Xport Tax Rebate and Energy Efficiency of Chinese Enterprises

1
Export Tax Rebate and Energy Efficiency of Chinese
Enterprises
Liu Yuan, Shaoming Chen*
(International Business School，Guangzhou City University of Technology, Guangzhou 510850, China)
Abstract：Based on the data of micro-enterprise level, this paper systematically explores the
impact of export tax rebate on the improvement of enterprises’ energy efficiency. The research
shows that export tax rebate generally inhibits the improvement of enterprise energy efficiency.
The core conclusion still holds after dealing with sample selection bias, changing the measurement
method of core variables and overcoming endogeneity problems. In non-export enterprises,
processing trade enterprises, state-owned enterprises and enterprises in the eastern region, the
inhibitory effect of export tax rebate on energy efficiency is stronger. The mechanism test shows
that the resource misplacement effect of export tax rebate reduces the energy efficiency of
enterprises, the innovation and research and development effect improves the energy efficiency of
enterprises, and the net effect of export tax rebate on enterprise energy efficiency is negative. The
above conclusions show that the reduction or gradual cancellation of export tax rebate rate has
important practical significance to alleviate the misplacement and distortion of resources, improve
enterprise energy efficiency, achieve energy conservation and emission reduction and economic
development.
Key words：Export Tax Rebate；Energy Efficiency; Misallocation of resources；Innovative
Research and Development; Mediating Effect Model
This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4730227
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Export Tax Rebate and Energy Efficiency of Chinese
Enterprises
Liu Yuan, Shaoming Chen*
(International Business School，Guangzhou City University of Technology, Guangzhou 510850, China)
Abstract：Based on the data of micro-enterprise level, this paper systematically explores the
impact of export tax rebate on the improvement of enterprises’ energy efficiency. The research
shows that export tax rebate generally inhibits the improvement of enterprise energy efficiency.
The core conclusion still holds after dealing with sample selection bias, changing the measurement
method of core variables and overcoming endogeneity problems. In non-export enterprises,
processing trade enterprises, state-owned enterprises and enterprises in the eastern region, the
inhibitory effect of export tax rebate on energy efficiency is stronger. The mechanism test shows
that the resource misplacement effect of export tax rebate reduces the energy efficiency of
enterprises, the innovation and research and development effect improves the energy efficiency of
enterprises, and the net effect of export tax rebate on enterprise energy efficiency is negative. The
above conclusions show that the reduction or gradual cancellation of export tax rebate rate has
important practical significance to alleviate the misplacement and distortion of resources, improve
enterprise energy efficiency, achieve energy conservation and emission reduction and economic
development.
Key words：Export Tax Rebate；Energy Efficiency; Misallocation of resources；Innovative
Research and Development; Mediating Effect Model
1. Introduction
Since the reform and opening up in 1978, China's foreign trade has grown rapidly. By the end
of the 20th century, China had become an important trading power in the world (Hu and Tan,
2016; Yu and Luo, 2018; Kong et al., 2021; Xu et al., 2022). Many scholars attribute the growth
of China's export trade to China's export promotion policies, among which the export tax rebate
policy is an important policy (Chandra and Long, 2013; Lee et al., 2021). Export tax rebate policy
is to encourage the development of export trade by refunding the value-added tax and
consumption tax paid in the domestic production and operation process of export goods in
accordance with the tax law (Song et al., 2015). Export tax rebate is often adjusted to promote or
hinder the export of certain products. In fact, in addition to China, South Korea, Pakistan,
Bangladesh, Malaysia, Brazil and Mexico have also adopted export tax rebate policy as an
important tool to promote foreign trade (Mah, 2007; Ahmed et al., 2014; Ayob and Freixanet,
2014). With the rapid expansion of foreign trade, the problem of environmental pollution caused
by export enterprises is becoming increasingly serious. Many empirical studies have shown that
the emissions of China's exports are very significant (Peters et al., 2007; Peters and Hertwich,
2008; Weber et al., 2008; Zhang, 2012). According to the report "Global CO2 Emissions in 2022"
released by the International Energy Agency (IEA), the global CO2 emissions in 2022 are about
36.07 billion tons, and the CO2 emissions in Asia account for more than half of the global total.
China's CO2 emissions are about 11.48 billion tons, accounting for 30% of the global total
emissions. The United States and India's emissions also exceed 10% and 7% of the global total,
ranking second and third respectively. The sudden increase of CO2 emissions has destroyed the
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sustainable development of the environment, economy and society. Therefore, reducing CO2
emissions and improving energy efficiency are the key to adhering to the path of sustainable
development. With the Chinese economy entering the "new normal" period, technological
progress and innovation are the key factors to promote economic development. It is imperative to
accelerate technological progress and improve energy efficiency. As an export promotion policy,
export tax rebate will increase export emissions while promoting foreign trade development. But
how does it affect the energy efficiency of Chinese enterprises? At present, there are few studies
on the relationship between export tax rebate and enterprise energy efficiency. This paper intends
to discuss this issue accordingly.
The studies on the relationship between international trade and energy efficiency are mostly
carried out from the perspectives of trade liberalization, foreign direct investment, foreign trade
dependence, import technology spillover, export trade and import technology complexity. For
example, Gordon (1993) and Plourde (1993) both found that trade liberalization significantly
improved energy efficiency; Cole et al. (2005) systematically investigated the relationship
between trade liberalization and energy consumption and efficiency; Dan Shi (2006) found that
foreign trade promoted the improvement of energy efficiency. Moreover, foreign direct
investment is also significantly positively correlated with energy efficiency. Yanting Xiong and
Ning Huang (2010) found that foreign trade dependence is significantly positively correlated with
energy efficiency, and foreign investment participation is also significantly positively correlated
with energy efficiency. Dawei Gao and Dequn Zhou (2010) found a significant positive
correlation between technology spillover from international trade and total factor energy
efficiency in various regions of China through empirical tests. Meng Wang et al. (2013) found that
export learning effect and positive externalities of export are important ways for foreign trade to
promote energy efficiency in various provinces of China. Boqiang Lin and Hongxun Liu (2015)
argued that free trade significantly promoted the improvement of energy effect; Xiaoyi Wu and
Jun Shao (2016) found a significant positive correlation between import openness and energy
efficiency in manufacturing; Ping Li and Shihao Ding (2019) explored the relationship between
technology spillover from imports and total factor energy efficiency at the industry level through
empirical tests. The conclusion is that there is a significant positive correlation between imported
technology spillover and energy efficiency at the industry level. By measuring energy efficiency at
the micro enterprise level, Xinheng Liu (2022) found that there was a significant positive
correlation between trade liberalization and enterprises’ energy efficiency. Liu Yuan (2023) was
also based on total factor energy efficiency at the micro enterprise level. This paper systematically
investigated the relationship between imported technology complexity and enterprises’ energy
efficiency, and found that imported technology complexity significantly promoted the
improvement of energy efficiency of Chinese enterprises through two channels of technology
spillover and competition. Zhihao Yang (2023) investigated the relationship between transnational
joint investment and enterprises’ energy use efficiency through empirical tests. It was found that
transnational joint investment significantly promoted the improvement of energy utilization
efficiency of enterprises. So far, there is a lack of discussion on the relationship between export
tax rebate and enterprises’ energy efficiency. As an important regulatory force for the growth of
export trade, export tax rebate policy plays a decisive role in China's foreign trade growth.
However, while promoting China's foreign trade development, it will also bring some negative
effects, such as increasing export emissions and causing the misplacement of economic resources.
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How to reduce carbon dioxide emissions and improve enterprises’ energy efficiency is the
inevitable requirement of the current "green" development, so how the export tax rebate policy
affects the energy efficiency of Chinese enterprises, in the current background, to explore this
issue has a more significant practical significance.
Existing studies have shown that the increase of export tax rebate rate promotes the growth of
export trade (Chao et al., 2001; Chen et al., 2006; Jianguo Xie and Lili Chen, 2008; Xiaosong
Wang et al., 2010; Jin Yuan and Qiren Liu, 2016), expands the export intensive marginal (An et
al., 2017), enhances the export sustainability of enterprises (Yuying Jin and Beibei Hu, 2017;
Anwar et al., 2019), while the decrease of export tax rebate rate will reduce enterprises’ exports,
and even promote enterprises’ exports to domestic sales (Qing Liu et al., 2020). In addition,
relevant studies further point out that the increase of export tax rebate rate will also improve the
quality of export products (Yi Liu and Chun Geng, 2016), the domestic value-added rate of
exports (Xinheng Liu, 2020), export competitiveness (Tianjiao Tan and Gen Li, 2023), and
increase the investment in R&D and innovation (Hui He and Yixuan Fan, 2018). It is conducive to
the "incremental quality improvement" of export agricultural products (Jiyu Li et al., 2023), while
the decrease of export tax rebate rate will significantly reduce the soot emission intensity of
enterprises (Qian Tian et al., 2023) and carbon emission intensity (Jiadong Tong et al., 2023). It
can be seen that the current evaluation of the implementation effect of export tax rebate policy
rarely involves the exploration of the influence of energy utilization efficiency and its mechanism.
This paper focuses on the impact of export tax rebate on corporates’ energy efficiency, and its
possible marginal contributions are as follows: on the one hand, exploring the impact of export tax
rebate on corporates’ energy efficiency from the perspective of policy implementation effect
evaluation is conducive to enriching our comprehensive understanding of the implementation
effect of export tax rebate policy; on the other hand, digging deeply into the channels and paths
that export tax rebate policies affect the energy efficiency of enterprises is conducive to helping us
deeply understand the internal mechanism of international trade affecting energy efficiency.
This paper proceeds as follows: The next section is the theoretical mechanism, the third section
is the model setting, variables measurement and data processing, the fourth section is the empirical
test results, the fifth section is the channel mechanism analysis, and the last section is the
conclusion and policy implications.
2. Theoretical mechanism analysis
By combing through the existing literature, it is found that the two main channels for export
tax rebate to affect the energy efficiency of enterprises are the misallocation effect of resources
and the R&D innovation effect.
(1)The misallocation effect of resources. First of all, in view of the typical characteristic of the
difference in export tax rebate rate, various production factors, such as land, capital and labor, are
transferred and flowed between enterprises with different export tax rebate rates. If the production
factors flow from enterprises with low export tax rebate level to enterprises with high export tax
rebate level, and the efficiency of enterprises with low export tax rebate level is higher than that of
enterprises with high export tax rebate level, the misallocation and distortion of resources will
occur (Xiaoguang Chen, 2013). Secondly, if the government's export tax rebate policy is inclined
to low-productivity enterprises, aiming to help the development of vulnerable enterprises, the
production factors and resources will be transferred to low-productivity enterprises, and the
efficiency of low-productivity enterprises will gradually be higher than that of high-productivity
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enterprises, as a result, the degree of misallocation of resources between enterprises will be
improved (Xuefeng Qian et al., 2015).The misallocation effect of resources will have a negative
impact on productivity (Baihui Liu et al., 2019; Xiaoyu Jin, 2018), that is, the misallocation of
resources will reduce the productivity of enterprises, and the decline in productivity and
technology level will further reduce the efficiency of the production factors put into use, and then
further reduce the energy efficiency of enterprises. Klein and Robison (1992) examined the
relationship between technological progress and energy efficiency at the industry level in the
United States through an empirical test system, and concluded that the progress of enterprises’
technology significantly promoted the improvement of energy efficiency at the industry level in
the United States. Lin and Polenske (1995) also found that the progress of technological level
promoted the improvement of energy efficiency in China. Lianshui Li and Yong Zhou (2006) also
believed that the important channel for the improvement of energy efficiency was technological
progress. Xinheng Liu (2022) found that the improvement of total factor productivity was
conducive to improving the energy efficiency of enterprises. Liu Yuan (2023) based on the data at
the micro enterprise level, reached the same conclusion, that is, the improvement of productivity
and technological level enhanced the efficiency of the input factors, and thus significantly
promoted the improvement of energy efficiency. Therefore, the decline in production efficiency
and technological level will further reduce the energy efficiency of enterprises.
(2)Innovation and R&D effect. The increase of export tax rebate rate will expand the export
scale, thereby increasing the profit of enterprises. The increase of profits makes enterprises have
sufficient funds for innovation and R&D activities, thereby improving the level of technological
innovation, and the improvement of technological level promotes the improvement of energy
efficiency of enterprises. At the same time, while expanding the sales scale of enterprises in the
export market, the increase of export tax rebate rate will also prolong the survival time of
enterprises in the export market (Yuying Jin and Beibei Hu, 2017), and the extension of export
duration is conducive to the deeper integration of enterprises into the export market, the deeper the
integration into the export market. It is more conducive to enterprises to learn new technologies
from the production of foreign advanced products, crack the technical experience hidden in
foreign advanced products, and then apply it to the production and design of their own products,
and promote the improvement of energy efficiency of enterprises. In addition, under normal
circumstances, if the international environment is volatile or the domestic and local economy is
depressed, the government will usually introduce a positive export tax rebate policy to create a
convenient and good production and operation environment for enterprises, improve the ability of
enterprises to resist risks, and promote the improvement of product quality to ensure that they can
continue to maintain market share. In order to continuously improve product quality, maintain or
expand market share, enterprises usually increase R&D investment to develop new technologies
and products. The R&D and innovation of enterprises is often an important path to improve
product quality (Jiyu Li et al., 2023), and the improvement of technological level is conducive to
improving the energy efficiency of enterprises.
Based on the above analysis, it can be found that the negative external effect of export tax
rebate reduces the energy efficiency of enterprises through the misplacement of resources, which
is called the "misplacement effect"; At the same time, the positive externalities of export tax
rebates improve the energy efficiency of enterprises through innovative research and
development, the so-called "innovative research and development effect". Whether export
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rebates inhibit or enhance energy efficiency depends on the size and direction of the two
opposing effects.
3. Empirical Strategy and Data Processing
3.1 Empirical model
This study focuses on the relationship between export tax rebate and enterprises’ energy
efficiency. Drawing on relevant literature, the following empirical model is obtained:
(1)
Where represents the enterprise, represents the industry, represents the year, and
represents the region. is the dependent variable of this paper, namely the total factor energy
efficiency of the enterprise; represents the export tax rebate rate at the enterprise level,
which is also the core explanatory variable of this paper; represents the control variables at
the enterprise level, including the age of the enterprise (Age), financing constraints (Loan), capital
intensity (Capital), profit of the enterprise (Profit), and dummy variable of state-owned enterprises
(State), etc. In addition, this paper also controls the year fixed effect and the region fixed
effect .
3.2 Measurement of Key Variables
(1)Total factor energy efficiency. Taking labor, capital and energy (coal consumption)① as
inputs and the total industrial output of the enterprise as desired output (Xiaodong Lu and Yujun
Lian, 2012), the production function of the enterprise is assumed to be the Cobb-Douglas function:
(2)
Where represents the total factor energy efficiency of the enterprise, represents the labor
input of the enterprise, represents the capital input of the enterprise, represents the
energy input of the enterprise, and represents the output of the enterprise. Taking the
logarithm of both sides of the Cobb–Douglas production function gives the following linear
regression equation:
(3)
Where , , and are the logarithm values of , , and respectively,
and represents the residual term, covering the information of the total factor energy efficiency
of the enterprises after taking the logarithm. In order to obtain the total factor energy efficiency of
① Since coal consumption accounts for nearly 70% of China's total energy consumption, coal consumption is
adopted as the energy input here.
fit ft fit t r fit
tfee tax X
     
     
f i t r
fit
tfee
ft
tax
fit
X
t
δ
r
δ
α β θ
ft ft ft ft ft
Y A L K E

ft
A ft
L
ft
K ft
E
ft
Y
ft ft ft ft ft
y l k e u
   
ft
y ft
l ft
k ft
e ft
Y ft
L ft
K ft
E
ft
u
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the enterprises, it is necessary to conduct linear regression on Equation (3), but this method has
problems such as sample selection bias and simultaneity bias. Therefore, in order to avoid such
problems, this paper uses Lucas-Pigou (LP) method to measure the total factor energy efficiency
of enterprises for reference to the research of Xiaodong Lu and Yujun Lian (2012).
(2) Export tax rebate. Referring to the research ideas of Xinheng Liu (2020), the export tax
rebate rate of 10-bit HS code in the export tax rebate library is first replaced by the export tax
rebate rate of 8-bit HS code, and then the 8-bit HS code export tax rebate rate is matched with the
customs trade database. Finally, the export tax rebate rate at the enterprise level is calculated
according to the following formula:
(4)
Where represents the export tax rebate rate at the enterprise level, represents the
export quota of 8-digit HS products of the enterprise, represents the total export quota of
the enterprise, and represents the export tax rebate rate of 8-digit HS products.
3.3 Data source and processing
This paper adopts four sets of databases, namely China Customs Trade Database (2000-2012),
China Industrial Enterprise Environmental Statistics (2000-2012), China Industrial Enterprise
Database (2000-2012) and Export Tax Rebate Database (2000-2012). Before measuring the total
factor energy efficiency at the enterprise level, we firstly learn from the research methods of
Huihua Nie et al. (2012) and process the China Industrial Enterprise Database. The China
Industrial Enterprise Database is provided by the National Bureau of Statistics, and the China
Industrial Enterprise Environmental Statistics is also provided by the National Bureau of Statistics.
The matching of the two can measure the total factor energy efficiency at the enterprise level. The
Export Tax Rebate Database data is provided by the International Tax Administration, and the
customs database is provided by the General Administration of Customs of China. The matching
of the two can measure the export tax rebate rate at the enterprise level.
4. Empirical results
4.1 Benchmark regression results
Table 1 reports the benchmark estimated results, namely the impact of export tax rebate on
enterprises’ energy efficiency. Column (1) is the result of only considering the impact of export
tax rebate on enterprises’ energy efficiency. The results show that the estimated coefficient of
export tax rebate variable is significantly negative, which preliminarily indicates that export tax
rebate has a significant negative correlation with enterprise energy efficiency, that is, the higher
the export tax rebate rate is, the lower the enterprises’ energy efficiency is. In the case of gradually
adding control variables, the estimated coefficients of export tax rebate variable in columns (2) to
(6) are still negative, and all of them pass the significance level test, indicating that the significant
negative effect of export tax rebate on enterprises’ energy efficiency is robust. The estimated
coefficient of enterprise age variable is significantly positive, which means that enterprises’ age
has a significant positive impact on enterprises’ energy efficiency. The possible explanation is that
the earlier the enterprise starts business, the longer its establishment time is, and then the more
8
8
hs
ft hs
ft
value
tax tax
value
 

ft
tax 8
hs
value
ft
value
8
hs
tax
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mature its production and management experience is, the higher its technical level is, and the more
conducive it is to improving productivity and energy utilization efficiency. The estimated
coefficient of financing constraint variable is significantly positive, indicating that the stronger the
financing ability is, the higher the enterprise energy efficiency is. The estimated coefficient of
capital intensity variable is significantly positive, indicating that the higher the capital intensity is,
the higher the enterprise energy efficiency is. The estimated coefficient of the variable of
corporates’ profit is significantly positive, which means that corporates’ profit promotes the
improvement of corporates’ energy efficiency.
Table 1 Basic results
Variables （1）（2）（3）（4）（5）（6）
Tax
-0.0148***（
0.0018）
-0.0145***（0.0018） -0.0152***（0.0018） -0.0159***（0.0019） -0.0149***（0.0017） -0.0149***（0.0017）
Age 0.0071***（0.0020） 0.0074***（0.0020） 0.0117***（0.0021） 0.0025***（0.0019） 0.0033***（0.0020）
Loan 0.2225***（0.0129） 0.2064***（0.0135） 0.1487***（0.0123） 0.1478***（0.0123）
Capital 0.0130***（0.0077） 0.0176**（0.0070） 0.0175**（0.0070）
Profit 0.0314***（0.0009） 0.0313***（0.0009）
State -0.0073***（0.0043）
Constant
1.6555***（0.0045
）
1.6734***（0.0068） 1.6457***（0.0069） 1.6676***（0.0073） 1.7873***（0.0073） 1.7874***（0.0073）
Year FE Yes Yes Yes Yes Yes Yes
Region FE Yes Yes Yes Yes Yes Yes
Observations 26991 26946 26929 22410 18781 18781
Adj. R-squared 0.2622 0.2624 0.2704 0.3043 0.3792 0.3793
Notes：Robust standard errors are in parenthesis. Year FE, indicates time fixed effects, Region FE, indicates region fixed effects. ***, **,
and * indicate significant at the 1%, 5% and 10% levels, respectively.
4.2 Dealing with endogeneity
(1) Consider the possible sample selection bias. This paper adopts Heckman's (1979) two-stage
method for endogenous test to overcome the possible sample selection bias and obtain consistent
estimates. Specifically, the first step is the selection equation, which is estimated by Probit model
to obtain the inverse Mills ratio (nivmillsss); the second step is to add the inverse Mills ratio to the
benchmark regression equation to analyze the determinants of energy efficiency. According to the
existing relevant research, the selection model of the enterprise is set as follows:
(5)
Where represents the successfully matched enterprises, and represents
the unsuccessfully matched enterprises. The meanings of other variables are consistent with the
above Model (1). The estimation results of Heckman’s two-step method are listed in columns (1)
and (2) of Table 2. After controlling the sample selection bias, the estimated coefficient of the
export tax rebate variable is still significantly negative, which means that the core conclusion is
established. The estimated coefficient of inverse Mills ratio also passes the significance level of
1%, which means that the benchmark estimation in this paper may have sample selection bias, so
it is feasible and reasonable to investigate the impact of sample selection bias.
(2) Deal with the endogeneity problems caused by reverse causality and omitted variables. The
( 1)
fit fit t r fit
probit port X
    
     
1
fit
prot  0
fit
prot 
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core explanatory variable (export rebate rate) is used as the instrumental variable of export rebate
rate with one-stage lag and two-stage lag (Xuefeng Qian and Dongmei Fan, 2015). The estimated
results of the two-stage least squares (2SLS) are listed in Column (3) and Column (4) of Table 2.
The results show that whether the lag is one or two, the estimated coefficient of export tax rebate
rate is significantly negative, indicating that export tax rebate rate and enterprises’ energy
efficiency is significantly negatively correlated. In addition, this paper also uses the research
methods for reference to conduct a variety of tests to ensure the validity and rationality of
instrumental variables. KP-LM statistics are used for testing (Kleibergen and Paap, 2006), and it is
found that the conclusion rejects the original hypothesis of "insufficient identification of
instrumental variables" and is significant at the level of 1%, indicating that the uncovered
instrumental variables are not associated with endogenous variables; The Wald rk F statistic was
used for the test (Kleibergen and Paap, 2006), and the conclusion is also found to reject the
original hypothesis that "instrumental variables are weakly identified" and to be significant at the
1% level. Both of these test results show that the 2SLS regression results are robust, so the
selected instrumental variables are reasonable.
Table 2 Endogeneity test
Heckman two-stage method 2SLS
Variables
（1）Stage 1（Probit）（2）Stage 2
（3）a lag of one period （4）a lag of two
periods
Tax -0.2246***（0.0015） -0.0043***（0.0038） -0.0251***（0.0287） -0.0024***（0.0100）
KP-LM 2189.760*** 1322.299***
Wald rk F 2365.569*** 1384.731***
invmillsss 0.0018***（0.0011）
Control Variables Yes Yes Yes Yes
Year FE Yes Yes Yes Yes
Region FE Yes Yes Yes Yes
Observations 16589 18781 14232 14281
Adj. R-squared 0.4789 0.3434 0.0461 0.0283
4.3 Robustness test
(1) Other measurements of enterprises’ energy efficiency. FE method and OLS method are
adopted to re-measure the total factor energy efficiency of enterprises. The estimated results are
shown in columns (1) and (2) of Table 3. It can be found that the estimated coefficients of export
tax rebate variable are still significantly negative, and the core conclusion is still valid. Changing
the measurement method of the dependent variable will not change the core conclusion. At the
same time, the proportion of industrial output value in coal consumption is also adopted to
represent the single factor energy efficiency of enterprises. The test results are shown in column
(3) of Table 3. The test results are shown in Column (3) of Table 3, which shows that the
estimated coefficient of the export tax rebate variable is still significantly negative, meaning that
the conclusion that the increase of export tax rebate inhibits the improvement of enterprises’
energy efficiency is robust and reliable. In summary, changing the measurement method of the
explained variable will not change the core conclusion of this study, that is, export rebate
significantly inhibits the improvement of enterprise energy efficiency.
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(2) Other measurements of export tax rebate. In the benchmark regression, this paper measures the
export tax rebate rate at the enterprise level. For the sake of robustness, this part measures the
export tax rebate rate at the industry level to replace the export tax rebate rate at the enterprise
level in the benchmark regression. The specific measurement steps are as follows: first, convert
the 8-bit coded export tax rebate library into the 6-bit coded HS96, and then match it with the
HS96-ISIC code conversion table, convert it into the ISIC code of the international standard
industry classification, then calculate the arithmetic mean export tax rebate rate at the industry
level according to ISIC code, and finally, match the measured enterprises’ energy efficiency index
according to ISIC industry code and then conduct empirical tests. The estimated results are shown
in Column (4) of Table 3, which shows that the estimated coefficient of the export tax rebate
variable changes little, no matter in size, direction or significance, which means that the core
conclusion is still valid and will not change due to different measurement methods of independent
variables.
Table 3 Robustness test
Other measures of enterprises’ energy efficiency
Other measures of export tax
rebates
Variables
（1）OLS （2）FE （3）single factor （4）industry export rebate rate
Tax -0.0233***（0.0028） -0.0054***（0.0015） -0.2588***（0.0204） -0.0075***（0.0007）
Constant 1.4676***（0.0117） 2.0662***（0.0061） 3.6853***（0.0849） 1.7586***（0.0028）
Observations 18746 18787 10913 114465
Adj. R-squared 0.3558 0.3100 0.1116 0.3312
4.4 Heterogeneity analysis
(1) Whether the enterprises export or not. According to whether the export delivery value is 0, the
sample enterprises are divided into export and non-export enterprises. The estimated results are
shown in Column (1) and Column (2) of Table 4, and it is found that the estimated coefficients of
export tax rebate variable of export and non-export enterprises are both significantly negative,
which means that both of them significantly inhibit the improvement of enterprise energy
efficiency. However, from the absolute value of the coefficient, it can be seen that the increase of
export tax rebate rate has a stronger inhibitory effect on the energy efficiency of non-export
enterprises than that of export enterprises. The possible explanation is that the increase of export
tax rebate rate increases the profits of export enterprises, and the increase of profits is conducive
to encouraging enterprises to invest more resources in R&D and innovation activities, which
offsets part of the negative effects caused by the increase of export tax rebate rate. Therefore, the
increase of export tax rebate rate has a stronger negative impact on the energy efficiency of
non-export enterprises than that of export enterprises.
(2) Trade modes of enterprises. The sample enterprises are divided into general trade enterprises
and processing trade enterprises, and empirical tests are conducted respectively. The results are
shown in Column (3) and Column (4) of Table 4, which shows that the estimated coefficients of
export tax rebate variable of the two types of enterprises are both negative and have passed the
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significance level test. However, from the absolute value of the coefficient, the processing trade
enterprises are significantly larger than general trade enterprises, which means that the increase of
export tax rebate rate has a stronger inhibitory effect on the energy efficiency of processing trade
enterprises than that of general trade enterprises. The possible reason is that processing trade
enterprises do not need to pay VAT when importing, so in most cases, they do not need to refund
VAT, or only for a small number of domestic intermediate input production factors, while general
trade enterprises invest more domestic production factors in the production process, and then get a
higher VAT rebate, so the tax rebate rate enjoyed by processing trade enterprises is much lower
than that of general trade enterprises (Ziying Fan and Binbin Tian, 2014). The difference in export
tax rebate rates leads to the reallocation of resources among different enterprises, resulting in
resource misplacement and distortion. However, general trading enterprises enjoy higher tax
rebate rates, which means they face greater policy benefits. In the face of resource misallocation
and distortion, it has more buffer and mitigation room, so it will be less affected by the policy,
therefore, the export tax rebate policy on the energy efficiency of general trading enterprises is
less than the processing trade enterprises.
Table 4 Subsamples regression Ⅰ
Variables （1）Export （2）Non-export （3）General Trade （4）Processing Trade
Tax -0.0140***（0.0020） -0.0191***（0.0038） -0.0135***（0.0019） -0.0192***（0.0039）
Constant 1.7766***（0.0081） 1.8318***（0.0175） 1.7785***（0.0080） 1.8107***（0.0182）
Observations 15884 2897 14379 4401
Adj. R-squared 0.3657 0.4353 0.3705 0.3771
(3) Enterprises’ ownership. The estimated results of state-owned enterprises and non-state-owned
enterprises are shown in Column (1) and Column (2) of Table 5. It can be found that the estimated
coefficients of export tax rebate variable of state-owned enterprises and non-state-owned
enterprises are significantly negative, indicating that the increase of export tax rebate rate
significantly inhibits the improvement of energy efficiency of state-owned enterprises and
non-state-owned enterprises. However, by comparing the absolute values of the two coefficients,
it is found that the SOEs are larger than the non-SOEs, which means that the increase of export tax
rebate rate has a stronger inhibitory effect on the energy efficiency of SOEs than that of non-SOEs.
The possible explanation is that non-SOEs have less interests linked with the government. When
facing policy shocks, their more independent choice rights make them more flexible, more
sensitive to the market, and more innovative than SOEs. Therefore, export tax rebate has a
stronger inhibitory effect on the energy efficiency of SOEs than that of non-SOEs.
(4) Regions. There are significant differences in the economic development levels of different
regions in China, which lead to significant differences in the impact of export tax rebate policy on
the energy efficiency of enterprises in different regions. Therefore, it is necessary to divide the
sample enterprises into the eastern region and the central and western regions for empirical tests to
explore the differences between them. Column (3) and Column (4) in Table 5 list the empirical
estimated results of the two samples. It can be found that the estimated coefficients of the export
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tax rebate variable in the eastern region and the central and western region are significantly
negative, indicating that the increase of export tax rebate rate significantly inhibits the
improvement of the energy efficiency of enterprises in the eastern region and the central and
western region. However, by comparing the absolute values of the two coefficients, it is found that
the absolute value of the estimated coefficient of the export tax rebate variable in the eastern
region is significantly greater than that in the central and western regions, which means that the
increase of the export tax rebate rate has a stronger inhibitory effect on the energy efficiency of
enterprises in the eastern region than that in the central and western regions.
Table 5 Subsamples regression Ⅱ
Variables （1）State-owned （2）Non-state-owned （3）Eastern region
（4）Central and
western regions
Tax -0.0181***（0.0027） -0.0133***（0.0023） -0.0174***（0.0020） -0.0128**（0.0045）
Constant 1.8826***（0.0129） 1.7327***（0.0094） 1.7977***（0.0085） 1.7655***（0.0193）
Observations 6578 12203 11312 6002
Adj. R-squared 0.4821 0.1617 0.3735 0.4164
5. Channels and paths through which export tax rebate affects enterprises’ energy efficiency
5.1 Construction of the mediation model
The above content does not deeply explore the internal mechanism of export tax rebate and
enterprises’ energy efficiency. This part constructs the mediation effect model to explore the
channel mechanism of export tax rebate affecting enterprises’ energy efficiency. Selecting
enterprises’ productivity ( ) and enterprises’ innovation and R&D ( ) as the mediating
variables, the following mediation effect model is constructed for channel test:
(6)
(7)
(8)
(9)
Where is the productivity of the enterprises, which is measured by Olley-Pakes
semi-parameter, namely OP method; is the innovation and R&D of the enterprises, which is
measured by the proportion of the output value of new products in the total sales of the
enterprises.
5.2 Regression results of mediation model
The test results of the mechanism of export tax rebate on enterprises’ energy efficiency are
fit
tfp fit
Inn
1 1
fit ft fit t r fit
tfee α β tax γX δ δ ε
     
2 2
fit ft fit t r fit
tfp α β tax γX δ δ ε
     
3 3
fit ft fit t r fit
Inn α β tax γX δ δ ε
     
1 4
fit ft fit fit fit t r fit
tfee α βtax tfp Inn γX δ ε
  
       
fit
tfp
fit
Inn
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shown in Table 6. Column (1) corresponds to the estimated results of Equation (6). Column (2)
and Column (3) are the estimated results with productivity ( ) and innovation R&D ( ) as
the explained variables, which correspond to Equation (7) and Equation (8) respectively. Column
(4) and Column (5) are the estimated results after adding two mediating variables respectively.
Column (6) reports the regression results after adding two mediating variables at the same time,
which corresponds to Equation (9). The estimated results in Column (2) show that the estimated
coefficient of export tax rebate variable is significantly negative, indicating that export tax rebate
significantly reduces enterprises’ productivity. The possible explanation is that the increase of
export tax rebate rate promotes the flow and transfer of various production factors, aggravates the
distortion and misplacement of resources, and the misplacement of resources reduces enterprises’
productivity. It can be seen from the estimated results in Column (4) that enterprises’ productivity
significantly promotes the improvement of enterprises’ energy efficiency. It can be found from the
estimated results in Column (3) that the increase of export tax rebate rate significantly promotes
the innovation and R&D level of enterprises. The possible explanation is that, on the one hand, the
increase of export tax rebate rate expands the scale of exports, and the expansion of export scale
increases the profits of enterprises, and the increase of profits makes enterprises have sufficient
funds to engage in innovation and R&D activities, thus improving the level of technological R&D
and innovation. On the other hand, the increase of export tax rebate rate prolongs the continuous
survival time of enterprises in the export market, and the extension of the export duration is
conducive to the deeper integration of enterprises into the export market, which is more conducive
to the enterprises to learn new technologies from the production of foreign advanced products,
crack the technical experience hidden in foreign advanced products, and apply it to the production
and design of their own products. In turn, it has improved the level of innovative research and
development. From the estimation results in column (5), it is found that innovation R&D of
enterprises significantly improves the energy efficiency of enterprises.
It should be noted that after adding and respectively, the absolute value of the
estimated coefficient of export tax rebate increases or decreases respectively compared with the
benchmark estimated results, but the significance does not change significantly, which
preliminarily indicates the existence of negative "misplacement effect of resources" and positive
"innovation and R&D effect". At the same time, these two mediating variables are put into the
estimated equation for testing, and it is found that the absolute value of the estimated coefficient
of export tax rebate further decreases, and the significance remains unchanged, which once again
indicates that export tax rebate significantly reduces the energy efficiency of enterprises mainly
through two possible channels: improving the degree of misplacement and distortion of resources
and improving the level of innovation and R&D. The above analysis indicates that both
"misplacement effect of resources" and "innovation and R&D effect" exist.
Table 6 Regression of mediation model
Variables （1）Efficiency （2）tfp （3）Inn （4）Efficiency （5）Efficiency （6）Efficiency
Tax -0.0149***（0.0017） -0.0115***（0.0016） 0.2666***（0.0432） -0.0026***（0.0003） -0.0163***（0.0029） -0.0014***（0.0004）
tfp 1.0834***（0.0013） 1.1226***（0.0027）
Inn 0.0342***（0.0010） 0.0048***（0.0002）
Control Variables Yes Yes Yes Yes Yes Yes
fit
tfp fit
Inn
fit
tfp fit
Inn
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Year FE Yes Yes Yes Yes Yes Yes
Region FE Yes Yes Yes Yes Yes Yes
Constant 1.7874***（0.0073） 1.8583***（0.0068） 10.6120***（0.1693） -0.2257***（0.0027） 1.4832***（0.0158） -0.2708***（0.0049）
Observations 18781 18783 14238 18781 14238 14238
Adj. R-squared 0.3793 0.2525 0.1110 0.9840 0.6137 0.9908
For the sake of rigorousness of the study, to further test whether export tax rebate will affect the
energy efficiency of enterprises through the "misplacement effect" and "innovation and R&D
effect", we draw lessons from the research ideas of Sobel (1987) to test and
respectively. If the null hypothesis is rejected, it means that the mediating effect
has passed the significance test. The specific steps are as follows: first calculate the two product
terms and , and then calculate the standard deviation of the two product terms,
namely and , where represents the standard
deviation of the corresponding regression coefficient. According to the formula
and , =-8.99 and =6.01 are calculated,
and both of them have passed the significance level of 1%. Therefore, it can be determined that
misplacement of resources and innovation and R&D are the two channels through which export
tax rebate affects the energy efficiency of enterprises.
In addition, we also learn from the research methods of Zhonglin Wen et al. (2004) to clarify
which of the two effects plays a dominant role in the process of influencing the energy efficiency
of enterprises. The specific method is to calculate the shares of the two effects in the total effect,
namely and , through calculation, =-9.45
and =0.94 are obtained, namely, the misplacement effect of resources is -9.45 and the
innovation and R&D effect is 0.94. Both the size and direction of the two effects are consistent
with the core conclusion of this paper, that is, export tax rebate reduces productivity by improving
the degree of misplacement and distortion of resources, and then reduces the energy efficiency of
enterprises, which is called the misplacement effect of resources; export tax rebate promotes the
improvement of energy efficiency of enterprises by improving the level of innovation and R&D,
which is called the innovation and R&D effect, but the inhibition effect of resource misplacement
effect is much higher than the promotion effect of innovation and R&D, so export tax rebates
ultimately reduce the energy efficiency of enterprises.
6. Conclusions and policy implications
This paper systematically explores the relationship between export tax rebate and enterprises’
energy efficiency using China Industrial Enterprises Environmental Statistics Data, China
Industrial Enterprises Database, China Customs Trade Data and Export Tax Rebate Database from
2000 to 2012. The results show that: first, export tax rebate reduces the energy efficiency of
0 2
: 0
H   
0 3
: 0
H   
2
  3
 
2 4
2 2 2 2
2 4
S s s
   
 
  3 3
2 2 2 2
3
S s s
   
 
  s
2 2
2 /
Z S
   
 
 3 3
2 2 2 2
3
S s s
   
 
  2
Z  3
Z 
2 4
/
tfp
Effect   
 3 4
/
Inn
Effect   
 tfp
Effect
Inn
Effect
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enterprises on the whole, and the core conclusion remains valid after dealing with sample
selection bias, re-measuring the core variables and overcoming the endogeneity of variables;
second, the heterogeneity test finds that the inhibitory effect of export tax rebate on the energy
efficiency of non-export enterprises, processing trade enterprises, state-owned enterprises and
enterprises in the eastern region is stronger than that of export enterprises, general trade
enterprises, state-owned enterprises and enterprises in the central and western regions; third, the
mechanism test finds that export tax rebate not only reduces the energy efficiency of enterprises
by increasing the degree of resource misplacement and distortion, but also promotes the
improvement of energy efficiency of enterprises by increasing the level of innovation and R&D.
However, in general, the inhibiting effect of resource misallocation effect is greater than the
promoting effect of innovation and R&D effect. Therefore, export tax rebate ultimately
significantly reduces the energy efficiency of enterprises.
The above conclusion means that although the export tax rebate policy ensures the stable
growth of exports and achieves China's "export miracle", it also exacerbates the misplacement and
distortion of resources, reduces the productivity of enterprises, and then reduces the energy
efficiency of enterprises, which is not conducive to the realization of the "win-win" goal of energy
conservation and emission reduction and economic growth. The improvement of energy efficiency
is the key link of "green development". The conclusion of this study means that the government
can gradually reduce or cancel the export tax rebate to a certain extent to improve energy
efficiency and achieve energy conservation and emission reduction. Of course, this study is not to
negate the economic effect of "tax and fee reduction" policy, but to demonstrate the negative
impact of export tax rebate policy on the improvement of energy efficiency from the relationship
between export tax rebate and energy efficiency.
In the current China's energy supply and demand contradiction is increasingly acute, high
pollution and high consumption of extensive development mode has been unable to meet the
requirements of "green development" in the severe situation, reducing energy consumption per
unit GDP, promoting economic development is an important part of the transformation of
backward economic development mode, direct large-scale closure of high investment, high
consumption and low output enterprises "one size fits all" development mode although in the short
term can promote the improvement of energy efficiency, but in the long run will drag on economic
development, harm social welfare. Therefore, the "one size fits all" development mode is not a
good path for sustainable development, the government should take downward or gradually
restrict the export tax rebate behavior to reduce the degree of resource misplacement and
distortion, and then improve energy efficiency; enterprises should strengthen the training of labor
skills, increase investment in innovation and R&D, further improve the technical level and
productivity, and then promote the improvement of energy utilization efficiency, to achieve the
two-way goal of energy conservation and economic development.
Acknowledgments
This work is partially supported by Guangdong Social Science Planning 2022 annual discipline
co-construction project (No. GD22XYJ25), the 14th Five-Year Plan for the Development of
Philosophy and social Sciences in Guangzhou in 2022 (No. 2022GZGJ27), the Featured
Innovation Project of Guangdong Provincial Education Department in 2022 (No.
2022WTSCX139). The authors also gratefully acknowledge the helpful comments and
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suggestions of the reviewers, which have improved the presentation.
Conflicts of Interest: The authors declare no conflict of interest.
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