Chinas war against the many faces of poverty towards a new long march

China’s War against the Many
Faces of Poverty

China’s War against the Many Faces of Poverty measures multidimensional
poverty in China and deprivation related to income, education, health issues, living
standards and social security. The book adopts a well-developed methodology
using three different empirical datasets to analyse aspects of regional diversity across
rural and urban and migrant populations of China.
The book also analyses the links between development policies considered by
the government and the various facets of poverty in light of rapid economic
growth and addresses important policy implications.
In the existing literature, in-depth research on multidimensional poverty in
China is almost non-existent. This book is a pioneer study in this important
field of research. Its innovative approach in concepts and methodologies and
its analysis of policy implications make this book a definitive and valuable addition
to the literature.
Jing Yang is Lecturer at Jiangxi Agricultural University, China.
Pundarik Mukhopadhaya is Associate Professor at the Department of Economics,
Macquarie University, Australia.


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122 China’s War against the
Many Faces of Poverty
Towards a new long march
Jing Yang and Pundarik
Mukhopadhaya


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China’s War against the
Many Faces of Poverty
Towards a new long march

Jing Yang and Pundarik
Mukhopadhaya


First published 2016
by Routledge
2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN
and by Routledge
711 Third Avenue, New York, NY 10017
Routledge is an imprint of the Taylor & Francis Group, an informa
business
© 2016 Jing Yang and Pundarik Mukhopadhaya
The right of Jing Yang and Pundarik Mukhopadhaya to be
identified as authors of this work has been asserted by them in
accordance with sections 77 and 78 of the Copyright, Designs
and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or
reproduced or utilised in any form or by any electronic,
mechanical, or other means, now known or hereafter invented,
including photocopying and recording, or in any information
storage or retrieval system, without permission in writing from the
publishers.
Trademark notice: Product or corporate names may be trademarks
or registered trademarks, and are used only for identification and
explanation without intent to infringe.

British Library Cataloguing in Publication Data
A catalogue record for this book is available from the British
Library
Library of Congress Cataloging-in-Publication Data
Names: Yang, Jing, 1982- author. | Mukhopadhaya, Pundarik,
author.
Title: China’s war against the many faces of poverty : towards a
new long march / by Jing Yang and Pundarik Mukhopadhaya.
Description: Abingdon, Oxon ; New York, NY : Routledge, 2016. |
Series: Routledge studies in development economics ; 122
Identifiers: LCCN 2015039767 | ISBN 9781138819603
(hardback) | ISBN 9781315744346 (ebook)
Subjects: LCSH: Poverty—China. | Economic development—
China. | China—Economic conditions. | China—Economic
policy.
Classification: LCC HC430.P6 Y344 2016 | DDC
339.4/60951—dc23
LC record available at />ISBN: 978-1-138-81960-3 (hbk)
ISBN: 978-1-315-74434-6 (ebk)
Typeset in Galliard
by Apex CoVantage, LLC


To my parents Wanxian Yang and Fenglan Peng,
husband Zhanbin Liu, children Jiayang and Mengyang
—Jing Yang
To Chandrama, Proteeti and Prajusha
—Pundarik Mukhopadhaya

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Contents

List of figures
List of tables
Acknowledgements
List of abbreviations

x
xii
xviii
xx

1

Introduction

2

Multidimensional poverty: concept, methodology
and application

17

Income destitution in China and government
attempts to combat it: an overview

65

3

4

5

6

7

1

The measurement of multidimensional
poverty in China: rural–urban, regional and
provincial variations

125

Trends in multidimensional poverty and the
determination of key indicators in rural, urban
and regional China

167

Analysis of the multidimensional poverty
of migrants in comparison with rural and
urban groups (2002–2010)

235

Conclusion

308

References
Index

321
339


Figures

2.1
2.2
3.1
3.2
3.3
4.1
4.2
4.3
4.4
4.5
4.6
4.7
5.1
5.2
5.3
5.4

5.5
5.6
5.7
5.8
5.9
5.10
5.11
5.12
5.13

The link of functioning and capability
Intersection poverty and union poverty
The Urban Pension System (for Employees)
The Urban Pension System (for Non-employees)
The New Rural Pension System
Provinces covered
Urban multidimensional poverty in each region
Rural multidimensional poverty in each region
Overall multidimensional poverty in each region
The provincial contribution to national
multidimensional poverty
The provincial contribution to urban
multidimensional poverty
The provincial contribution to rural
multidimensional poverty
Coverage of the dataset
The trends of multidimensional poverty measurement
The trends of deprivation in each dimension
The distinction of multidimensional poverty measurement
The distinction of deprivation in indicators

The trends in multidimensional poverty measurements
using Weight (II)
The trend of rural multidimensional poverty measurement
The trend of urban multidimensional poverty measurement
Rural–urban ratio of raw headcount ratios: various indicators
and different years
Rural–urban ratio of censored headcount ratios:
various indicators and different years
The trend of multidimensional poverty measurement
in AF approach
The change in M0 in each region
The trend of multidimensional poverty measurement
in TFR approach

19
28
105
105
106
126
137
137
137
157
157
158
169
176
177
187

188
195
200
201
206
207
213
215
218


Figures xi
6.1
6.2
6.3
6.4

The trends in regional multidimensional poverty
measurement
Comparison of the AF multidimensional poverty
measurements (k = 0.2 to 0.6)
Comparison of the AF multidimensional poverty
measurements (k = 0.25 to 0.75)
The comparison of AF multidimensional poverty
measurements (k = 0.2 to 0.6)

252
260
273
284

Tables

A1.1
A1.2
A1.3
A1.4
A1.5
2.1
2.2
2.3
2.4
A2.I.1
A2.I.2
A2.II.1
A2.II.2
A2.II.3
A2.II.4
A2.II.5
A2.II.6
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9

3.10
3.11
3.12
3.13

The global poverty with the $1.25 poverty line
The four stages of China’s development
The Gini coefficient estimated by World Bank and NBS
Urban and rural per-capita disposable income
The statistics of migrants
Some possible dimensions of poverty
Sources of dimensions
The feasible dimensions in Chapters 4 to 6
The dimensions/indicators used in previous literatures
Well-being theories: a summary of the literature
Indicators of capability well-being
Deprivation scores of four individuals
Calculation of weights
The reporting of eigenvalues
The reporting of eigenvectors of retained components
The rescale weights of dimensions for retained
components
The weights of dimensions
Estimation of the FGT index by the World Bank
Other World Bank indicators of development
The ADB’s poverty line and measurement of poverty
Achievement in the MDGs indicators
Progress of the MDGs in China
The four stages of the rural poverty reduction
The rural poverty line, the poor population and the

headcount ratio
Other dimensions of rural development by the NBS
The regional distribution of rural poverty
The poverty headcount ratio from previous studies
The dimensions discussed in the literatures
The evolution of special poverty-alleviation programs
The amount of anti-poverty funding for key counties in
national poverty alleviation

12
13
14
15
16
20
22
24
34
45
46
49
49
51
51
52
52
66
68
70
72

76
77
79
80
81
82
87
92
95


Tables
3.14
A3.I.1
A3.II.1
A3.II.2
A3.II.3
A3.II.4
A3.II.5
A3.II.6
A3.II.7
A3.II.8
A3.II.9
A3.II.10
A3.II.11
A3.II.12
A3.II.13
4.1
4.2
4.3

4.4
4.5
4.6
4.7
4.8
4.9
4.10
4.11
4.12
4.13

The standard minimum wage per month in 2014
Millennium Development Goals
The amount of subsidies to increase agricultural income
Average budget expenditure per student
Expenditure on education
The statistics of the New Cooperative Medical Care
System
The fund collection and payment of the urban medical
insurance system
The statistics of the rural highway
The statistics of electricity
The statistics of methane
The statistics of construction of safe drinking water
The statistics of the rural Minimum Income Guarantee
system
The statistics of the urban Minimum Income Guarantee
system
The statistics of the Urban Pension Insurance System
for Employees

Financial expenditure for the New Pension Insurance
for Rural Residents
The distribution of samples in CFPS
The dimensions, indicators and their cut-offs
The weights of each dimension and indicator
The multidimensional poverty measurements in 2010
using Weight (I)
Provincial multidimensional poverty measurements
using Weight (I)
The multidimensional poverty measurements using
Weight (II)
The multidimensional poverty measurements using
Weight (III)
The multidimensional poverty measurements using
Weight (IV)
The correlation coefficients between the different
weights
The Friedman test for the ranking concordance of
provinces
The provincial ranking of M0 across the different
weights
The change in the provincial ranking of M0 across the
different weights
The new weights of each dimension and the indicator
without the income

xiii
107
111
115

116
116
117
118
118
119
119
119
120
120
121
121
127
128
131
133
135
138
139
140
142
142
143
145
147


xiv

Tables

4.14 The correlation coefficients between M0 with and
without income dimension
4.15 The multidimensional poverty of each province and the
ranking
4.16 The correlation between the income poverty and the
multidimensional poverty
4.17 The decomposition by dimensions and indicators
4.18 The raw headcount ratio and the censored headcount
ratio
4.19 Top six indicators contributing to multidimensional
poverty: various weights
4.20 The decomposition by provinces
4.21 Major indicators of poverty for various provinces using
different weights
4.22 The financial fund of poverty reduction in 2012
5.1 Size of the valid sample households
5.2 The change of samples in each wave
5.3 The dimensions, indicators and indicators’ cut-offs
5.4 The weights of each dimension and indicator
5.5 Trends in multidimensional poverty measurements
5.6 Raw headcount ratio of each indicator
5.7 Censored headcount ratio for each indicator
5.8 The contribution of each dimension
5.9 The contribution of each indicator in AF approach
5.10 The dimensions, indicators and membership function
5.11 The TFR multidimensional poverty index
5.12 The degree of deprivation in income and highest-levelof-education indicator
5.13 The contribution of each indicator in TFR approach
5.14 The weights of each indicator
5.15 The AF multidimensional poverty measurements using

other weights
5.16 Top three indicators in order of contribution to
multidimensional poverty: various weights
5.17 The TFR multidimensional poverty measurements
using other weights
5.18 Major contributing factors to the TFR
multidimensional poverty approach: various weights
5.19 The correlation coefficients between the different
weights with the AF approach
5.20 The correlation coefficients between the different
weights in the TFR approach
5.21 The rural multidimensional poverty index
5.22 The urban multidimensional poverty index

147
148
149
150
152
155
156
160
165
168
169
170
174
175
177
180

181
182
184
185
186
187
190
191
192
193
194
195
197
199
200


Tables
5.23 The rural–urban ratio of the multidimensional poverty
index
5.24 The decomposition by rural and urban areas
5.25 Comparison of raw headcount ratio
5.26 Comparison of censored headcount ratio
5.27 Comparison of contributions of indicators
5.28 The rural–urban ratio of the multidimensional poverty
index with other weights
5.29 The decomposition by rural and urban areas using
other weights
5.30 Top three indicators in order contributing
multidimensional poverty: various weights

5.31 The provincial M0 in each wave
5.32 The change in M0 in each province
5.33 The decomposition of M0 by province
5.34 The provincial TFR poverty index in each wave
5.35 The change in TFR poverty index in each province
5.36 The major contributing indicators to provincial
multidimensional poverty
5.37 Major contributing indicators to regional
multidimensional poverty
5.38 The summary of existing literature using CHNS and a
comparison with our results
5.39 The best and worst performer in poverty reduction
6.1 The codes in the questionnaires of the indicators
6.2 The size of the samples and missing values of each
indicator
6.3 Size of the valid sample individuals
6.4 The cut-off and membership function of each indicator
6.5 Categories of highest level of education in different
datasets
6.6 The categories of work status in the datasets
6.7 Weights of each indicator
6.8 The AF multidimensional poverty measurements
6.9 The raw headcount ratio in AF approach
6.10 The censored headcount ratio of each indicator
6.11 Contribution of each indicator in the AF approach
6.12 The regional M0 in each wave
6.13 Decomposition by regions
6.14 The TFR multidimensional poverty measurements
6.15 Degrees of deprivation in the TFR approach
6.16 The contribution of each indicator

6.17 The regional TFR multidimensional poverty
measurements

xv
202
203
204
205
208
209
210
211
212
214
216
217
218
219
221
222
230
237
238
240
242
243
246
247
248
249

249
251
252
253
254
254
255
256


xvi

Tables
6.18 The urban AF multidimensional poverty measurements
6.19 The rural AF multidimensional poverty measurements
6.20 The rural–urban ratio of the multidimensional poverty
index
6.21 The TFR multidimensional poverty measurements
6.22 The decomposition by urban and rural sub-groups
6.23 Raw headcount ratio in the AF approach
6.24 Censored headcount ratio for each indicator
6.25 Degree of deprivation in the TFR approach
6.26 The contribution of each indicator for each group in
AF approach
6.27 The contribution of each indicator for each group in
the TFR approach
6.28 The rural–urban ratio of the multidimensional poverty
index in each region
6.29 Decomposition by urban and rural sub-groups
6.30 The rural AF multidimensional poverty measurements

6.31 The migrant AF multidimensional poverty
measurements
6.32 The migrant–rural ratio of the multidimensional
poverty index
6.33 The TFR multidimensional poverty measurements
6.34 The decomposition by rural and migrant sub-groups
6.35 The raw headcount ratio in the AF approach
6.36 Censored headcount ratio of each indicator
6.37 Degree of deprivation in the TFR approach
6.38 Contribution of each indicator for the rural and
migrant groups in the AF approach
6.39 Contribution of each indicator for the rural and
migrant groups in the TFR approach
6.40 The migrant–rural ratio of the multidimensional
poverty index in each region
6.41 The raw headcount ratio of health insurance for
migrants in each region
6.42 The decomposition by rural and migrant sub-groups
6.43 The urban AF multidimensional poverty measurements
6.44 The migrant AF multidimensional poverty
measurements
6.45 Migrant–urban ratio of the multidimensional poverty
index
6.46 The TFR multidimensional poverty measurements
6.47 The decomposition by urban and migrant sub-groups
6.48 The raw headcount ratio in AF approach
6.49 The statistical description of the income for the urban
and migrant group

257

258
259
260
261
262
263
264
265
267
268
269
271
272
272
273
274
275
275
276
277
278
279
280
281
282
283
284
285
285
286

286


Tables
6.50 Censored headcount ratio of each indicator
6.51 The degree of deprivation in TFR approach
6.52 Contribution of each indicator for each group with the
AF approach
6.53 Contribution of each indicator for each group with
TFR approach
6.54 Migrant–urban ratio of the multidimensional poverty
index in each region
6.55 Decomposition by urban and migrant sub-groups
A6.I.1 The AF multidimensional poverty measurements in the
Eastern region
A6.I.2 The AF multidimensional poverty measurements in the
Central region
A6.I.3 The AF multidimensional poverty measurements in the
Western region
A6.II.1 The urban and rural multidimensional poverty
measurements in the Eastern region
A6.II.2 The urban and rural multidimensional poverty
measurements in the Central region
A6.II.3 The urban and rural multidimensional poverty
measurements in the Western region
A6.III.1 The rural and migrant multidimensional poverty
measurements in the Eastern region
A6.III.2 The rural and migrant multidimensional poverty
measurements in the Central region
A6.III.3 The rural and migrant multidimensional poverty

measurements in the Western region
A6.IV.1 The urban and migrant multidimensional poverty
measurements in the Eastern region
A6.IV.2 The urban and migrant multidimensional poverty
measurements in the Central region
A6.IV.3 The urban and migrant multidimensional poverty
measurements in the Western region
7.1 The coverage of the three datasets
7.2 The selected dimensions and indicators in the three
datasets
A7.1 The government expenditure on education
A7.2 The public expenditure on health

xvii
288
288
290
292
293
294
297
298
299
300
301
302
303
304
304
305

306
307
309
311
315
317


Acknowledgements

This book is developed from research conducted when the first author, Jing
Yang, was at Macquarie University, Sydney, as a visiting scholar from July 2013
to July 2014. Her visit was supported by a State Scholarship Fund from the
China Scholarship Council (CSC). We thank CSC for its financial support and
also the Faculty of Business and Economics at Macquarie University for providing the necessary facilities. Further, we acknowledge the generous merit scholar
grants provided by Macquarie University for the accomplishment of this research.
A part of this research was also carried out when Jing Yang returned to Jiangxi
Agricultural University. Jing Yang would like to thank Professor Zhaojiu Chen,
Dean of the Department of Economics and Management, and other colleagues
for their support and encouragement. Further, we warmly acknowledge and
thank the Chinese National Social Science Funds No.13CJL070 (“The Research
on the Pro-poor Ecological Compensation Policies: From the Sustainable Livelihood Perspective”) for research support.
The findings of this research, at its preliminary stage, were presented at a
number of places: Chinese Academy of Social Sciences (CASS), Fudan University;
Central University of Finance and Economics at Beijing, East Asian Economic
Association Meeting; and workshops at Nagoya University and the Asian Development Bank. From these presentations we received helpful comments, corrections, improvements and suggestions, and I am especially indebted to Jacques
Silber, Guanghua Wan, Zhang Zhanxin, Meng Xin, Li Shi and Luo Chuliang.
Luo Chuliang and Xue Jinjun have been extremely generous with giving access
to some special data sources. Discussion with Wei Zhong on the pension reform
system in China, and with Zhang Zhanxin on hukou and Dibao helped me to

formalize the idea of social reforms in China. CASS and Macquarie University
financed me for my several trips to China.
Ms Laura Billington copy edited the whole draft manuscript with great care
and patience, for which I am grateful. I deeply appreciate the attentive and
gentle support of Chang (Michael) Wu (under Macquarie’s Merit Scholar
scheme) and my students Sigit Triandaru and Steven Yuan who collected some
material and assembled the bibliography with high precision and expertly
processed literature searches. It is a joy to thank the commissioning editor
Yongling Lam at Taylor and Francis and also people from Apex CoVantage for


Acknowledgements xix
managing the production of the book. Jing especially appreciates her husband
Zhanbin Liu and her two children Jiayang and Mengyang for their support. I
would like to thank my family, whose understanding of my frequent absences
and inability to meet usual commitments made it possible to conduct this
research. The usual disclaimers apply.
Pundarik Mukhopadhaya
Sydney, 12 February, 2016


Abbreviations

ADB
AF approach
ALEP approach
ANU
BMI
BNU
BRICS

CA
CASS
CFPS
CHIP
CHNS
CIID
CPC
CPI
CRRA
DFID
Dibao
ECHP
FDI
FGT
Hukou
ISSS
IZA
MCA
MDGs
MOA
MPI
NBS
OECD
Outline
PCA

Asian Development Bank
Alkire-Foster method
Aupspitz, Lieben, Edgeworth and Pareto
Australian National University

body mass index
Beijing Normal University
Brazil, Russia, India, China and South Africa
capability approach
Chinese Academy of Social Sciences
China Family Panel Studies
China Household Income Project Survey
China Health and Nutrition Survey
China Institute for Income Distribution
Communist Party of China
Consumer Price Index
constant relative risk aversion
The Department for International Development of UK
Minimum Income Guarantee
European Community Household Panel
foreign direct investment
Foster-Greer-Thorbecke
the household registration
Institute of Social Science Survey of Peking University
Institute for the Study of Labor
multiple correspondence analysis
Millennium Development Goals
Ministry of Agriculture
Multidimensional Poverty Index
National Bureau of Statistics of China
Organization for Economic Co-operation and Development
Development-oriented Poverty Reduction for China’s Rural
Areas (2011–2020)
principal component analysis

Abbreviations
PPP
R&D
RCRE
RMB
RUMiC
SARS
SE approach
SL approach
SOEs
TFA
TFR approach
UNDP
UQ
VWA
WHO
WTO

xxi

purchasing power parity
research and development
Research Centre for Rural Economy of the Ministry of Agriculture of China
Chinese currency renminbi
rural–urban migration in China
Severe Acute Respiratory Syndrome
social exclusion approach
sustainable livelihoods approach
state-owned enterprises

totally fuzzy approach
totally fuzzy and relative approach
United Nations Development Programme
University of Queensland
Vero and Werquin Approach
World Health Organization
World Trade Organisation


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1

Introduction

China has been carrying out a frontal attack on mass poverty and unemployment after dispossessing landlords and nationalizing industry. It is not easy
to see how the Third World can mount the attack while preserving private
property in the means of production and respecting the rules of free-market
economy.
Joan Robinson (1979, p. 10)

Regardless of how poverty is defined, addressing abject poverty has always been
one of the ultimate objectives of economic development in developing and
developed countries. Being poor is generally defined as being deprived of what
is required to live a meaningful life. The exact definition of poverty has long
been debated. The concepts of absolute and relative poverty are often invoked
in the relevant literature. But because of the ambiguous nature of these concepts,
they often generate controversy and debate. The absolute concept may suggest
greater precision and objectivity, while the idea of relativity may convey a sense

of subjectivity and arbitrariness. The choice between these concepts would
depend partly on the purpose for which the concept is to be used and partly
on philosophical and moral considerations. The use of the relative measure can
help establish the idea that poverty can exist even in societies with a high mean
income. Amartya Sen (1980) invoked the notion of deprivation to capture the
essence of an absolute measure of poverty. He accepts that what constitutes
“deprivation” may vary from society to society but observes that these variations
are matters of objective study. While “low income” may be an indicator of
poverty, a target income is not an end in itself but only a means to achieving
what Sen (1989) has called “human functioning”. To emphasise the connections
between poverty and human functioning, Sen has developed the concept of
“capabilities”. To have capability in this sense is to be able to “function” in a
chosen way or to have options in a “capabilities set”. In interpreting this concept, Atkinson (1995) writes, quoting Sen, that “in the chain Commodities – >
Characteristics – > Capabilities – > Utility, it is “the third category – that of
the capability to function – that comes closest to the notion of standard of
living”, and that, if the argument is accepted, it provides a basis for “sorting
out . . . the absolute–relative disputation in the conceptualisation of poverty.


2

Introduction

At the risk of oversimplification, I would like to say that poverty is an absolute
notion in the space of capabilities but very often it will take a relative form in
the space of commodities and characteristics” (p. 17). This method of viewing
absolute and relative deprivation has not only helped to resolve the conceptual
ambiguity inherent in the concepts themselves, it has also influenced empirical
implementation of the ideas to broaden the definition of human development.
In this book we will look into absolute and relative poverty in China from a

broader perspective of human development.

1.1

Poverty scenario worldwide

There is no doubt that global income poverty has declined tremendously in
recent decades. The World Bank’s estimate shows that the number of poor in
the population who live under the $1.25 poverty line has halved since 1990
from a global perspective, and the incidence of poverty had dropped to 16.99 percent by 2011 (see Table A1.1 in the Appendix). However, this reduction of
poverty is uneven across regions. East Asia and the Pacific have experienced the
greatest decrease in poverty, while Sub-Saharan Africa has not only recorded
the lowest decreases in poverty, the number of poor in the population has been
increasing since 1990.
Furthermore, the World Bank (2015) reports that more than 70 percent of
global extreme poverty (under the $1.25 poverty line) is concentrated in 10 countries: India (30 percent), Nigeria (10 percent), China (8 percent), Bangladesh
(6 percent), the Democratic Republic of Congo (5 percent), Indonesia (4 percent),
Ethiopia (3 percent), Pakistan (2 percent), Madagascar (2 percent) and Tanzania
(2 percent). Although the two most populous countries – China and India – are
still the top countries with the largest share of global poverty, they have played
an important role in the reduction of global poverty. From 2008 to 2011, the
five countries contributing the most to global poverty were India, China, Indonesia,
Pakistan and Vietnam (World Bank, 2015).
The other faces of poverty have been promoted unevenly. For example, the
Millennium Development Goals Report 2014 (UN, 2014) reveals that the
proportion of undernourished people in developing regions decreased to 14.3 percent in 2011–2013 but was 25 percent in Sub-Saharan Africa and 11 percent
in Eastern Asia. Similar observations can be made for education. The adjusted net
enrolment rate for primary education in developing regions increased to 90 percent in 2012. Among the regions, Northern Africa, which had a net enrolment
rate of 99 percent, had almost achieved the universal primary education goal,
compared to Sub-Saharan Africa, which only had a net enrolment rate of 78

percent.
The World Bank (2015) also presents that economic growth’s inclusiveness
(including jobs and a social contract) and its sustainability (including social,
fiscal and environmental dimensions) are the key elements of poverty reduction.
Thus, for developing countries, investing in human capital (e.g. earlier and
greater investments in educating the young), establishing efficient social safety