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Lesson 0:
Understanding China
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-1
Gross Regional Product of China (100 million yuan)
(from http://www.stats.gov.cn/tjsj/ndsj/2005/indexee.htm)
Region
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
Gross Regional Product (100 million yuan)
2000
2001
2002
2003
2004
2478.76
1639.36
5088.96
1643.81
1401.01
4669.06
1821.19
3253.00
4551.15
8582.73
6036.34
3038.24
3920.07
2003.07
8542.44
5137.66
4276.32
3691.88
9662.23
2050.14
518.48
1589.34
4010.25
993.53
1955.09
117.46
1660.92
983.36
263.59
265.57
1364.36
2845.65
1840.10
5577.78
1779.97
1545.79
5033.08
2032.48
3561.00
4950.84
9511.91
6748.15
3290.13
4253.68
2175.68
9438.31
5640.11
4662.28
3983.00
10647.71
2231.19
545.96
1749.77
4421.76
1084.90
2074.71
138.73
1844.27
1072.51
300.95
298.38
1485.48
3212.71
2051.16
6122.53
2017.54
1756.29
5265.66
2246.12
3882.16
5408.76
10631.75
7796.00
3553.56
4682.01
2450.48
10552.06
6168.73
4830.98
4140.94
11735.64
2455.36
597.50
1971.30
4875.12
1185.04
2232.32
161.42
2101.60
1161.43
341.11
329.28
1598.28
3663.10
2447.66
7098.56
2456.59
2150.41
6002.54
2522.62
4430.00
6250.81
12460.83
9395.00
3972.38
5232.17
2830.46
12435.93
7048.59
5401.71
4638.73
13625.87
2735.13
670.93
2250.56
5456.32
1356.11
2465.29
184.50
2398.58
1304.60
390.21
385.34
1877.61
4283.31
2931.88
8768.79
3042.41
2712.08
6872.65
2958.21
5303.00
7450.27
15403.16
11243.00
4812.68
6053.14
3495.94
15490.73
8815.09
6309.92
5612.26
16039.46
3320.10
769.36
2665.39
6556.01
1591.90
2959.48
211.54
2883.51
1558.93
465.73
460.35
2200.15
ECON1003: Analysis of Economic Data
Lesson0-2
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
Lesson0-3
Cross-sectional data
Region
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
Gross Regional Product (100 million yuan)
2000
2001
2002
2003
2004
2478.76
1639.36
5088.96
1643.81
1401.01
4669.06
1821.19
3253.00
4551.15
8582.73
6036.34
3038.24
3920.07
2003.07
8542.44
5137.66
4276.32
3691.88
9662.23
2050.14
518.48
1589.34
4010.25
993.53
1955.09
117.46
1660.92
983.36
263.59
265.57
1364.36
2845.65
1840.10
5577.78
1779.97
1545.79
5033.08
2032.48
3561.00
4950.84
9511.91
6748.15
3290.13
4253.68
2175.68
9438.31
5640.11
4662.28
3983.00
10647.71
2231.19
545.96
1749.77
4421.76
1084.90
2074.71
138.73
1844.27
1072.51
300.95
298.38
1485.48
3212.71
2051.16
6122.53
2017.54
1756.29
5265.66
2246.12
3882.16
5408.76
10631.75
7796.00
3553.56
4682.01
2450.48
10552.06
6168.73
4830.98
4140.94
11735.64
2455.36
597.50
1971.30
4875.12
1185.04
2232.32
161.42
2101.60
1161.43
341.11
329.28
1598.28
3663.10
2447.66
7098.56
2456.59
2150.41
6002.54
2522.62
4430.00
6250.81
12460.83
9395.00
3972.38
5232.17
2830.46
12435.93
7048.59
5401.71
4638.73
13625.87
2735.13
670.93
2250.56
5456.32
1356.11
2465.29
184.50
2398.58
1304.60
390.21
385.34
1877.61
4283.31
2931.88
8768.79
3042.41
2712.08
6872.65
2958.21
5303.00
7450.27
15403.16
11243.00
4812.68
6053.14
3495.94
15490.73
8815.09
6309.92
5612.26
16039.46
3320.10
769.36
2665.39
6556.01
1591.90
2959.48
211.54
2883.51
1558.93
465.73
460.35
2200.15
ECON1003: Analysis of Economic Data
Lesson0-4
Regional Nominal GDP in Year 2004
Region
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
GDP (100 million yuan)
4283.31
2931.88
8768.79
3042.41
2712.08
6872.65
2958.21
5303.00
7450.27
15403.16
11243.00
4812.68
6053.14
3495.94
15490.73
8815.09
6309.92
5612.26
16039.46
3320.10
769.36
2665.39
6556.01
1591.90
2959.48
211.54
2883.51
1558.93
465.73
460.35
2200.15
GDP per capita (yuan)
37058
31550
12918
9150
11305
16297
10932
13897
55307
20705
23942
7768
17218
8189
16925
9470
10500
9117
19707
7196
9450
9608
8113
4215
6733
7779
7757
5970
8606
7880
11199
ECON1003: Analysis of Economic Data
Lesson0-5
2004 Regional Nominal GDP
Summary Statistics (100 million yuan)
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
Ka-fu Wong © 2007
5265.82
783.88
3495.94
#N/A
4364.43
19048264.72
1.10
1.29
15827.92
211.54
16039.46
163240.43
31
ECON1003: Analysis of Economic Data
Tibet
Guangdong
Lesson0-6
Regional Nominal GDP in Year 2004 (sorted by GDP)
Region
Tibet
Ningxia
Qinghai
Hainan
Gansu
Ka-fu Wong © 2007
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
GDP (million yuan)
211.54
460.35
465.73
769.36
GDP per capita (yuan)
7779
7880
8606
9450
1558.93
5970
1591.90
2200.15
2665.39
2712.08
2883.51
2931.88
2958.21
2959.48
3042.41
3320.10
3495.94
4283.31
4812.68
5303.00
5612.26
6053.14
6309.92
6556.01
6872.65
7450.27
8768.79
8815.09
11243.00
15403.16
15490.73
16039.46
4215
11199
9608
11305
7757
31550
10932
6733
9150
7196
8189
37058
7768
13897
9117
17218
10500
8113
16297
55307
12918
9470
23942
20705
16925
19707
ECON1003: Analysis of Economic Data
Lesson0-7
2004 Regional Nominal GDP per Capita
Summary Statistics (yuan per person)
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count
Ka-fu Wong © 2007
14079.39
1912.88
9608.00
#N/A
10650.44
113431828.11
7.14
2.50
51092.00
4215.00
55307.00
436461.00
31
ECON1003: Analysis of Economic Data
Guizhou
Shanghai
Lesson0-8
Regional Nominal GDP in Year 2004
(sorted by GDP per capita)
Region
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
GDP (100 million yuan)
1591.90
1558.93
2959.48
3320.10
2883.51
4812.68
211.54
460.35
6556.01
3495.94
465.73
5612.26
3042.41
769.36
8815.09
2665.39
6309.92
2958.21
2200.15
2712.08
8768.79
5303.00
6872.65
15490.73
6053.14
16039.46
15403.16
11243.00
2931.88
4283.31
7450.27
GDP per capita (yuan)
4215
5970
6733
7196
7757
7768
7779
7880
8113
8189
8606
9117
9150
9450
9470
9608
10500
10932
11199
11305
12918
13897
16297
16925
17218
19707
20705
23942
31550
37058
55307
ECON1003: Analysis of Economic Data
Lesson0-9
Time Series

A time series is a sequence of data points, measured typically at
successive times, spaced at (often uniform) time intervals.
Region
Gross Regional Product (100 million yuan)
2000
2001
2002
2003
2004
Beijing
2478.76
2845.65
3212.71
3663.10
4283.31
Tianjin
1639.36
1840.10
2051.16
2447.66
2931.88
Hebei
5088.96
5577.78
6122.53
7098.56
8768.79
Shanxi
1643.81
1779.97
2017.54
2456.59
3042.41
Inner Mongolia
1401.01
1545.79
1756.29
2150.41
2712.08
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-10
Nominal Gross Domestic Product (100 million yuan)
160000
140000
120000
100000
80000
60000
40000
20000
0
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
Year
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-11
Per Capita Nominal GDP (yuan per person)
12000
10000
8000
6000
4000
2000
0
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
Ka-fu Wong © 2007
Year
ECON1003: Analysis of Economic Data
Lesson0-12
Nominal GDP and Per Capita nominal GDP
160000
140000
120000
100000
80000
60000
40000
20000
0
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
Year
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-13
Nominal GDP and Per Capita nominal GDP
4000
nominal GDP index (year 1978=100)
Per capita nominal GDP index (year 1978=100)
3500
3000
2500
2000
1500
1000
500
0
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
Ka-fu Wong © 2007
Year
ECON1003: Analysis of Economic Data
Lesson0-14
Real GDP and Per Capita Real GDP
1200
Real GDP index (year 1978=100)
Per capita Real GDP index (year 1978=100)
1000
800
600
400
200
0
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
1979
1978
Year
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-15
Panel data

A data set containing observations on multiple phenomena
observed over multiple time periods is called panel data.
Region
Gross Regional Product (100 million yuan)
2000
2001
2002
2003
2004
Beijing
2478.76
2845.65
3212.71
3663.10
4283.31
Tianjin
1639.36
1840.10
2051.16
2447.66
2931.88
Hebei
5088.96
5577.78
6122.53
7098.56
8768.79
Shanxi
1643.81
1779.97
2017.54
2456.59
3042.41
Inner Mongolia
1401.01
1545.79
1756.29
2150.41
2712.08
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-16
Example
Financial Intermediation in China
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.
All bank financial intermediation rate and GDP per capita in Chinese provinces 1997.
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.
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-17
Example
Fiscal development in China
Economic development level and rent from land development.
The negative
relationship reveals that
the revenue capacity to
support the public
payroll in poor counties
is much weaker than in
more developed ones.
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
Lesson0-18
Example
Development of Motorcycle industry in China
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
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.)
ECON1003: Analysis of Economic Data
Lesson0-19
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 valueadded 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 2001. 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
Lesson0-20
Example
Return to Schooling in China
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
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 1990.
Lesson0-21
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
Lesson0-22
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
2000.
 Summarized and briefly describe this ratio of year 2000 across
regions. For example, which province has the highest crossborder marriages? Why?
 Plot the ratio against GDP per capita of year 2000. Do you see
any relationship between the two variables?
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-23
Lesson 0:
Understanding China
- END -
Ka-fu Wong © 2007
ECON1003: Analysis of Economic Data
Lesson0-24