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DEPARTMENT OF ECONOMICS
ISSN 1441-5429
DISCUSSION PAPER 13/16
Fiscal Decentralisation, the Knowledge Economy and School Teachers’
Wages in Urban China*
Yi Longa, Chris Nylanda and Russell Smythb
Abstract: We examine how fiscal decentralisation and progress towards the development of a
knowledge-intensive economy has impacted on teachers’ wages in China, utilising a panel
dataset of 31 provincial administrations from 2001 to 2013. We find that fiscal
decentralisation has a negative impact on teachers’ wages and this effect is further
enhanced by a deepening of the knowledge intensity of the economy, while knowledge
economy itself has no significant impact on teachers’ wages. The findings suggest that
incentives being offered to local administrators need to be revisited if the national
government is convinced of the need to increase teacher quality in ways suited to the
knowledge economy China wishes to construct.
Keywords: fiscal decentralisation, knowledge economy, teachers, wages, human capital,
China
JEL Classification Numbers: H73, J31, J45
* We thank Roland Cheo, Zhiming Cheng and Brian Cooper for helpful suggestions on earlier versions of this
paper. We alone are responsible for the content. a Department of Management, Monash Business School, Monash University b Department of Economics, Monash Business School, Monash University
© 2016 Yi Long, Chris Nyland and Russell Smyth
All rights reserved. No part of this paper may be reproduced in any form, or stored in a retrieval system, without the prior
written permission of the author.
monash.edu/ business-economics ABN 12 377 614 012 CRICOS Provider No. 00008C
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Introduction
China is undergoing a fundamental structural transformation from a low skilled,
surplus-labour economy to a more capital-intensive, and technology-intensive,
economy (Garnaut, 2011). To complement this shift, China’s government accepts that
it needs to increase the nation’s investment in human capital accumulation (World
Bank, 2013). This is a development that is evidenced by the marked increase in
resources now directed to education and by the increased emphasis on the need to
build a workforce that is both innovative and creative (Pang & Plucker, 2013). What
China’s national government also recognises is that socio-economic diversity
influences the extent to which regional administrations need to subsidise education
provision. This is evidenced by the fact that the national government has embraced a
regime that entails the specification of a common national minimum teacher wage
schedule and permits local authorities to decide whether, and to what extent, they will
supplement this minimum. For example, Zeng and Yu (2015) find that in 2010
regional supplements for teachers in Shanghai, Beijing, Zhejiang and Tibet were
almost four times higher than the national minimum. Regional supplements introduce
a degree of competition for teachers between provinces, although the level of regional
competition for teachers should not be overstated. While teachers are free to move
across provinces, regional administrators retain market power because teachers are
unable to transfer highly desired permanent positions across provinces.
Despite the increased value accorded to human capital development through
3
education, whether China can build a workforce suited to the utilisation of
sophisticated technology remains an open question. Heckman (2005) has charged that
China underinvested in human capital in the 1990s and that this resulted in a shortage
of workers with the cognitive capacities required to master the skills demanded by
new technologies. Consequently, there was a relatively low rate of return to the capital
that was invested in the upgraded technologies. A number of researchers have posited
that the underinvestment in education Heckman underscores was due to the system of
fiscal decentralisation that permits local governments, that tend to favour investments
that generate short term returns, to determine precisely how much will be invested in
social service provision (Fu, 2010; Luo & Chen, 2010; Wang et al., 2012).
Fiscal decentralisation is a concept that captures the extent to which national
governments permit local administrators to retain a share of their locally generated
revenue and/or decide how resources are allocated (Porcelli, 2009; Zhang & Zou,
1998). Focusing on the effect of this institutional factor on human capital formation,
this paper examines how fiscal decentralisation, and progress towards the
development of a knowledge-intensive economy, influences teachers’ wages in China.
Locating the analysis in the foregoing context, this paper makes two contributions to
teacher wage determination theory and the Chinese teacher wage determination
literature. First, it enriches our knowledge of the teacher wage determination process
by examining the role that fiscal decentralisation, and its interaction with the
knowledge economy, play as institutional determinants of teachers’ wages. Fiscal
4
decentralisation, to different degrees, is observed in many countries and is held to
influence government behaviours (OECD & Korea Institute of Public Finance, 2013).
The impact of labour market institutions, such as unions and collective bargaining, on
teacher wages has been extensively studied (Goldhaber, 2009; Hoxby, 1996).
However, although the government is a key player in the teacher wage determination
process, we really know little about the effect of the institutional incentives faced by
governments in this process. China provides the ideal setting in which to address this
issue because its fiscal reforms provide us with an opportunity to examine how
institutional incentives that governments face influence teachers’ wages.
Second, incorporating the knowledge economy into wage determination theories also
underscores the fact that the wage determination process is evolutionary. That this is
the case has been recognised by scholars who have documented how changing
attitudes to gender and race have influenced wages (Blau & Kahn, 2000; Podgursky &
Springer, 2007). But what has gone unexplored is the possibility that the changing
knowledge intensity of economies may change the context in which teachers work
and that it may be necessary to introduce wage adjustments when the labour market
increasingly rewards high skills (Acemoglu, 1998; Katz & Margo, 2014). Whether
this general trend has been reflected in a specific skill-intensive occupation, such as
teachers, is of interest and has far-reaching implications for the recruitment and
retention of high quality workers in the education sector.
To examine whether, and to what extent, fiscal decentralisation, knowledge economy
5
and their interaction affects teacher wages, we focus on China for two reasons. First,
fiscal decentralisation has been a prominent feature of China’s intergovernmental
fiscal system (Jin, et al., 2005; Zhang & Zou, 1998). While China is not unique in
experimenting with fiscal decentralisation, the fiscal reforms that China has
implemented have accentuated regional differences in the incentives faced by
governments. This provides an excellent setting in which to examine the role that the
institutional incentives faced by government play in determining the wages that
teachers receive.
A second reason for situating our study in China is that its education system has
recently been at the centre of international debates about the best way to develop a
high-performing education system. Shanghai topped the league table in the 2009 and
2012 Programme for International Student Assessment organised by the OECD,
generating considerable international attention in its approach to education. This has
also initiated fierce public debate about the average level of academic achievement
and the quality of education in China (OECD, 2011; Tucker, 2012; Zhao, 2014). There
is a need to examine how the evolution of the knowledge economy that China desires,
has effected the incentives offered to governments to attract the best people into the
education sector, not just in Shanghai, but across the country.
Teachers’ compensation includes both wages and fringe benefits. While, in the past,
many fringe benefits have not been totally transparent, recent reforms have
incorporated fringe benefits into the wage bill. For example, free housing has been
6
replaced with the housing provident fund, which is clearly listed on the wage bill. In
the past, like all civil servants, teachers did not have to contribute to social insurance,
even though they received better pensions on retirement than did employees working
in the private sector or state-owned enterprises. The pension reforms in 2014 and
2015, however, mandated that teachers now have to pay the same proportion of their
wages to the social insurance program and that the base wage should be increased to
compensate for wages contributed to social insurance. Hence, pensions are also
visible on the wage bill. These reforms suggest that differences in teachers’ wages are
the main drivers of differences in total remuneration across provinces.1
We find that fiscal decentralisation has a negative influence on teacher wages. A one
percent increase in fiscal decentralisation reduces the average annual primary school
teacher’s wages by 0.87% to 0.92% and the average annual secondary school
teacher’s wages by 0.47% to 0.52%. Finding that there is a negative link between
decentralisation and wages is important because it is commonly assumed that
devolution will enhance the extent to which wages reflect the needs of local
economies, but this may not be the case if long-term development requires a high rate
of human capital accumulation and local administrators have shorter term priorities.2
We find that progression toward a knowledge-intensive economy has no significant
1 As discussed below our measure of teachers’ remuneration covers the total wage bill, including base and
supplement wages and salaries as well as other payments both in kind and in cash. 2 One might be concerned that the negative link between fiscal decentralisation and wages is being driven by
differences in teacher quality where better qualified teachers are migrating to wealthier, higher paying, provinces
leaving less well qualified teachers in the poorer provinces. If this was the case, we would observe that wages of
teachers would be falling not because the government is paying less, but because the remaining pool are less
qualified. However, as we note above, interprovincial competition for teachers should not be overstated and, in our
modelling below, we at least partly control for differences in teacher quality through including teachers’ education
and professional rank as control variables, although neither are perfect proxies for teacher quality.
7
influence on school teacher wages. The upward pressure on teacher wages exerted by
the knowledge economy through increasing demand for skilled workers may be offset
by the rise in the supply of college graduates in China since the expansion of the
higher education sector in 1999. This explanation is in line with the observation that
the skill wage premium may not increase if the supply of educated workers outpaces
skill demand that is induced by an upgrading of technology as Goldin and Katz (2007)
find occurred in the United States through 1915-1980.
Despite finding no significant direct effect of the knowledge economy on teacher
wages, we find that progression to a knowledge-intensive economy strengthens the
negative association between fiscal decentralisation and teachers’ wages.
Conditioning on the average level of knowledge economy, a one percent increase in
fiscal decentralisation reduces the average annual primary school teacher wages by
0.94% to 1.27% and the average annual secondary school teacher wages by 0.55% to
0.92%.
While the findings generated by the study are derived from China’s experience they
have wider relevance to ongoing debates being sustained in many nations on how to
improve the quality of the teaching workforce. Giving more local and school
autonomy in wage determination have been advanced as strategies to improve the
quality of teaching (OECD, 2005; Propper & Britton, 2012). Our finding regarding
China’s experience suggests localised determination may not lead to the desired
outcome if autonomy is not balanced by appropriate incentives and accountability
8
systems.
Conceptual model
Fiscal decentralisation and teachers’ wages
That fiscal decentralisation may impact on teachers’ wages is suggested by two
strands of literature. The first argues that fiscal decentralisation tends to diminish
public services. It stems from theories of fiscal federalism which study the incentives
embedded in institutions and the types of decentralisation that best support economic
prosperity (Jin et al., 2005; Oates, 2008). China’s national government provides
strong economic and personal promotion incentives that are designed to encourage
local governments to promote economic growth and development (Chen et al., 2005;
Li & Zhou, 2005).
With autonomy to make fiscal decisions, these incentives motivate administrators to
prioritise items that contribute to short-term economic growth, which tends to mean
directing resources to build physical infrastructure that attracts investment inflow
(Cheung, 2008) and encouraging firms to take advantage of China’s abundance of
cheap labour (Gaulier et al., 2007).
In the period in which China's development strategy focussed on low value-added
production only, basic literacy was required to complement this approach. Research
for the 1990s found that providing the population with a primary school education had
a positive effect on GDP growth, but the effect of higher levels of education was
statistically insignificant (Qian & Smyth, 2006). Given this was the case and given
9
local governments were encouraged to focus on growth, it is not surprising that local
officials discounted the importance of human capital accumulation and the need to
invest in education (Gordon & Li, 2011; Li et al, 2012; Qian & Roland, 1998). This
downplayed the need to raise teachers’ wages for recruiting and retaining high skilled
staff.
In summary, this strand of thought holds that the higher the level of fiscal
decentralisation and the consequent greater fiscal autonomy, the more likely
administrators will align expenditure with fiscal and political incentives (Fu & Zhang,
2007). With a higher level of fiscal decentralisation, local government officials who
are rewarded for accelerating growth are more likely to underinvest in public service
provision and overinvest in infrastructure construction that has a significant and
immediate impact on growth.
The second strand of literature that has examined the impact of fiscal decentralisation
on local administrators suggests the priorities of the party-state have shifted over time.
In brief, it is posited that the national government has expanded its agenda and now
seeks to promote economic development and expand public service provision (Liu,
2011; Yang, 2013). Given this new mix of priorities, if incentives to encourage the
long-term development of human capital are greater than the incentives to promote
short-term growth, fiscal decentralisation will exert a positive impact on public goods
provision and, vice versa.
The overwhelming majority of empirical studies continue to find economic growth is
10
being prioritised over human capital accumulation (Fu, 2010; Jia et al., 2014; Li, 2007;
Luo & Chen, 2010; Qiao et al., 2006). It is possible that this is because most studies
use historical data even though China is continuing to change rapidly. But given the
current weight of evidence we posit the following hypothesis:
Hypothesis 1: When the level of fiscal decentralisation is higher, teachers’ wages
will be lower.
Knowledge economy and teacher wages
The possibility that progression towards a knowledge economy will have a positive
impact on teachers’ wages is suggested by Heckman’s (2005) claim that as more
sophisticated technology was introduced into Chinese industry it became necessary to
increase investment in human capital accumulation, that this was not done at a
commensurate rate, and as a consequence the return to physical capital was
diminished.
The global nature of this transformation has also been highlighted by the OECD
(1996). It has observed repeatedly that knowledge has become a primary driver of
productivity, economic growth, and competitiveness. In so doing the OECD (2008)
has also stressed that as technology becomes more sophisticated so too does the need
both for workers who can learn sophisticated skills and for teachers who have the
capacity to graduate students who have the requisite capacity to learn (see also,
Tucker, 2012).
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Teachers’ contribution to students’ learning capacities has been evidenced by the
finding that a one standard deviation increase in teacher quality raises test scores of a
national standardised test by almost 0.1 standard deviation in reading and
mathematics in the United States (Rockoff, 2004, see also Aaronson et al., 2007;
Chetty et al., 2014a; Hanushek & Rivkin, 2010). In addition, Chetty et al. (2014b)
find students taught by high value-added teachers in primary school are more likely to
attend college and earn higher salaries. Outside the United States, research for
Australia (Leigh, 2010), Brazil (Harbison & Hanushek, 1992), the United Kingdom
(Slater et al., 2012), and Peru (Metzler & Woessmann, 2012) has confirmed that
teacher quality has a positive impact on students’ academic achievement. Thus, high
quality teachers are a prerequisite for cultivating the knowledge economy workforce.
Skill-biased technological progress increases the demand for high skilled workers and
raises their wages (Acemoglu, 1998; Katz & Margo, 2014). Thus, there is the need to
recompense teachers that will induce high quality students to become teachers and
ensure high quality teachers remain in this profession (OECD, 2008; Schleicher,
2011).
In China skill requirements have risen in line with industrial upgrading occurring at
different rates in accordance with the extent to which regions have developed a
knowledge-intensive economy (Cai & Wang, 2014; Heckman & Yi, 2012). We
suggest that given the evidenced link between the quality of teachers and wages there
will also be a positive association between wages and the extent to which regions
12
have been able to develop a knowledge intensive economy. This suggests our second
hypothesis.
Hypothesis 2: When the level of knowledge economy is higher, teacher wages
will be higher.
The moderating role of the knowledge economy on the relationship between fiscal
decentralisation and teachers’ wages
That local government fiscal independence arguably induces local administrators to
curtail teachers’ wages begs the question: is this tendency mitigated by the advance of
the knowledge economy? In the early stages of the transition to a knowledge-intensive
economy this mitigation effect is likely to occur only at the level of primary school
education given that a primary school education is sufficient for the overwhelming
majority of workers to undertake their employment. As the level of technology within
the economy increases, along with increased demand for more skilled workers and for
higher quality teachers, this effect will tend to become pronounced at higher levels of
education and local administrators will come under mounting pressure to increase the
proportion of their expenditure that they apportion to education and to the
employment of ever higher quality teachers.
The OECD (2015) and the National Centre on Education and the Economy in the
United States (Tucker, 2012) has observed that high-performing education systems
are inclined to prioritise higher teacher salaries over other forms of education
13
expenditure. Dolton and Marcenaro-Gutierrez (2011) have lent support to this claim
by evidencing that teachers’ wages, both measured in absolute terms and relative to
the average wages in a country, are positively associated with student performance
even after controlling for country fixed effects.
The development of a knowledge economy in China creates an imperative for
governments to accept the policy implications drawn from the experience of
high-performance education systems. Ramesh (2013) argues that progression towards
a knowledge-based economy is the product of a cumulative and overlapping set of
reforms which over 30 years have embedded knowledge creation in coastal regions
with the process progressively diffusing to the rest of China. Central to this process,
Ramesh (2013) adds, is education policy and more specifically the government’s
effort to raise the quality of the nation’s education workforce. If local governments
embrace this insight, we can expect the knowledge economy to moderate the negative
impact of fiscal decentralisation on teachers’ wages.
Hypothesis 3: The level of knowledge economy moderates the relationship
between the degree of fiscal decentralisation and teacher wages, such that when
the level of knowledge economy increases, the negative impact of fiscal
decentralisation on teacher wages is weakened.
Model specification, measurement of variables and dataset
The basic specification of the model can be represented by:
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𝑊𝑖𝑡 = α𝑖 + β1FD𝑖𝑡 + β2KE𝑖𝑡 + ∑𝑋𝑖𝑡 + 𝑖𝑡
This unconditional model will be employed to test the first and second hypothesis.
The dependent variable 𝑊𝑖𝑡 is the average teacher wages in region 𝑖 in year t. The
major explanatory variables are FD𝑖𝑡, representing fiscal decentralisation, and KE𝑖𝑡
denoting knowledge economy. In addition, we also control for variables that have
been deemed important in the extant teacher wage determination literature. The set of
control variables 𝑋𝑖𝑡 include local government’s fiscal capacity, teachers’ human
capital and other demographic attributes, job attributes, changes in student enrolments,
cost of living (COL) and local unemployment rate. The intercept i may be the same
or varying across regions. The error term 𝑖𝑡 is assumed to have a zero mean, and to
be independent and identically distributed across observations.
To test whether the knowledge economy moderates the effect of fiscal decentralisation
on teachers’ wages, the interaction term of the two independent variables FD𝑖𝑡 ∗ KE𝑖𝑡
is added to the basic model. Below shows the conditional model:
𝑊𝑖𝑡 = α𝑖 + β1‘ FD𝑖𝑡 + β2
‘ KE𝑖𝑡 + β3′ FD𝑖𝑡 ∗ KE𝑖𝑡 + ∑
’𝑋𝑖𝑡 + µ𝑖𝑡
Fiscal decentralisation has been measured using various approaches
(Martinez-Vazquez & Timofeev, 2010). The most commonly used measurement in
studies for China since the mid-1990s has been the ratio of subnational government
expenditure to national government expenditure (Fu & Zhang, 2007; Li, 2007; Zhang
& Zou, 1998; Zheng, 2008). A similar measure that has been employed is the ratio of
15
subnational government revenue to national government revenue (Guo & Jia, 2010; Li,
2007; Liang, 2009; Shen & Fu, 2005). Another often utilised measurement is the
fiscal autonomy indicator or self-reliance ratio, which is derived by dividing total
subnational fiscal revenue by subnational fiscal expenditure (Chen, 2010; Gong & Lu,
2009; Xing & Deng, 2012).
Despite their widespread usage, the first two measures are problematic since a
common denominator across provinces for any given year merely captures the amount
of provinces’ public revenue or expenditure, instead of the level of fiscal
decentralisation (Chen & Gao, 2012; Niu, 2013; Zhang, 2011). Chen and Gao (2012)
and Zhang (2011) point out the choice of fiscal decentralisation measurement is
dependent on the time period covered in the study and fiscal autonomy is a better
indicator to reflect regional fiscal decentralisation variation after 1994 compared to
revenue and expenditure measurement. Thus, we use the third measure in this study.
We focus on three dimensions of the knowledge economy, based on the work of
Ramesh (2013); namely, research and development (R&D), size of the knowledge
economy workforce and knowledge creation, measured by full-time equivalent R&D
personnel per 10,000 people, population with a college or above education as a
percentage of the working age population and certified patent applications.
The dataset consists of a 13-year panel for the 31 provinces and municipalities
directly under the national government in Mainland China from 2001 to 2013. School
teachers’ average wages are obtained from the China Labour Statistical Yearbook,
16
which only has data for those working in urban areas.3 As the average wage of
teachers in primary education and secondary education are given separately, we
consider these groups independently. Table A1 in the appendix contains details of
measurement and data sources. The descriptive statistics are given in Table 1.
Table 1. Descriptive statistics for all variables
a. Wages and fiscal capacity data are adjusted for inflation by converting the figures to 2013 RMB
constant prices using the national consumer price index (CPI) as the deflator. The reason that we
did not use provincial CPI is that COL as measured by the spatial price index has captured the
regional price variation. So we only have to adjust for inflation over time.
b. P and S in the parentheses refer to primary schools and secondary schools respectively.
c. KE refers to knowledge economy
3 According to the explanatory notes in the China Labour Statistical Yearbook, “the average wage of employees
refers to the average wage level in monetary terms per employee in a certain period of time, which is calculated by
dividing the total wage bill for employees in that period by the average number of employees in that period. The
calculation of the total wage bill is based on the total remuneration payment, including wages, salaries and other
payments to employees, regardless of its source or category, both in kind and in cash”.
Variable Observations Mean SD Min Max
Wages (P) 403 31145 16469 9448 90950
Wages (S) 403 33764 16572 10869 94669
FD 403 47.96 18.67 5.07 87.23
R&D 403 15.89 19.87 0.83 114.50
Size of KE workforce 403 10.28 6.72 0.36 48.22
Knowledge creation 403 14564 32123 7 269944
Fiscal capacity 403 2803 3048 319 17501
Female (P) 403 70.45 7.53 50.21 83.14
Female (S) 403 50.04 10.86 30.74 73.82
Education (P) 403 14.42 0.72 12.06 15.89
Education (S) 403 15.65 0.27 14.94 16.41
Senior rank (P) 403 49.84 12.24 14.62 80.46
Senior rank (S) 403 53.95 11.30 16.47 81.44
Ratio (P) 403 18.56 2.66 10.97 25.43
Ratio (S) 403 16.40 2.55 9.62 22.58
Enrolment growth (P) 403 -2.28 4.49 -17.55 40.84
Enrolment growth (S) 403 0.12 5.55 -17.34 29.92
COL 403 3289 447 2430 4614
Unemployment rate 403 3.70 0.71 1.2 7.1
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Results
The estimated direct effect of fiscal decentralisation and knowledge economy on
teachers’ wages in primary schools and secondary schools are reported in column 1 to
3 and column 4 to 6 in Table 2 respectively. As the results are similar across the two
sub-sectors in education, we discuss these two sets of results together.
Table 2. The direct effect of fiscal decentralisation and knowledge economy on teachers’ wages
a. Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1
b. The Breusch and Pagan LM test rejects the pooled OLS estimator as being unbiased and
efficient and suggests the existence of individual effects. We select the fixed effect model over the
random effect model to address the individual effects. When the unit of observation is a large
geographical unit such as state or province, we cannot treat our sample as a random sample from a
large population (Wooldridge, 2012).
c. Modified Wald test for groupwise heteroscedasticity and Wooldridge test for autocorrelation
in panel data suggest the existence of heteroscedasticity and autocorrelation in the residuals. Thus,
we clustered the standard error on the panel variable (province), producing an estimator robust to
cross-sectional heteroscedasticity and serial correlation.
Fiscal decentralisation has a negative impact on primary and secondary school
teachers’ wages, consistent with our first hypothesis. It suggests that where the level
of fiscal decentralisation is higher, teacher’s wages tends to be lower, confirming the
theoretical argument that fiscal decentralisation will underplay investment in human
VARIABLES (1) (2) (3) (4) (5) (6)
FD -274.6*** -287.6*** -270.1*** -165.4*** -175.7*** -160.1***
(47.87) (50.58) (47.08) (55.24) (52.51) (57.02)
R&D 64.21 118.9
(82.86) (99.96)
Size of KE
workforce
-174.3 -115.7
(139.5) (150.3)
Knowledge
creation
0.0144 0.0214
(0.0104) (0.0154)
Observations 403 403 403 403 403 403
Within R2 0.952 0.952 0.952 0.958 0.957 0.958
F-statistics 518.10 473.98 406.61 488.85 337.42 306.84
18
capital (Gordon & Li, 2011; Li et al., 2012; Qian & Roland, 1998).
In addition, the absolute value of the coefficients on fiscal decentralisation for
primary school teachers in all three equations are uniformly higher than those for
secondary school teachers, implying that while local governments undermine teacher
wages, they set even lower value on primary school teachers. The regression
coefficient suggests that for a one percent increase in fiscal decentralisation, the
reduction of average primary school teachers’ wages per year ranges between 270.1
RMB and 287.6 RMB and that of average secondary school teachers’ wages ranges
between 160.1 RMB and 175.7 RMB depending on the measurement of the
knowledge economy, which account for 0.87% to 0.92% of the average annual
primary school teacher’s wages and 0.47% to 0.52% of the average annual secondary
school teacher’s wages. While we do not report the results of the controls, this is
equivalent to a decrease in years of schooling of primary school and secondary school
teachers of 0.058 to 0.062 years and 0.011 to 0.013 years. In other words, the impact
of a one standard deviation increase in fiscal decentralisation on teachers’ wages is
equal to that of a 1.50 to 1.60 standard deviation decrease and a 0.76 to 0.89 standard
deviation decrease in years of schooling of primary school and secondary school
teachers, respectively.
However, the level of knowledge economy is found to have no significant influence
on primary and secondary school teacher wages, consistent across all three measures
of knowledge economy. The results reject our second hypothesis which posits a
19
positive relationship between the knowledge economy and school teacher wages.
Table 3. The effect of fiscal decentralisation on teachers’ wages conditioned on the knowledge
economy
Notes: See notes to Table 2
The interaction between fiscal decentralisation and knowledge economy has a
negative impact on both primary and secondary school teachers’ wages, which means
that the knowledge economy strengthens the negative influence of fiscal
decentralisation on teachers’ wages, inconsistent with the third hypothesis which
posits that a higher level of knowledge economy weakens the negative impact of
fiscal decentralisation on teachers’ wages. As is indicated in Figures 1 and 2, when the
level of knowledge economy increases4, the negative effect of fiscal decentralisation
4 Here we only show the graph with the size of the knowledge economy workforce as the measurement of
knowledge economy. Other graphs are available upon request.
VARIABLES (1) (2) (3) (4) (5) (6)
FD -232.0*** -234.5*** -258.3*** -139.6** -141.7*** -154.5**
(57.17) (57.82) (48.21) (58.64) (48.11) (57.84)
R&D 882.5*** 992.3***
(265.4) (249.2)
Size of KE
workforce
607.1** 426.8*
(225.0) (245.0)
Knowledge
creation
0.201** 0.192**
(0.0819) (0.0899)
FD* R&D -10.23*** -10.68***
(3.396) (3.166)
FD* Size of KE
workforce
-14.62*** -10.32*
(4.366) (5.301)
FD* Knowledge
creation
-0.233** -0.212*
(0.103) (0.112)
Observations 403 403 403 403 403 403
Within R2 0.956 0.954 0.953 0.962 0.958 0.958
F-statistics 537.22 582.34 427.51 1145.45 659.91 334.42
20
on both primary and secondary school teachers’ wages becomes larger.
At the average level of knowledge economy, as measured by the size of the
knowledge economy workforce, a one percent increase in fiscal decentralisation
reduces primary school teachers’ wages by 384.7 RMB and secondary school teachers’
wages by 247.8 RMB, which are 1.24% and 0.73% of the average annual primary and
secondary school teachers’ wages, respectively. And when the level of knowledge
economy decreases by one standard deviation, a one percent increase in fiscal
decentralisation reduces primary school teachers’ wages by 286.5 RMB and
secondary school teachers’ wages by 178.5 RMB, which are 0.92% and 0.53% of the
average annual primary and secondary school teachers’ wages, respectively. When the
level of knowledge economy increases by one standard deviation, a one percent
increase in fiscal decentralisation reduces primary school teachers’ wages by 482.9
RMB and secondary school teachers’ wages by 317.2 RMB, which are 1.55% and
0.94% of the average annual primary and secondary school teachers’ wages,
respectively.
21
Figure 1. Conditional marginal effects of fiscal decentralisation on primary school teachers’ wages with
95% confidence interval
Figure 2. Conditional marginal effects of fiscal decentralisation on secondary school teachers’ wages
with 95% confidence interval
We calculated the total effect of fiscal decentralisation which sums the coefficients on
fiscal decentralisation and the interaction between fiscal decentralisation and the
knowledge economy evaluated at the average level, expressed as β1‘ +β3
‘ 𝐾𝐸̅̅̅̅ 𝑖𝑡. The
22
results are shown in Table 4. The total effect of fiscal decentralisation on primary
school teachers’ wages ranges between 292.29 RMB and 394.6 RMB, which are 0.94%
to 1.27% of the average annual primary school teacher wages, depending on the
specification of knowledge economy. The negative effect of fiscal decentralisation on
teachers’ wages is smaller in secondary schools, which are in the range 185.4-309.3
RMB, accounting for 0.55% to 0.92% of the average annual secondary school teacher
wages.
Table 4. Total effect of fiscal decentralisation on teachers’ wages
The national government introduced wage reform for teachers in 2009 and required
subnational government to pay local supplements to teachers. Does the effect of FD
and KE on wages change before and after the 2009 teacher wage reform? We created
a reform dummy variable, with the value zero for the period 2001 to 2009 and 1 for
the period 2010 to 2013, since Pang et al. (2010) observed that this reform was not in
effect in most provinces until 2010. First, we added the reform dummy and its
interaction with each independent variable in the unconditional model to ascertain
whether the direct effect of FD and KE changes and then, second, to the conditional
Measurement of KE dy/dx SE z P>z
Primary
school
teacher
R&D -394.6 74.1 -5.32 0.000
Size of KE workforce -384.7 50.9 -7.56 0.000
Knowledge creation -292.3 45.0 -6.50 0.000
Secondary
school
teachers
R&D -309.3 68.2 -4.53 0.000
Size of KE workforce -247.8 69.9 -3.55 0.000
Knowledge creation -185.4 56.5 -3.28 0.001
23
model to check whether the interaction effect of FD and KE changes.
When we interacted the reform dummy with FD in the unconditional model we found
that the interaction term was insignificant, suggesting that our results are not affected
by the reform. Moreover, the interaction of the reform and KE was insignificant as
well in five out of six regressions. Only in the secondary school teacher wages
regression, when KE is measured by knowledge creation, did the interaction term
become significant with a negative sign. When we interacted the reform dummy with
the interaction of FD and KE in the conditional model, the interaction term was
insignificant in five out of six regressions; the exception being the secondary school
teacher wages regression when KE is measured by R&D.
An alternative explanation for our results may be that FD has a negative impact on
local government's expenditure on both infrastructure and public service provision,
resulting in lower teacher wages in higher FD regions. To test this explanation, we
examined whether FD influenced expenditure on infrastructure, replicating the
frequently cited study by Fu and Zhang (2007). The dependent variable is the
percentage of expenditure on capital construction in total government expenditure of a
province, which is regressed on FD and a series of controls. The results were mixed
depending on the measure of FD. Employing the measure of FD used by Fu and
Zhang (2007), which is the ratio of subnational government expenditure per capita to
national government expenditure per capita, we found that FD is positive, consistent
with our theoretical argument that local governments with higher FD divert fiscal
24
resources away from public service provision and into infrastructure, and thus lower
teachers’ wages. However, as discussed above, this measure of FD has been criticised
on the basis that the denominator is the same for all provinces in a given year (see eg.
Chen & Gao, 2012; Niu, 2013; Zhang, 2011). When we use the ratio of local fiscal
revenue to local fiscal expenditure to measure FD, the coefficient on FD is
insignificant. Hence, the effect of FD on infrastructure is either positive or
insignificant, casting doubt on this alternative explanation for our results.
Discussion of findings
The study has found that fiscal decentralisation has a negative impact on teachers’
wages. This finding resonates with existing theoretical arguments and empirical
evidence which contends that in China fiscal decentralisation commonly undermines
investment in social service provision (Fu, 2010; Luo & Chen, 2010; Wang et al.,
2012). The finding is a source of concern given that Heckman (2005) has shown
China has a history of underinvestment in the development and accumulation of
human capital. It is also disconcerting given that the national government is seeking to
encourage local administrators to expand their foci to include both short term
economic growth and long term development and social stability by increasing the
provision of social services and the resources required to generate the accumulation of
high quality human resources.
In choosing to examine the association between fiscal decentralisation and teachers’
wages and by showing that this form of decentralisation may impact wages this paper
25
has expanded the variables that are normally considered when theorising the teacher
wage determination process. This is a contribution that has pertinence both for China
and for the teacher wage determination literature more broadly as fiscal
decentralisation, to varying degrees, is the norm in many nations. That the study has
shown that fiscal decentralisation has a negative impact on teachers’ wages in China
is also a significant finding. This revelation extends the extant literature on fiscal
decentralisation and government expenditure and shows that this contingency can
have a decided impact on teachers’ wages. In the study the focus has been directed to
the wages of teachers, but it is highly plausible that a similar relationship may exist in
relation to other public service occupations across China.
That the study finds that there is no association between teachers’ wages and the
intensity of the knowledge economy across China’s regions is somewhat unexpected.
The public policy literature argues consistently that increasing the knowledge
intensity of a nation or a region’s economy will normally require an increase in
investment in education (OECD, 2008; Schleicher, 2006; World Bank, 2003). It also
argues that high wages can make an important contribution to the quality of teaching.
This is not least by increasing the quality of the high school graduates who become
teachers and by inducing good teachers to remain in the field (OECD, 2005). But
whether the association between the knowledge intensity of economies and teachers’
wages exists has not previously been documented.
Ramesh (2013) argues that China has facilitated the development of a knowledge
26
intensive economy by establishing high-technology parks, encouraging research, and
expanding the provision of education services. But he suggests that Confucian based
methods of teaching and learning prevent innovation. Consequently, China’s
government needs to find ways to produce teachers who can embrace forms of
pedagogy that are better suited to the generation of graduates who are critical,
innovative and able to learn the skills they will need to effectively participate in a
knowledge intensive economy. This need is likely to be assisted by raising teachers’
wages as the economy becomes more knowledge intensive. We, however, do not find
a positive association between the knowledge intensity of economies and teachers’
wages in China.
A possible and also reasonable explanation for this result is that an increasing demand
for high skilled labour is balanced by a rising supply of such workers. According to
Goldin and Katz (2007), the skill wage premium will not increase if the supply of
educated workers outpaces skill demand due to the upgraded technology. They find
that the wage return to education initially peaked in the United States in 1915 and did
not return to this peak until the 1980s. At the latter date the increasing demand for
skilled labour began to outpace the increased supply of educated workers and as this
situation unfolded the wage return to knowledge began to increase. In China, the
situation is similar to what occurred in the United States between 1915 and the 1980s.
Li et al. (2011) argue that China intentionally prioritised the development of tertiary
education over primary and secondary education and this created significant problems
27
of absorption and unemployment for tertiary education graduates in the labour market.
As is shown in Figure 3, the number of tertiary education graduates in China
increased dramatically from 2001 to 2013. This pushed up the supply of highly
educated workers and put downward pressure on the wages of these workers. In this
environment an increase in demand for highly skilled teachers was likely to be met by
the increasing supply of graduates and consequently the growth of the knowledge
economy was not associated with increases in teachers’ wages.
Figure 3. The number of tertiary education graduates in China from 1995 to 2013 (unit, 10,000 people)
Our finding that the development of a knowledge economy in China’s regions has not
mitigated the negative effect of fiscal decentralisation is both surprising and
disconcerting. This finding suggests that while administrators who have experienced a
deepening in the knowledge intensity of their regional economy may have become
prone to increase investment in human capital accumulation they may have also
0
100
200
300
400
500
600
700
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
28
gained kudos for realising a goal favoured by the national government. If this is the
case they may also have gained an increase in their capacity to exercise autonomy and
succumb to pressures to favour short-term growth.
It is also possible that our finding may reflect the fact that determining a wage that
will balance the need to contain education expenditures while concomitantly building
a teaching labour force that can graduate students with the learning capacities of a
future society is bound to be difficult. So doing requires that administrators accurately
forecast the attributes required of teachers in 15-20 years and pay current teachers a
wage that will induce today’s high school graduates to become educators who can
garner these skills. Setting teachers’ wages at a level that is commensurate with
economies that are becoming more knowledge intensive requires, moreover, that local
governments not succumb to the temptation to concentrate education expenditure in
areas that are easily measured or are highly prestigious. That local governments are
likely to fall prey to this last possibility has been underscored by Hanushek &
Woessmann (2015) who have documented the marked tendency for administrators to
invest in measures such as years of school attainment, class size reduction, or number
of tertiary institutions established rather than on raising teacher quality. The latter
possibility is disconcerting given that recent studies suggest education quality matters
more than quantity and that the contribution of tertiary education to economic growth
disappears when the quality of schooling is considered in growth models (Hanushek
& Woessmann, 2015; OECD, 2015).
29
Conclusion
This paper has provided evidence that fiscal decentralisation does have a significant
effect on urban school teachers’ wages in China. It finds that fiscal decentralisation
has a negative impact on teachers’ wages. But unexpectedly, our research does not
find that the growth of a knowledge economy in China is an important teacher wage
determinant.
Although there seems no direct effect of knowledge economy on teacher wages, the
negative impact of fiscal decentralisation has been strengthened by knowledge
economy. We have proposed possible explanations for this finding in the discussion
section. Whether this is the case awaits testing.
These findings suggest that local governments in China have not sufficiently modified
their inclination to concentrate on short-term growth. Given this is the case we
conclude that that if the national government is convinced of the need to increase
teacher quality it will need to revisit the incentives being offered to local
administrators to invest in the development of human capital and embrace wage
policies that are suited to the knowledge economy China wishes to construct.
30
References:
Aaronson, D., Barrow, L., & Sander, W. (2007). Teachers and student achievement in
the Chicago public high schoos. Journal of Labor Economics, 25(1), 95-135.
Acemoglu, D. (1998). Why do new technologies complement skills? Directed
technical change and wage inequality. Quarterly Journal of Economics, 113,
1055-1090.
Blau, F. D., & Kahn, L. M. (2000). Gender differences in pay. Journal of Economic
Perspectives, 14(4), 75-99.
Brandt, L., & Holz, Carsten A. (2006). Spatial price differences in China: Estimates
and implications. Economic Development and Cultural Change, 55(1), 43-86.
Cai, F., & Wang, M. (2014). Accumulate human capital for China's sustainable growth.
In F. Cai (Ed.), Chinese Research Perspectives on Population and Labor,
Volume 1. Leiden: Brill.
Chen, S. (2010). Fenshuizhi gaige, difang caizheng zizhuquan yu gonggongpin gongji
[Tax-share reform, local fiscal autonomy, and public goods provision]. China
Economic Quarterly, 9(4), 1427-1446.
Chen, S., & Gao, L. (2012). Yangdiguanxi: Caizhengfenquan duliang ji zuoyongjizhi
zaipinggu [Central-local relations: Evaluation on the measurement of fiscal
decentralisation and its impact]. Management World, (6), 43-59.
Chen, Y., Li, H., & Zhou, L.-A. (2005). Relative performance evaluation and the
turnover of provincial leaders in China. Economics Letters, 88(3), 421-425.
Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014a). Measuring the impacts of
teachers I: Evaluating bias in teacher value-added estimates. American
Economic Review, 104(9), 2593-2632.
Chetty, R., Friedman, J. N., & Rockoff, J. E. (2014b). Measuring the impacts of
teachers II: Teacher value-added and the student outcomes in adulthood.
American Economic Review, 104(9), 2633-2679.
Cheung, S. N. S. (2008). The economic system of China. Paper presented at the
Conference on China's Economic Transformation, Chicago.
Dolton, P., & Marcenaro-Gutierrez, O. D. (2011). If you pay peanuts do you get
monkeys? A cross-country analysis of teacher pay and pupil performance.
Economic Policy, 26(65), 5-55.
Fu, Y. (2010). Caizhengfenquan, zhengfuzhili, yu feijingjixing gonggongwupin gongji
[Fiscal decentralisation, governance, and non-economic public goods
provision]. Economic Research Journal, (8), 4-15.
Fu, Y., & Zhang, Y. (2007). Zhongguoshi fenquan yu caizhengzhichujiegou pianxiang:
Wei zengzhang er jingzheng de daijia [Chinese style decentralisation and
distorted fiscal expenditure structure: The cost of competing for economic
growth]. Management World, (3), 4-12.
Garnaut, R. (2011). Australian opportunities through the Chinese structural
transformation. Australian Economic Review, 44(4), 437-445.
31
Gaulier, G., Lemoine, F., & Ünal-Kesenci, D. (2007). China’s integration in east Asia:
Production sharing, FDI & high-tech trade. Economic Change and
Restructuring, 40(1-2), 27-63.
Goldhaber, D. (2009). The politics of teacher pay reform. In M. G. Springer (Ed.),
Performance incentives: Their growing impact on American K-12 education
(pp. 25-42). Washington, DC: Brookings Institution Press.
Gong, F., & Lu, H. (2009). Gonggongzhichujiegou, pianhaopipei yu caizhengfenquan
[Public expenditure components, preference-matching and fiscal
decentralisation]. Management World, (1), 10-21.
Goldin, C., & Katz, L. F. (2007) The race between education and technology: The
evolution of U.S. educational wage differentials, 1890 to 2005. NBER
Working Paper No. 12984. National Bureau of Economic Research.
Cambridge, MA.
Gordon, R. H., & Li, W. (2011). Provincial and local governments in China: Fiscal
institutions and government behavior. NBER Working Paper No.16694.
National Bureau of Economic Research. Cambridge, MA.
Guo, Q., & Jia, J. (2010). Caizhengfenquan, zhengfu zuzhijiegou yu difangzhengfu
zhichuguimo [Fiscal decentralisation, government structure and local
government's expenditure size]. Economic Research Journal, 11, 59-72.
Hanushek, E. A., & Rivkin, S. G. (2010). Generalizations about using value-added
measures of teacher quality. The American Economic Review, 100(2), 267-271.
Hanushek, E. A., & Woessmann, L. (2015). The knowledge capital of nations:
Education and the economics of growth. Cambridge, MA: The MIT Press.
Harbison, R. W., & Hanushek, E. A. (1992). Educational performance of the poor:
Lessons from rural northeast Brazil. New York: Oxford University Press.
Heckman, J. J. (2005). China's human capital investment. China Economic Review,
16(1), 50-70.
Heckman, J. J., & Yi, J. (2012). Human capital, economic growth, and inequality in
China. NBER Working Paper No.18100. National Bureau of Economic
Research. Cambridge, MA.
Hoxby, C. M. (1996). How teachers' unions affect education production. The
Quarterly Journal of Economics, 111(3), 671-718.
Jia, J., Guo, Q., & Zhang, J. (2014). Fiscal decentralisation and local expenditure
policy in China. China Economic Review, 28, 107-122.
Jin, H., Qian, Y., & Weingast, B. R. (2005). Regional decentralisation and fiscal
incentives: Federalism, Chinese style. Journal of Public Economics, 89(9–10),
1719-1742.
Katz, L. F., & Margo, R. A. (2014). Technical change and the relative demand for
skilled labor: The United States in historical perspective. In L. P. Boustan & C.
M. Frydman, Robert A. (Eds.), Human capital in history: The American
record (pp. 15-57). Chicago: University of Chicago Press.
Leigh, A. (2010). Estimating teacher effectiveness from two-year changes in students’
test scores. Economics of Education Review, 29(3), 480-488.
32
Li, H., & Zhou, L.-A. (2005). Political turnover and economic performance: The
incentive role of personnel control in China. Journal of Public Economics,
89(9–10), 1743-1762.
Li, J., Zhang, Q., & Wang, X. (2012). Caizhengfenquan yu touzi pianhao de
difangzhengfu xingwei: Jiyu shengji mianbanshuju de shizheng yanjiu [Fiscal
decentralisation and local government behavior of investment bias: an
empirical study based on provincial panel data]. Industrial Economics
Research, 60(5), 72-79.
Li, W. (2007). Caizhengfenquan yu difangzhengfu zhichujiegou pianxiang: Jiyu
zhongguo shengji mianbanshuju de yanjiu [Fiscal decentralisation and fiscal
expenditure composition of subnational governments: based on China's
provincial panel data]. Journal of Shanghai University of Finance and
Economics, 9(5), 75-82.
Li, Y. A., Whalley, J., Zhang, S., & Zhao, X. (2011). The higher educational
transformation of China and its global implications. The World Economy,
34(4), 516-545.
Liang, R. (2009). Caizhengfenquanxia de jinshengjili, bumenliyi yu tudiweifa
[Promotion incentives, departmental interests and land law breaking under
fiscal decentralisation]. China Economic Quarterly, 9(1), 283-306.
Liu, T.-w. (2011). The politics of social spending in China: The role of career
incentives. (PhD thesis), University of California, San Diego, the United
States.
Luo, W., & Chen, S. (2010). Fiscal decentralisation and public education provision in
China. Canadian Social Science, 6(4), 28-41.
Martinez-Vazquez, J., & Timofeev, A. (2010). Decentralisation measures revisited.
Public Finance and Management, 10(1), 13-47.
Metzler, J., & Woessmann, L. (2012). The impact of teacher subject knowledge on
student achievement: Evidence from within-teacher within-student variation.
Journal of Development Economics, 99(2), 486-496.
Niu, M. (2013). Fiscal decentralisation in China revisited Australian Journal of Public
Administration, 72(3), 251-263.
Oates, W. E. (2008). On the evolution of fiscal federalism: Theory and institutions.
National Tax Journal, 61(2), 313-334.
OECD. (1996). The knowledge-based economy. Retrieved from
http://www.oecd.org/sti/sci-tech/1913021.pdf
OECD. (2005). Teachers matter: Attracting, developing and retaining effective
teachers. Paris: OECD publishing.
OECD. (2008). Innovating to learn, learning to innovate. Paris: OECD Publishing.
OECD. (2011). Strong performers and successful reformers in education: Lessons
from PISA for the United States. Paris: OECD Publishing.
OECD. (2015). Universal basic skills: What countries stand to gain. Paris: OECD
Publishing.
OECD, & Korea Institute of Public Finance. (2013). Measuring fiscal
33
decentralisation: Concepts and policies. Paris: OECD Publishing.
Pang, L., Han, X., Xie, Y., Li, L., & Xia, J. (2010). Wanshan jizhi, luoshi yiwujiaoyu
jiaoshi jixiaogongzi zhengce [Improving mechanism to implement the policy
of performance-related pay of compulsory education teachers]. Educational
Research, 363(4), 40-44.
Pang, W., & Plucker, J. (2013). Recent transformations in China's economic, social,
and education policies for promoting innovation and creativity. The Journal of
Creative Behavior, 46(4), 247-273.
Podgursky, M., & Springer, M. G. (2007). Teacher performance pay: A review.
Journal of Policy Analysis and Management, 26(4), 909-949.
Porcelli, F. (2009). Fiscal decentralisation and efficiency of government: A brief
literature review. Department of Economics, University of Warwick, the
United Kingdom. Retrieved from
http://www2.warwick.ac.uk/fac/soc/economics/staff/fporcelli/dec_efficiency_
gov.pdf
Propper, C., & Britton, J. (2012). Does wage regulation harm kids? Evidence from
English Schools. The Centre for Market and Public Organisation, University
of Bristol, the United Kingdom. Retrieved from
www.bristol.ac.uk/cmpo/publications/papers/2012/wp293.pdf
Qian, X., & Smyth, R. (2006). Growth accounting for the Chinese provinces 1990–
2000: Incorporating human capital accumulation. Journal of Chinese
Economic and Business Studies, 4(1), 21-37.
Qian, Y., & Roland, G. (1998). Federalism and the soft budget constraint. American
Economic Review, 88(5), 1143-1162.
Qiao, B., Fan, J., & Feng, X. (2006). Fiscal decentralisation and compulsory primary
education: The case of China. Social Sciences in China: A Quarterly Journal,
27(2), 62-76.
Ramesh, S. (2013). China's transition to a knowledge economy. Journal of the
Knowledge Economy, 4(4), 473-491.
Rockoff, J. E. (2004). The impact of individual teachers on student achievement:
Evidence from panel data. The American Economic Review, 94(2), 247-252.
Schleicher, A. (2006). The economics of knowledge: Why education is key for
Europe's success. Lisbon Council Policy Brief, 1(1). Retrieved from
http://www.oecd.org/education/skills-beyond-school/36278531.pdf
Schleicher, A. (2011). Building a high-quality teaching profession: Lessons from
around the world. Paris: OECD publishing.
Shen, K., & Fu, W. (2005). Zhongguo de caizhengfenquan zhidu yu diqu
jingjizengzhang [The relationship between China's decentralised system in
finance and the regional economic growth]. Management World, (1), 31-39.
Slater, H., Davies, N. M., & Burgess, S. (2012). Do teachers matter? Measuring the
variation in teacher effectiveness in England. Oxford Bulletin of Economics
and Statistics, 74(5), 629-645.
Tucker, M. S. (2012). Researching other countries' education systems: Why it's
34
indispensable but tricky, how we did it, why this time it's different. In M. S.
Tucker (Ed.), Surpassing Shanghai: An agenda for American education built
on the world's leading systems (pp. 1-18). Cambridge: Harvard Education
Press.
Wang, W., Zheng, X., & Zhao, Z. (2012). Fiscal reform and public education spending:
A quasi-natural experiment of fiscal decentralisation in China. Publius: The
Journal of Federalism, 42(2), 334-356.
Wooldridge, J. M. (2012). Introductory econometrics: A modern approach (5th ed.).
New York: South-Western College Pub.
World Bank. (2003) Lifelong learning in the global knowledge economy: Challenges
for developing countries. Washington D.C.: The World Bank.
World Bank. (2013). China 2030: Building a modern, harmonious, and creative
society. Washington, DC: World Bank.
http://documents.worldbank.org/curated/en/2013/03/17494829/china-2030-bui
lding-modern-harmonious-creative-society
Xing, Z., & Deng, C. (2012). Caizhengfenquan yu nongcun yiwujiaoyu yanjiu: Jiyu
caizhengzizhudu shijiao [Fiscal decentralisation and rural compulsory
education: Based on self-financing rate]. Economic Issues in China, 273(4),
62-68.
Yang, L. (2013). Zhongguo ganbu guanlitizhi jianshaole difangzhengfu jiaoyuzhichu
ma? Laizi shengji guanyuan de zhengju [Does China's cadres' management
system lead to less educational spending? Evidence from provincial data].
Journal of Public Management, (2), 41-51.
Zeng, X., & Yu, X. (2015). Jiaoshi lanpishu: Zhongguo zhongxiaoxue jiaoshi fazhan
baogao (2014) [Blue Book of Teacher: Annual Report on the Teachers in
China (2014)]. Beijing: Social Sciences Academic Press.
Zhang, G. (2011). Celiang zhongguo de caizhengfenquan [Measure fiscal
decentralisation in China]. Comparative Economic and Social Systems, 158(6),
48-60.
Zhang, T., & Zou, H.-f. (1998). Fiscal decentralisation, public spending, and
economic growth in China. Journal of Public Economics, 67(2), 221-240.
Zhao, Y. (2014). Who's afraid of the big bad dragon? Why China has the best (and
worst) education system in the world. CA: Jossey-Bass.
Zheng, L. (2008). Caizhengfenquan, zhengfujingzheng yu gonggongzhichujiegou:
Zhengfu jiaoyuzhichubizhong de yingxiangyinsu fenxi [Fiscal decentralisation,
local government competition and public expenditure structure: An analysis on
the factors affecting the proportion of education expenditure], Economic
Science, (1), 28-40.
35
Appendix
Table A1. Measurement and data sources of variables
a. China Innovation Index calculated by National Bureau of Statistics of China uses 10,000
persons as the denominator- see
http://www.stats.gov.cn/english/PressRelease/201402/t20140220_513946.html for more
information.
b. Values are missing in this source, such as Shanghai 2001, Tibet 2001, 2003, 2006, 2007 and
2008. The Shanghai 2001 data was retrieved from Shanghai Statistical Yearbook 2002. And Tibet
2001 and 2003 data were retrieved from Comprehensive Statistical Data and Materials on 55
Years of New China. Tibet 2006, 2007 and 2008 data was found in the Tibet Autonomous Region
Government Report 2007, 2008 and 2009.
c. Brandt and Holz (2006) computed the index up to 2004. We updated the index to 2013
following their method.
Variable Measurement ata sources
Wages (P) Primary school staff average wages per year (RMB) China Labour Statistic Yearbook
Wages (S) Secondary school staff average wages per year (RMB) China Labour Statistic Yearbook
FD Provincial revenue/provincial expenditure (%) Finance Yearbook of China
R&D R&D personnel in full-time equivalent per 10,000 persons a China Statistical Yearbook of Science and
Technology
Size of KE workforce Population with college or above education as a percentage
of working age population (15 to 64)
China Population and Employment
Statistics Yearbook/ China Population
Statistics Yearbook
Knowledge creation Certified patent applications per year China Statistical Yearbook of Science and
Technology
Fiscal capacity Fiscal revenue per capita Finance Yearbook of China
Female (P) Proportion of female teachers in primary schools (%) Educational Statistic Yearbook
Female (S) Proportion of female teachers in secondary schools (%) Educational Statistic Yearbook
Education (P) Average years of schooling of primary school teachers Educational Statistic Yearbook
Education (S) Average years of schooling of secondary school teachers Educational Statistic Yearbook
Senior rank (P) Proportion of teachers with senior professional rank in
primary schools (%)
Educational Statistic Yearbook
Senior rank (S) Proportion of teachers with senior professional rank in
secondary schools (%)
Educational Statistic Yearbook
Ratio (P) Student-teacher ratio in primary schools Educational Statistic Yearbook
Ratio (S) Student-teacher ratio in secondary schools Educational Statistic Yearbook
Enrolment growth (P) Enrolment change rate in primary schools (%) Educational Statistic Yearbook
Enrolment growth (S) Enrolment change rate in secondary schools (%) Educational Statistic Yearbook
COL Spatial price index Brandt and Holz (2006) c
Unemployment rate Urban registered unemployment rate (%) Website of National Bureau of Statistics
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