Religious Diversity and Economic
Development in China
Shinbao Liua, Shuming Baob, c
a,b
School of Economics, Xiamen University, Xiamen 361005, China
China Data Center, University of Michigan, Ann Arbor, MI 48106, USA
c
Lab for Urban and Regional Analysis, East China University of Science and Technology,
Shanghai 200237, China
b
Abstract:
This paper investigates the interaction between religious diversity and economic
development in China. We use religious fragmentation and polarization to measure
the diversity of religion. Based on the panel data of religious sites by province from
economic census in China, we apply panel data regression to find the following
evidence: (1) Religious fragmentation demonstrates a positive and significant impact
on regional economic development while religious polarization has a negative and
significant impact on regional economic development with different patterns in the
eastern, central and western regions of China. (2) Economic development shows a
positive and significant influence on religious fragmentation while its impact on
polarization is positive but insignificant. A significant two-way relationship exists
between religious diversity and economic development in China. We discussed policy
implication with convincible results.
JEL: O1, R1, Z1
Key words: Religion Diversity, Fragmentation, Polarization, Economic Development
1. Introduction
Religion is usually related to the people’s lifestyle and country culture, but less in
the determinants of economic development. According to Karl Marx, religion is like
other social institutions in that it is dependent upon the material and economic
realities in a given society. It has no independent history; instead it is the creature of
productive forces. As Marx wrote, “The religious world is but the reflex of the real
world.”
Since Azzi and Ehren-berg (1975), the economics of religion has grown into a
sizable body of research. They pay their attention to the topics following: the nature
of religion; the determinants of individual religiosity and participation rates;
conversion, commitment, and religious mobility; the emergence and evolution of
religious institutions; secularization and pluralism; deviant religions; the
1
socioeconomic correlates of sect membership; church–state issues; the economic
consequences of religion; and so on. They deem that religion has close relationship
with people’s life, society and economic growth.
Different conclusions are reached because different data sources and different
measurable indicators are adopted in the research of religion. Montalvo and
Reynal-Querol (2003) also made a contribution to this research using diversity
measurements of fragmentation and polarization. Then Eum (2011) tests the theories
of Montalvo and Reynal-Querol with updated datasets to see if their conclusions still
hold true. When we take China into account, it has a significant background of
religion, so what of the specific relationship between its religious diversity and
economic development? This paper refers to religious fragmentation and religious
polarization of Montalvo & Reynal-Querol (2003) from the point of religion sites as
the indicator of Religious Diversity in China. By analyzing China nationwide and
regional Religious Diversity and economic growth from 1987 to 2004, we try to find
whether the religious diversity in China significantly influence its economic growth
and analyze the way of influence based on the results.
The rest of this paper is organized as follows. In section 2, literatures studied,
religious diversity, and economic development are reviewed. We present econometric
methodology used in this paper in section 3. Section 4 describes the datasets and
discusses the estimation results of regressions. Finally, section 5 shows the conclusion
and extended work.
2. Literature Review
When we study religion, religious diversity is the first kernel we meet. Barro
(1999) and Sala-i-Martinet al. (2004) used the fractions of the population affiliated
with different religious groups to measure religious diversity. With the same religious
measurement, Noland (2005) used both cross-country and within-country regressions
to investigate the relationship between religion and economic performance, and found
they were related in most case.
Based on international survey data on religiosity for a broad panel of countries,
Barro and McCleary (2003) constructed instrumental variables of state religion,
regulation of the religion market and measures of religious pluralism 1 based on
Herfindahl indexes for the religion shares to investigate the effects of church
attendance and religious beliefs on economic growth. They find that economic growth
responds positively to the extent of religious beliefs, notably those in hell and heaven,
but negatively to church attendance. Later, McCleary and Barro (2006a) used state
religion, regulation of religion market and religious pluralism to study the effect of
religious diversity.
Most of them use state religion to show the polarity effect and use religious
affiliation as the differentiated effects of religious diversity.
Moreover, Montalvo and Reynal-Querol (2003) used religious fragmentation and
1
The Herfindahl index equals the sum of the squares of the population fractions belonging to each religion,
Barro and McCleary’s pluralism index equals 1 - the Herfindahl index.
2
polarization to measure religious diversity. By using the augmented Solow model
proposed by Mankiw, Romer, and Weil (1992), they analyzed the relationship
between religion and economic development in 83 countries from 1960 to 1992 and
found that religious polarization had a negative significant effect on economic
development while religious fragmentation does not have any effect. They argued that
polarization is superior to fragmentation as a explanatory variable of economic
development. Eum (2011) also uses the augmented Solow model with Montalvo’s two
religiosity factors. When testing Montalvo and Reynal-Querol’s theory, he includes
religious dummies and continent factors as well to account for geographical
differences. This paper uses religious fragmentation and polarization to measure
religious diversity.
Another important research area for religion and economic development is the
two-way interaction between them.
McCleary and Barro (2006a) extended two important theories of religiosity:
secularization hypothesis from a demand-side theory and the religion-market model
from a supply-side theory, by using survey information for 68 countries over the last
20 years, found that economic development tended to reduce religiosity, which was in
accord with the secularization view. However, according with the religion-market
model, religiosity negatively related with government regulation of the religion
market and Communist suppression. Moreover, their instrumental estimates showed
that there was only one way causation from economic development to religiosity.
McCleary and Barro (2006b) focused on macroeconomic aspects of interaction
between religion and political economy and used international data to test the
two-way relationship. This paper also tests the interaction of religious diversity and
economic development in China.
3. Econometric methodology
According to Montalvo & Reynal-Querol (2003), the index of religious
fragmentation (FRAG) that can be interpreted as the probability that two randomly
selected individuals in a country will belong to different religious groups. The form of
this indicator is the following:
𝑛
𝐹𝑅𝐴𝐺𝑖 = 1 − ∑𝐽𝑗=1 ( 𝑁𝑖𝑗)
2
(1)
𝑖
Where
𝑛𝑖𝑗
𝑁𝑖
represents the proportion of sites of religion type j in total religion sites in
province i. Therefore FRAG increase when the number of religion type increase, it
gets the maximum as each religion has an equal size. An alternative indicator of
religious diversity is the index of religious polarization of Montalvo and
Reynal-Querol (2000), which is as following:
𝑃𝑂𝐿𝑖 = 1 − ∑𝐽𝑗=1 (
3
0.5−𝜋𝑖𝑗 2
0.5
) 𝜋𝑖𝑗
(2)
𝒏𝒊𝒋
Where 𝜋𝑖𝑗 is equal to 𝑵 . The index POL ranges from 0 to 1. Opposite to what
𝒊
happens with the fragmentation index, polarization reaches a minimum when there are
four religious groups of equal size.
Likewise, we estimate the augmented Solow model proposed by Mankiw et al. (1992)
with the inclusion of religious indicators. The basic empirical specification can be
written as:
𝑌(𝑡)
𝑙𝑛 𝐿(𝑡) = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘 + 𝛽2 𝑙𝑛𝑠ℎ + 𝛽3 ln(𝑛 + 𝑔 + 𝛿) + 𝑢
(3)
Where Y/L is the output per worker, 𝑠𝑘 is the rate of investment in physical capital,
𝑠ℎ is the rate of investment in human capital, n is the growth rate of population g is
the rate of technological change and 𝛿 is the depreciation rate. When we take the
impact of religion into account, the equation becomes:
𝑌(𝑡)
𝑙𝑛 𝐿(𝑡) = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘 + 𝛽2 𝑙𝑛𝑠ℎ + 𝛽3 ln(𝑛 + 𝑔 + 𝛿) + 𝛽4 𝑟𝑒𝑙𝑖𝑔𝑖𝑜𝑛 + 𝑢
(4)
Based on equation (4), considering the panel data model, then (4) becomes:
𝑙𝑛𝑟𝑝𝑔𝑑𝑝𝑖𝑡 = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘,𝑖𝑡 + 𝛽2 𝑙𝑛𝑠ℎ,𝑖𝑡 + 𝛽3 ln(𝑛 + 𝑔 + 𝛿)𝑖𝑡 + 𝛽4 𝑟𝑒𝑙𝑖𝑔𝑖𝑜𝑛𝑖𝑡 + 𝑢𝑖𝑡
(5)
When we use fragmentation to measure religion development, we get:
𝑙𝑛𝑟𝑝𝑔𝑑𝑝𝑖𝑡 = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘,𝑖𝑡 + 𝛽2 𝑙𝑛𝑠ℎ,𝑖𝑡 + 𝛽3 ln(𝑛 + 𝑔 + 𝛿)𝑖𝑡 + 𝛽4 𝐹𝑅𝐴𝐺𝑖𝑡 + 𝑢𝑖𝑡 (6)
When we use polarization to measure religion development, we get:
𝑙𝑛𝑟𝑝𝑔𝑑𝑝𝑖𝑡 = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘,𝑖𝑡 + 𝛽2 𝑙𝑛𝑠ℎ,𝑖𝑡 + 𝛽3 ln(𝑛 + 𝑔 + 𝛿)𝑖𝑡 + 𝛽4 𝑃𝑂𝐿𝑖𝑡 + 𝑢𝑖𝑡
(7)
When we take the two dimensional indicators of religion together, we can get:
𝑙𝑛𝑟𝑝𝑔𝑑𝑝𝑖𝑡 = 𝛽0 + 𝛽1 𝑙𝑛𝑠𝑘,𝑖𝑡 + 𝛽2 𝑙𝑛𝑠ℎ,𝑖𝑡 + 𝛽3 ln(𝑛 + 𝑔 + 𝛿)𝑖𝑡 + 𝛽4 𝐹𝑅𝐴𝐺𝑖𝑡
+𝛽5 𝑃𝑂𝐿𝑖𝑡 + 𝑢𝑖𝑡
(8)
4. Empirical Studies
To conduct our analyses, we need measures of religion diversity, economic
development and some other economic development explanatory variables.
1. Data and summary statistics
The data of fragmentation and polarization used to measure religion is from the
religion sites of the 2004 China economic census. There are four main types of
religion in China: Buddhism, Christianity, Daoism and Islam, the distributions of the
4
two indicators are shown in figure 1 and 2. Based on the panel data model of (6), (7)
and (8), we use real income per capita to measure the level of economic development,
average education attainment to measure human capital level, government
expenditure excluding, education, arts and health expenditure to measure the policy
variable, and fixed asset investment to measure the rate of investment in physical
capital. The data of these variables is from Statistical material in 60 years of new
China and managed by the author. The summary statistics of these variables are listed
in table 1. Although the variation among provinces is influenced by some outliers, the
variation does indicate differences in the timing and extent of economic development
across China. We include these observations in our model as individual fixed effect
for provinces.
As we will study the relationship between religion and economic development of
the nationwide and regions of China from all its provinces, we have the following
hypothesizes: 1. All the provinces have the same growth rate of technology as the
nationwide of China, which we quote from Guo & Jia (2005). 2. All the provinces
have the same rate of depreciation, which is from Fang (2012). 3. The size of religion
sites is homogenous during all the religion sites, the religion sites is in direct
proportion to the attendance. 4. The percentage share of each type of religious sites in
each province is representative of each religion’s respective provincial share of total
sites. If the sites will disappear after they are founded, they will disappear in equal
proportion.
2. Empirical results
According to panel data model, using panel data regression, when we only take
one of the indicators of religion into account, we can get the results as table 2 shows.
As table 2 shows, (1), (2), (3) and (4) represent case of nationwide, east, middle
and west respectively, while (5), (6), (7) and (8) have the analogous reference with
polarization instead of fragmentation. All tables after this have similar representatives.
When we study the impact of religion on economic development from fragmentation
or polarization of religion, we found that fragmentation of religion has a positive
influence on economic development in the nationwide of China, while extreme
variation exists in different regions of China. In eastern China, religion fragmentation
has a positive significant impact on its economic development, in middle of China,
the influence is positive but insignificant while in western China, the influence is
negative and insignificant. When it comes to polarization, to the nationwide of China,
it has a positive but insignificant influence on its economic development while in its
three regions the influence has a remarkable different performance. East has the same
case as in nationwide; the Middle part of China has negative but insignificant
influence while West has a positive and very significant impact.
Now we take two indicators into consideration at the same time in the panel data
model, we can get the results as table 3.
In order to measure the religion development more accurately, we add
fragmentation and polarization of religion into the panel data at the same time, and we
get equation (8). As table 3 shows, we can find that in all of China, religion
fragmentation has a positive significant influence on its economic development while
5
polarization has a negative significant one. The eastern and middle of China has the
same conclusion of both religion indicators, with larger influence in middle than east.
For western China, the conclusion is just the opposite. The religion fragmentation has
a negative significant influence on its economic development while polarization has a
positive significant impact.
Montalvo & Reynal-Querol (2003) showed that religious polarization is superior
to the explanatory power of religious fragmentation; however, in the case of China,
we found that both of them have significant influences on economic development
while fragmentation have a positive influence and polarization has a negative one. A
key reason is that the political regime of provinces is different from countries; in
addition, all provinces share the same law rule while countries face different ones.
That is to say, according to the history of China, the equalizing the size of different
religions can promote its economy, while centralizing in one religion will mitigate its
economy in some extent. We try to explain these with the actual situation of China.
The three main regions of China have remarkable difference in its economic
development level, regional diversity, supportive policies, population distribution,
economic diversity and religion development and so on. When it comes to economic
growth rate, east is bigger than middle and middle is bigger than west. In fact, big
difference exists in the distribution of religion in each region; some provinces have a
number of religion sites while some provinces have so few ones. Different
distribution of religion sites in each region and different economic diversity make
different impacts of religion on economic development possible.
Next, we study the impact of economic development on religion, by using
religious fragmentation to measure religion, we can get table 4. While using religious
polarization to measure religion development, we can get table 5.
As table 4 shows, from the nationwide, economic development has a positive
significant influence on religion development. When it comes to the three main
regions of China, a huge difference exists between them. Due to the economic
development of each region, the eastern economy has a positive significant influence
on its religion development; the middle economy has a positive but insignificant one
while western economy has a negative insignificant influence on religious
fragmentation. After we take polarization into consideration, the same conclusion
exists.
When we turn to religious polarization, from the nationwide, economic
development has a positive but insignificant influence on its religion development.
Eastern economy has a positive but insignificant influence on religious polarization,
middle economy has a negative insignificant one while western economy has a
positive and significant influence on its religious polarization. When religious
fragmentation was added in the model, the conclusion changed totally. From
nationwide of China, the influence becomes negative and significant. The influence of
the eastern economy becomes negative and stays insignificant, for the middle
economy the influence becomes significant from insignificant and stays negative
while the western economy stays the same. Whether from religious polarization to
economic development or the inverse way, the impact is negative. One of the possible
6
reasons is that religious polarization reflects potential religious conflict in a society
(Montalvo & Reynal-Querol (2003)). The smaller the polarization is, the bigger is the
conflict. Given that conflict both causes and exacerbates poverty and interrupts
development, religious polarization is used to explain some of society conflict and
violence, especially after 9/11 (Nath, 2007).
From the two-way interaction analysis, we show that two-way relationship exists
between religious diversity and economic development in China. From the point of
religious fragmentation, the two-way interaction is positive while that is negative for
religious polarization.
5. Summary and Discussions
Due to long history of China, religion development in China and its main regions
has a complicated relationship with its economic development. We study religious
diversity from its two characters: fragmentation and polarization, and we study the
relationship between religious fragmentation and polarization and economic
development. We found that bi-directional relationship between religion and
economic development existed. From the nationwide of China, religious
fragmentation has a positive significant promoting function on its economic
development while religious polarization has a negative significant one, and different
influences exist in eastern, middle and western of China.
For the impact of economic development on religion, from the nationwide,
economic development has a positive significant influence on religious fragmentation
with or without polarization included as an explanatory variable, while the impact on
polarization is positive but insignificant, it becomes negative and significant with
fragmentation included as an explanatory variable.
According to our empirical study, we can find that from 1987 to 2004, religion
has been playing a significant role in Chinese economic development. The policy
makers should take the effect of religion and the impact on religion into consideration.
Due to the limit of data sources, we can’t study longer term relationship between
religion and economic development in China. We can have further study on the
relationship between religion and economic development by developing more
accurate religion development indicators and getting longer time span data.
Acknowledgement: The authors would like to thank Henry Luce Foundation for their
funding support for the project of “Spatial Study of Chinese Religions and Society”
and anonymous reviewers for their valuable comments and suggestions to improve
the quality of the paper.
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7
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8
Figures and Tables
Fig. 1. Religious Fragmentation of Main Land China in 2004
Fig. 2. Religious Polarization of Main Land China in 2004
9
Table 1 descriptive statistics of variables
Variable
Description
Obs
Mean
Std. Dev.
rpgdp
fra
pol
edu
capi
publ
n+g+ 𝛿
real income per capita
522
522
522
522
522
522
522
2140.291
0.724
0.838
6.937
0.339
0.129
5.184
2186.746
0.154
0.104
1.142
0.098
0.050
2.469
religious fragmentation
religious polarization
average education attainment
investment in physical capital
policy variable
Growth rate of labor & tech, dep.
Min
Max
374.784 18885
0
0.967
0
0.966
4.354 10.559
0.153
0.731
0.049
0.349
-2.202 15.688
Data source: Economic census 2004, Statistical material in 60 years of new China and
http://chinadataonline.org/
Table 2 the impact of religion (one indicator) on economic development
lnfra
ln(n+g+ 𝛿)
lnedu
lncap
lnpub
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
0.505***
0.442***
0.0714
-0.0961
(6.53)
(4.26)
(0.99)
(-0.52)
-0.0045
-0.0005
-0.0140
0.0104
-0.0020
0.00003
-0.0146
0.0205
(-0.36)
(-0.03)
(-0.66)
(0.67)
(-0.15)
(0.00)
(-0.69)
(1.36)
-0.475***
0.0332
0.248
-0.443***
-0.411***
0.103
0.245
-0.418***
(-3.44)
(0.14)
(1.25)
(-2.78)
(-2.85)
(0.41)
(1.23)
(-2.79)
0.0298
0.239***
0.0670**
0.0855*
0.0577**
0.280***
0.0725**
0.0933**
(1.06)
(5.75)
(2.15)
(1.78)
(1.98)
(6.56)
(2.35)
(2.12)
-0.108***
-0.271***
0.0798
-0.135*
-0.133***
-0.311***
0.101*
-0.0809
(-2.63)
(-5.32)
(1.43)
(-1.94)
(-3.10)
(-5.77)
(1.76)
(-1.26)
0.137
0.153
-0.115
1.596***
lnpol
(1.02)
(1.05)
(-0.85)
(4.03)
7.486***
6.853***
6.280***
6.959***
7.221***
6.579***
6.295***
7.343***
(28.40)
(15.67)
(15.24)
(21.96)
(26.57)
(14.45)
(15.26)
(25.63)
N
516
192
144
180
516
192
144
180
R2
0.973
0.986
0.993
0.980
0.971
0.984
0.993
0.982
A-R2
0.970
0.983
0.992
0.976
0.967
0.981
0.992
0.978
F Sta.
761.5
502.9
781.6
332.7
697.4
453.7
779.8
369.4
_cons
t statistics in parentheses,
A-R2
is adjusted
R2 ,
F Sta. is F statistics. * indicates significance levels of p <
1%, ** indicates significance levels of p < 5%, *** indicates significance levels of p < 1%. All the tables
following have the same expressions.
10
Table 3 The impact of religion (two indicators) on economic development
(1)
(2)
(3)
(4)
lnrpgdp
lnrpgdp
lnrpgdp
lnrpgdp
0.713***
0.545***
0.569***
-0.472**
(7.46)
(4.40)
(3.92)
(-2.48)
-0.0074
-0.0020
-0.0106
0.0223
(-0.58)
(-0.11)
(-0.53)
(1.50)
-0.576***
-0.251
-1.058***
2.037***
(-3.63)
(-1.51)
(-3.89)
(4.76)
-0.496***
0.0169
0.268
-0.344**
(-3.63)
(0.07)
(1.43)
(-2.29)
0.0356
0.241***
0.0336
0.132***
(1.28)
(5.83)
(1.10)
(2.87)
-0.0777*
-0.249***
0.150***
-0.120*
(-1.88)
(-4.73)
(2.69)
(-1.83)
7.558***
6.923***
6.348***
7.106***
(28.96)
(15.81)
(16.32)
(23.88)
N
516
192
144
180
R2
0.974
0.986
0.994
0.983
A-R2
0.971
0.983
0.993
0.979
F Sta.
748.0
485.1
840.7
365.9
lnfra
Ln(n+g+ 𝛿)
lnpol
lnedu
lncap
lnpub
_cons
Table 4 The impact of economic development on religion (fragmentation)
lnrpgdp
lnedu
lncap
lnpub
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Lnfra
lnfra
lnfra
lnfra
lnfra
lnfra
lnfra
lnfra
0.166***
0.232***
0.121
-0.0194
0.150***
0.201***
0.212***
-0.0818**
(6.53)
(4.28)
(1.01)
(-0.54)
(7.45)
(4.42)
(3.97)
(-2.40)
0.200**
0.134
-0.0691
0.127*
0.184***
0.138
-0.0934
0.122*
(2.51)
(0.78)
(-0.27)
(1.77)
(2.91)
(0.96)
(-0.82)
(1.90)
0.0538***
0.0453
0.0640
0.0737***
0.0223*
0.0150
0.0528***
0.0891***
(3.38)
(1.38)
(1.58)
(3.58)
(1.75)
(0.54)
(2.93)
(4.78)
-0.0181
0.0013
0.0989
-0.110***
-0.056***
-0.0482
-0.107***
-0.089***
(-0.76)
(0.03)
(1.38)
(-3.70)
(-2.98)
(-1.43)
(-3.21)
(-3.28)
0.976***
0.710***
1.680***
1.040***
(16.73)
(8.45)
(21.62)
(6.09)
lnpol
_cons
-1.755***
-2.14***
-0.677
-0.549*
-1.58***
-1.96***
-1.412***
0.0816
(-7.44)
(-4.51)
(-0.74)
(-1.93)
(-8.46)
(-4.95)
(-3.44)
(0.30)
N
516
192
144
180
516
192
144
180
R2
0.134
0.258
0.348
0.158
0.460
0.488
0.872
0.327
A-R2
0.0435
0.114
0.189
-0.0112
0.402
0.385
0.840
0.186
F Sta.
3.448
2.645
2.917
1.334
17.98
6.883
35.33
3.265
11
Table 5 The impact of economic development on religion (polarization)
lnrpgdp
lnedu
lncap
lnpub
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
lnpol
lnpol
lnpol
lnpol
lnpol
lnpol
lnpol
lnpol
0.0164
0.0448
-0.0542
0.060***
-0.048**
-0.0566
-0.112***
0.064**
(1.03)
(1.05)
(-0.85)
(3.85)
(-3.60)
(-1.51)
(-3.92)
(4.56)
0.0168
-0.0051
0.0145
0.0043
-0.0602
-0.0636
0.0475
-0.0201
(0.34)
(-0.04)
(0.11)
(0.14)
(-1.51)
(-0.57)
(0.78)
(-0.72)
0.032***
0.0426*
0.0067
-0.0148*
0.0116
0.0229
-0.0239**
-0.029***
(3.24)
(1.66)
(0.31)
(-1.67)
(1.45)
(1.06)
(-2.47)
(-3.50)
0.039***
0.0696**
0.123***
-0.0209
0.046***
0.069***
0.075***
0.0004
(2.63)
(2.24)
(3.20)
(-1.63)
(3.92)
(2.66)
(4.38)
(0.03)
0.385***
0.436***
0.479***
0.193***
(16.73)
(8.45)
(21.62)
(6.09)
lnfra
_cons
-0.180
-0.258
0.437
-0.607***
0.495***
0.677**
0.761***
-0.501***
(-1.22)
(-0.69)
(0.89)
(-4.97)
(4.00)
(2.06)
(3.48)
(-4.51)
N
516
192
144
180
516
192
144
180
R2
0.163
0.222
0.340
0.181
0.477
0.463
0.871
0.345
A-R2
0.0749
0.0710
0.179
0.0160
0.421
0.355
0.838
0.208
F Sta.
4.318
2.171
2.818
1.567
19.31
6.231
34.85
3.542
12