American Journal of Industrial and Business Management, 2012, 2, 136-144
http://dx.doi.org/10.4236/ajibm.2012.24018 Published Online October 2012 (http://www.SciRP.org/journal/ajibm)
Services Trade and Labor-Demand Elasticities of Service
Sector: Empirical Evidence from China
Hao Wei, Qiang Fu, Sui Yang
School of Economics and Business Administration, Beijing Normal University, Beijing, China.
Email: weihao1006@gmail.com
Received May 26th, 2012; revised June 25th, 2012; accepted July 23rd, 2012
ABSTRACT
This paper analyses the impact of services trad e on th e labor-demand elasticities o f service secto r with the da ta of China
from 1982 to 2009. We find that: 1) First, no matter in the long run or in the short term, China’s services export dis-
tinctly impacts on the labor-demand elasticities of service sector. In the long-term influence, the substitution effect is
much more powerful than the output effect, howeve r, as to the short period, the output effect is a little stronger than the
substitution effect; 2 ) Seco nd, in th e long run, we cannot rej ect th e hypo thesis of no relation ship between serv ice import
openness and the labor-demand elasticities of service sector. Whereas, studying the result of the short term, trade liber-
alization of services import does affect the service sector labor-demand elasticity weakly.
Keywords: Trade Liberalization; Labor-Demand Elasticities; Service Sector; Substitution Effect; Output Effect
1. Introduction
From the Reform and Open, China’s service sector has
been developing quickly and the growth of services trade
accelerate rapidly. With the increase of proportion in the
China’s foreign trade, services trade’s average growth
rate is higher than that of goods trade, however, from the
1990s the deficit emerges in the service trade. Consider-
ing the elastic labor-demand of service sector, various
forms of service trade, huge employment supply of ser-
vice business and the inevitable tendency of liberaliza-
tion, boosting the service trade is an effective way to
promote employment. Through exporting of labor service
and undertaking foreign contracted projects, service ex-
port could offer more jobs; accompanying by the inflow
of foreign funds and advanced technology, service im-
port could also create more employment.
At present, different from most studies which focus on
service trade’s impact on the employment and wage, this
paper concentrates itself on the labor-demand elasticities,
and by utilizing the data of China’s services trade and
service sector from 1982 to 2009, the empirical analysis
dedicates to revealing the relationship of China’s services
trade liberalization and the service sector’s labor-demand
elasticities, which indicates that through labor-demand
elasticities services trade is able to influence the em-
ployment. Starting from Cobb-Douglas model and other
theories, the paper deduces a basic model and further
works out optimization ones to estimate the substitution
effect and the output effect. In the empirical analysis part,
three tests—the tests of stationarity, cointegration analy-
sis and the error correction model tests are carried out.
Lastly, the conclusion an d some deduction are reached.
2. Literature Review
In the study field concerning the trade’s impact on labor
market, abundant literature once just focused on the in-
fluence exerted by trade on employment and wage. Until
1990s, some scholars have started to promote this re-
search from the perspective of labor-demand elasticity.
In the theory research, Hamermesh (1993) [1] summa-
rizes that an industry’s equilibrium own-price labor-de-
mand elasticity is determined by its labor share in the
total revenue, constant-output elasticity of substitution
between labor and all other factors of production, and
product-demand elasticity for industry’s output market,
in which labor-demand elasticity rises along with the
increase of factors substitution elasticity and prod-
uct-demand elasticity. Rodrik (1997) [2 ] believes that the
impact of trade on labor market in developed countries
manifests in the following two aspects. Firstly, trade re-
sults in an inward shift in the demand curve for low-
skilled labor in advanced countries (the effect of trade is
small). Secondly, trade and foreign investment flatten the
demand curve for labor at home and increases the elas-
ticity of demand for labor. Since developing countries
tend to export low-skilled-intensive products, in devel-
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China 137
oped countries the demand for unskilled labor decreases
and domestic workers could be substituted by foreign
workers more easily. The degree of substitution means
labor-demand elasticity. Slaughter (2001) [3] establishes
the labor-demand elasticity model composed by substitu-
tion effect and output effect on the basis of “fundamental
law of factor demand” proposed by Hamermesh (1993)
[1].
In the empirical research, trade’s impact on labor-de-
mand elasticity is not so significant as the theories shown,
and due to the difference on sample selection and spe-
cific model building, different empirical studies yield
different conclusion.
By using the manufacturing industries data of US from
1961 to 19 91, Slaughter (2001) [3] estimates th e demand
elasticity of production-labor and non-production labor
and finds that trade or technology could influence wage
model weakly, and factor price change and factor-de-
mand elasticity are still largely unexplained, thus the
hypothesis that international trade could increase labor-
demand elasticity just could be proved partly.
By using India’s industry-level data (1980-1997) dis-
aggregated by states and across industries, Hasan, Mitra
and Ramaswamy (2003) [4] find that labor-demand elas-
ticities are not only higher for Indian states with more
flexible labor regulations, they are also impacted to a
larger degree by trade reforms.
By using data (1971-1996) for 6 sectors in manufac-
turing industries in Tunisia, Haoua and Yagoubi (2004)
[5] perform empirical test on the effects of trade liberali-
zation on labor-demand elasticities. They find that labor
demand elasticity is large for contract workers while for
permanent workers labor demand seems to be inelastic.
This supports the conclusion that in liberalization periods
labor markets have become more flexible, and that em-
ployers prefer recruiting cont ract workers.
Fajnzylber and Maloney (2005) [6] conduct empirical
analysis on the trade liberalization’s impact on labor-
demand elasticities concerning to blue- and white-collar
workers for Chile (1979-1995), Colombia (1977-1991)
and Mexico (1984-1990). They find that periods of
greater openness to trade do not coincide with those of
higher labor-demand elasticities in both Chile and Co-
lombia; in Mexico, trade liberation would reduce
white-collar labor-demand elasticities, but there are only
limited effects on blue-collar elasticities. In brief, the
results do not strongly support the hypothesis that trade
liberalization has a direct impact on own-wage elastic-
ities.
Zhou Shen (2006) [7] estimates the trade’s impact on
the labor-demand elasticities of China’s manufacturing
industries by utilizing panel data across 34 industries
from 1993 to 2002. He find that the liberalization of
China’s manufacturing export could increases the labor-
demand elasicities in manufacture sector, and the
effect of that is significant statistically and big in de-
gree.
From the literature review, we could conclude that the
research on the relationship of service trade and service
sector’s labor-demand elasicities is in shortage. Whereas,
with the rapid development of service trade, its impact on
the service sector labor market would increase gradually.
Maybe not through the direct channel, service trade could
exert influence on wage and employment through la-
bor-demand elasiticities. Consequently, this paper con-
centrates its attention on service trade and service sector
labor-demand elasiticities.
3. Theory and Estimation Framework
Supposing in China’s service sector, only labor and
capital are used. To simply the analysis, this paper as-
sumes that the function of service sector to be a Cobb-
Douglas type (C-D model):
1
QALK
(1)
Where A denotes total factor productivity,
and
1
denotes the coefficient of labor output elasticity
and capital output elasticity respectively.
is between
0 and 1. Greenway, Hine and Wright (1999) [8] discov-
ered, in open economy, parameter A is correlated with
trade changes and varies with time in the production
function as the following manner:
012
012
=e,, ,0
T
jjj
AMX


(2)
where j
M
denotes the import penetration of industry j,
X denotes the export penetration of industry j, T is the
time tend and 01
,
and 2
are parameters. To dem-
onstrate theoretically how changes in trade policy result-
ing in greater product market competition and larger
product market elasticities, and to establish theoretical
underpinnings for the empirical work to follow, Haoua
and Yagoubi (2004) [5] propose to work with a model of
monopolistic competition, where each firm faces its own
less than infinitely elastic demand curv e and where there
is assumed to be no strategic interaction between firms.
Thus, any firm i in industry j is assumed to face an in-
verse demand curve of the type:
1/
ijj ij
PpQ
(3)
where ij denotes own price, P
j
p denotes industry av-
erage price,
is parameter,
is a scaling factor, ij
denotes firm output, and Q
denotes the (constant) price
elasticity of demand
The firm is assumed to face given factor prices. Par-
tially differentiating profits with respect to the Lth input
and Kth input gives us firm’s profit maximization condi-
tions just as the following first order conditions:
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China
138

1
1
1
j
ij ijj
pQ Lw
 
(4)
1
1
(1) (1)jij ijj
P
QK r

 (5)
where denotes labor input, ijij
L
K
denotes capital
input,
j
w denotes the price of the Lth input,
j
r de-
notes the price of the Kth input. By employing Equ ations
(1), (2), (4) and (5), we could get the following equation:

 
11
111
11j1
j
ji
j
j
w
j
A
pL
r
w


 




 
 
 
(6)
In log form, Equation (6) can be rewritten as:

 

 
11
11
lnln1 ln
11ln11ln
ij j
j
j
LA
w
p

 










 
 

j
j
r
p
(7)
Unite Equation (7) with the Equation (2), we get:

 
 
 

11
01
2
11
ln ln
11ln
1ln1 1ln
11ln
ij
j
j
j
j
j
j
L
TM
w
Xp
r
p

 

 
 





 
 



 


(8)
In this paper’s empirical analysis part, the metric
equations are based on the Equation (8). And from Equa-
tion (8), the own price elasticity of labor input is given
by:

1
ln 11
ln
ij
j
j
L
w
p




(9)
The partial derivative of the ab solute value of the own
price elasticity of labor input demand with respect to the
product demand elasticity is given by:

111
0
d
d
dd


 

(10)
Equation (10) shows the higher the product demand
elasticity could lead to the increase of the own price elas-
ticity of labor factor. Furthermore, if the completion
triggered by the trade liberalization could make the
product demand elasticity in domestic service sector in-
crease, the own price elasticity of labor factor would also
ascend (Zhou Shen, 2006) [7].
4. Variables Selection and Optimization
Models
In Equitation (8), we make


11
0
11
ln

 
 




and here 0
stands for the intercept,
10
1

 ,
21
1

,

32
1

 ,
11

4

 
, ,

51

 
1
j
t
is
the random error, so we get:
jt0 12
345
lnL ln
lnln ln
j
jj
j
jt
jj
wr
Xpp
TM
 
 


 



(10)
Considering the time tend could arouse to the un-
steadiness, we remove the time tend and get the estimat-
ing equation:
01 2
34
lnln ln
ln ln
jtj j
jj
j
t
jj
LM
wr
pp
X
 



 



(11)
The equation above is the static model , whic h means the
employment in current period is affected by the export,
import, wage and rate of current period. However, in real-
ity, lots of economic phenomena are dynamic. As a result,
we take a time-lag into consideration and therefore th e em-
ployment in current p e riod is a f fected by the e mployment of
prior period. The following is the dynamic equation.
01 ,123
45
lnlnln ln
ln ln
j
tjtj
jj
jt
jj
LLM
wr
pp
j
X
 
 


 



(12)
On the basis of Equation (12), including the factor
measuring the trade liberalization, we could estimate the
labor-demand elasticities with respect to export and im-
port respectively according to the following equations:
01 ,12
34j
lnln ln
lnln ln
j
jtj tj
j
jj
j
w
LL
p
w
XX
P
 
t





 
(13)
01 ,12
34j
lnln ln
lnln ln
j
jtj tj
j
j
jt
j
w
LCCLC p
w
CMCM p

 


 
(14)
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China 139
where denotes the labor demand of industry j in
time t, ij
L
,1
j
t
L denotes the labor demand of industry j in
time t – 1 and represent the time-lag;
j
j
w
p denotes the
real wage of industry j, and could be calculated by the
nominal wage against the consumer price index; 2
or
stands for the labor-demand elasticities of industry j;
2
C
ln
j
X
, which is reflected the log form of the export
penetration of industry j, is the indicator of the export
openness; ln
j
M
, which is reflected the log form of the
import penetration of industry j, is the indicator of the
import openness; 3
shows the export penetration’s
influence on the demand of labor, and correspondently
3 shows the import penetration’s influence on the de-
mand of labor; 4
C
measures the impact of export open-
ness on the demand of labor, and 4 weighs the impact
of import openness on the demand of labor similarly,
both of which are the focus of the estimation part;
C
j
t
is the random error. Since the capital price is usually
measured by the central bank’s benchmark interest rate,
which could not mirror the market level, we do not in-
clude the rate into the metric equation.
According to the research conducted by Slaughter
(2001) [3], the international trade determines the la-
bor-demand elasticities through the substitution effect
and the output effect. Therefore, to estimate the impact of
the substitution effect or the output effect on the labor-
demand elasticities, we establish the equations con-
cerned to labor-demand elasticities with respect to the
output (15) (17) and labor-demand elasticities with re-
spect to the capital:
01 ,123
4j 5
lnln lnln
ln lnln
j
j
tjt
j
jjjt
j
w
LL
p
w
XQ
p
 


 




j
X
(15)
01 ,123
4j 5
lnln lnln
ln lnln
j
j
tjt
j
jjjt
j
w
LL
p
w
XK
p
 


 




j
X
(16)
01 ,123
4j 5
lnlnlnln
ln lnln
j
j
tjt
j
jjjt
j
w
LCCL CCM
p
w
CM CQ
p
j

 




(17)
where the basic variables’ meaning is the same with
those in Equations (13) and (14);
j
Q is the real output
of industry j, which can be got through the industry j’s
gross output against GDP index;
j
K
is th e real input of
fixed assets, which could be figured out according to the
results of the industry j’s nominal input of fixed assets
against the price index of investment in fixed assets.
5. Data
Due to the limited statistical data, the empirical analysis
part just adopts the related data of China’s services trade
and service sector from 1982 to 2009. To get the import
penetration and the export penetration, the data of the
services trade is assembled from the statistics results
from the WTO website concerning to commercial ser-
vices. And because of the units used there is billion dol-
lars, we employ the average exchange rate of the yuan
against dollar and g et the value measured by the units of
yuan. To simplify the research, we regard the service
sector as the tertiary industry. As to the employment
number of the service sector, we utilize the statistics of
the tertiary industry’s employment from the China Statis-
tical Yearbook as substitution. The average wage of the
service sector is got from the results of the total wage of
tertiary industry divided by the total employment of ter-
tiary industry. However, considering the lack of the sta-
tistics of the total wage of tertiary industry, we use the
result of the national total wage minus the sum of the
total wage of the primary industry and the second indus-
try. Owing to the change of the statistic scope in 2003, to
collect the fixed assets investment of service sector, we
use the capital investment data from 1982 to 2002 and
the urban fixed assets investment data from 2003 to 2009.
The consumer price index, GDP index and the price in-
dex of investment in fixed assets are assembled from the
China Statistical Yearbook. The CPI and the GDP index
are based on the year 1978, while the price index of in-
vestment in fixed assets is based on the year 1991 and the
previous years’ indexes are assumed to be 100.
6. Empirical Analysis
6.1. Tests of Stationarity
01 ,123
lnlnlnln
j
4j 5
ln ln ln
j
tjt j
j
w
LCCL CCM
p

 



jjj
t
j
w
CM CK
p

(18)
According to the theories of econometrics, if empirical
study aims to set up time series’ regression models, the
tests of stationarity are required to avoid the spurious
regression. A test of stationarity that has become popular
widely over the past several years is the unit root test.
And the usual methods to conduct the unit root test are
DF test, ADF test and PP test. This paper adopts the for-
mal one—ADF test, and utilizes Eviews 6.0 to test the
steadiness of the level data and the data after the first
order difference. The results of the ADF test indicates
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China
140
that unit roots exist in all level data, which reveals the
original data are un steady. Howev er, the ADF test for the
data after the first order difference shows the null hy-
pothesis that unit root exists could be rejected. As a result,
all the variables are qualified with the cointegration of
the first order, and therefore live up to the requirement of
cointegration analysis.
6.2. Cointegration Analysis
The cointegration analysis is the popular method to deal
with the nonstationary time series, and could clearly
demonstrate the equilibrium relationship in the long run.
So we utilize the Engle-Granger cointegration test to
judge whether the independent variables are cointegrated
with the dependent ones in Equations (13)-(18), and use
ADF test to examine the estimated residual series. The
test results show that each model’s estimated residual
series are significant on the level of 1%. Hence, we can
assert that those estimated residual series are steady and
the dependent variables are in cointegration relationship
with the independent variables.
6.2.1. Service Export’s Impact on Labor-Demand
Elasticities
6.2.1.1 . E x port’s Gross Es t imate
On the basis of the model (13), we estimate the gross impact
of export on labor-demand elasticities. We get the estimated
results in Table 1. On the basis of the results above, we
could get the equation of cointegration regression:
1
ln4.390 0.877ln0.645ln
1.135ln0.234ln ln
tt
w
LL
P
w
XX
P

 


As the Table 1 shown, without regard to the influence
of export, the service sector’s labor-demand elasticity is
about –0.644. Export’s impact on the labor-demand elas-
ticity is remarkable on the significant level of 10%. The
every 10% increase of export penetration rate (in log
form)) could result in the 2.33% increase of labor-de-
mand elasticity (absolute value), whose effect is power-
ful. The labor demand of precious period has distinctly
positive impact on the labor demand in current period,
and the degree of the impact is up to 0.877. The mortal
inertia on the service employment demonstrates the ne-
cessity of including the time lag. The export penetration
also throws conspicuously positiv e influence on the labo r
demand, which indicates the increase of the service ex-
port could raise the employment of service sector.
6.2.1.2. Export’s Estimate with the Output Constraint
Table 2 is the estimate result of service export’s impact
Table 1. Export’s gross estimate.
Variable CoefficientStd. Error t-Statistic Prob.
1
ln t
L
0.8774230.026165 33.53438 0.0000
ln w
P



–0.6437420.365323 –1.762118 0.0919
ln X 1.1346110.564561 2.009724 0.0569
lnln w
XP


–0.2325590.121795 –1.909430 0.0693
R2 0.996415 Mean Dependent Var 9.646432
Adj-R2 0.995763 S.D. Dependent Var 0.416269
S.E. 0.027097 F-Statistic 1528.510
D.W. Stat2.156893 Prob(F-sta tisti c) 0.000000
Table 2. Export’s estimate with the output constraint.
Variable CoefficientStd. Error t-Statistic Prob.
1
ln t
L
0.6171460.112046 5.507952 0.0000
ln w
P



–0.7517350.335017 –2.243872 0.0357
ln X 1.3097720.518210 2.527494 0.0196
lnln w
XP


–0.2669210.111600 –2.391774 0.0262
Qln 0.0796600.033512 2.377059 0.0270
R2 0.997175 Mean Dependent Var 9.646432
Adj-R2 0.996502 S.D. Dependent Var 0.416269
S.E. 0.024619 F-Statistic 1482.418
D.W. Stat2.167449 Prob(F-statistic) 0.000000
on service sector’s labor-demand elasticities with the
output constraint. On the basis of the results above, we
could get the equation of cointegration regression:
1
ln6.6530.617ln0.752ln
1.310ln0.267ln ln0.080ln
tt
w
LL
P
w
X
XQ
P

 

 
As Ta ble 2 shown, with the output constraint, export’s
impact on the labor-demand elasticity is remarkable on
the significant level of 5%. The every 10% increase of
export penetration rate (in log form) could result in the
2.67% increase of labor-demand elasticity (absolute
value), whose effect is powerful. Because when output is
restrained the trade could only change the labor-demand
elasticities through influencing the constant-output elas-
ticity of substitution between labor and all other factors
of production, the measurement results manifest that the
export openness could increase the elasticity of factors’
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China 141
substitution effectively, and thus raise the labor-demand
elasticities of service sector.
6.2.1.3. Export’s Estimate with the Capital Constraint
Table 3 is the estimate result of service export’s impact
on service sector’s labor-demand elasticities with the
capital constraint. On the basis of the results above, we
could get the equation of cointegration regression:
1
j
ln6.5260.965ln1.263ln
2.163ln0.446lnln0.227ln
tt
w
LL
P
w
X
X
P

 

 K
As Table 3 shown, with the capital constraint, export’s
impact on the labor-demand elasticity is remarkable on
the significant level of 1%. The every 10% increase of
export penetration rate (in log form) could result in the
4.46% increase of labor-demand elasticity (absolute
value), whose effect is powerful. And the real input of
capital throws significant effect on labor-demand elastic-
ity. Because when capital is restrained the trade could
only change the labor-demand elasticities through influ-
encing the product-demand elasticity, the measurement
results manifest the export openness could increase
product-demand elasticity effectively and thus raise the
labor-dem a nd el ast i ci ti es of s ervi ce sect or .
The result indicates that the export openness could in-
crease the labor-demand elasticity significantly through
the substitution effect and the output effect from 1982 to
2009. The above analysis indicates that from 1982 to
2009 the export openness could increase the labor-de-
mand elasticity significantly through the substitution
effect and the output effect. In this period, if Chinese
service sector’s export penetration (in log form) increases
10%, the trade’s substitution effect would make la-
bor-demand elasticity (absolute value) increase 2.67%
Table 3. Export’s estimate with the capital constraint.
Variable Coefficient Std. Error t-Statistic Prob.
1
ln t
L
0.965397 0.034555 27.93826 0.0000
ln w
P



–1.263034 0.357954 –3.528483 0.0020
ln X 2.162685 0.564901 3.828431 0.0010
lnln w
XP



–0.446228 0.120512 –3.702782 0.0013
ln
K
0.022652 0.006908 3.279267 0.0036
R2 0.997629 Mean Dependent Var 9.646432
Adj-R2 0.997064 S.D. Dependent Var 0.416269
S.E. 0.022554 F-Statistic 1767.085
D.W. Stat 1.712048 Prob(F-statistic) 0.000000
and trade’s output effect would make labor-demand elas-
ticity (absolute value) increase 4.46%. The substitution
effect is almost twice stronger than the output effect, and
through those two effects, labor-demand elasticity of
service sector (absolute value) could increase 7.13%.
According to statistic material, the average export pene-
tration rate (in log form) of China’s service sector is
6.09%, and on the basis of the results above, export lib-
eration could increase labor-demand elasticities (abso lute
value) of China’s service sector about 4.34% from 1982
to 2009, which indicates that trade could exert some
power on labor-demand elasticities of China’s service
sector.
6.2.2. Service Import’s Impact on Labor-Demand
Elasticities
6.2.2.1. Import’s Gross Estima t e
Table 4 is the estimate result of service import’s impact
on service sector’s labor-demand elasticities with the
Gross Estimate. On the basis of the results, we could get
the equation of cointegration regression:
1
ln3.071 0.887ln0.376ln
0.552ln0.106ln ln
tt
w
LL
P
w
MM
P

 


As the Table 4 shown, whether it is the labor-demand
elasticities without regard to the influence of import, the
import’s impact on the labor-demand, or the import
openness’ impact on the labor-demand elasticities, all of
them are insignificant on the test level of 10%. Conse-
quently, we couldn’t reject the h ypothesis of no relation-
ship between service import openness and labor-demand
elasticities of the service sector. That is to say, the re-
search results are unable to support the assumption that
the service import could increase the labor-demand elas-
ticities of the service sector.
Table 4. Import’s gross estimate.
Variable CoefficientStd. Error t-Statistic Prob.
1
ln t
L
0.8871440.026545 33.42060 0.0000
ln w
P



–0.3761440.245474 –1.532320 0.1397
ln
M
0.5523270.323774 1.705901 0.1021
lnln w
XP


–0.1055300.068826 –1.533288 0.1395
R2 0.996224 Mean Dependent Var 9.646432
Adj-R2 0.995537 S.D. Dependent Var 0.416269
S.E. 0.027808 F-Statistic 1451.053
D.W. Stat2.320243 Prob(F-statistic) 0.000000
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China
142
6.2.2.2. Import’s Estimate with the Capital Constraint
Table 5 is the estimate result of service import’s impact
on service sector’s labor-demand elasticities with the
Capital Constraint. On the basis of the results, we could
get the equation of cointegration regression:
1
ln3.155 0.939ln4.899ln
0.710ln0.135ln ln0.012ln
tt
w
LL
P
w
M
MK
P

 

 
As Table 5 shown, with capital constraint, import’s
impact on the labor-demand elasticity is remarkable on
the significant level of 10%. The every 10% increase of
export penetration rate (in log form) could result in the
1.35% increase of labor-demand elasticity.
6.2.2.3. Import’s Estimate with the Output Constraint
Table 6 is the estimate result of service import’s impact
on service sector’s labor-demand elasticities with the
Output Constraint. On the basis of the results, we could
get the equation of cointegration regression:
1
ln4.394 0.677ln0.356ln
0.515ln0.945ln ln0.645ln
tt
w
LL
P
w
M
MQ
P

 

 
As Table 6 shown, lnln w
MP



does not pass the
test on the significant level of 10%, which means that
service import could not remarkably increase the la-
bor-demand elasticities of the service sector through sub-
stitution effect.
7. Error Correction Model
The cointegration analysis could clearly demonstrates the
Table 5. Import’s estimate with the capital constraint.
Variable Coefficient Std. Error t-Statistic Prob.
1
ln t
L
0.939281 0.039341 23.87545 0.0000
ln w
P



–0.488838 0.243763 –2.005382 0.0580
ln
M
0.709941 0.322933 2.198413 0.0393
lnln w
XP



–0.134665 0.067982 –1.980885 0.0609
ln
K
0.012284 0.007077 1.735840 0.0972
R2 0.996698 Mean Dependent Var 9.646432
Adj-R2 0.995912 S.D. Dependent Var 0.416269
S.E. 0.026617 F-Statistic 1267.669
D.W. Stat 2.098845 Prob(F-statistic) 0.000000
Table 6. Import’s estimate with the output constraint.
Variable CoefficientStd. Error t-Statistic Prob.
1
ln t
L
0.6769030.119619 5.658810 0.0000
ln w
P



–0.3558150.234160 –1.519534 0.1435
ln
M
0.5149340.309192 1.665418 0.1107
lnln w
XP


–0.0947560.065850 –1.438960 0.1649
ln Q 0.0645760.035911 1.798237 0.0865
R2 0.996728 Mean Dependent Var 9.646432
Adj-R2 0.995949 S.D. Dependent Var 0.416269
S.E. 0.026495 F-Statistic 1279.349
D.W. Stat2.312158 Prob(F-statistic) 0.000000
equilibrium relationship in the long run, however, in
short term, variables often diverge the equilibrium
state and gradually adjust to the long-run equilibrium.
After the empirical analysis of the cointegration rela-
tionships, to learn the export trade’s impact on the
labor-demand elasticities in short period, we establish
the error correction model (ECM) in which the error
correction term is included. Get the ECM for (13)-(18)
as t h e following:
01 123
41
lnln lnln
ln lnln
ttt
ttt
t
w
LL
P
w
XEC
P
 


 






t
X
(19)
01 123
41
lnln lnln
ln lnln
ttt
ttt
t
w
LL
P
w
MEC
P
 


 



 


t
M
(20)
01 12
34
51
lnln ln
lnln lnln
ln
ttt
tt
t
ttt
w
LL
P
w
XX
P
QEC
 



 



 

 
(21)
01 12
34
51
lnln ln
lnln lnln
ln
ttt
tt
t
ttt
w
LL
P
w
XX
P
KEC
 



 



 

 
(22)
01 12
34
51
lnln ln
lnln lnln
ln
ttt
tt
t
ttt
w
LL
P
w
MM
P
QEC
 



 



 

 
(23)
Copyright © 2012 SciRes. AJIBM
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China
Copyright © 2012 SciRes. AJIBM
143
pact on the labor-demand elasticities is much stronger.
What’s more, with the output constraint and the capital
01 12
34
51
lnln ln
lnln lnln
ln
ttt
tt
t
ttt
w
LL
P
w
MM
P
KEC
 



 



 

 
(24) constraint, the coefficients of lnlnw
XP



are both
sig nificant on the level of 1%, but the output effect is
much stronger than the substitution effect, which is quite
different with the conclusion of the long term.
Table 7 is the estimate results of error correction
model. We can find that: In ECM of the import’s impact on the labor-demand
elasticities, lnlnw
XP



passes the test on the sig-
In ECM of the export’s impact on the labor-deman-
delasticities, lnln w
XP



passes the test on the sig- nificant level of 5%, indicting the service import has di-
rect influence on the service sector’s labor-demand elas-
ticities, which is obviously different from the results of
the cointegration analysis. The coefficient of error cor-
rection term passes the test on the significant level of 1%
and the rate of adjustment is 1.358%, which reflects the
long-term equilibrium could adjust the short-term fluc-
tuation effectively. But in short term, import penetration
(in log form) increase 10% could just result in about
0.925% increase of labor-demand elasticity (absolute
value), which shows the service import openness’s im-
pact on the service sector’s labor-demand elasticities is
nificant level of 1%, which indicates that in short run
service openness could remarkablely increase the service
sector’s labor-demand elasticities. The every 10% in-
crease of export penetration rate (in log form) could re-
sult in about 3% increase of labor-demand elasticity (ab-
solute value), whose effect is powerful. Besides, the co-
efficient of error correction term passes the test on the
significant level of 1% and the rate of adjustment is
1.103, which reflects the long-term equilibrium could
adjust the short-term fluctuation effectively. Compared to
the long-term one, in short term the service export’s im-
Table 7. Estimate results of error correction model.
Explanatory Variable Model(19) Model(20) Model(21) Model(22) Model(23) Model(24)
C 0.002533
(0.206875) 0.007690
(0.496499) 0.003714
(0.301735) –0.001818
(–0.143259) 0.007143
(0.458574) –0.002721
(–0.206123)
1
ln t
L
0.838548***
(4.326182) 0.964177***
(3.229528) 0.868645***
(4.424883) 0.931067***
(4.590453) 1.176797***
(3.675410) 0.927554***
(4.468316)
ln w
P



–0.851663***
(–2.888481) –0.874167***
(–2.887797) –0.954209***
(–3.051547) –0.374318***
(–2.270063) –0.436917***
(–2.473867) –0.374549***
(–2.221755)
ln X 1.474111***
(3.082964) 1.522215***
(3.080960) 1.635835***
(3.235571)
lnln w
XP



–0.300258***
(–2.925990) –0.310459***
(–2.928933) –0.334494***
(–3.087129)
ln
M
0.516877***
(2.273383) 0.624628***
(2.478206) 0.521634***
(2.240623)
lnln w
MP



–0.092493**
(–1.926950) –0.115021***
(–2.165445) –0.093604**
(–1.903806)
lnQ –0.068532
(–0.560556)
–0.127550
(–0.992132)
ln
K
0.010294
(0.989072)
–0.003578
(–0.366685)
t1
E
C –1.103303***
(–3.445943) –1.174804***
(–3.357658) –0.837646**
(–2.003706) –1.358452***
(–4.315011) –1.480467***
(–4.378735) –1.441716***
(–3.660105)
R2 0.633473 0.639436 0.651421 0.632880 0.650962 0.635460
Adj-R2 0.541842 0.525574 0.541343 0.541100 0.540740 0.520342
D.W. Stat 1.807238 1.721977 2.016680 1.816729 1.705330 1.801549
F-Statistic 6.913258 5.615879 5.917831 6.895614 5.905896 5.520070
Prob(F-statistic) 0.000676 0.001699 0.001272 0.000687 0.001286 0.001865
Note: stands for the first order difference. ***,**,* respectively denote that the test passes under the s ignificance level of 1%, 5%, 10%.
Services Trade and Labor-Demand Elasticities of Service Sector: Empirical Evidence from China
144
considerably limited. And different from the export’s
effect in short term, in the short run the import’s substi-
tution effect is much stronger than the output effect.
8. Conclusions
This paper analyses the impact of services trade on the
labor-demand elasticities of service sector with the data
of China from 1982 to 2009. We find that:
1) In long run, China’s service export exerts distinctly
simulative impact on the service sector labor-demand
elasticities, which is significant statistically and big in
degree. Export openness could increase the labor-demand
elasticity remarkably through the substitution effect and
the output effect, but the substitution effect is much
stronger than the output effect. In short term, the service
export also throws distinctly positive impact on the ser-
vice sector’s labor-demand elasticities, which is more
powerful than the influence in the long run, but the out-
put effect is stronger than the substitution effect.
2) In long run, the service import doesn’t have direct
influence on the service sector’s labor-demand elastic-
ities, thus the research results couldn’t reject the hy-
pothesis of no relationship between service import open-
ness and labor-demand elasticities of the service sector.
In short run, the service import could increase the la-
bor-demand elasticities in some deg ree. That is to say, as
to the short term, trade liberalization of service import
does affect the service sector labor-demand elasticity
weakly.
The increase of the labor-demand elasticities indicates
the status of the labor suppliers is weakened relatively,
and meanwhile the shocks brought by the labor demand
would arouse the lager fluctuation of wage and employ-
ment. Just as the conclusions above shown, no matter in
the long run or in the short term, China’s services expo rt
exerts distinctly stimulative impact on the service sector
labor-demand elasticities, therefore even the service ex-
port has no direct influence on the wage and employment
in service sector, through the labor-demand elasticities
service export could exert pressure on the labor market.
And as to the service import, in long run its impact on
labor-demand elasticities hasn’t been proved, but in short
run it would aggravate the fluctuation of wage and em-
ployment. So China government should pay more atten-
tion to the changes of labor-demand elasticities with
trade.
9. Acknowledgements
This research is supported by “Research Fund of Na-
tional Social Science” (No.10zd & 017,No.11AJL005
and No.11FJL008), “The Fundamental Research Funds
for the Central University” (No.105563GK), “Scientific
Research Fund of Education Ministry of China” (No.10-
YJC-790272), and “The Fundamental Research Funds for
985 Projects”.
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