Impact of foreign trade on energy efficiency in China’s textile industry

Journal of Cleaner Production xxx (xxxx) xxx

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Impact of foreign trade on energy efficiency in China’s textile industry Hongli Zhao a, Boqiang Lin b, * a

School of Economics and Management, Beijing Institute of Petrochemical Technology, Beijing, 102617, PR China School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Fujian, 361005, PR China

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 18 December 2018 Received in revised form 1 October 2019 Accepted 12 October 2019 Available online xxx

Improving energy efficiency is important to ensure economic growth while conserving energy and reducing emissions. Based on the total factor energy efficiency of China’s textile industry, this paper constructs a simultaneous equation model that includes the Tobit model, and empirically analyzes whether foreign trade affects energy efficiency in the textile industry as well as the mechanism of any such influence. The empirical results demonstrate positive feedback between foreign trade and energy efficiency in the textile industry, with imports impacting energy efficiency more than do exports. The foreign trade of textile industry is divided into import trade and export trade, which have different impacts on energy efficiency. Simultaneously, the results also confirm that R&D input, ownership structure and energy price significantly impact the energy efficiency of China’s textile industry. © 2019 Elsevier Ltd. All rights reserved.

Handling editor: Zhifu Mi Keywords: Foreign trade Energy efficiency Simultaneous equations

1. Introduction With the rapid development of China’s economy, industrialization and urbanization have accelerated, industrial energy demand has grown, and the dependence of the economy on energy has increased, which brings about increasing the constraints and pressures associated with a shortage of energy and other resources (Xu and Lin, 2018). Reducing energy consumption and improving energy efficiency are important goals for China’s enterprises seeking to save energy (Lin and Jia, 2019). Improving energy efficiency is important to ensuring economic growth while conserving energy and reducing emissions. Technological progress is important to improving the energy efficiency of China’s textile industry, and foreign trade is important to promoting technological progress (Gao et al., 2010). Lin and Liu (2015) found in an empirical study that foreign trade is both an important source of technological progress and a key driver of improvement in energy efficiency. Foreign trade generally works on both active and passive levels to help enterprises to improve their energy efficiency (Zhao and Lin, 2019). On the active level, foreign trade increases the opportunities for enterprises to learn advanced technology. On the passive level, it requires enterprises to meet the higher product quality * Corresponding author. School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Fujian, 361005, PR China. E-mail address: [email protected] (B. Lin).

requirements of the international market. The intensely competitive international market demands that enterprises improve their managerial and technical levels. Both levels, active and passive, contribute to improving the energy efficiency of industrial enterprises. The textile industry is one of China’s traditional pillar industries and enjoys obvious international competitive advantages. Simultaneously, the textile industry is very important to the national standard of living (Lin et al., 2012; Zhao and Lin, 2019). The textile industry contributes significantly to stimulating the market, absorbing labor, increasing rural incomes, accelerating urbanization, and promoting harmonious social development. The China Statistical Yearbook classifies the manufacturing industry into 29 industries. In 2013, the textile industry accounted for 6.23% of total industrial added value for the manufacturing industry. The textile industry thus is an important contributor to the manufacturing industry. From 1995 to 2013, combined import and export value steadily increased as a proportion of the total output value of China’s textile industry. Because foreign trade exerts a significant catalytic effect on technological progress, the decrease in the energy intensity of the textile industry and the increase in imports and exports relative to total output may not be entirely coincidental. China is the world’s largest textile exporter, and its textile industry has benefited from international trade. We analyze the relationship between energy efficiency and foreign trade in the textile industry, and clarify how foreign trade can increase energy efficiency. This analysis can guide

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Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

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policy recommendations on how best to improve the development of the textile industry and increase its efficiency. We have consulted some documents and materials to show that there are many studies on energy efficiency and foreign trade in macro or high energyconsuming industries (Zhang et al.,2014; Li and Bao, 2016; Yang et al., 2017; Wu, 2012; Zeng, 2014). However, the textile industry as the research object, the relationship between energy efficiency and foreign trade, and the mechanism of foreign trade affecting energy efficiency, relatively speaking, the number of literatures is not very large. Therefore, this paper constructs simultaneous equations containing the Tobit model, deals with the endogeneity of the variables and uses the Geweke-Hajivassiliou-Keane algorithm for model estimation. Furthermore, two forms of foreign trade, namely imports and exports, are empirically studied, and the internal mechanism through which foreign trade affects the energy efficiency of China’s textile industry is analyzed. The contributions of this study are as follows. First, this study attempts to construct a provincial panel data to use the GewekeHajivassiliou-Keane algorithm for model estimation. Most of the previous research on the foreign trade of the textile industry is time series data. The analysis in this paper can provide a new perspective to analyze the relationship between energy efficiency and foreign trade in the textile industry. Second, the empirical results of this paper draw new conclusions. The foreign trade of the textile industry has two ways of importing and exporting, which affects energy efficiency. However, the impact of imports on energy efficiency is greater than that of exports. Third, the common way to solve the problem of two-way causality is to choose the instrumental variable and use the two-stage method to control the reverse influence of dependent variable on independent variable, but the instrumental variable method is difficult to judge the direction and exact size of the influence. Compared with the instrumental variable method used in most literatures, this paper analyzes the two-way causal relationship between energy environment efficiency and foreign trade by constructing simultaneous equations, which can better avoid the shortcomings of instrumental variable method and overcome endogeneity problems. The remainder of this article is structured as follows. Section two introduces the data sources used in this paper, as well as the methods of data processing. Section three then introduces the present situation of foreign trade in the textile industry. Next, section four conducts empirical analysis, verifies the influence of foreign trade on energy efficiency, and analyzes the mechanism of this influence. Finally, conclusions and suggestions are provided. 2. Literature review Present academic research on energy efficiency and foreign trade mainly focuses on the relationship between export trade and energy consumption. Egger and Url, 2010 analyzed the impact of export trade on energy consumption in Latin America, and concluded that the rapid growth of export trade was the key to insufficient energy supply in Austria during the sample period. Fresner and Morea, 2017 analyzed the relationship between import and export trade and energy consumption structure during the sample period from the perspective of supply and demand, and concluded that the former influenced the change of the latter. Svensson and Paramonova, 2016 found that trade reduced the resource-intensity of productive activities in developed industrialized countries, and increased the resource-intensity of the production structure of developing countries. Li et al. (2014) analyzed China’s trade situation based on the input-output method, and found that the structural change in foreign trade was unfavorable to China’s energy conservation. Kohler (2013) found an important link

between the development of export trade and energy consumption. Farrow et al. (2018), Meng et al. (2016) and Zhang et al. (2017) all found a significant relationship between export structure and energy constraints. In summary, scholars have conducted in-depth research on the relationship between energy consumption and foreign trade, mainly from the perspective of the scale and structural effects of export trade. As we all know, production technology is important to export promotion. Therefore, from the perspective of production technology, scholars use empirical research to analyze the relationship between foreign trade and energy efficiency. Lin et al. (2012) found that production technology significantly impacts energy efficiency, as does the technical effect of export trade. Weitzel and Ma, 2014 took China’s industrial industry as the research object, analyzed the factors affecting its energy efficiency, and found that domestic R&D capital and international R&D spillover affect energy efficiency differently. The former always promotes energy efficiency, while the impact of the latter differs according to industry. Gao et al. (2010) found that, compared with export trade, import trade is more conducive to the introduction of foreign advanced technology, and thus to the improvement of energy efficiency. Lin and Liu (2015) took China’s industrial industry as an example and adopted an empirical method to deeply analyze how foreign trade affects energy and environmental efficiency. They found that foreign trade can improve energy and environmental efficiency, and a positive feedback effect exists between the two. In-depth studies of foreign trade and energy efficiency have found that foreign trade can promote energy efficiency (Roy and Yasar, 2015). Research by domestic scholars on energy efficiency and foreign trade mainly comprises the following three categories (Zhang et al., 2017; Lin and Zhao, 2015). The first category uses a single factor energy efficiency index, such as energy intensity, to analyze the relationship between single factor energy efficiency and foreign trade (Shi, 2002). The second category is based on total factor energy efficiency and adopts the research methods of Hu and Wang (2006). Such research takes total factor energy efficiency as the dependent variable, and further analyzes the relationship between energy efficiency and foreign trade (Gao and Zhou, 2010). Representing the third category, Fan et al. (2009) and Wu and Shao, 2016 take the entire industrial sector as the research object. Yan and Yang, 2010 and Xie and Zhou, 2009 take a country or region as the research object. Finally, Li et al. (2014) posits that economic opening can expand foreign trade and upgrade industrial structure and technological progress, thus contributing to improved energy efficiency. Looking at the literature on foreign trade and efficiency in China, few studies avoid endogeneity in their models, and studies on the mechanism of influence of the energy efficiency of foreign trade are also scarce. Accordingly, the literature on the relationship between foreign trade and energy efficiency is inadequate. Foreign trade can promote energy efficiency by increasing competition, and increased energy efficiency in turn can promote foreign trade. Twoway causality may also exist between foreign trade and energy efficiency. 3. Model setting and data sources First, we calculate the energy efficiency of China’s textile industry. We also introduce regression analysis to examine the impact of foreign trade on energy efficiency in the textile industry. Because the range of the static total factor energy efficiency index is (0, 1], the data are truncated, and if traditional linear regression is used to return the model directly, a negative fitting value may be obtained. Therefore, empirical studies usually use the Tobit model of the dependent variable.

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

H. Zhao, B. Lin / Journal of Cleaner Production xxx (xxxx) xxx

y*k;t ¼ d þ h  Traj;t þ    N 0; f2

Xm



u qj þ sj þ pt þ 4j;t ; 4j;t t k¼1 k j;t (1)

yj;t ¼ y*j;t ; if y*j;t 2ð0; 1 yj;t ¼ 0; if y*j;t 2ð∞; 0Þ yj;t ¼ 1; if y*j;t 2ð1; þ ∞Þ: Among the equation variables, yj;t is the estimated energy efficiency of area J for year t; y*j;t is the corresponding hidden variable, and meets the classic assumptions of the built model; qj represents the control variables; sj represents individual heterogeneity; and pt represents time heterogeneity. This paper mainly studies the impact of foreign trade on the energy efficiency of China’s textile industry and the internal mechanism through which this effect occurs. This paper mainly discusses the impact of foreign trade on energy efficiency, and energy efficiency is the explanatory variable. Foreign trade is the most important explanatory variable in the model. The research comprises three levels: First, verify the impact of foreign trade on energy efficiency. Second, the simultaneous equations of the Tobit model are constructed to deal with the endogenous problems of variables and explore the relationship between foreign trade and energy efficiency. Based on this, the empirical research logic shown in Fig. 1 of this study is obtained. As one of the most important explanatory variables in the model, foreign trade (Tra) is used as a measure of “the ratio of the total import and export value to the total output value of the textile industry”. The data are obtained from the China Statistical Yearbook, China Industry Statistical Yearbook, China Textile Industry Development Report, the Statistical Yearbooks of provinces, and the CEIC database. We add the corresponding control variables to the model to control for their impact on energy efficiency. These control variables are classified into the following three categories: (1) Research and Development investment (R&D). Lin and Du (2013) identified research and development investment as an important force promoting technological progress, which is the key factor in continuously improving energy efficiency (Rajbhandari and Zhang, 2017). Wu (2006) and He et al. (2018) adopted an empirical method to further verify that R&D significantly and positively affects total factor productivity in China. Existing research generally uses internal expenditure on science and technology activities as a measure of R&D investment (Li and Lin, 2018). Accordingly, this

Fig. 1. The mechanism of foreign trade in textile industry on energy efficiency. Source: Self-made by the authors.

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paper uses internal textile industry expenditure on research and experiment development to measure R&D investment in the textile industry. Data are obtained from the relevant calendar year of the China Statistical Yearbook on Science and Technology. (2) Ownership structure (Str). Ownership structure somewhat reflects the structural adjustment of the textile industry. Since China’s reform and opening up, state ownership and control in the textile industry has gradually decreased in proportional terms, while non-state ownership has increased. Liu and Li (2001) and Lin et al. (2012) identified the promotion of energy efficiency as an effective way to increase non-state ownership in the national economy. Ownership reform can contribute to the promotion of improved energy efficiency (Fan and Liao, 2007). Because ownership structures affect energy efficiency differently between developed and underdeveloped areas, government policies should be developed to fit the actual local situation and conditions (Yuan and Zhang, 2009). Different ownership structures can lead to differences in management mode and incentive system, which can significantly impact energy efficiency (Wei and Shen, 2008). Scholars have found stateowned enterprises to generally be less efficient than other enterprises (Nie and Jia, 2011). This paper uses the proportion of textile industry capital comprising owners’ equity to measure the ownership structure of the textile industry. Data are obtained from relevant calendar year entries in the China Industry Statistical Yearbook. (3) Energy price (EP). Scholars have found that increased energy prices improve enterprise awareness of energy savings (Lin et al., 2012), reduce energy waste, and increase energy utilization efficiency (Chen, 2015; Bye et al., 2018). Table 1 presents a descriptive statistical analysis of the above variables. The research data mainly came from past issues of the China Industry Statistical Yearbook, China Energy Statistical Yearbook, the CEIC database and Statistical Yearbooks of provinces in China.

4. Empirical analysis and discussion of results 4.1. Foreign trade in the textile industry China’s reform and opening up has brought the country new opportunities and challenges and rapidly expanded foreign trade. During the period of the Ninth Five-Year Plan, China’s imports and exports increased only moderately in volume terms, but the increase rapidly accelerated from the Tenth Five-Year Plan. From 148.78 billion dollars in 1995, China’s total exports increased 14 times to 2,210.02 billion dollars in 2013. Although China’s textile exports also increased gradually over this same period, their growth lagged far behind that of total exports. As shown in Fig. 2, the proportion of textile exports to China’s total exports by volume gradually decreased during the sample period. This phenomenon may reflect how China’s reform and opening up first affected the textile industry, with other industries experiencing their own phases of rapid growth and development only more recently. As a traditional and labor-intensive industry, the textile industry has recently developed slower than more capital and technologyintensive industries. During the 1995e2013 sample period, although China’s textile imports and exports declined as a proportion of total imports and exports, China remains the world leader in textile exports owing to a growth in absolute export value and its share of global textile exports continues to grow. This is shown in Fig. 3.

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

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Table 1 Descriptive statistical analysis of variables. Variables

Sample size

Mean

Standard deviation

Minimum value

Maximum value

Expected impact

Tra R&D Str EP

532 532 532 532

39.1776 15339.5429 0.4006 164.1561

74.1554 38776.8188 1.1103 19.4838

0.2210 56.7784 0.0016 91.2816

372.5700 276262.9565 24.4286 244.7730

þ þ e þ

Fig. 2. The proportion of imports and exports in Chinese textile industry. Data sources: China Textile Industry Development Report (1996e2014).

4.2. Energy efficiency of China’s textile industry From Table 2, the average static total factor energy efficiency of the textile industry in eastern China exceeded those of central and western China during the sample period. From 1995 to 2013, the average static total factor energy efficiency of the textile industry in eastern China was 0.7775, compared with just 0.4600 and 0.2486 in central and western China, respectively. The average total energy

efficiency of the eastern region was about 1.69 times that of the central region and 3.13 times that of the western region. 4.3. Tobit model and the results of simultaneous equations This paper mainly discusses the impact of foreign trade on energy efficiency, and energy efficiency is the explanatory variable. The energy efficiency calculated in Chapter 4.2 is taken as

Fig. 3. Imports and exports of China’s textile industry relative to total global imports and exports. Data sources: textile industry development report (1996e2014).

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

H. Zhao, B. Lin / Journal of Cleaner Production xxx (xxxx) xxx Table 2 Three regional static total factor values of energy efficiency.

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Table 3 Estimation results of Tobit model parameters.

Years

Eastern

Central

Western

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 The average

0.7087 0.6701 0.6491 0.6796 0.6883 0.6325 0.6914 0.7250 0.7708 0.7396 0.8364 0.8182 0.8480 0.8440 0.8529 0.8692 0.8976 0.9121 0.9381 0.7775

0.4882 0.5045 0.4906 0.4619 0.5042 0.5259 0.4695 0.5045 0.5236 0.5314 0.5284 0.5125 0.4176 0.4901 0.4103 0.3448 0.3471 0.3613 0.3737 0.4600

0.2565 0.2521 0.2528 0.2383 0.2308 0.3299 0.2654 0.3637 0.3213 0.2950 0.2346 0.2074 0.1857 0.1719 0.2017 0.2062 0.2094 0.2502 0.2504 0.2486

dependent variable, and the Tobit model is applied to analyze it. This chapter takes the measured total factor static energy efficiency of the textile industry as the dependent variable, and estimates formula (1) using textile industry data for different provinces and cities from 1995 to 2013. The result is shown in Table 3. Regression (2) adds the three explanatory variables of R&D investment, ownership structure and energy price, but did not control for provincial heterogeneity and time heterogeneity. Furthermore, to reduce the effect of unobservable variables on the results, regression (3) adds the two virtual variables of year and province to control for the fixed effects of year and province in the textile industry. From Table 3, foreign trade is known to significantly improve energy efficiency in China’s textile industry, consistent with theoretical expectations. Foreign trade is a key variable, and may be linked to energy efficiency by two-way causality. That is, given that engagement in foreign trade is associated with comparative advantage, enterprises with high energy efficiency may be more likely to engage in foreign trade, potentially causing problems of endogeneity. In practice, endogeneity has numerous causes, including missing variables, measurement deviations, or two-way causality between variables. In this paper, the simultaneous equations model is established to analyze the endogenous problems caused by the simultaneous (that is, mutual causal relationship) between independent and dependent variables. Endogeneity problems associated with foreign trade may cause errors in the estimated results in Table 3. Moreover, efforts to avoid problems of endogeneity may adversely impact the estimation. Hence this manuscript further introduces the hybrid simultaneous

Tra Ln R&D Str Ln EP Constant term Dummy_T Dummy_P Sample size

(1) TFEE

(2) TFEE

(3) TFEE

0.1447*** (27.94) e e e 0.2291*** (17.15) No No 532

0.0693*** (8.28) 0.0694*** (8.73) 0.0329*** (4.64) 0.0094 (0.13) 0.1615 (0.46) No No 532

0.2553*** (16.22) 0.1406*** (8.12) 0.0023 (0.35) 0.1672*** (2.99) 1.9522*** (7.15) Yes Yes 532

Note: the estimate of the t value is in brackets; "*", "* *" and "* * *" represent significance levels of 10%, 5% and 1%, respectively.

equations model based on the Tobit model to solve the problem of two-way causality among the variables. The most prominent feature of foreign trade is its association with comparative advantage (Koesler and Swales, 2016). Industries or sectors with higher productivity generally exhibit greater comparative advantage. First, from the perspective of export trade, Melitz (2003) demonstrated that export enterprises have unique advantages over non-export enterprises and clearly exhibit higher productivity. This occurs because of two effects, namely the “selfselection effect” and the “export learning effect”. The former implies that energy efficient enterprises have comparative advantages in foreign trade. To cope with the fiercely competitive international market and meet the necessary requirements to export successfully, enterprises must improve their product quality and technology level, and also cultivate foreign trade opportunities. The last is important because foreign trade enables enterprises to learn advanced technology from abroad, and also helps them improve their productivity (Fan and Tian, 2014). Scholars have pointed out that energy efficiency is an organic part of enterprise productivity. Therefore, the “self selection effect” and “export learning effect” also apply to energy efficiency. Import trade intuitively offers enterprises a means to improve energy efficiency. Imports enable enterprises to directly learn advanced foreign technologies and experiences, helping to save energy consumption and promote energy efficiency. In turn, energy efficiency may impact imports due to the demand effect associated with exports. To effectively solve the problem of two-way causality of variables, many scholars adopt instrumental variables, and use the two-phase method to control the interpreted variables in reverse of explanatory variables. However, this method has defects, such as difficulty in distinguishing effect size and direction. Based on the research of Lin and Liu (2015), this manuscript uses simultaneous equations to avoid the endogenous problems and discusses the relationship between foreign trade and energy efficiency. The equations used are as follows:

8 > T T T T > > > TFEEjt ¼ h0 þ h1  Trajt þ h2  ln R&Djt þ h3  Strjt > > > > > þhT  ln EP þ uT Dummy H þ pT Dummyy Y þ 4T > jt jt jt > 4 j j jt > < ð2  1Þ > > > > > Traj;t ¼ fT0 þ fT1  TFEEjt þ fT2  ln R&Djt þ fT3  Strjt > > > > > T T > T T y T > : þf5  ln taxjt1 þ f6  ln profitjt1 þ lj Dummy Hjt þ dj Dummy Yjt þ sjt

(2)

ð2  2Þ

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

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Equations (2)e(1) is the deterministic equation for total factor energy efficiency (TFEE) in the textile industry. The truncated characteristics of the variable mean that the Tobit model is used. Equations (2)e(2) is the determining equation of foreign trade, which excludes the energy price factor and adopts the nontruncated regression equation. Because financial conditions significantly impact foreign trade decisions in the textile industry, we use taxj and profitj to represent industry profitability and add them to the decision-making equation. The measure taxj is “the ratio between value-added tax payable (VAT) and sales income of the textile industry”, and profitj represents “total profit as a proportion of sales revenue in the textile industry”. Because of the internal nature of industry tax and profit, this manuscript assigns them a time lag. In the equation, the coefficient hj measures the positive effect of foreign trade on energy efficiency in the textile industry, and fj reflects the reverse effect, namely that of energy efficiency on foreign trade. Because the system contains both the traditional truncated regression equation and the Tobit equation with double censored variables, in the empirical analysis, the estimation of the 2SLS or 3SLS by simultaneous equations may lead to errors in the regression results. Geweke (1989), Keane (1994), and Hajivassiliou and Mcfadden (1998) proposed the GewekeHajivassiliou-Keane algorithm to estimate these mixed models. Domestic scholars have used this algorithm to conduct relevant research, further verifying its practicability (Lin and Liu, 2015). This paper uses this algorithm to estimate the hybrid model (2). The specific results are shown in Table 4. The estimated results listed in Table 4 (1) further confirm that foreign trade significantly and positively affects energy efficiency in the textile industry, with an influence coefficient of 0.0639. Because the unobservable factors of region and year may impact the empirical estimation, we re-establish the empirical results after further controlling for the fixed effects of provinces and cities in the regression of column (2). The results show a significant improvement in the energy efficiency of the textile industry, supported at the 1% significance level. After adding the virtual variables of provinces and cities, as well as years, and after controlling for fixed effects, the influence coefficient is considerably increased relative to when the fixed effects are uncontrolled. The influence coefficient increased from 0.0639 to 0.2338, somewhat confirming that the heterogeneity of provinces and cities impacted the empirical results of the model. Therefore, the virtual variables of provinces and cities, as well as years, should be added to the equation to control for the regional and time effects. The regression results from columns (1) and (2) in Table 4 are in line with theoretical expectations, further supporting our conclusion that foreign trade significantly improves energy efficiency in the textile industry. From columns (1) and (2) in Table 4, R&D investment

significantly impacts textile industry energy efficiency after controlling for the fixed effects of province and year. Increased R&D investment promotes energy efficiency mainly because it reflects the importance textile enterprises assign to technological innovation and their own technological level. By increasing the financial and material resources devoted to technology research and development, we can develop more advanced textile production technology and more effective management methods, promote technological progress, and so increase energy utilization efficiency. Energy prices positively and significantly affect the energy efficiency of the textile industry after controlling for the fixed effects of provinces and cities, as well as years, showing that higher energy prices promote energy efficiency in the textile industry. Coal and electricity are the main energy sources used by the textile industry, and increased energy prices increase enterprise costs, and can encourage reduced energy consumption, thus promoting energy efficiency. In the case of China, energy prices remain under government control and marketization is very limited (Zhang and Worrell, 2014). Therefore, energy price reform can positively affect energy efficiency in China. Ownership structure also significantly impacts the energy efficiency of China’s textile industry and moreover the influence coefficient is negative, consistent with our expectations and most of the research results. This is mainly because state-owned enterprises have inadequately developed competition mechanisms, and so the rationalization of production and operation is insufficient. Therefore, ownership structure is an important part of the production factor. Finally, because energy utilization efficiency decreases with increasing nationalization, the negative impact on improvement in energy efficiency increases with state ownership. Columns (3) and (4) in Table 4 set the foreign trade of the textile industry as the main explanatory variable, while the energy efficiency level, R&D investment and ownership structure comprise the other explanatory variables. Energy price factors are excluded as explanatory variables. Meanwhile, two control variables are added that reflect profitability, namely taxj and profitj . From the empirical results of the foreign trade equation in Table 4, the energy efficiency of the textile industry significantly and positively affects foreign trade. This confirms that the energy efficiency of the textile industry will positively affect foreign trade. R&D investment of the textile industry significantly and positively impacts foreign trade at the 1% significance level if the fixed effect is not controlled for. Regardless of whether the fixed effect is controlled for, ownership structure significantly impacts foreign trade at the 5% and 10% significance levels, and the direction of influence is negative. Therefore, it is essential to adopt simultaneous equation estimation, including the Tobit model, to effectively avoid the two-way causal relationship between the energy efficiency of the textile

Table 4 Parameter estimation results of simultaneous equations.

TFEE Tra Ln R&D Str Ln EP Taxt-1 Profitt-1 Constant term Dummy_T Dummy_P Sample size

(1) TFEE

(2) TFEE

(3) Trade

(4) Trade

e 0.0639*** (8.73) 0.0604*** (8.74) 0.0306*** (4.92) 0.0250 (0.40) e e 0.2721 (0.88) No No 532

e 0.2338*** (17.56) 0.1292*** (8.75) 0.0029 (0.50) 0.2015*** (4.07) e e 1.9821*** (8.14) Yes Yes 532

2.1278*** (9.09) e 0.4645*** (12.23) 0.0767* (1.89) e 0.0083 (1.22) 0.0040** (2.10) 2.8255*** (12.67) No No 532

1.5416*** (17.84) e 0.0340 (0.89) 0.0383** (2.38) e 0.0004 (0.21) 0.0045*** (6.70) 1.2988*** (4.82) Yes Yes 532

Note: the estimate of the t value is in brackets; "*", "* *" and "* * *" represent significance levels of 10%, 5% and 1%, respectively.

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

H. Zhao, B. Lin / Journal of Cleaner Production xxx (xxxx) xxx

industry and foreign trade. 4.4. Influence mechanism of foreign trade on energy efficiency in the textile industry From the above analysis, the development of foreign trade significantly promotes energy efficiency in the textile industry, but we cannot identify the internal mechanism by which foreign trade impacts energy efficiency. Specifically, foreign trade can be divided into import trade and export trade, each of which impacts energy efficiency via a different mechanism. On the one hand, enterprises can directly learn advanced technology and experience from foreign countries through import trade, which helps to reduce energy consumption and promote energy efficiency. On the other hand, export trade allows enterprises to expand their production and realize economies of scale. Simultaneously, to meet the product standards of importing countries and cope with fierce international competition, enterprises must raise their technological level, which helps improve their energy efficiency. We analyze the impact of import and export trade on the energy efficiency of China’s textile industry by building a simultaneous equation model. Import trade (Import) is a measure of “the proportion of imports relative to total industrial output value” of the textile industries of various provinces and cities. Similarly, export trade (Export) is a measure of “the proportion of exports relative to total industrial output value” of the textile industries of various provinces and cities. Table 5 shows the regression results for the influences of these two forms of trade on energy efficiency. The empirical results show that the foreign trade of China’s textile industry significantly and positively affects its energy efficiency. Compared with export trade, the import trade of the textile industry impacts energy efficiency more than does the export trade. This occurs mainly for the following reasons. First, import trade allows textile enterprises to introduce foreign advanced machinery and equipment, thus promoting energy efficiency. Second, import trade allows textile enterprises to directly learn foreign advanced technology and experience, which helps to reduce energy consumption and promote energy efficiency (Gao et al., 2010). The difference in impact between the import and export trades mainly reflects the current trade structure in China and the characteristics of the textile industry. Processing trade remains important, with labor-intensive products comprising a large proportion of total trade. The textile industry is labor intensive, and cheap labor remains important to the development of China’s textile industry. These factors limit the positive influence of the export trade on energy efficiency in the Chinese textile industry. In column (1) of Table 5, the import trade of the textile industry significantly and positively impacts energy efficiency at the 1% significance level. In column (2), we add regional and time virtual variables to control for the fixed effects of provinces and cities, as

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well as years. At this point, the impact of textile import trade on energy efficiency remains significant at the 1% significance level, and the impact coefficient is positive. Comparing columns (2) and (1), with and without controlling for fixed effects, respectively, it is found that under these two situations, the impact of textile import trade on energy efficiency is significantly positive at the 1% level. In column (3) of Table 5, in the absence of virtual variables controlling for the effects of provinces and cities, as well as years, the impact of textile exports on energy efficiency is significant at the 1% significance level and the impact coefficient is significantly positive. In column (4), we add regional and time virtual variables to control for the fixed effects of provinces and cities, as well as years. At this point, the impact of the textile export trade on energy efficiency remains positive at the 1% significance level. Comparing columns (4) and (3), with and without controlling for fixed effects, respectively, in both cases the impact of the textile export trade on energy efficiency is positive at the 1% significance level. Overall, the textile import trade influences energy efficiency more than the export trade. To verify our speculation about whether energy efficiency significantly impacts imports and exports in the textile industry, we take textile industry imports and exports as the dependent variable, respectively, and conduct an empirical study on the determining equation for imports and exports. The results are shown in Table 6. From Table 6, we find that in column (1), without adding virtual variables to control for the effects of provinces and cities, the impact of energy efficiency on textile industry imports is significant at the 1% significance level, and the influence coefficient is significantly positive. In column (2), we add regional and time virtual variables to control for the fixed effects of provinces and cities, as well as years. At this point, the impact of energy efficiency on textile industry imports remains positive at the 1% significance level. From column (3) in Table 6, it is found that in column (1), energy efficiency affects textile industry exports at the 1% significance level, without adding the dummy variables to control for the effects of provinces and years, and the coefficient of influence is significantly positive. In column (4) we add regional and time virtual variables to control for the fixed effects of provinces and cities, as well as years. At this point, the impact of energy efficiency on the export of textile industry exports remains significant at the 1% level, and the influence coefficient is positive. From Table 6, it can be seen that before controlling for the year and heterogeneity of provinces, or before we add regional and temporal dummy variables to control for the year and provincial heterogeneity, energy efficiency significantly and positively impacts textile industry imports and exports. The table also confirms our earlier hypothesis that textile imports and exports significantly and positively impact energy efficiency, which itself also significantly and positively impacts textile industry imports and exports. From the above research, we find that foreign trade significantly

Table 5 Analysis of estimation results for impact mechanism.

Import Export Ln R&D Str Ln EP Constant term Dummy_T Dummy_P Sample size

(1) TFEE

(2) TFEE

(3) TFEE

(4) TFEE

0.0047*** (5.93) e 0.1092*** (19.24) 0.0323*** (4.33) 0.0634 (0.88) 0.0795 (0.22) No No 532

0.0054** (2.39) e 0.2487*** (12.33) 0.0267*** (3.29) 0.1263* (1.78) 1.9478*** (5.61) Yes Yes 532

e 0.0010*** (5.76) 0.1001*** (15.55) 0.0293*** (3.83) 0.0637 (0.87) 0.0166 (0.05) No No 532

e 0.0011*** (4.44) 0.2549*** (12.85) 0.0220*** (2.74) 0.1160* (1.68) 1.9245*** (5.68) Yes Yes 532

Note: the estimate of the t value is in brackets; "*", "* *" and "* * *" represent significance levels of 10%, 5% and 1%, respectively.

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

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Table 6 Impact of total factor energy efficiency on textile industry imports and exports.

TFEE Ln R&D Str Ln EP Constant term Dummy_T Dummy_P Sample size

(1) Import

(2) Import

(3) Export

(4) Export

1.1871*** (4.77) 0.5052*** (12.33) 0.1282*** (3.13) 1.9687*** (5.39) 6.7737*** (3.65) No No 532

0.1738* (1.88) 0.0128 (0.32) 0.0593*** (4.36) 0.1302 (0.95) 2.2449*** (3.27) Yes Yes 532

2.6604*** (4.70) 0.7338*** (8.36) 0.1616** (2.14) 0.9545 (1.28) 2.3343 (0.62) No No 532

8.5411*** (19.04) 0.1763 (0.82) 0.0468 (0.73) 1.5161* (1.81) 3.3595 (0.77) Yes Yes 532

Note: the estimate of the t value is in brackets; "*", "* *" and "* * *" represent significance levels of 10%, 5% and 1%, respectively.

promotes energy efficiency improvement in the textile industry. Moreover, this promotion effect is achieved through two different mechanisms for imports and exports, with each exerting slightly different impacts on energy efficiency. Specifically, textile imports impact energy efficiency mainly through knowledge spillover. On the one hand, domestic enterprises save on independent R&D costs, in terms of both time and money, by importing advanced production equipment and intermediate products from abroad. This occurs because such imports leave domestic enterprises with more resources to improve their technology level and develop equipment to realize energy savings and emissions reduction, thus directly improving the energy efficiency of the importing countries. On the other hand, imported production equipment and intermediate products contain innovative knowledge and advanced technology related to overseas textile production, which domestic textile enterprises can imitate and learn from. In the long term, the import trade of the textile industry significantly and positively affects the energy efficiency of the importing countries. Meanwhile, textile exports impact energy efficiency mainly through learning by exporting. On the one hand, exporting exposes domestic textile enterprises to opportunities for contact with advanced international production technology and associated learning opportunities. On the other hand, to meet their own demands in terms of textile price and quality, developed country clients provide their international suppliers with professional guidance on innovation and production technologies. This guidance increases production efficiency and improves product quality in supplier countries, decreases production costs, and so promotes the upgrading of energy efficiency in importing countries. 5. Conclusions and suggestions Since the beginning of the 21st century, China’s textile exports have increased rapidly, from 10.3% of total global exports in 2000 to 37.07% in 2013. China has become the world’s largest exporter of textiles, and naturally its textile industry is internationally competitive. In this manuscript, panel data are used to investigate the impact of foreign trade on the energy efficiency of China’s textile industry, as well as associated mechanisms. The main conclusions are as follows: First, there may be a two-way causal relationship between the textile industry’s foreign trade and energy efficiency, resulting in problems of endogeneity. Second, the research results prove that R&D investment significantly and positively impact the energy efficiency of China’s textile industry. To some extent, R&D investment reflects level of technological innovation, while R&D investment helps to improve energy efficiency. Third, the energy prices significantly impact the energy efficiency of China’s textile industry. Increasing energy prices can effectively encourage enterprises to save energy, reduce energy consumption, reduce production costs, and ultimately promote energy efficiency. Furthermore, the

empirical results show that ownership structure significantly and negatively impacts energy efficiency. Rather than improving the energy efficiency of the textile industry, increased nationalization will have precisely the opposite effect. We compare the empirical results with Lin and Liu (2015) and find that there is still a positive feedback between foreign trade and energy environment efficiency. Different from the conclusion of this paper, Lin and Liu (2015) show that the impacts of the two mechanisms of import pathways and export pathways on energy environment efficiency are not much different. Lin and Zhao (2016) measured the energy efficiency and rebound effects of the textile industry. It has verified the rebound effect of the textile industry, but improving the energy efficiency of the textile industry is still reflected in energy conservation. Gao et al. (2010) argue that technology spillovers in international trade can promote technological advancement and total factor productivity in a country, thereby enabling energy efficiency through technological advancement. This is consistent with the conclusion of this study. In order to effectively improve the energy efficiency of textile industry, based on the empirical results, we put forward relevant countermeasures and suggestions. The first, increasing the degree of nationalization is not conducive to improving the energy efficiency of textile industry. The government needs to further the reform of state-owned enterprises and encourage private enterprises to participate in the reform. The second, it is necessary to promote energy price reforms, ensure that energy prices truly reflect resource scarcity, and achieve marketization of energy supply and demand as soon as possible. The third, the government and enterprises must invest more in research and development, devote more resources to improve energy efficiency, develop more advanced production facilities, and manage more efficiently. The forth, in the future, China should gradually move away from processing trade that relies on cheap labor, further open its textile industry, promote exports, and encourage both the study of advanced technologies from abroad and the import of advanced intermediate products and production equipment. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The paper is supported by Report Series from Ministry of Education of China (No.10JBG013), China National Social Science Fund (No. 17AZD013), China Postdoctoral Science Fund (No. 2018M631376) and Beijing Municipal Social Science Fund Research Base Project (No. 18JDYJB022).

Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878

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Please cite this article as: Zhao, H., Lin, B., Impact of foreign trade on energy efficiency in China’s textile industry, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.118878