DP2011-17

Measurement of GD P per capita andregional disparities in C h ina, 1979‒2009
Masashi H O SHI N O

Revised April 18, 2011

Measurement of GDP per capita and regional
disparities in China, 1979–2009∗
Masashi HOSHINO†
April 18, 2011

Abstract

This paper analyzes provincial GDP per capita disparities in China from 1979 to 2009.
Provincial GDP per capita of oﬃcial statistical materials has several problems such asproblems of data correctness and reliability, because the data cover the huji populationand the changzhu population. This study compares results using modified changzhu
population GDP per capita data with results using oﬃcial statistical materials. The
empirical results are as follows: (1) Studies since the 1990s have overestimated interprovince disparities; (2) inter-province disparities have decreased since 2005; and (3)The western region has experienced an increase in intra-regional disparities since 2002.
These results suggest that provincial GDP per capita statistics should be used more
carefully.
Keywords: Regional disparities; GDP per capita; Statistics; China
JEL classification: E01, O18, O53, R12, R23∗ This research was supported in part by a grant from the Ministry of Education and Science of Japan, in theform of a grant-in-aid for scientific research on innovative areas, entitled Comparative Research on Major Regional Powers in Eurasia. The author wishes to thank Hiroyuki Kato, Belton Fleisher, Katsuji Nakagane, Shoji
Nishijima, Shinichiro Tabata, Kuanghui Chen, Takashi Oshio, Tomoo Marukawa, Shingo Takagi, TakahiroSato, Hisatoshi Hoken, Tomokazu Nomura, Yoshimichi Murakami, and the seminar participants at the 2009
Annual Meeting of the Japan Association for Asian Political and Economic Studies at Hosei University, andat the 2011 RIEB Kanematsu Seminar at Kobe University for their helpful suggestions and comments on thatdraft. Responsibility for the text (and any surviving errors) rests entirely upon the author.
† Slavic Research Center, Hokkaido University, Kita-9, Nishi-7, Kita-ku, Sapporo, 060-0809, Japan. E-mail:mhoshino@gakushikai.jp1

1

Introduction
China has experienced an increase in regional disparities and rapid growth in its economy

since the adoption of the Reform and Opening Up (gaige kaifang) policy. The Chinese government has realized the significance of regional disparities. In 1995, Chinese policy makers
looked at regional disparities at the Fourth Plenary Session of the 14th Central Committee
held by the National People’s Congress and the Chinese Communist Party for the first timesince the adoption of the Reform and Opening Up policy. In 1997, a decision was made by
the National People’s Congress to implement a balanced regional development strategy. The
Chinese government has launched the Western Development Program (xibu dakaifa) in the
Great Western region since 2000, Revive the Northeast Program (dongbei zhenxing) in thenortheastern region since 2003, and Promotion of the Rise of Central China (Zhongbu jueqi)
in the central region since 2004.
Numerous studies have shown that inter-province disparities in China exhibited a U-shaped
curve during transition, e.g., Tsui [1], Lyons [2], Wu [3], Chen and Fleisher [4], Tsui [5],Nakagane [6], Chen [7], Lin, Cai, and Li [8], Kanbur and Zhang [9], Cai and Du [10], Fujita and Hu [11], Cai, Wang and Du [12], Kato [13], Liu, Wei, and Li [14], Kanbur andZhang [15], and Fleisher, Li, and Zhao [16]. These studies mainly used province-level output
data such as national income utilized or per capita GDP, and they observed that inter-province
disparities in China decreased from 1978 because of decreases in coastal region disparities.
2

In contrast, provincial disparities have grown with increasing disparities between the coastal
and inland regions since the mid- or late 1980s.*1 Hence, many studies have investigatedthe main causes of increasing inter-province disparities during China’s transition phase. For
example, Kato [13] discusses how marketization and privatization impact increasing regional
non-primary industry disparities. Wang and Fan [17] use regional (didai) data to argue that regional productivity disparities aﬀect capital flow among three regions. Liu, Wei, and Li [14]consider regional development strategy and policy, globalization and economic liberalization, and market distortions to be important factors in regional disparities. Fleisher, Li, andZhao [16] study regional growth patterns in China since 2003, they find that human capital
positively aﬀects regional output and regional TFP growth, and the returns to human capital
investment in inland area is higher than that of coastal area. They imply that human capital
investment in poor region contributes to decreases in regional disparities.
It should be noted that several articles have observed decreasing inter-province disparities
in China since the mid-2000s (see Table 1). Xu and Li [18] show that the Gini index ofinter-province nominal GDP per capita disparities declined in 2004. Liu and Zhang [19] use
the Gini index and the coeﬃcient of variation, which reveal that inter-province disparities
decreased from 2000 to 2001 and from 2003 to 2006. Fan and Sun [20], using revised GDP
data after China’s 2004 Economic Census, observe decreasing regional disparities from 2005
to 2006. Chan and Wang [21] show that inter-province disparities decreased in 2000, 2003,*1 Several studies show a sudden dip from 1989 to 1991, e.g., Chen [7] and Kato [13].

3Table1 Literature reviews on decreasing inter-province disparities in China after 2000.
Publication

Type of data (period studied)

Population data(period studied)

Xu and Li [18]sourceMeasurements of inequality (Period of decreasing
regional disparities)
G (2004)30-provinces
nominal
Rocal Statistical Yearbook
GDP per capita (1978–04)(1978–2004)
Liu and Zhang [19]27-provinces 1952 value
50 Years (1952–98); G and CV (2000–01; 03–real GDP per capita
China Statistical Yearbook06); V (2000–01; 05–06)(1952–06)(1999–06)
Fan and Sun [20]31-provinces 2005 value
55
Years(1978–04); CV, T , and G (2005–06)
real GDP per capita
China Statistical Yearbook(1978–92); 31-provinces(2005–06)
2005 value real revised
GDP per capita (1993–06)
Chan and Wang [21]31-provinces 2000 value
China Statistical Abstract CV (2000; 03; 05–06)
real revised GDP per(2000–06)
capita (2000–06)
China Population and EmMLD (2005)
Aoki [22]30-provinces 2000 value
real GDP per capita
ployment Statistics Yearbook (1978–06)(1978–92); 30-provinces
2000 value real revised
GDP per capita (1993–06)
Notes: 50 Years = Comprehensive Statistical Data and Materials on 50 Years of New China (Department ofComprehensive Statistics of the NBS [26]); 55 Years = China Compendium of Statistics 1949–2004 (Department ofComprehensive Statistics of the NBS [27]); G = the Gini index; CV = the coeﬃcient of variation; V = the variance;
T = the Theil index; MLD = the mean logarithmic deviation.

2005, and 2006. Aoki [22] argues that regional disparities have fluctuated since 2005 becauseof variable accuracy in population statistics.
However, these results are open to question. Previous studies have used the questionable
GDP per capita data because their statistical materials are composed of the two-type GDP per
capita data. The former is based on the huji population data. The huji population is registeredwith the police, and such registration does not reflect migration patterns; the huji population
data are based on surveys undertaken by the National Bureau of Statistics (NBS) up until
42004. The huji population in the coastal provinces that have many immigrants, e.g., Shanghai and Guangdong, is underestimated, and that in the inland provinces that are the homeof many immigrants, e.g. Henan, Hubei, Hunan, Chongqing, and Sichuan, is overestimated.
Many studies have neglected inter-province population mobility in China since the 1990s.
The latter is based on the changzhu population data. The changzhu population data reflect theresident population that has stayed in the same area for more than 6 months and indicate migration patterns. The 1990 Population Censuses, 1995 1% Population Sample Survey, 2000
Population Censuses, 2005 1% Population Sample Survey, and annual data since 2006 are thechangzhu population. Previous studies have not used statistical materials such as the Population Censuses but have used the others. The China Statistical Yearbook (NBS [23]), China
Statistical Abstract (NBS [24]), China Population and Employment Statistics Yearbook (Department of Population and Employment Statistics of the NBS [25]), Comprehensive Statistical Data and Materials on 50 Years of New China (Department of Comprehensive Statisticsof the NBS [26]) (50 Years), and China Compendium of Statistics 1949–2004 (Departmentof Comprehensive Statistics of the NBS [27]) (55 Years) are composed of the huji population
data and changzhu population data (see Table 1).
No studies have yet tried to estimate regional disparities after the Reform and Opening Up
policy using the changzhu population GDP per capita data. The studies to give much attention
to the diﬀerence between the huji population and the changzhu population are Groenewold,
Lee, and Chen [28], Fan and Sun [20], and Chan and Wang [21]. Groenewold, Lee, and5

Chen [28] which analyzes inter-regional spillovers in China use huji population GDP per
capita data. Fan and Sun [20], using the huji data, compute population size for 1990, 1995,
2000, and 2005, taking the arithmetic average of each preceding year’s figure and that of
the year that follows. Chan and Wang [21] argue that the NBS revises provincial GDP per
capita based on the changzhu population by 2006, and they calculate inter-province 2000value real GDP disparities from 2000 to 2006. However, according to the footnote on the
China Statistical Abstract 2007, the parts of their data for the period from 2001 to 2004 are
GDP per capita based on the huji population.
The purpose of this paper is to analyze inter-province disparities in China from 1979 to
2009. This study uses modified changzhu population GDP per capita data and compares theresults obtained with the results of using oﬃcial statistical materials, which preceding studies
employ.
This paper is organized as follows. Section 2 discusses the GDP per capita data issues. Section 3 presents the disparity measurement methods. Section 4 provides an empirical analysis
of disparities. The final section oﬀers some concluding remarks.

2 DataThere are several problems in the oﬃcial statistical materials that are composed of the huji
population data and changzhu population data. The objective of this section is to consider the
problem of population statistics and to determine original GDP per capita data on the basis
6

of the 1990 and 2000 Population Censuses and the 2005 1% Population Sample Survey.

2.1

Problems of the China Statistical Yearbook

First, this study considers the changing definition of population statistics in China fromthe China Statistical Abstract and the China Statistical Yearbook.*2 According to the China
Statistical Abstract 2007, 2008, 2009, and 2010, the parts of provincial population data for theperiod from 2001 to 2004 are the huji population. Further, the data of 2005 are based on the2005 1% Population Sample Survey, while the data from 2006 to 2009 are calculated using a
population change sample survey. One cannot compare directly the population data in someprovinces from 2004 with data from 2005, because the data from 2005 include the floating
population (liudong renkou) who resided in the same area for more than 6 months, according
to the China Statistical Yearbook 2006 (see Table 2). Thus, the definition of population
statistics up to 2004 diﬀers from the definition after 2005.
This study discusses the subject from a population growth point of view. Table 3 compares
the provincial population with that of the previous year from 2001 to 2009. The population
data are based on the China Statistical Yearbook.
The point to observe is that the large change in 2005 reflects diﬀerences between the 2004
definition of population statistics and the 2005 definition. For example, the population ofZhejiang increases by more than 1.78 million and the population of Guangdong increases by*2 The China Statistical Yearbook, China Statistical Abstract, China Population Statistics Yearbook, and China

Population and Employment Statistics Yearbook contain the same population data.

7

Table2 Definition of population data in China Statistical Abstract and China Statistical Yearbook
Statistical Materials
Abstract 2002

Definition of Population
Data
The data in 2000 have been estimated on the basis of the 2000 Population
1996–01
Census; others have been estimated on the basis of the annual national sample surveys on population changes.
Yearbook 2002
N. A.
2001
Abstract 2003
N. A.
1997–02
Yearbook 2003
N. A.
2002
Abstract 2004
N. A.
1998–03
Yearbook 2004
N. A.
2003
Abstract 2005
N. A.
1999–04
Yearbook 2005
N. A.
2004
Abstract 2006
N. A.
2000–05
Yearbook 2006
Data of total population by region are based on the 1% Population Sample
2005
Survey with careful consideration of floating population. Thus, the data insome regions are not comparable with those from the preceding year.
Abstract 2007
In 2001–2004, the parts of provincial population data are not the de facto 2000–06
population.
Yearbook 2007
Data in the table are estimates from the 2006 National Sample Survey on
2006
Population Changes. The data are not adjusted on the basis of sampling
errors and survey errors.
Abstract 2008
In 2001–2004, the parts of provincial population data are not the de facto 2001–07
population.
2007
Yearbook 2008
Data in the table are estimates from the 2007 National Sample Survey on
Population Changes. The data are not adjusted on the basis of sampling
errors and survey errors.
Abstract 2009
In 2002–2004, the parts of provincial population data are not the de facto 2002–08
population.
2008
Yearbook 2009
Data in the table are estimates from the 2008 National Sample Survey on
Population Changes. The data is not adjusted on the basis of sampling errors
and survey errors.
Abstract 2010
In 2003–2004, the parts of provincial population data are not the de facto 2003–09
population.
2009
Yearbook 2010
Data in the table are estimates from the 2009 National Sample Survey on
Population Changes. The data are not adjusted on the basis of sampling
errors and survey errors.
Source: China Statistical Abstract (NBS [24]) and China Statistical Yearbook (NBS [23])Notes: Abstract = China Statistical Abstract; Yearbook = China Statistical Yearbook; de facto population (thechangzhu population) = resident population of those who stayed in the same area more than 6 months.

8

Table3 Provincial population compared with the previous year in China, using the China
Statistical Yearbook: 2001–2009 (in 10,000s).
Province
2001
2002
2003
2004
2005
2006
2007
2008
2009
Definition
h&c
h&c
h&c
h&c
c
c
c
c
c
Eastern Region
Beijing
26
40
33
37
45
43
52
62
60
Tianjin
3
3
4
13
19
32
40
61
52
Hebei
25
36
34
40
42
47
45
46
45
Shanghai
▲ 27
11
86
31
36
37
43
30
33
Jiangsu
28
26
24
28
42
75
75
52
48
Zhejiang
17
34
▲ 52
41
178
82
80
60
60
Fujian
30
26
22
23
24
23
23
23
23
Shandong
44
41
43
55
68
61
58
50
53
Guangdong
76
76
95
350
890
110
145
95
94
Hainan
8
7
7
8
10
8
9
9
10
Northeastern Region
Liaoning
10
9
7
7
4
50
27
17
4
Jilin
9
8
4
6
7
7
7
4
6
Heilongjiang
4
2
2
2
3
3
1
1
1
Central Region
Shanxi
24
22
20
21
20
20
18
18
16
Anhui
42
10
72
51
▲ 341
▲ 10
8
17
▲4
Jiangxi
37
36
32
30
27
28
29
32
32
Henan
67
58
54
50
▲ 337
12
▲ 32
69
58
Hubei
15
13
13
15
▲ 306
▲ 17
6
12
9
Hunan
34
33
33
36
▲ 372
16
13
25
26
Western Region
I-Mongolia
6
1
0
5
2
11
8
9
8
Guangxi
38
34
35
32
▲ 229
59
49
48
40
Chongqing
5
10
23
▲8
▲ 324
10
8
23
20
Sichuan
38
33
27
25
▲ 513
▲ 43
▲ 42
11
47
Guizhou
43
38
33
34
▲ 174
27
5
31
5
Yunnan
46
46
43
39
35
33
31
29
28
Tibet
5
4
3
4
3
4
3
3
3
Shaanxi
15
15
16
15
15
15
13
14
10
Gansu
18
18
10
16
▲ 25
12
11
11
7
Qinghai
6
6
5
5
4
5
4
2
3
Ningxia
9
9
8
8
8
8
6
8
7
Xinjiang
27
29
29
29
47
40
45
36
28
Source: Author’s calculations. The calculations are based on population data taken from the China Statistical
Yearbook (NBS [23]).
Notes: Definition = definition of population statistics. h&c = composed of the huji population and changzhu
population. c = the changzhu population. ▲= minus.

9more than 8.9 million. In contrast, the populations of Anhui, Henan, Hubei, Hunan, Guangxi,
Chongqing, Sichuan, and Guizhou decrease by more than one million. In other words, higheconomy eastern region provinces saw an increase in population, and low economy provinces
in other regions saw a decrease. Migrant peasants have emigrated from the central and western regions to the eastern region since the 1990s. In the central and western regions, the huji
population is larger than the changzhu population; in contrast, the changzhu population islarger than the huji population in the eastern region.
The provincial population data of the two statistical materials are questionable, because
they are composed of data on the huji population and the changzhu population until 2004.
Thus, provincial GDP per capita using these population data are open to question.

2.2

Problems of the 55 Years and the 60 Years

There are also some problems in historical statistical materials such as the 55 Years and the
60 Years (the China Compendium of Statistics 1949–2008 (Department of Comprehensive
Statistics of the NBS [29])), which preceding studies use. This study confirms the definitionof provincial population data of the 55 Years and 60 Years and finds three problems.
First, the definitions vary between changzhu and huji. For instance, according to the 55
Years, the definition of the population of Beijing is changzhu (1949–04), that of Tianjin ishuji (1949–86) and changzhu (1987–04), and that of Hebei is huji (1949–04). According to
the 60 Years, the definition of the population of Beijing is huji (1949–81) and changzhu
10

Table4 Definition of provincial population data of the 55 Years and the 60 Years.
Province
55 Years (period of data)
60 Years (period of data)
Diﬀerence
Eastern Region
Beijingc (1949–04)
h (1949–81); c (1982–08)
same
Tianjinh (1949–86); c (1987–04) h (1949–08)
same
Hebei
h (1949–04)
h (1949–81); c (1982–08)
same
Shanghaih (1949–04)
N.A.
same
Jiangsuh (1949–89); c (1990–04) h (1949–89); c (1990–08)
same
Zhejiangh (1949–89); c (1990–04) h (1949–89); c (1990–08)
from 0 to +84
Fujianc (1952–04)
N.A.
from -40 to +16
Shandongc (1949–04)
h (1949–84); c (1985–08)
from -44 to +69
Guangdongh (1949–04)
h (1949–79); c (1980–08)
from +2 to +1306
Hainanc (1950–04)
h (1950–87); c (1988–08)
same
Northeastern Region
Liaoning
h (1949–81); c (1982–04) h (1949–04); c (2005–08)
from -68 to +26
Jilin
h (1949–04)
N.A.
same
Heilongjiangc (1949–04)
h (1949–81); c (1982–08)
same
Central Region
Shanxic (1949–04)
h (1949–81); c (1982–08)
same
Anhui
c (1949–04)
h (1949–08)
from +7 to +233
Jiangxic (1949–04)
h (1949–82); c (1983–08)
same
Henan
h (1949–04)
N.A.
same
Hubei
c (1949–04)
h (1949–81; 08); c (1982–07)
same
Hunan
h (1949–95); c (1996–04) h (1949–08)
same
Western Region
I-Mongoliac (1949–04)
h (1949–89); c (1990–08)
same
Guangxih (1950–91); c (1992–04) h (1949–04); c (2005–08)
same
Chongqingh (1951–04)
h (1951–95); c (1996–08)
from -147 to -351
Sichuanh (1950–04)
h (1950–04); c (2005–08)
same
Guizhouc (1949–04)
h (1949–04); c (2005–08)
same
Yunnanc (1949–04)
h (1949–81); c (1982–08)
same
Tibet
h (1951–04)
h (1951–89); c (1990–08)
from +3 to +11
Shaanxic (1949–04)
h (1949–89); c (1990–08)
same
Gansu
h (1949–89); c (1990–04) h (1949–82); c (1983–08)
from +9 to +13
Qinghaic (1949–04)
N.A.
same
Ningxiac (1949–04)
h (1949–99); c (2000–08)
same
Xinjiangc (1949–04)
h (1949–89); c (1990–08)
same
Source: Author’s calculations are based on population data taken from the 55 Years (Department of Comprehensive
Statistics of the NBS [27]) and the 60 Years (Department of Comprehensive Statistics of the NBS [29]).
Notes: 60 Years = China Compendium of Statistics 1949–2008; Diﬀerence = between Population of 60 Years andthat of 55 Years (in 10,000s); h = the huji population (population of those registered with the police); c = thechangzhu population (resident population of those who stayed in the same area more than 6 months).

11

Table5 Provincial population compared with the previous year in China, using the 60
Years: 1999–2006 (in 10,000s).
Province
Definition
1999
2000
2001
2002
2003
2004
2005
2006
Eastern Region
Beijingchangzhu
12
106
20
40
33
36
45
43
Tianjin
huji
5
2
2
5
7
7
7
10
Hebei
changzhu
45
60
25
36
34
40
42
47
Shanghai
N.A.
7
9
6
7
8
11
8
8
Jiangsuchangzhu
31
114
28
26
25
27
42
75
Zhejiangchangzhu
19
205
17
33
33
40
95
82
Fujianchangzhu
17
94
30
26
22
23
24
23
Shandongchangzhu
45
114
44
41
43
55
68
61
Guangdongchangzhu
228
432
83
109
121
148
83
110
Hainanchangzhu
9
26
8
8
7
7
10
8
Northeastern Region
Liaoningchange 05
13
32
12
8
7
11
48
50
Jilin
N.A.
13
11
10
12
9
3
8
10
Heilongjiangchangzhu
19
15
4
2
2
2
3
3
Central Region
Shanxichangzhu
31
44
24
22
21
21
20
19
Anhui
huji
53
73
47
44
41
51
55
77
Jiangxichangzhu
40
▲ 83
37
37
32
29
28
28
Henan
N.A.
72
101
67
58
54
50
51
52
Hubei
changzhu
31
22
15
13
14
14
15
19
Hunan
huji
30
30
34
33
34
35
34
36
Western Region
I-Mongoliachangzhu
17
11
5
1
1
5
2
6
Guangxichange 05
38
38
37
34
35
32
▲ 229
59
Chongqingchangzhu
▲ 10
▲ 12
▲ 20
▲ 14
▲ 12
▲ 10
5
10
Sichuanchange 05
43
49
29
38
55
66
▲ 383
▲ 43
Guizhouchange 05
52
46
43
39
32
34
▲ 174
27
Yunnanchangzhu
49
48
47
46
43
40
35
33
Tibet
changzhu
4
4
3
4
3
4
3
4
Shaanxichangzhu
22
26
15
15
16
15
15
15
Gansu
changzhu
23
14
18
17
11
15
▲ 24
12
Qinghai
N.A.
7
7
7
6
5
5
5
5
Ningxiachange 00
7
11
9
8
9
8
8
8
Xinjiangchangzhu
28
74
27
29
29
29
47
40
Source: Author’s calculations are based on population data taken from the 60 Years (Department of Comprehensive
Statistics of the NBS [29]).
Notes: ▲ = minus. change 00 = changing huji into changzhu in 2000; change 05 = changing huji into changzhu in
2005.

12

(1982–08), that of Tianjin is huji (1949–08), and that of Liaoning is huji (1949–04) andchangzhu (2005–08) (see Table 4 ).
The second problem is low reliability of the definitions of the 55 Years. In the data of
20 provinces, there are no diﬀerences between the population of 60 Years and that of 55
Years; nevertheless, the definition has changed. To take a simple example, the definition of
Beijing changes from changzhu (1949–04) to huji (1949–81) and back to changzhu (1982–04), although the population data for the period from 1949 to 2004 of 55 Years are the sameas that of 60 Years (see Table 4).
Third, the most recent historical statistical material, namely the 60 Years, has serious problem (see Table 5). Although the definitions of changzhu do not change in 2000, the populations of parts of provinces increase by more than one million. For instance, Beijing’s
population increases by more than 1.06 million, and Guangdong’s increases by more than
4.32 million. The reliability of the definition is called into doubt.

2.3

The Changzhu Population Data

In the analysis, this study uses the Changzhu population data based on the 1982, 1990,
and 2000 Population Censuses and the 2005 1% Population Sample Survey.*3 The modified*3 This study does not use the 1964 Population Censuses because local governments were reported to overesti-

mate the population to the NBS to receive large subsidies after the Great Chinese Famine (Xue, Maeda, andMinami [30]).

13

population data for the period from 1978 to 1982 are based on the China Population Statistics
Yearbook 1990 (Department of Population Statistics of the NBS [31]) and the China Compendium of Statistics 1949–2008; the data for 1982 are based on the 1982 Population Census
of China (Results of Computer Tabulation) (Population Census Oﬃce under the State Council and Department of Population Statistics, State Statistical Bureau, People’s Republic ofChina [32]); the data for 1990 are based on the Tabulation on the 1990 Population Census of
the People’s Republic of China (Population Census Oﬃce under the State Council and Department of Population Statistics, State Statistical Bureau, People’s Republic of China [33])and the Tabulation on the 1990 Population Census of Sichuan Province (Computer Tabulation) (Population Census Oﬃce under Sichuan Province [34]); the data for 2000 are based on
the Tabulation on the 2000 Population Census of the People’s Republic of China (Population
Census Oﬃce under the State Council and Department of Population, Social, Science andTechnology Statistics, NBS [35]); and the data for 2005, 2006, 2007, 2008, and 2009 are
based on the China Statistical Abstract 2010 (NBS [24]). Populations for the period from1983 to 1989 are estimated using the geometric mean of two year’s data, say 1982 and 1990.
For instance, the population for 1983 is calculated by multiplying the geometric mean of thedata for 1982 and 1990 by the population figure of 1982. The calculation of the population
for the periods from 1991 to 1999 and from 2001 to 2004 uses the same methods (see Table
6).

14

Table6 Definition and source of the modified provincial changzhu population dataYears
1979–81Definition
huji

1982

changzhu

1983–89
1990

Close to changzhu
changzhu

1991–99
2000

Close to changzhu
changzhu

2001–04
2005–09

Close to changzhu
changzhu

2.4

Source(1) China Population Statistics Yearbook 1990 (Department of Population
Statistics of the NBS [31]); (2) 60 years (Department of Comprehensive
Statistics of the NBS [29]) (Guangdong, Hainan, Chongqing, and Sichuan)
1982 Population Census of China (Results of Computer Tabulation) (Population Census Oﬃce under the State Council and Department of Population
Statistics, State Statistical Bureau, People’s Republic of China [32])estimated from geometric mean of the data for 1982 and 1990
(1) Tabulation on the 1990 Population Census of the People’s Republicof China (Population Census Oﬃce under the State Council and Department of Population Statistics, State Statistical Bureau, People’s Republicof China [33]); (2) Tabulation on the 1990 Population Census of Sichuan
Province (Computer Tabulation) (Population Census Oﬃce under Sichuan
Province [34]) (Chongqing and Sichuan)
estimated from geometric mean of the data for 1990 and 2000
Tabulation on the 2000 Population Census of the People’s Republic of China(Population Census Oﬃce under the State Council and Department of Population, Social, Science and Technology Statistics, NBS [35])estimated from geometric mean of the data for 2000 and 2005
China Statistical Abstract 2010 (NBS [24])GDP per Capita Data

This study employs the 31 provinces’ data for 1978 real GDP per capita. In order to compare the result using the changzhu population GDP per capita data with the results of previous
studies, this study uses four other statistical publications: the China Statistical Yearbook, 55
Years, 60 Years, and China Population Statistics by County (Ministry of Public Security of
the People’s Republic of China [36]). The China Population Statistics by County is published by the Ministry of Public Security of China, which registers the huji population; all the
population data are for the huji population.
In the analysis, this study uses the average (mid-year population) between the population15

in the previous year and the population of the present year to calculate GDP per capita (Eq.
(1)). Because the population data of oﬃcial statistical publications such as the China Statistical Yearbook, 55 Years, 60 Years, and China Population Statistics by County are year-end
population data, GDP per capita is based on mid-year population, according to this study’s
fact-finding in the NBS on March 16, 2010.

GDP per capitat =GDPt(populationt−1 + populationt )/2(1)

GDP data of China have several problems, such as problems with data correctness andreliability, as shown by Maddison [37], Rawski [38], and Kojima [39]. Even the revised
GDP is open to doubt (Holz [40]). Moreover, the problem is more severe when one turns
from national GDP to provincial GDP, e.g., diaoru diaochu (counting enterprises operating
across provincial borders), panbi (comparing and competing with each other) among local
governments, the fabrications by local governments because of estimations of political leaders’ achievements, the diﬀerences of statistical authorities between NBS and the local Bureauof Statistics, and the data sources according to this study’s fact-finding in the NBS on March
15, 2011, and the research of NBS staﬀ (Xu [41]; Xu [42]; Xu [43]).
Therefore this study uses indices of revised GDP which are more correct and reliable. Indices of GDP for the period from 1979 to 1992 are drawn from Kato and Chen [44]. The
revised indices of GDP for the period from 1993 to 2003, which were adjusted after China’s

16

Table7 Definition and source of indices provincial GDP
Years
1979–92
1993–032004
2005–09

Definitionindices of GDP
the revised indices of GDP adjusted after
China’s first Economic Census conducted in
2004
the repeated revised indices of GDP
the revised indices of GDP adjusted after
China’s second Economic Census conducted in
2008

SourceKato and Chen [44]Data of Gross Domestic Product of China
1952–2004 (NBS, Department of National Accounts [45])China Statistical Yearbook 2008 (NBS [23])China Statistical Yearbook 2010 (NBS [23])first Economic Census conducted in 2004, are published in the Data of Gross Domestic Product of China 1952–2004 (NBS, Department of National Accounts [45]). Furthermore, the repeated revised indices of GDP for 2004 are published in the China Statistical Yearbook 2008
(NBS [23]). Finally, the revised indices of GDP for the period from 2005 to 2008 adjusted
after China’s second Economic Census conducted in 2008 indices of GDP in 2009 and are
published in the China Statistical Yearbook 2010 (NBS [23]) (see Table 7).

2.5

Differences of GDP per Capita

This study analyzes the diﬀerence between the modified changzhu population GDP per
capita data and four other GDP per capita data sets, and it considers the diﬀerences in GDP
per capita of the oﬃcial statistical materials that previous studies use.
Table 8 compares the huji population GDP per capita with the modified changzhu population GDP per capita from 1999 to 2008. The huji population data are taken from the China

17

Table8 Diﬀerences in GDP per capita of the huji: 1999–2008 (percent)
Province
1999 2000
2001
2002
2003
2004
2005
2006
2007
2008
Eastern Region
Beijing
19
21
23
24
26
28
29
31
33
36
Tianjin
6
7
8
8
9
10
10
12
14
18
Hebei
0
0
▲0
0
▲0
▲0
▲0
▲0
▲1
▲2
Shanghai
21
23
25
26
28
29
30
32
34
35
Jiangsu
3
3
3
3
3
3
3
3
3
4
Zhejiang
1
2
2
3
4
5
6
7
8
9
Fujian
2
3
3
4
4
4
4
4
4
4
Shandong
0
0
0
0
0
0
0
0
0
0
Guangdong
13
13
14
15
15
16
16
16
16
16
Hainan
0
▲0
▲0
0
1
1
1
1
▲0
▲1
Northeastern Region
Liaoning
1
1
1
1
1
1
1
1
2
2
Jilin
1
2
2
2
2
2
2
2
1
1
Heilongjiang
▲1
▲2
▲2
▲1
▲0
0
1
1
0
▲0
Central Region
Shanxi
2
2
2
1
1
1
2
1
1
▲0
Anhui
▲5
▲6
▲6
▲6
▲6
▲6
▲6
▲7
▲8
▲9
Jiangxi
▲2
▲3
▲3
▲3
▲3
▲2
▲2
▲2
▲3
▲4
Henan
▲4
▲4
▲4
▲6
▲6
▲5
▲6
▲7
▲9
▲ 10
Hubei
▲1
▲0
▲0
▲2
▲3
▲4
▲4
▲5
▲6
▲6
Hunan
▲3
▲3
▲3
▲3
▲4
▲4
▲5
▲6
▲7
▲8
Western Region
I-Mongolia
▲1
0
1
1
1
1
1
1
0
▲1
Guangxi
▲6
▲7
▲7
▲6
▲6
▲6
▲5
▲5
▲5
▲6
Chongqing
▲1
▲1
▲2
▲4
▲6
▲8
▲ 11
▲ 12
▲ 13
▲ 13
Sichuan
▲2
▲2
▲2
▲3
▲3
▲4
▲5
▲6
▲7
▲8
Guizhou
▲2
▲3
▲4
▲4
▲4
▲4
▲4
▲4
▲5
▲6
Yunnan
4
4
4
4
4
4
4
4
4
3
Tibet
3
4
4
5
5
4
4
4
4
3
Shaanxi
▲0
▲1
▲1
▲0
0
0
0
0
▲1
▲1
Gansu
▲1
▲1
▲1
▲1
▲1
▲1
▲0
▲0
▲1
▲2
Qinghai
1
1
1
3
5
6
7
8
7
5
Ningxia
▲1
▲1
▲1
▲1
▲1
▲1
0
1
0
▲1
Xinjiang
3
3
3
3
3
3
3
3
3
2
Source: Author’s calculations.
Notes: ▲ = minus. Table 8 shows that diﬀerence in GDP per capita using population data of the huji and modified
changzhu population data. The huji data are taken from the China Population Statistics by County (Ministry of
Public Security of the People’s Republic of China [36]).

18

Population Statistics by County. In the wealthy provinces of the eastern region that have
many immigrants, GDP per capita is overestimated. For example, the diﬀerences are 19%
to 36% for Beijing, 6% to 18% for Tianjin, 21% to 35% for Shanghai, and 13% to 16%
for Guangdong. On the other hand, GDP per capita is underestimated for almost all inland
provinces. The diﬀerences are -5% to -9% for Anhui, -4% to -10% for Henan, -3% to -8%
for Hunan, -1% to -13% for Chongqing, and -2% to -8% for Sichuan.
Moreover, there are some diﬀerences in GDP per capita between the oﬃcial statistical publications such as the China Statistical Yearbook, 55 Years, and 60 Years, which are composedof the huji and changzhu population GDP per capita data. In the China Statistical Yearbook,the diﬀerences are from 1% to 8% for Shanghai, from 6% to 13% for Guangdong, from -4%
to -6% for Anhui, from -5% to -7% for Guangxi, from -1% to -8% for Chongqing, and from
-1% to -6% for Sichuan. In the 55 Years, the diﬀerences are from 13% to 29% for Shanghai,
and they are from 7% to 16% for Guangdong from 1995 to 2004. Inland poor provinces havealso underestimated GDP per capita; for instance, the diﬀerences are -5% to -7% for Guangxi,
and they are from -1% to -8% for Chongqing. Even the 60 Years, which most recent historicalstatistical publications, has large diﬀerences. From 1999 to 2008, the diﬀerences are 7% to
19% for Tianjin, 21% to 35% for Shanghai, and -5% to -9% for Anhui.
As a result, the oﬃcial GDP per capita statistics of the wealthy eastern region provinces,e.g., Beijing, Tianjin, Shanghai, and Guangdong, are overestimated through underestimating
19

the population data, and those of the inland provinces are underestimated through overestimating the population data. In the case of the huji population, the population of the wealthy
coastal provinces is overestimated, whereas that of the inland poor provinces is underestimated.
Thus, the provincial GDP per capita data of oﬃcial statistical publications have some problems, such as problems with data correctness and reliability, and previous studies that use
oﬃcial data are open to question. One should note that many previous studies might haveoverestimated inter-province disparities since the 1990s because the oﬃcial statistical publications that the preceding studies use are composed of the huji population and the changzhu
population GDP per capita data.

3 Methods
In order to calculate regional disparities, this study uses five disparity measurements: thepopulation weighted coeﬃcient of variation (CVw ), population weighted Theil index (T w ),Gini index (G), population weighted mean logarithmic deviation (MLDw ), and population
weighted Atkinson index (Aw ).
CVw , T w , MLDw , and Aw are defined as follows:
√∑
CVw =

m
2
j=1 w j (yw j − µw )

µw

20

(2)

Tw =

m
∑
j=1

MLDw =wj

yw j yw j
ln
µw
µw

m
∑

w j lnj=1

Aw = 1 −

{∑
m

(3)

µw
yw j

(4)

(

) }1
yw j 1−ε 1−ε
wj
µw
j=1

f or

ε ≥ 0, ε , 1(5)where m is the number of provinces (m = 31), yw j is GDP per capita of the jth province, w j is
the ratio between the population of the jth province and the total population of all provinces,and µw is the weighted mean of yw j using w j for the weights, or in other words, total GDP of
all provinces divided by the total population of all provinces. The ε of Aw is a measure of thedegree of inequality aversion, or the relative sensitivity to transfers at diﬀerent income levels(ε = 2) (Atkinson [46]).
There are diﬀerences in sensitivity to income mobility in these four measurements. In theorder of CVw , T w , MLDw , and Aw , these measurements have relative sensitivity to transfers
at high income levels (Aoki [47]). T w is more sensitive to change at high income levels than
MLDw (Theil [48]).
Moreover, this study uses two disparity decomposition measurements that are based on T w
and MLDw . Consider the hierarchical structure of a country: country-region-province, thesemeasurements decompose total disparity into intra-region (inter-province) and inter-region

21disparities. They are defined as:nm∑
Yi ∑ Yi jn
Yi j /Yi ∑Yi Yi /Y
Tw =
ln
+
ln
Y j=1 YiXi j /Xi i=1 Y
Xi /X
i=1
n
m
∑
Xi ∑ Xi jn
Xi j /Xi ∑Xi Xi /X
MLDw =ln
ln+
X j=1 Xi
Yi j /Yi i=1 X
Yi /Y
i=1

(6)

(7)

where n is the number of regions (n = 4), X is the total population of all provinces, Xi is the
population of the ith region, Xi j is the population of the jth province in the ith region, Y isthe total GDP of all provinces, Yi is the GDP of the ith region, and Yi j is the GDP of the jth
province in the ith region.*4
G has several definitions. This study uses the definition of G as the area between the 45degree line and the Lorenz curve because this definition considers the population ratio. It isdefined as:
{
m
∑
)}
1 (
G = 2 0.5 −w j cyw j + cyw j−1
2
j=1

f or

yw1 ≤ yw2 ≤ · · · ≤ ywm(10)

where cyw j is the jth cumulative percentage of GDP, and yw j is ranked by lowest GDP per
capita.

*4 If one defines w j = X j /X, yw j = Y j /X j , and µw = Y/X in Eqs. (3) and (4), T w and MLDw are calculated asfollows:
Tw =

m
∑
Yj

Y
j=1

MLDw =

ln

m
∑
Xj
j=1

.

22

X

Y j /Y
X j /Xln

X j /X
Y j /Y

(8)

(9)

4

Results
This study calculated CVw , T w , G, MLDw , and Aw from the five GDP per capita data sets:huji (1982–2008), 55 Years (1979–2004), 60 Years (1979–2008), China Statistical Yearbook

Figure1 Inter-province disparities (CVw ): 1979–2009
0.76
huji
55 Years

60 Years

China Statistical Yearbook

0.68

changzhu
0.60
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: huji = are computed based on the China Population Statistics by County (Ministry of Public Security of thePeople’s Republic of China [36]) population GDP per capita data; 55 Years = are computed based on the China
Compendium of Statistics 1949–2004 (Department of Comprehensive Statistics of the NBS [27]) population GDP
per capita data; 60 Years = are computed based on the China Compendium of Statistics 1949–2008 (Departmentof Comprehensive Statistics of the NBS [29]) population GDP per capita data; chagnzhu = are computed based on
modified changzhu population GDP per capita data (see Table 6). This study uses the mid-year population. Data
sources of Indices of GDP are shown in Table 7. The coeﬃcient of variation (CVw ) is weighted by population.

23

Figure2 Inter-province disparities (T w ): 1979–2009
0.20
huji
55 Years

60 Years
China Statistical Yearbook

0.16

changzhu

0.12
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The Thiel index (T w ) is weighted by population.

(1979–2009), and changzhu (1979–2009). The China Statistical Yearbook and changzhu
contain the same data for the period from 2005 to 2009. The figures present the overall
disparity measures over the period from 1979 to 2009, and the diagram helps to define theresults of the diﬀerences in huji, 55 Years, 60 Years, the China Statistical Yearbook, andchangzhu (Figures 1, 2, 3, 4, 5, 6, 7, 8, and 9). The thin line designates changzhu, and thebroken line designates huji, 55 Years, 60 Years, and the China Statistical Yearbook.

24

Figure3 Inter-province disparities (G): 1979–2009
0.34
huji
55 Years
China Statistical Yearbook
60 Yearschangzhu
0.28

0.22
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The Gini index (G) is ranked by lowest real GDP per capita.

4.1

Inter-province Disparities

These diagrams show two features. First, they suggest that previous studies have overestimated inter-province disparities that occurred since the 1990s. The overall disparity indicesindicated that the disparities of changzhu have been smaller than those of huji, 55 Years, 60
Years , and China Statistical Yearbook since the 1990s. There are large diﬀerences between

25

Figure4 Inter-province disparities (MLDw ): 1979–2009
0.19

huji

55 Years
China Statistical Yearbook
60 Years
0.14
changzhu

0.09
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The mean logarithmic deviation (MLDw ) is weighted by population.

changzhu and the others. For example, the diﬀerences correspond roughly to the decreases
in disparities in the 1980s in Figure 1. The large diﬀerence between the changzhu and thehuji since 1990 indicated inter-province migration, because the changzhu population GDP
per capita reflects migration.
One may recall that numerous previous studies have relied on oﬃcial statistical publications, such as 55 Years, 60 Years, and the China Statistical Yearbook, in which the data arecomposed of data on the huji population and the changzhu population. If one uses the huji
population data, the population of the wealthy coastal provinces is underestimated, whilethat of the inland poor provinces is overestimated. Thus, oﬃcial GDP per capita statistics of26

Figure5 Inter-province disparities (Aw ): 1979–2009
0.27
huji
55 Years
60 Years
China Statistical Yearbook
changzhu

0.20

0.13
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The Atkinson index (Aw ) (ε = 2) is weighted by population.

the wealthy eastern region provinces are overestimated through underestimating the population data, and those of the inland poor provinces are underestimated through overestimating
population data, as shown in Table 8.
Second, inter-province disparities decreased from 2005 at the earliest, according to thechangzhu population GDP per capita. There are diﬀerent results among the disparity measures. For example, CVw declined after 2005 (from 0.654 in 2004 to 0.606 in 2009) (seeFigure 1), T w also declined gradually after 2005 (from 0.159 in 2004 to 0.146 in 2009) (seeFigure 2), G decreased after 2007 (from 0.298 in 2006 to 0.289 in 2009) (see Figure 3), and
MLDw and Aw dipped in 2007 (from 0.143 in 2006 to 0.135 in 2009 and from 0.230 in 200627

to 0.222 in 2009, respectively) (see Figure 4 and 5).
The main point to note is the rapid drop in the data from the China Statistical Yearbook
in 2005. As was mentioned above, the drop in 2005 reflects diﬀerences between the 2004
definition of population statistics and the 2005 definition. If one does not distinguish thechangzhu population from the huji population, one might be misled by this drop.

4.2

Decomposition of Inter-province Disparities

One should distinguish provinces according to economic level. As can be seen in Figure 1,
2, 3, 4, and 5, there were larger declines in the mid-2000s in the order of CVw , T w , MLDw ,and Aw . As mentioned in Section 3, this decline was due to the relative sensitivity to transfers
at high income levels in the order of CVw , T w , MLDw , and Aw .
This study divides the 31 provinces into four regions: the eastern, northeastern, central,
and western regions. The eastern region provinces have experienced rapid growth in theireconomy since the adoption of the Reform and Opening Up (gaige kaifang) policy. Since the2000s, the Chinese government has launched regional development programs in three poor
regions, namely the Western Development Program (xibu dakaifa), the Revive the Northeast
Program (tongbei zhenxing), and the Promotion of the Rise of Central China (zhongbu jueqi).
As a result, the compound annual growth rate of the inland poor provinces has increased
since 2005 (see Table 9). For example, the growth rate of Jilin is 15.2%, that of I-Mongolia
is 18.2%, that of Chongqing is 14.4%, and that of Shaanxi is 14.9%.
28

Table9 Provincial compound annual growth rate in China: 1979–2009 (percent)Eastern Region
Beijing
Tianjin
Hebei
Shanghai
Jiangsu
Zhejiang
FujianShandong
Guangdong
Hainan
Northeastern Region
Liaoning
Jilin
Heilongjiang
Central Region
ShanxiAnhui
Jiangxi
Henan
Hubei
Hunan
Western Region
I-Mongolia
Guangxi
Chongqing
Sichuan
Guizhou
YunnanTibet
Shaanxi
Gansu
Qinghai
Ningxia
Xinjiang

1979–1992

1992–2005

2005–2009

9.3
7.7
9.4
8.0
11.8
12.6
12.8
11.1
14.1
13.1

11.5
12.9
12.1
12.4
13.2
13.7
12.9
13.1
13.8
9.4

11.7
15.8
11.6
11.4
13.7
11.9
13.8
13.3
12.4
12.7

8.5
9.2
7.1

10.2
10.3
9.4

13.9
15.2
11.8

8.2
9.0
8.9
10.2
9.1
8.0

11.6
11.5
10.3
11.7
10.7
10.3

10.6
13.1
12.9
13.0
13.7
13.8

9.7
8.7
8.9
8.6
9.0
10.1
7.1
9.5
8.7
7.7
9.1
11.2

13.4
10.8
10.9
10.5
9.4
9.5
13.1
11.1
10.4
10.0
10.0
9.2

18.2
13.8
14.4
13.4
12.6
11.6
12.4
14.9
11.0
12.6
12.5
10.6

Source: See Table 7.

29

Figure6 Decomposition of inter-province disparities (inter-regional and within-easternregion disparities) (T w ): 1979–2009
0.12
huji
55 Years
China Statistical Yearbook
Within eastern region disparities
60 Yearschangzhu

0.08
55 Yearshuji
60 Years
China Statistical Yearbook
changzhu
Inter-regional disparities
0.03
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: Inter-regional disparities = regional disparities between the eastern, northeastern, central, and westernregions. The Thiel index (T w ) is weighted by population.

This study decomposed total inter-province disparities into inter-regional, within-easternregion, within-northeastern-region, within-central-region, and within-western-region disparities, using the Theil index and the mean logarithmic deviation. The eastern region is defined
as Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, andHainan; the northeastern region, as Liaoning, Jilin, and Heilongjiang; the central region, as

30

Figure7 Decomposition of inter-province disparities (within-northeastern-, -central-, and-eastern-region disparities) (T w ): 1979–2009
0.012

Withinwestern
regiondisparitieshuji
55 Years
60 Years
China Statistical Yearbook
changzhu

0.006

Withinnortheasternregiondisparities
Withincentralregiondisparities

0.000
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The Thiel index (T w ) is weighted by population.

Shanxi, Anhui, Jiangxi, Henan, Hubei, and Hunan; and the western region, as the others.
Figure 6, 7, 8, and 9 displays three features.

First, previous studies overestimatedinter-regional, within-eastern-region, within-northeastern-region, within-central-region, andwithin-western-region disparities that have occurred since the 1990s. All disparity measuresindicated that the disparities of changzhu were smaller than those of huji, the 55 Years, the60 Years, and the China Statistical Yearbook after the 1990s.
Second, inter-regional disparities and within-eastern-region disparities contributed to thedecrease in overall inter-province disparities during the mid-2000s. T w decreased in inter-31

Figure8 Decomposition of inter-province disparities (inter-regional and within-easternregion disparities) (MLDw ): 1979–2009
0.12
huji
55 Years
China Statistical Yearbook
60 Yearschangzhu

0.07
Within eastern region disparities

55 YearsInter-regional disparities

China Statistical Yearbook

0.02
1979

1984

1989

1994

1999

2004

huji
60 Yearschangzhu
2009

Source: Author’s calculations.
Notes: The mean logarithmic deviation (MLDw ) is weighted by population.

regional disparities since 2007 (from 0.096 in 2006 to 0.086 in 2009) and in within-easternregion disparities since 2005 (from 0.053 in 2004 to 0.045 in 2009) (see Figure 6). MLDw
reduced inter-regional disparities after 2005 (from 0.097 in 2004 to 0.087 in 2009) and withineastern-region disparities after 2005 (from 0.029 in 2004 to 0.026 in 2009) (see Figure 8). A
decrease in inter-regional disparities could reflect rapid economic growth as a result of theregional development programs in the northeastern, central, and western regions (see Table
9).
Third, within-western-region disparities have increased rapidly since 2002 (from 0.004 in

32

Figure9 Decomposition of inter-province disparities (within-northeastern-, -central-, and-eastern-region disparities) (MLDw ): 1979–2009
0.018

huji
55 Years
60 Years
China Statistical Yearbook
changzhu

Withinwestern
regiondisparities

0.009

Withincentralregiondisparities

Within northeanternregion disparities
0.000
1979

1984

1989

1994

1999

2004

2009

Source: Author’s calculations.
Notes: The mean logarithmic deviation (MLDw ) is weighted by population.

2001 to 0.011 in 2009, using T w ; from 0.008 in 2001 to 0.017 in 2009 and using MLDw ) (seeFigure 7 and 9). I-Mongolia has experienced the most rapid economic growth of any regionin China since 2002 through its development of natural resources and mining industries. Thisdevelopment lifted the I-Mongolian GDP per capita higher than the average Chinese GDP
per capita in 2005. Further, Chongqing and Shaanxi have experienced accelerated economic
growth since 2005 (see Table 9). On the other hand, Yunnan, Gansu, and Xinjiang havemaintained low economic growth rates.

33

5Conclusions
This paper presented provincial GDP per capita disparities in China from 1979 to 2009.

The provincial GDP per capita of oﬃcial statistical publications that previous studies use
has several problems, such as problems with data correctness and reliability, because thedata of oﬃcial statistical publications are composed of the huji population and the changzhu
population. In order to compare this study’s result using changzhu population GDP per capita
data with results using oﬃcial statistical materials, this study employs provincial real GDP
per capita data. The five data sets are based on modified changzhu population data, the China
Statistical Yearbook, the 55 Years, the 60 Years, and the huji population. The reason for using
the changzhu population GDP per capita data is that the changzhu population better reflects
regional migration.
The empirical results are summarized as follows: (1) Studies since the 1990s have overestimated inter-province disparities, because their GDP per capita data are based on the huji
population and the changzhu population; (2) inter-province disparities have decreased since2005 because of decreases in inter-regional disparities and within-eastern-region disparities;and (3) the western region, which is the poorest region, has seen an increase in intra-regional
disparities since 2002.
These results suggest that provincial GDP per capita statistics should be used more carefully. If this paper does not distinguish the two types of population, this study exaggerates
34

increases in regional disparities since the 1990s and this research may be misled to find decreases in inter-provincial disparities since 2005 by changes in data definition.
Regional disparities and inter-region disparities have decreased in China since the mid2000s. The Chinese government has recognized the importance of regional disparities since
1995, and it launched a regional development program in 2000. Is there a causal relationshipbetween decreases in regional disparities and regional development programs? The question
to consider next is why China has experienced decreases in regional disparities since 2005.

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