decreasing trend in 1990 s, and it is 51.2% in 2000. 7
Table 1 about here Further Analysis In order to analyze the contribution of change of population factors and economic factors to change China component, the countries chosen should have the data of per capita GDP the in 1978 and population in contemporary year, therefore there are 107 countries chosen in 2000 and 122 countries chosen in 1980 (Table 1). For consistency sake, the same countries are chosen in analysis above on the contribution of change of China component to change of international income inequality. But if only considering the contribution of change of China component to change international income inequality, the data of population and per capita GDP in contemporary year are only needed, so there more countries can be chosen. Even that, the relation between change of China component and change of international income inequality is just the same. Now if only considering the contribution of change of China component to change of international income inequality,rcm, there are 134 countries chosen in 2000 and 125 in 1980. And the contribution is 126.4% in 1980, and fluctuates between 83.4% and 157.2% in 1980 s and decreases in 1990 s, and iis 85.6% in 2000 (Figure 5, Table 2). Figure 5 about here The results is just the same as that of the last section, the change of international income inequality is mainly driven by the change of China component, the contribution of change of China component to change of international income inequality is above 100% some year in 1980 s and 1990 s. The international income inequalities including China and excluding China in Figure 1 are also estimated in this way, considering that there more countries can be chosen. Table 2 about here 8
Conclusions The international income inequality has decreased from 1978 to 2000, and the change of China component is the main engine for that. The contribution of change of China component is above 79% in 1980 s and 1990 s and even over 100% some years. By applying the method of controlling economic factors or controlling population factors, the change of China component is decomposed into change of population factors and economic factors. The former method has been applied in this analysis, and it is revealed that the contribution of change of population factors to change of China component fluctuates between 32% and 42.7% in 1980 and 1990 s, and contribution of change of economic factors does between 57.3% and 68%.Therefore, though economic growth is mainly responsible for change of China component, and population growth is secondary, but it is important, that is, the population growth also plays an important role for change of China component and therefore decline of international income inequality. Acknowledgement Author has benefited from suggestion and criticism of Professor Lin Shaogong, Xu Changsheng and Qi Tongchun. Author is also grated to Jiang Qingyi, Gao Xiuzhen, Cai Jiangwei and Jiang Zhe for their support and Ouyang Jianxin, Yang Min and Dong Jisheng for their help. References Atkinson, A. B. (1970). On the Measurement of Inequality, Journal of Economic Theory 2: 244-263. Bourguignon, F. and C. Morrisson (2002). Inequality among World Citizens: 1820-1992, American Economic Review 92(4): 727-744. 9
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8904. Sala-i-Martin, Xavier (2002b). The World Distribution of Income. NBER Working Paper. No. 8905. Schultz, T. P. (1998). Inequality in the Distribution of Personal Income in the World: How It Is Changed and why, Journal of Population Economics 37(3): 313-329. Summers, R. and A. Heston (1991). Penn World Tables (Mark 5): An Explained Set of International Comparisons, 1950-1988, Quarterly Journal of Economics 106: 327-368. Theil, H. (1967). Economics and Information Theory. Amsterdam: North Holland. Theil H. (1996). Studies in Global Econometrics. Amsterdam: Kluwert Academic Publishers. Unite Nation Development Program (1999). Unite Nation s Human Development Report. Wade, R. (2001). The Rising Inequality of World Income Distribution, Finance and Development. International Monetary Found. December. 11
Figure 1 The curve on top is international income inequality in Gini index, on bottom is that excluding China 12
Figure 2 The contribution of change of China component to change of international income inequality 13
Figure 3 The contribution of change of population factors to change of China component 14
Figure 4 The contribution of change of economic factors to change of China component 15
Figure 5 The contribution of change of China component to change of international income inequality when more countries are chosen 16
Year Num Gm Gcm GPcm Gm Gcm Table 1 GPcm GEcm Rcm RPcm REcm SPcm SEcm 1978 122 0.594 0.209 0.209 0 0 0 0 1979 122 0.593 0.205 0.208 0.001 0.004 0.001 0.003 2.893 0.281 0.719 0.812 2.081 1980 122 0.59 0.202 0.207 0.005 0.007 0.003 0.004 1.453 0.364 0.636 0.528 0.925 1981 122 0.586 0.199 0.205 0.008 0.01 0.004 0.006 1.255 0.368 0.632 0.462 0.793 1982 122 0.577 0.195 0.205 0.018 0.015 0.005 0.01 0.82 0.32 0.68 0.263 0.557 1983 122 0.575 0.192 0.204 0.02 0.017 0.006 0.012 0.875 0.325 0.675 0.285 0.591 1984 122 0.576 0.19 0.203 0.019 0.02 0.007 0.013 1.046 0.343 0.657 0.358 0.687 1985 122 0.577 0.189 0.202 0.018 0.02 0.008 0.013 1.15 0.377 0.623 0.433 0.716 1986 121 0.573 0.187 0.201 0.021 0.023 0.008 0.014 1.076 0.371 0.629 0.399 0.677 1987 121 0.573 0.185 0.2 0.022 0.024 0.009 0.015 1.107 0.377 0.623 0.417 0.69 1988 121 0.574 0.184 0.2 0.021 0.025 0.01 0.015 1.209 0.388 0.612 0.469 0.739 1989 121 0.578 0.185 0.199 0.017 0.024 0.01 0.014 1.447 0.427 0.573 0.619 0.829 1990 121 0.574 0.183 0.198 0.02 0.026 0.011 0.015 1.323 0.422 0.578 0.558 0.765 1991 121 0.568 0.18 0.197 0.026 0.029 0.012 0.017 1.12 0.414 0.586 0.464 0.656 1992 121 0.564 0.177 0.196 0.031 0.032 0.013 0.019 1.044 0.404 0.596 0.422 0.622 1993 121 0.556 0.174 0.195 0.038 0.035 0.014 0.022 0.929 0.39 0.61 0.363 0.567 1994 121 0.553 0.172 0.194 0.041 0.037 0.015 0.023 0.911 0.396 0.604 0.36 0.55 1995 121 0.548 0.169 0.193 0.046 0.04 0.016 0.024 0.866 0.394 0.606 0.342 0.525 1996 122 0.543 0.166 0.192 0.051 0.043 0.017 0.026 0.838 0.398 0.602 0.334 0.505 1997 116 0.543 0.166 0.192 0.052 0.043 0.017 0.026 0.837 0.396 0.604 0.332 0.505 1998 117 0.537 0.163 0.193 0.058 0.046 0.016 0.029 0.795 0.36 0.64 0.286 0.509 1999 112 0.535 0.162 0.193 0.059 0.047 0.016 0.031 0.794 0.342 0.658 0.271 0.523 2000 107 0.534 0.161 0.192 0.06 0.048 0.017 0.031 0.791 0.353 0.647 0.279 0.512 17
Gm Table 2 Year Num Gm Year Num Gm Gm Gcm Gm Gcm Rcm (China excluded) (China excluded) 1950 54 0.522 0.522 1976 118 0.587 0.536 1951 61 0.525 0.525 1977 123 0.588 0.539 1952 62 0.576 0.52 1978 122 0.594 0.544 0.209 0 0 1953 64 0.576 0.521 1979 123 0.591 0.547 0.203 0.004 0.006 1.632 1954 67 0.574 0.516 1980 125 0.587 0.546 0.201 0.007 0.009 1.264 1955 71 0.576 0.522 1981 125 0.584 0.547 0.197 0.01 0.012 1.186 1956 71 0.571 0.522 1982 125 0.575 0.541 0.193 0.02 0.016 0.834 1957 71 0.57 0.52 1983 125 0.573 0.543 0.19 0.021 0.019 0.881 1958 71 0.561 0.511 1984 125 0.574 0.55 0.188 0.02 0.021 1.035 1959 75 0.571 0.521 1985 126 0.574 0.551 0.187 0.02 0.022 1.117 1960 112 0.569 0.529 1986 126 0.571 0.552 0.184 0.023 0.025 1.055 1961 114 0.575 0.527 1987 127 0.57 0.554 0.183 0.024 0.026 1.082 1962 114 0.577 0.53 1988 127 0.571 0.556 0.182 0.023 0.027 1.174 1963 114 0.577 0.53 1989 129 0.575 0.558 0.179 0.019 0.031 1.572 1964 114 0.576 0.531 1990 135 0.571 0.558 0.175 0.023 0.034 1.473 1965 114 0.578 0.54 1991 138 0.559 0.547 0.168 0.035 0.042 1.178 1966 113 0.582 0.545 1992 141 0.554 0.549 0.164 0.04 0.045 1.123 1967 114 0.585 0.545 1993 143 0.547 0.548 0.16 0.047 0.049 1.035 1968 114 0.592 0.545 1994 148 0.543 0.549 0.156 0.051 0.053 1.041 1969 114 0.587 0.54 1995 150 0.538 0.548 0.153 0.056 0.056 1.004 1970 117 0.578 0.526 1996 168 0.535 0.547 0.149 0.06 0.06 1.016 1971 117 0.58 0.528 1997 146 0.534 0.547 0.151 0.061 0.058 0.962 1972 117 0.585 0.533 1998 146 0.527 0.544 0.151 0.067 0.059 0.873 1973 117 0.588 0.538 1999 140 0.526 0.545 0.15 0.068 0.059 0.87 1974 117 0.588 0.537 2000 134 0.524 0.547 0.149 0.07 0.06 0.856 1975 118 0.581 0.532 18