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China is at crossroad – According to Digital Model Analysis According to the Digital Model Analysis based on Penn World Table, which compared the status of civilization progress by comparing the detailed economic data between China and South Korea, there’re lots of phenomenon indicating that . China is at the crossroad of transformation of society. Penn World Table is dedicated to grasp the general trend of economy based on the concrete details of economic data and trade statistics of various countries. Those detailed data may help people find some general trend of development in macro-economy activities through the digitalized system of analysis. Below is a detailed comparison between China and Korea in the aspects of trade and economy. I.Per Capita Income Gap As mentioned above, data from the Penn World Table are used in calculating the income gap. The Penn World Table calculates the real GDP per capita of various countries in international dollars(I$) using 2005 as the base year. According to this analysis, the 1990 per capita income of China resembles the 1963 per capita income of Korea most. Therefore, there was a 27-year gap in terms of per capita income as of 1990. This income gap has been narrowed ever since. As of 2007, there was a 21-year gap between the income levels of the two countries, as shown in Table 1. In estimating and comparing income levels across countries and years, statistical error can arise due to inaccurate growth rate estimates and purchasing power disparities. Therefore, it is more important to find out the general trend of estimation rather to take the estimated numbers seriously. <Table 1> Real GDP per capita of China and Korea (unit: I$, 2005 constant prices) China* | Korea | Time Gap(Years) | 1990 | 1,924 | 1963 | 1,926 | 27 | 1995 | 3,072 | 1970 | 3,030 | 25 | 2000 | 4,400 | 1976 | 4,436 | 24 | 2005 | 6,483 | 1983 | 6,520 | 22 | 2007 | 7,868 | 1986 | 8,093 | 21 | Note: * China Version 2 data are used. This is based on recent modifications of the official growth rate. Source: Alan Heston, Robert Summers and Bettina Aten, Penn World Table Version 6.3, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, August 2009. (http://pwt.econ.upenn.edu/). In order to verify the above estimation, let us estimate the income gap using data from the IMF. IMF publishes time series data of GDP per capita at current and constant prices as well as purchasing power parity(ppp) conversion rate of each country from 1980. Using these database, we can estimate the income gap between China and Korea. First, we can convert the Chinese GDP per capita at current price in yuan into Korean won using ppp conversion rates of two countries. For example, the Chinese GDP per capita at current price in 2010 was 29,669 yuan. Based on ppp conversion rates of two countries, 29,669 yuan in 2010 is as valuable as 5,998,777 won. In order to convert it into real GDP per capita, we use GDP deflator of Korea(base year=2005). Then, 5,998,777 won at 2010 current price is as valuable as 5,360,166 won at 2005 constant price. It implies that the Chinese GDP per capita in 2010 is as valuable as 5,360,166 won in real term when we consider ppp of two countries. In this case, the 2010 per capita GDP of China resembles the 1985 per capita income of Korea most. Therefore, we can conclude that there exists 25-years time gap in term of income level between two countries as of 2010. When we apply the same method, we can also find that the 2007 per capita GDP of China resembles the 1981 per capita income of Korea most. It implies that there was 26-year time gap as of 2007, which is slightly different from the results of Table 1. Even though the estimation of time gap in terms of income level is different from Table 1, we could still find that China has narrowed its income gap with Korea between 2007 and 2010. Another way to verify the income gap is to compare proxy variables that reflect income level. One such variable would be the enrollment rate at the tertiary school. As both Korea and China have been eager to increase the enrollment rate at the higher education as their income level increases, there would be a close relationship between income level and the enrollment rate at the tertiary school. According to World Bank, the 2009 tertiary school enrollment rate of China was 24.5%, which was close to the 1983 tertiary school enrollment rate of Korea. Therefore, we can also conclude that there exists 26-year time gap between two countries, which coincides with the above estimation. Another proxy variable can be the ratio of agriculture to GDP in terms of value-added. As income increases and industrialization proceeds, this ratio would fall both in Korea and China. According to the World Bank, the 2009 agriculture value-added/GDP ratio in China was 10.3%, which was close to the 1989 ratio of Korea. From the above estimations, we can conclude that as of 2009 and 2010, there exists roughly 20- to 25-year time gap in terms of income between Korea and China. As shown in Table 1, China has narrowed the income gap with Korea gradually but continuously since 1990. Considering the fact that the annual average growth rate of Korea has slowed significantly since the mid-1990s, the rate at which China closes this gap in terms of per capita income with Korea is likely to accelerate in the near future. One important feature of the Chinese economy in terms of income is that there exists considerable regional disparities. For example, Fleisher, Li, and Zhao(2010) and Pan and He(2010) analyzed regional inequality in terms of human capital and social capital. Hence, it would be possible that per capita income levels in some regions of China lag far behind the average level of Korea, when residents in some Chinese cities would be almost as wealthy as the average Korean. For example, the GRP(gross regional product) per capita of Beijing in 2007 was 57,277 yuan when the nationwide GDP per capita was 18,934 yuan. On the other hand, the GRP per capita of Guizhou was merely 3,762 yuan, meaning that Beijing’s income is roughly 3 times higher than the national average level and that Guizhou’s income is merely 1/5 of the national average level. As the real GDP per capita of China in 2007 was I$ 7,868 according to Table 1, this implies that Beijing’s real income per capita was I$ 23,803 as of 2007, when Guizhou’s real income per capita was I$ 3,029. In this case, we can say that Beijing’s real per capita income was at par with Korea’s as of 2007, when Guizhou’s real per capita income was close to the real per capita income of Korea in the 1970s. Table 2 shows each region’s real income per capita in I$ and shows the years when Korea’s income level matches each region’s income level. When we calculate the income gap between Beijing and Korea using the IMF database, we can find out that 2007 per capita GRP of Beijing resembles the 1995 per capita GDP of Korea most. Considering the fact that 2007 per capita GDP of China resembled the 1981 per capita GDP of Korea most, it implies that income gap between Beijing and Korea is much smaller than the income gap between China and Korea. Table 2 shows that there is wide range of income levels in various regions in China. Generally speaking, large cities like Beijing, Tianjin, and Shanghai have real per capita income levels that are close to those of Korea in the 2000s. Provinces in the coastal area, such as Shandong, Jiangsu, Zhejiang, and Guangdong, have income levels similar to those of Korea in the 1990s. The western inland areas of China, which are relatively underdeveloped, have income levels similar to those of Korea in the 1970s. <Table 2> Real GRP Per Capita of Each Region (2007) and Matching Years of Korea Regions | Real GRP per capita (I$) | Matching Years | Regions | Real GRP per capita (I$) | Matching Years | Beijing | 23,803 | 2007 | Hubei | 6,964 | 1984 | Tianjin | 18,823 | 2000 | Hunan | 6,016 | 1982 | Hebei | 8,206 | 1986 | Guangdong | 13,671 | 1992 | Shanxi | 7,019 | 1984 | Guangxi | 5,191 | 1977 | Inner Mongolia | 10,525 | 1989 | Hainan | 6,016 | 1982 | Liaoning | 10,659 | 1989 | Chongqing | 6,351 | 1983 | Jilin | 8,526 | 1987 | Sichuan | 5,372 | 1978 | Heilongjiang | 7,678 | 1985 | Guizhou | 3,029 | 1970 | Shanghai | 27,262 | 2007 | Yunnan | 4,365 | 1976 | Jiangsu | 14,029 | 1993 | Tibet | 5,007 | 1977 | Zhejiang | 15,424 | 1994 | Shaanxi | 6,060 | 1982 | Anhui | 5,002 | 1977 | Gansu | 4,291 | 1975 | Fujian | 10,838 | 1989 | Qinghai | 5,899 | 1982 | Jiangxi | 5,233 | 1978 | Ningxia | 6,058 | 1982 | Shandong | 11,520 | 1990 | Xinjiang | 6,989 | 1984 | Henan | 6,665 | 1983 | | | | Source: Calculated by authors using data from http://pwt.econ.upenn.edu/ and China Statistical Yearbook 2008 (China Statistics Press, Beijing, China). II. Export Structure Gap The concern of this paper, however, is not only to measure the income gap but also to estimate the structural time gap between two countries. According to the flying geese hypothesis of Akamatsu(1962), there exists a certain hierarchical order among East Asian economies. Japan has played a leading role in this hierarchy. The second tier of this hierarchy consists of NIEs, and the third tier consists of the ASEAN countries. Recently, the southeast coastal area of China has formed the fourth tier. The comparative advantage of exports shifted from one group of countries to the next group of countries as their industrial structures evolved over time. More specifically, as the labor cost of leading countries increases and as technological transfer from leading countries to following countries takes place, the comparative advantage of exports has changed over time. Following this hypothesis, we can assume that there will be a certain time gap in terms of the export structure among East Asian countries. In particular, it is the concern of this paper to determine this time gap between Korea and China. 1. Structural Gap Based on Rank Correlation Let us first measure the structural time gap based on the export structure. As most exports are manufactured by the manufacturing sector in both countries, this paper focuses on export data from the manufacturing sector only. In particular, this paper uses 150 export commodities classified by the SITC(Rev 2) 3-digit data of the UN. To measure the export structure gap, it is necessary to find the year Korea’s export structure resembles the export structure of 2009 China most. This paper employs Spearman’s rank correlation measure(Rs) to find this. First, we need to assign a rank to each commodity according to its export volume in each country. Then, using the following equation, we can calculate Rs between the 2009 Chinese export data and the Korean export data of various years. |