Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-1 Lesson 0: Understanding China

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-2 Gross Regional Product of China (100 million yuan) (from Region Gross Regional Product (100 million yuan) Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Tibet Shaanxi Gansu Qinghai Ningxia Xinjiang

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-3 Cross-sectional data Cross-sectional data in statistics and econometrics is a type of one-dimensional data set. Cross-sectional data refers to data collected by observing many subjects (such as individuals, firms or countries/regions) at the same point of time, or without regard to differences in time. Analysis of cross-sectional data usually consists of comparing the differences among the subjects.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-4 Cross-sectional data Region Gross Regional Product (100 million yuan) Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Tibet Shaanxi Gansu Qinghai Ningxia Xinjiang

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-5 Regional Nominal GDP in Year 2004 RegionGDP (100 million yuan) GDP per capita (yuan) Beijing Tianjin Hebei Shanxi Inner Mongolia Liaoning Jilin Heilongjiang Shanghai Jiangsu Zhejiang Anhui Fujian Jiangxi Shandong Henan Hubei Hunan Guangdong Guangxi Hainan Chongqing Sichuan Guizhou Yunnan Tibet Shaanxi Gansu Qinghai Ningxia Xinjiang

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson Regional Nominal GDP Summary Statistics (100 million yuan) Mean Standard Error Median Mode#N/A Standard Deviation Sample Variance Kurtosis1.10 Skewness1.29 Range Minimum Maximum Sum Count31 Tibet Guangdong

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-7 Regional Nominal GDP in Year 2004 (sorted by GDP) RegionGDP (million yuan)GDP per capita (yuan) Tibet Ningxia Qinghai Hainan Gansu Guizhou Xinjiang Chongqing Inner Mongolia Shaanxi Tianjin Jilin Yunnan Shanxi Guangxi Jiangxi Beijing Anhui Heilongjiang Hunan Fujian Hubei Sichuan Liaoning Shanghai Hebei Henan Zhejiang Jiangsu Shandong Guangdong

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson Regional Nominal GDP per Capita Summary Statistics (yuan per person) Mean Standard Error Median Mode#N/A Standard Deviation Sample Variance Kurtosis7.14 Skewness2.50 Range Minimum Maximum Sum Count31 Guizhou Shanghai

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-9 Regional Nominal GDP in Year 2004 (sorted by GDP per capita) RegionGDP (100 million yuan)GDP per capita (yuan) Guizhou Gansu Yunnan Guangxi Shaanxi Anhui Tibet Ningxia Sichuan Jiangxi Qinghai Hunan Shanxi Hainan Henan Chongqing Hubei Jilin Xinjiang Inner Mongolia Hebei Heilongjiang Liaoning Shandong Fujian Guangdong Jiangsu Zhejiang Tianjin Beijing Shanghai

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-10 Time Series Region Gross Regional Product (100 million yuan) Beijing Tianjin Hebei Shanxi Inner Mongolia A time series is a sequence of data points, measured typically at successive times, spaced at (often uniform) time intervals.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-11 Nominal Gross Domestic Product (100 million yuan)

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-12 Per Capita Nominal GDP (yuan per person)

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-13 Nominal GDP and Per Capita nominal GDP

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-14 Nominal GDP and Per Capita nominal GDP

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-15 Real GDP and Per Capita Real GDP

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-16 Panel data Region Gross Regional Product (100 million yuan) Beijing Tianjin Hebei Shanxi Inner Mongolia A data set containing observations on multiple phenomena observed over multiple time periods is called panel data.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-17 Example Financial Intermediation in China All bank financial intermediation rate and GDP per capita in Chinese provinces Note: Excludes Beijing, Tianjin, Shanghai, and Tibet. Source: Park, Albert, and Kaja Sehrt (2001): “Tests of Financial Intermediation and Banking Reform in China,” Journal of Comparative Economics 29: 608–644. Provincial data of 1997 reveals a striking inverse relationship between financial intermediation and GDP per capita. This pattern suggests that the allocation of financial resources across provinces may be highly inefficient, with richer provinces being taxed relative to poorer provinces.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-18 Example Fiscal development in China The negative relationship reveals that the revenue capacity to support the public payroll in poor counties is much weaker than in more developed ones. Economic development level and rent from land development. Source: Zhang, Xiaobo (2006): “Fiscal decentralization and political centralization in China: Implications for growth and inequality,” Journal of Comparative Economics 34: 713–726.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-19 Example Development of Motorcycle industry in China Production grew rapidly in the early 1990s and, by 1995, it exceeded the production peak in 1981 in Japan, which had been the largest producer in the world. The export of motorcycles, mainly to Asia and Africa, began when the growth of domestic consumption stagnated in the late 1990s. Exports have increased rapidly since 2000 reaching three million in 2003, which accounts for 20.6% of the total number of motorcycles produced. (However, these data do not cover small producers operating without government permission.) Source: Sonobe, Tetsushi, Dinghuan Hu, and Keijiro Otsuka (2006): “Industrial development in the inland region of China: A case study of the motorcycle industry,” Journal of Comparative Economics 34: 818–838.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-20 Example Township and village enterprises in China The figure illustrates changes in employment and output value of TVEs in addition to their importance in the national economy over a twenty-year period. The share of TVE output in GDP is measured by the ratio of TVE value- added to national GDP of secondary industry. Initially, COEs were more important than PEs in terms of number of employees and output value but, over time, their positions reversed. Employment in COEs declined to less than 40 million following the record high level reached in 1995 of more than 60 million. By contrast, the employment of PEs shows an upward trend during the period and reaches nearly 100 million by 2002, which accounts for around 20 percent of the rural labor force. Likewise, aggregate output of COEs stagnated at around four trillion yuan since the mid-1990s, whereas the output of PEs grows rapidly from 1992 and reaches nine trillion yuan in This growth of TVEs is attributable to both enterprise privatization and the establishment of private enterprises. Source: Ito, Junichi (2006): “Economic and institutional reform packages and their impact on productivity: A case study of Chinese township and village enterprises,” Journal of Comparative Economics 34: 167–190

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-21 Example Return to Schooling in China The plotted log-income differences may be interpreted crudely as returns to schooling. Assuming a schooling gap between elementary-school and college graduates of 10 to 12 years, the implied marginal rate of return per year of schooling for college graduates was approximately 5.5% shortly after the beginning of the Communist era and it decreased to about half that in the very early years of reform. After reform, the earnings premium for college education accelerated sharply beginning around Source: Fleisher, Belton M., and Xiaojun Wang (2005): “Returns to schooling in China under planning and reform,” Journal of Comparative Economics 33: 265–277.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-22 Example Regional disparities in China On average, the coastal regions registered relatively higher growth than the inland provinces following the reforms and into the 1990s. Although the inland regions experienced growth similar to that of the coastal regions during the 1980s, these regions fell considerably behind their coastal counterparts during the 1990s when real GDP per capita increased by only 95 percent in the inland regions but by 144 percent in the coastal regions. In fact, GDP per capita in purchasing power terms in the coastal regions began to catch up with that of the Southeast Asian emerging economies, e.g., Malaysia, Philippines, Indonesia and Thailand, in the early 1990s and even surpassed that of these countries in 1996 Fu, Xiaolan (2004): “Limited linkages from growth engines and regional disparities in China,” Journal of Comparative Economics 32: 148–164.

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson0-23 Part 1 of Problem set #1 Download xmarriage.xls from our class website and perform the following tasks: Compute the ratio, the registered cross-border marriages per marriage registrations approved in each region, for the year Summarized and briefly describe this ratio of year 2000 across regions. For example, which province has the highest cross- border marriages? Why? Plot the ratio against GDP per capita of year Do you see any relationship between the two variables?

Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson END - Lesson 0: Understanding China