Effects of the EU Emission Trading Scheme on the international competitiveness of pulp-and-paper industry

Forest Policy and Economics 109 (2019) 102021

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Effects of the EU Emission Trading Scheme on the international competitiveness of pulp-and-paper industry Weiming Lina, Jianling Chenb, Yi Zhengc, Yongwu Daic,

T

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a

College of Jinshan, Fujian Agriculture and Forestry University, Fuzhou 350002, China College of Economics, Fujian Agriculture and Forestry University, Fuzhou 350002, China c College of Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China b

ARTICLE INFO

ABSTRACT

Keywords: Emission Trading Scheme International competitiveness Direct and indirect effects Pulp-and-paper industry Generalized method of moments

Unlike the previous literature focusing only on the direct effect of the European Union Emissions Trading Scheme (EU ETS) on the international competitiveness of a regulated industry, this study tackles both the direct and indirect effects. We designed an interactive item between the EU ETS dummy and the number of patent applications to represent the EU ETS's indirect effect. Then, based on the panel data of 42 countries' pulp-and-paper industry from 1998 to 2013, we conducted the test by using the system generalized method of moments to address the endogeneity problem. The results show that the EU ETS's direct effect is insignificant, while its indirect effect is significantly positive. That is, the EU ETS can bring positive effect by stimulating the pulp-and-paper making enterprises toward technological innovation. Our analysis further finds that this indirect effect changes from being insignificant in Phase I to be significantly positive in Phase II and Phase III as well as gradually become larger, suggesting that the ETS-induced innovation gradually became more prominent. The above findings provide convincing new evidence that the ETS's “innovative compensation effect” is greater than its cost-effect.

1. Introduction Emissions Trading Scheme (ETS) has been commonly viewed as a cost-effective climate change mitigation mechanism (Shinkuma and Sugeta, 2016). There are now > 20 ETS platforms across Europe, North America, South America, and Asia, and it appears that more will come into being as the efforts to mitigate climate change intensify (World Bank, 2014). However, policymakers and corporate managers concern that an ETS may have adverse effects on business competitiveness (Boutabba and Lardic, 2017), due to higher cost compared to international rivals from countries without an ETS or with less stringent emission regulations. As such, the competitiveness effect of an ETS has attracted broad policy and research attention. Many previous studies have revealed that an ETS's competitiveness effect is negligible (e.g., Allevi et al., 2018). Still, they have not put to rest the anxiety of policymakers and business managers. Moreover, our careful review of the literature suggests that almost all of the previous works have focused on an ETS's direct effect and thus ignored the offsetting effect of moderating forces on the relationship between the adoption of an ETS and the business competitiveness, i.e., the indirect effect. A possible case is that a potentially negative direct effect of ETS on regulated industries' international competitiveness may

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be mitigated if its indirect effect is positive. As a consequence, there is a risk of overemphasizing the ETS's negative effect on business competitiveness (Liang et al., 2007). If we are able to provide more comprehensive and convincing evidence that an ETS can stimulate technical innovation that will benefit business competitiveness over the longer term, then it will serve as a positive signal to encourage regional, national, and international organizations to continue their efforts of building and expanding emission trading systems. Therefore, the objective of this study is to assess the direct and indirect effect of the EU ETS on business competitiveness in an integrated framework, by using dynamic models of panel data of the pulp-andpaper industry covering 42 countries and 16 years (1998–2013). We used patent applications as a proxy for technological innovation and bilateral net exports to reflect the international competitiveness of pulpand-paper industry. Our analysis suggests that the EU ETS's direct effect is insignificant but the indirect effect is significantly positive. That is, there is indeed evidence of EU ETS-induced technological innovation positively improving the international competitiveness of pulp-andpaper industry. Further exploration shows that this indirect effect gradually rises from Phase I to Phase II and then to Phase III of the EU ETS. The conclusions drawn from this study would be of broad significance for two reasons. One is that the EU ETS is the first and largest

Corresponding author. E-mail address: [email protected] (Y. Dai).

https://doi.org/10.1016/j.forpol.2019.102021 Received 2 April 2019; Received in revised form 4 September 2019; Accepted 4 September 2019 Available online 22 October 2019 1389-9341/ © 2019 Elsevier B.V. All rights reserved.

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international system for trading allowances of greenhouse gas emissions (Abrell et al., 2017). Another is that pulp-and-paper industry accounts for 8.53% of all EU ETS-regulated installations in 2005, exceeding the average of the 28 industries covered by the EU ETS. In addition, the novelty of this work lies in its ability to provide an improved understanding of role of the ETS by going beyond the direct effect on competitiveness, because the indirect effect of the ETS can provide further information about the underlying mechanisms by which it affects a regulated industry's international competitiveness. Thus, our work also implies that technological change can be one of the primary factors for solving long-term environmental problems. The remainder of this paper is organized as follows. Section 2 provides a brief review of the literature. Section 3 elaborates the theoretical basis and selects variables, and describes the context of the pulpand-paper industry and our data. Section 4 presents our econometric model. Section 5 reports the empirical results. Discussion and conclusions follow in Section 6.

that the ETS can promote the development of cost-reducing technological innovation but that industries also incur opportunity costs because investments in technological innovation could have been used for other more productive projects (Lin et al., 2017). Obviously, there are a larger number of studies that have identified a negative or null effect of the ETS on business competitiveness than that showing a positive effect. After a careful and critical review of the literature, however, we have found that almost all of the studies ignored the mitigating role played by the moderating forces, especially that of technological innovation, on the ETS's competitiveness effect. Without taking into account the indirect effect, therefore, the preliminary evidence reported in the previous studies may run the risk of misjudging the ETS's competitiveness effect. As a countering example, by adding separately an input subsidy, a production subsidy, and an export rebate in a computable general equilibrium model, Bednar-Friedl et al. (2012) discovered that the ETS could increase the international competitiveness of the regulated industries. That means the negative direct effect of the EU ETS can be mitigated or even completely offset if the moderating effect is significantly positive. Thus, it is essential to incorporate the role of technological innovation into the assessment of the EU ETS' impact on international business competitiveness. Technological innovation can be a significant mediating force. First, most, if not all, scholars, including those associated with the PHH, as well as those with the PH and the FEH, acknowledge the strategic function of technological innovation for enhancing the international competitiveness of the regulated industry. The PHH insists that ETS-stimulated technological innovation cannot overcome ETS-induced costs, whereas the PH argues otherwise. The FEH focuses on the role of overall technological innovation, rather than on innovation stimulated by an ETS only. So, the essence of the dispute between the PHH and the PH centres on whether an ETS can stimulate timely and effective technological innovation and whether the ETS-stimulated innovation can offset the adverse impacts of the induced costs. As such, only when the ETS's indirect effect is considered can the complete impact of the ETS on the international competitiveness of the regulated industries be determined. As a matter of fact, the results reported by Meleo (2014), Borghesi et al. (2015), Calel and Dechezleprêtre (2016), Larsson (2017), Marcantonini et al. (2017), and Cui et al. (2018) indicated that by putting a price on carbon, an ETS could promote (low-carbon) technological innovation. Therefore, it is not only meaningful but also imperative to assess the indirect effect of the EU ETS on business competitiveness by testing whether or not it has stimulated the regulated industries toward technological innovation and how the potential technological innovation has affected business competitiveness. Despite the fact that such studies can provide new evidence for quantifying the competitiveness effect of the EU ETS, unfortunately, there has been very little work on it. In this study, we assess the direct and indirect competitiveness effect of the EU ETS simultaneously, which can potentially make a valuable contribution to an improved and much- needed understanding of the ETS' impact.

2. Literature review Since the inception of the EU ETS in 2005, a considerable amount of research has been conducted to assess its effect on the international competitiveness of the regulated industries. Depending on the potential effects, the findings of the current research fall into one of the following three categories. First, using various simulating schemes, several studies found a significantly negative effect. For instance, Hourcade and Crassous (2008), Abrell et al. (2017), and Allevi et al. (2018) showed that the ETS increased the production costs of energy-intensive enterprises by encouraging them to expand their operations in countries without an ETS, thus causing production losses in energy-intensive industries inside EU. The analyses conducted by the World Bank (2007), Demailly and Quirion (2008), Costantini and Mazzanti (2012), and Boutabba and Lardic (2017) also indicated that the ETS had a negative effect on the international competitiveness of the iron and steel and other emissionintensive sectors. These findings favour the Pollution Heaven Hypothesis (PHH), which states that the ETS can adversely affect the international competitiveness of regulated industries by causing their costs to increase and/or production to drop (Oberndorfer and Rennings, 2007). Meanwhile, Löfgren et al. (2013) demonstrated that the EU ETS had only a slight effect on the trade competitiveness of countries implementing the ETS. Other studies on the industries of aviation (Anger and Oberndorfer, 2008), aluminium (Reinaud, 2008), oil refinery (Lacombe, 2008), steel (Ellerman et al., 2010), power generation (Jaraitė and Di Maria, 2012), steel (Branger et al., 2016), pulp-andpaper (Meleo, 2014) similarly concluded that the ETS did not lead to a loss of international competitiveness. The investigation conducted by the International Energy Agency showed that the EU ETS did not cause observable carbon leakages, at least in such heavy industries as steel, cement, and aluminium making. Genovese and Tvinnereim (2018) further argued that some high-emission sectors are not likely to relocate, especially those that heavily rely on territorial constraints such as infrastructure and proximity to customers. These studies support the Factor Endowment Hypothesis (FEH), which suggests that the ETS should have no significant competitiveness effect, as the comparative advantage of a country's exports depends primarily on factor endowment and production technology (Antweiler et al., 2001). Moreover, by simulating the effect of the EU ETS on industrial competitiveness at the levels of 15€/t CO2 and 30€/t CO2, Smale et al. (2006) revealed a significantly positive effect on revenues of the cement, printing, dying, petroleum and steel industries. Such an effect is consistent with the Porter Hypothesis (PH), which suggests that the ETS can stimulate the regulated enterprises toward technological innovation to improve the efficiency of energy utilization, thus reducing carbon emissions and ETS-complying costs. Porter and van der Linde (1995) used the Innovative Compensation Effect, i.e., indirect effect, to explain this proposition. Notably, some scholars disagree to the PH, holding

3. Research design Our basic proposition is that the international competitiveness is determined by traditional influencing factors such as labor and capital, among other things, emission regulation as reflected in the enactment of an ETS and the likely technological innovation induced by it over time. Accordingly, this section will elaborate the measurement of international competitiveness and its potential influencing factors, including proxy variables for the EU ETS and its indirect effect, among others, before proceeding to the empirical analysis. 3.1. Measuring international competitiveness Measuring international competitiveness of pulp-and-paper industry based on export volume of pulp or paper products can smooth the impact of price fluctuation and exchange rates fluctuation, but the data are 2

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difficult to collect. Hence, we used bilateral net exports (NETEX) to capture the change in international competitiveness of pulp-and-paper industry based on value of imports and exports. First, the use of bilateral net exports can deal with the potential bias caused by focusing on either imports or exports. For example, France–China bilateral exports of pulp and paper products rose from $30 million USD in 1998 to $145 million USD in 2014, and the value of France–China bilateral imports of these products also increased from $36 million USD in 1998 to $296 million USD in 2014. Judged on its exports, the French pulp-and-paper industry appears to have boosted its competitive edge over its Chinese counterpart. However, when imports are taken into account, the bilateral net exports decrease from $-6 million USD in 1998 to $-151 million USD in 2014 (UN Comtrade 2017). This illustrates that bilateral net exports can account for changes in both imports and domestic markets. Likewise, the confounding effect of abnormal events, such as an economic crisis, can be mitigated by examining bilateral net exports. For example, the 2008 financial crisis weakened the global economy, limiting the growth of pulp and paper exports. Meanwhile, it also lowered the growth of pulp and paper imports. Therefore, the bilateral net exports can net out fluctuations embedded in exports or imports by combining the trends of both exports and imports, which can more accurately reflect of changes in the international competitiveness of pulp-and-paper industry. Also, differences in abatement efforts caused by the EU ETS may lead to shifts in trade through reduced consumption of carbon-intensive goods toward cheaper import substitutes or relocation of industrial production to regions with less stringent environmental regulations (Branger et al., 2016). If import decrease and/or business relocation occur, they will directly cause changes in bilateral net exports of ETS countries to non-ETS countries. Therefore, bilateral net exports can more adequately reflect the actual influence of the EU ETS on the competitiveness of carbon-intensive industries.

used as a measure of the effect of human capital on the international competitiveness of the industry; forest area (lnforest_diff), the quantity of labour force (lnlabour_diff), and per-capita fixed capital stock (lncapip_diff) were used to analyse how traditional factors affect the international competitiveness of the industry (Lin et al., 2017). Porter (1990) noted that the volume of domestic demand and the pickiness of domestic buyers can influence the international competitiveness of domestic enterprises by affecting their economies of scale and their investments in technological and product innovation. The success of a specific industry in a country often depends significantly on the presence of several supporting and related industries, and free competition on the domestic front can force enterprises to enhance operational efficiency, quality, and innovation levels to create and maintain an edge in international competition (Porter, 1990). Thus, following the steps taken by Lin et al. (2017), we used the differences in GDP (lngdp_diff), per-capita GDP (lngdpp_diff), and the trade competitiveness index of the papermaking machinery industry (machine_diff) to capture how the size of domestic demand, the pickiness of domestic buyers, and related supporting industries affect the international competitiveness of the pulpand-paper industry. Because the paper-making machinery industry is not included in the EU ETS, we need not to worry about its confounding effect on the pulp-and-paper industry's competitiveness from implementing the EU ETS on the development of paper-making machinery industry. The intensity of carbon emissions (intensity_diff) represents a country's dependence on fossil energy, which may affect energy costs and thus indirectly affect the international competitiveness of the pulp-and-paper industry (Aichele and Felbermayr, 2013). Multilateral trade resistance can reflect trade openness, trade costs, and distance between trade partners (e.g., whether a partner is a member of WTO and/or the EU, which reflects how difficult it is for a country to finalize trade partnerships). To consider this in the model, WTO member status, EU member status, bordering status, official language, and bilateral distance were used as variables and integrated into a composite indicator using the entropy weight method as a measure of multilateral trade resistance (mrs) reflecting trade openness and trade costs (Aichele and Felbermayr, 2013). As bilateral net exports were used as a dependent variable, any change in explanatory variables of exporters or importers might have an impact on bilateral net exports. Therefore, observed values of explanatory variables were represented by the difference between an exporter and importer (see Table 1 for details).

3.2. Proxies for the ETS and its effects The adoption of EU ETS can be viewed as the treatment of a natural experiment. So, we used a dummy variable to indicate the enactment of the ETS, with participating countries assigned a value of 1 since 2005 and non-participating countries assigned a value of 0. Given our attention on the bilateral trade with non-participating countries, country pairs included in the bilateral net exports were divided into two categories. The first category features a participating country trading with a non-participating country, and the second one features trading between non-participating countries. Under these circumstances, we let ets_diff be a treatment dummy that takes on a value of 1 for the first type of country pairs since 2005 and 0 for the second type of country pairs (see Table 1 for details). To be sure, all country pairs were assigned a value of 0 prior to 2005. The estimated coefficient of ets_diff would be used to judge the direction and significance of the EU ETS's direct effect. Then, we measured technological innovation induced by adopting the ETS by the number of patent applications, which can reflect the final output of R&D activities more directly in the pulp-and-paper industry than an input index like the R&D expenditure (Greenhalgh et al., 1994). Accordingly, patent_diff is the difference in patent applications between any country pair to reflect the potential variation in technological innovation. Therefore, we measured the indirect effect by an interactive term (etspatent_diff) between the ets_diff and patent_diff, similar to Preacher and Hayes (2004) and Lin et al. (2017). The estimated coefficient of that interactive term will be used to judge the direction and significance of indirect effect.

3.4. Data and style facts We took 42 countries that account for over 90% of the world's pulpand-paper exports in this study.1 In total, 12,464 observations were collected from 23 ETS countries and 19 non-ETS ones from 1998 to 2013, including 6992 (23 × 19 × 16) country pairs between ETS countries and non-ETS countries and 5472 (19 × 18 × 16) country pairs between non-ETS countries themselves. Data used to measure bilateral net exports and the trade competitiveness index of the paper-making machinery industry were drawn from the UN Comtrade database, including HS codes HS47 (paper pulp), HS48 (paper and paper products), HS8439 and HS8441 (pulp-and-paper machinery). Data on labour, gross fixed-asset 1 The 23 ETS countries include Austria, Belgium, Bulgaria, Czechoslovakia, Denmark, Finland, France, Germany, Great Britain, Hungary, Ireland, Italy, Lithuania, Luxembourg, the Netherlands, Portugal, Poland, Romania, Slovakia, Slovenia, Spain, Sweden, and Switzerland. Switzerland had just initiated an independent ETS operation, which would then be docked with the EU ETS. Bulgaria, Lithuania, Poland, and Romania are developing countries at the time of the study, and the rest of the sample includes developed countries; Great Britain employed an independent ETS at the time of the study, but the EU ETS acknowledges Great Britain's emission reduction responsibilities, and so it is included. The 19 non-ETS countries include the United States, China, Canada, Brazil, Indonesia, Japan, Korea, Chile, Russia, Singapore, Turkey, Mexico, South Africa, India, Malaysia, the Ukraine, Columbia, Argentina, and Egypt.

3.3. Control variables According to the New Factor Theory of international trade, included in the production function of any traded good are such factor inputs as capital, unskilled and skilled manpower (human capital), and knowledge (Keesing, 1971). Years of schooling of labour force (labouredu_diff) was 3

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Table 1 Definitions and summary statistics of all variables. Symbol

Variable name

Description

NETEX ets_diff

Bilateral net exports ($10 million USD) Difference in emissions control

patent_diff

Difference in technological innovation (piece)

The difference between bilateral exports and bilateral imports of country j to country l Before 2005, 0 for every country pair. Since 2005, 0 for country pair that non-ETS country exporting non-ETS country; 1 for country pair that ETS country exporting non-ETS country (Patent applications from the pulp-and-paper industry for country j) − (Patent applications from the pulpand-paper industry for country l) Product of ets_diff and patent_diff (piece) (Log value of per-capita fixed capital stocks [gross fixed assets stocks divided by population] for country j) − (Log value of per-capita fixed capital stocks for country l) (Log value of labour-force's quantity for country j) − (Log value of labour-force's quantity for country l)

etspatent_diff lncapip_diff

tax_diff

Difference in the log value of per-capita fixed capital stocks Difference in the log value of labour-force's quantity Difference in the years of schooling of labour force (year) Difference in the log value of GDP Difference in the log value of per-capita GDP Difference in the log value of forest size Difference in the TC index of the pulp-and-paper machinery industry Difference in carbon emissions intensity (t/10 thousand people) Difference in carbon taxes

Mrs WTO EU Dist contig comlang

Multilateral trade resistance Fellow member of the WTO Fellow member of the EU Bilateral distance (km) Bordering status Official language status

lnlabour_diff labouredu_diff lngdp_diff lngdpp_diff lnforest_diff machine_diff intensity_diff

(Years of schooling of labour force for country j) − (Years of schooling of labour force for country l) (Log value of GDP for country j) − (Log value of GDP for country l) (Log value of per-capita GDP for country j) − (Log value of per-capita GDP for country l) (Log value of forest size for country j) − (Log value of forest size for country l) (TC index of the pulp-and-paper machinery industry for country j) − (TC index of the pulp-and-paper machinery industry for country l) (Carbon emissions intensity [total CO2 emissions divided by the population] for country j) − (Carbon emissions intensity for country l) 1 for matching groups of countries levying carbon taxes with countries employing no carbon taxes; 0 for matching groups of countries employing no carbon taxes Comprehensive value of WTO, EU, dist, contig, and comlang evaluated from the entropy-weight method 1 for countries j and l being members of the WTO; 0 if they are not 1 for countries j and l being members of the EU; 0 if they are not Bilateral distance between country j and country l 1 for country j bordering country l; 0 for no shared border 1 for country j using the same official language as country l; 0 for not speaking the same official language

Note: We restrict our attention to exports to non-ETS countries, i.e., country j includes both ETS and non-ETS countries whereas country l includes only non-ETS countries. TC is an abbreviation of the trade competitiveness. Due to the observed values of etspatent_diff equal 0 in year 1998–2004, the average value of etspatent_diff is less than that of NETEX in year 1998–2013.

As showed in Fig. 2, a state of continuous fluctuation can be seen in average value of patent_diff of ETS country to non-ETS country (i.e. patents applied by ETS countries cyclically minus that of non-ETS countries) during 1998–2013. It declined in 2005 and 2006 compared with 2004, and another decline occurred in 2009 after a brief period of increase during 2006–2009 and then during 2010–2013. That is, the incremental gain is the normality for patent_diff between ETS country and non-ETS country in 2005–2013. Follow-up empirical investigation will test whether this normality induces a positive impact on the international competitiveness of the pulp-and-paper industry in ETS countries. The average value of patent_diff between two nonETS countries is zero every year, because the patent_diff of any two non-EST countries appears twice and their values are mutual offset. For that, the timeline of this average value is not shown.

formation, GDP, per-capita GDP, forest area, and carbon emissions were taken from World Development Indicators database released by the World Bank. EU membership status is confirmed from the EU website. Data for patent applications were obtained from the OECD database (https://stats.oecd.org/), including International Patent Classification codes of B31 (patents for paper making and paper processing) and D21 (patents for paper making), their directory position on the web-page is as follows: “Science, Technology and Patents—Patents Statistics—Patents by technology—Patents by IPC”. Geographic distance, official language, and bordering status data are taken from the CEPII database. It is worth noting the descriptive trends in the measured bilateral net exports (NETEX) over the period. Two clear patterns emerge from those trends (Fig. 1). First, the in NETEX of ETS country to non-ETS country was always greater than that between non-ETS countries during 1998–2013, indicating that international competitiveness of the pulpand-paper industry in ETS country performed better than that between non-ETS countries even before implementing the EU ETS. Second, the former one shows a relatively stable upward trend while a state of continuous fluctuation can be seen in the latter after 2005, which presages that the pulp-and-paper industry in the ETS countries has experienced systematically a more stable growth in international competitiveness compared with non-ETS countries. This preliminary evidence, however, should be validated by econometric analysis. During 1998 to 2013, the total and average number of patents filed by ETS countries in pulp-and-paper industry were larger than that of non-ETS countries. In addition, the Top 10 among ETS-countries were Germany (11270), Finland (6837), Sweden (3228), France (1861), Italy (1645), Switzerland (1596), United Kingdom (1417), Netherlands (915), Denmark (336), and Spain (297), while Top 5 non-ETS countries were United States (17756), Japan (4200), Canada (1023), China (346), Korea (328) and Brazil (146). The number in brackets were the total patent applications from 1998 to 2013, and the unit is piece. Obviously, top 10 in the world were the United States, Germany, Finland, Japan, Sweden, France, Italy, Switzerland, the United Kingdom, and Canada, there were only three non-ETS countries.

4. Empirical model Since an enterprise's trade behaviour exhibits inertia, causing the trade of the previous period to have a significant effect on the trade of the current period (Lin et al., 2017). However, a static panel data model cannot reflect these dynamic attributes, and the omission of time lags in bilateral net exports can result in biases, creating deviations and inconsistent estimated values (Marrero, 2010). Based on Marrero's (2010) method, the first-order lag value of bilateral net exports (NETEXt-1) was added as a right-hand-side variable to reflect its dynamics. A dynamic panel data model was established as follows:

NETEXljt =

+ NETEXljt

1

+ ets_diff ljt + etspatent_diff ljt + X jtl + µjl +

l jt

(1) where, as noted, NETEX represents bilateral net exports as a measure of the international competitiveness of the pulp-and-paper industry, which is defined as the difference between bilateral exports and imports between country j and country l; ets_diff is the difference in emissions control among country pairs, with ∂ being used to capture the EU ETS's 4

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Fig. 1. Trends in the average bilateral net exports (Unit: $10 million).

direct effect; etspatent_diff is the interactive term between ets_diff and patent_diff for measuring the ETS's indirect effect on the NETEX (see Table 1 for details), with β being the coefficient of etspatent_diff on the NETEX; X refers to other control variables affecting the NETEX, with σ being the corresponding parameters to be estimated; α is the intercept term; η is the coefficient of NETEXt-1 on the NETEX; μ denotes individual effect; and ε denotes the residuals. Following Preacher and Hayes (2004), who proposed a well-known procedure for estimating the indirect effects in this kind of mediation models, we need only to test the significance of the β; the correlations between ets_diff and NETEX, ets_diff and patent_diff, and patent_diff and NETEX would rarely be relevant to establishing the mediation. That is, if the β is significantly positive, we can claim that the EU ETS can stimulate pulp-and-paper enterprises toward technological innovation and ETS-stimulated innovation thereby can improve their business competitiveness against international competitors, which supports the PH. Whereas a

significantly negative β supports the PHH and a neutral β supports the FEH. Notably, to draw convincing conclusions, we need to determine the actual cause-and-effect relationship between the etspatent_diff (or ets_diff) and pulp-and-paper industry's NETEX. But the endogenity problems induced by omitted variable bias and two-way causality make it difficult to determine above cause-and-effect relationship. To solve these endogeneity problems, we estimate the Eq. (1) with the help of system GMM (the system Generalized Method of Moments) proposed by Arellano and Bover (1995) and Blundell and Bond (1998) which is one of the instrumental variables estimations (Baum et al., 2003). They integrated the first-differenced and level equations into an equation for GMM estimation. The benefits of doing that include four aspects: (1) erasing fixed effects by first differenced equation which can address omitted variable bias; (2) using lagged values of independent variables as the instrumental variables in the first differenced equations which can address two-way causality; (3) addressing weak instruments by

Fig. 2. Descriptive trends in average measures of patent_diff (Unit: piece). 5

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using lagged first differences of the variables as instrumental variables in the level equations; and (4) adopting the level equations to estimate the coefficients of time-independent variables. The reliability of GMM estimation depends on whether there is an autocorrelation between residual terms and whether the selected instrumental variables are valid (Arellano and Bond, 1991). To test for autocorrelations of a residual term, an AR(1) statistic is used wherein the residual terms difference sequence should be negative while its p-value should be < 0.05, whereas the p-value of the AR(2) statistic of the residual terms should be > 0.05. To determine whether problems of over-identification or of weak instrumental variables are involved, we apply the sargan test, which requires the p-value of the sargan statistic to be > 0.05 to support the null hypothesis of the instrumental variables selected for modelling as valid. In addition, Roodman (2009) proposed three options for reducing the number of instrumental variables: (1) counting only up to q-order lags rather than all available lags for instrumental variables based on the number that are linear in T, (2) replacing the instrumental variables matrix of an expanding GMM style with an instrumental variable matrix with a collapsing style, or (3) combining the above two approaches for instrument containment (i.e., collapsing the instrumental variables and up to q-order lags for the instrumental variables). The third option was used in this study. Is it a coincidence that patent applications of the paper-making industry in the ETS countries have generally increased after 2005 when the ETS was implemented? Or, is there a pre-determined trend for paper-making enterprises in the ETS countries anticipating intensified technological innovation, given that the EU countries had ratified the Kyoto Protocol on May 31, 2002. To address the above concerns and reconfirm the causality between etspatent_diff (or ets_diff) and NETEX, we conducted two placebo tests in Section 5.2 below. Moreover, to further capture more policy-oriented results, the lag effects of the EU ETS and the moderating effects of technology stocks on the EU ETS as well as the competitiveness effects in different stages of the EU ETS would be examined in Section 5.3 below.

Table 2 Benchmark results and estimation results of placebo tests. Benchmark results ets_diff

0.413

etspatent_diff

0.002***

lngdp_diff lnpgdp_diff lnlabour_diff lnforest_diff intensity_diff labouredu_diff capital_diff machine_diff mrs NETEXt-1 _cons N time range Instr.martix Z AR(1) AR(2) sargan test

−1.132 2.197** 1.303 −0.058 −0.181⁎ 0.004 −0.819*** −1.327 −0.162 1.013*** 0.129 11,685 1998–2013 21 0.004 0.075 6.77 (0.238)

Assuming ETS started in 2003 ets_diff 03 ets_diff 04 etspatent_diff 03 etspatent_diff 04 lngdp_diff lnpgdp_diff lnlabour_diff lnforest_diff intensity_diff labouredu_diff capital_diff machine_diff mrs NETEXt-1 _cons N time range Instr.martix Z AR(1) AR(2) sargan test

0.264 0.005 −0.573 1.678 0.738 −0.043 −0.091 0.003 −0.952** −0.545 0.573 1.027*** 0.035 11,685 1998–2013 21 0.003 0.077 6.64(0.249)

Assuming ETS started in 2004 0.006 0.153 −0.504 1.607 0.646 −0.037 −0.080 0.002 −0.978** −0.393 0.622 1.027** 0.036 11,685 1998–2013 21 0.003 0.077 6.67 (0.247)

Note: ⁎, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively. Instr.martix Z is an abbreviation of the number of instrumental variables. IV is an abbreviation of instrumental variables.

5.2. Placebo tests To address concerns about pre-determined trend mentioned in Section 4, we conducted a placebo test following the practice of Abadie et al. (2010). We used 2003 and 2004, instead of 2005, as the time of treatment; that is, we assumed that the ETS had been implemented in 2003 and 2004. We re-tested the existence of indirect effects of the ETS by constructing two interactive terms (etspatent_diff03 and etspatent_diff04) between the ets_diff03 (ets_diff 04) dummy and patent_diff. Our benchmark results would remain if the two coefficients are not significant. Indeed, the coefficients of etspatent_diff03 (0.005) and etspatent_diff04 (0.153) are not significant (column (4) and (5) of Table 2), indicating that there is little interference of the unobservable systematic errors and that our benchmark results are robust.

5. Results We used system GMM with collapsing the IVs and 2–4 lags for the IVs (discussed earlier) to estimate the parameters in Eq. (1). The number of instrumental variables decreases significantly from 141 (before collapsing IVs) to 21, effectively addressing over-identification problems, as the p-value of the sargan statistic is 0.238. Moreover, the AR(1) value of the residual term is negative (p < .05) while the p-value of AR(2) is 0.075, suggesting that no weak instrumental variables are present. See the final four rows of Table 2. Therefore, the results estimated by our econometric approach are reliable. This approach was also used to conduct placebo tests and further tests, their results were presented in Tables 3 and 4 .

5.3. Further tests 5.3.1. Moderating effect of technology stocks Parrado et al. (2012) found that countries with more knowledge stocks could better react to a carbon tax. Learn from them, we examined the moderating effect of technology stocks. The specific steps are as follows. First, the average value of the total numbers of patent applications of the paper-making industry in the 23 ETS countries from 1998 to 2004 was calculated. Second, the countries whose patent applications exceed the average value were classified as ones with more technology stocks; otherwise, they were classified as countries with less technology stocks. Third, we matched all the countries using the same interactive item (etspatent_diff). Our results indicate that the ETS's indirect effect is significantly positive (0.003) in countries with more technology stocks, whereas it is insignificant in countries with less technology stocks [column (2) and (3) of Table 3]. This further illustrates that technology stocks allow mitigating the pressures of implementing the ETS on international competitiveness.

5.1. Benchmark results The estimated results of Eq. (1) are presented in Column (2) of Table 2. The coefficient of ets_diff is 0.413 but insignificant. Similar results appear in other tests in Tables 2∼4, respectively. This is consistent with some previous studies showing that the EU ETS has no significant impact on the international competitiveness of the pulp-and-paper industry (Löfgren et al., 2013; Meleo, 2014; Genovese and Tvinnereim, 2018). Meanwhile, the coefficient of etspatent_diff (0.002) is significant at the 99% confidence level, suggesting that the EU ETS significantly enhances the international competitiveness of the pulp-and-paper industry by inducing enterprises toward technological innovation. The fitted coefficient of etspatent_diff is relatively small; nevertheless, we should not dismiss the indirect competitiveness effect of the EU ETS, not the least because the dependent variable (NETEX) is the difference between bilateral exports and imports, measured in units of $10 million USD. Taking the pair “Germany–Argentina” as an example, the observed value of NETEX is 5.524 in 2013—a small change in it would reflect a large actual amount. Also, we find that the observed values of etspatent_diff are generally much larger than that of NETEX after 2005.

5.3.2. The indirect effects in different phases Joltreau and Sommerfeld (2018) noted that the literature focused on the EU ETS's stimulating effects on the innovation behavior of regulated firms in Phases I and II, when allowances were freely allocated and traded at very low prices. But Phase III has moved from free 6

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allocation of allowances to “50% allocation and 50% auction,” its stimulating effects on innovation could thus be different under the heightened stringency. Seeing that, we tested whether the EU ETS's indirect effects in Phase I (1998–2004 and 2005–2007), II (1998–2004 and 2008–2012), and III (1998–2004 and 2013). The results are presented in Column (4)–(6) of Table 3. It is found the coefficient of etspatent_diff to be 0.001 in Phase I and insignificant and to be 0.002 and 0.189 in Phase II and III, respectively, at the 95% confidence level. These results indicate that the EU ETS's indirect effect gradually become larger in the pulp-and-paper industry, and that over time the EU ETSstimulated technological innovation can better offset the costs induced by itself.

6. Discussion and conclusions This study has assessed the EU ETS's direct and indirect effects of the EU ETS on the international competitiveness of the pulp-and-paper industry. The indirect effect could have been derived from the induced technological innovation. We designed an interactive item between the EU ETS dummy and the number of patent applications in the pulp-andpaper industry to represent the EU ETS's indirect effect. To our knowledge, this is one of the first empirical studies to analyse the EU ETS's indirect effects on the international competitiveness of a regulated industry. Unlike the direct effect explored in the previous studies, investigating the indirect effect provides an opportunity to identify the

Table 3 Moderating effect of technology stocks and estimated results in the three phases.

ets_diff etspatent_diff lngdp_diff lnpgdp_diff lnlabour_diff lnforest_diff intensity_diff labouredu_diff lncapital_diff machine_diff mrs NETEXt-1 _cons N Instr.martix Z AR(1) AR(2) sargan test time range

ETS countries with more technology stocks

ETS countries with less technology stocks

ETS phase I (1998–2004 and 2005–2007)

ETS phase II (1998–2004 and 2008–2012)

ETS phase III (1998–2004 and 2013)

0.003⁎ 1.174 −1.170 2.548** 1.424 −0.081 −0.203 0.008 −1.031 −1.764 0.083 1.017*** 0.083 6840 21 0.005 0.077 7.86 (0.124) 1998–2013

−0.0001 0.287 −1.447 2.792** 1.672 −0.075 −0.170 0.003 −1.053*** −1.373 −0.135 1.015*** 0.098 9975 21 0.007 0.079 8.92 (0.112) 1998–2013

−0.189 0.001 −2.108** 3.043*** 2.273** −0.091 −0.208 0.002 −0.766*** −1.460 0.401 1.033*** 0.250 7011 19 0.000 0.105 13.20 (0.067)

0.909 0.002** −3.651*** 5.292*** 4.117** −0.156 −0.218 0.005 −0.824 −4.272 8.128 1.067*** −0.074 8569 21 0.001 0.269 7.43 (0.059)

1.202 0.189*** 0.153 3.179 −0.710 0.477*** 0.227 −0.006 −3.501*** 1.872 32.940 0.159 −2.617 4674 17 0.008 0.290 9.81 (0.081)

Note: ⁎, **, and *** denote significance at the 10%, 5%, and 1% levels, respectively.

5.3.3. Lag effect of the ETS We designed two scenarios to test the persistence of the EU ETS's positive indirect effect: (1) an interactive item between ets_diff's lagged value and patent_diff's level to reflect ETS-induced stimuli for technological innovation and corresponding effect on the international competitiveness; and (2) a lagged value for etspatent_diff is designed to reflect how ETS-stimulated technological innovations have continued to affect the international competitiveness. To ensure the suitability of the sample, a maximum of four lags was set for the two variables. Results are shown in Table 4. The coefficient of both ets_difft-1 × patent_diff and ets_difft-3 × patent_diff in scenario I are significantly positive (0.002), and the coefficient of etspatent_difft-1 and etspatent_difft-3 in scenario II are significantly positive (0.001), showing that indirect effect of the ETS can endure at for least 3 years. These findings suggest that the EU ETS's positive indirect effect will last over time, confirming the stability of indirect effect of the EU ETS.

internal mechanism by which the EU ETS might have affected the international competitiveness. It is found that the direct effect of the EU ETS on the international competitiveness of the pulp-and-paper industry is insignificant. However, the more important finding of this paper is that the ETS has significantly positive indirect effect by stimulating technological innovation, which is in line with the view of PH. This implies that the patented technology accumulation allowed firms to reduce the pressure of losing international competitiveness driven by implementing the ETS. Our placebo test has reinforced the validity of above results. Also, the positive indirect effect changes from being insignificant in Phase I to be significantly positive in Phase II and Phase III as well as gradually become larger, suggesting that the ETS-stimulated innovation gradually became more prominent. And the competitiveness of the regulated industry in the ETS countries would not be compromised if the ETS-induced costs could be offset by the ETS-stimulated technological innovation in a timely manner. Thus, the “innovative compensation effect”

Table 4 Estimated results of the ETS's lag effects. Scenario I Scenario II

ets_difft-1 × patent_diff 0.002*** etspatent_difft-1 0.001**

ets_difft-2 × patent_diff 0.001 etspatent_difft-2 0.0004

ets_difft-3 × patent_diff 0.002⁎ etspatent_difft-3 0.001⁎

ets_difft-4 × patent_diff −0.004 etspatent_difft-4 −0.00002

Note: ⁎, ** and *** denote significance at the 10%, 5%, and 1% levels, respectively. Results of the 8 models are summarized with only test outcomes of the key explanatory variable. Detailed reports are available from lead author.

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of the ETS may be more significant than its cost effect (Zhang et al., 2016). Some scholars have argued that over-allocation of free emission allowance is a major cause of the EU ETS's positive effect on international competitiveness (Ellerman et al., 2010), as over-allocation helps ETS-regulated firms sell excessive allowances for additional profits. However, we can hardly agree with this viewpoint. According to data from the EU ETS Data Viewer run by the European Commission, verified emissions of pulp-and-paper industry in all ETS countries were below their free allowances in 2005–2014. Taking the year 2005 for example, the mean of pulp-and-paper installations' over-allocation was 9473 tCO2/year (the total over-allocation being 8458945 tCO2 and 893 installations being covered). Assuming that the allowances could be sold out at a price of €22/tCO2 (the price of allowances fluctuating around this level after the middle of 2005), every installation would receive €208,406. This income constitutes only a tiny fraction of a large-scale enterprise's operating revenue and is hard to take an obviously positive effect on regulated firms' competitiveness. The fact that the EU ETS's direct effect is insignificant is a case in point. So, let's go back to the stimulating effect of the ETS on technological innovation. Our confidence in the EU ETS's positive indirect effect on the international competitiveness of the pulp-and-paper industry is based on two findings. First, the impetus for the EU ETS to stimulate technological innovation has emerged. As noted earlier, Calel and Dechezleprêtre (2016) and Meleo (2014) have shown that the ETS could stimulate regulated enterprises or industries to seek (low-carbon) technological innovation or to introduce green-investment portfolios such as energyefficient technologies or processes, energy gasification technologies, and biomass energy technologies among others to reduce carbon emissions and to relieve pressures from carbon-emission controls. In addition, knowledge-spillover effects from ETS-regulated and non-regulated industries may increase the low-carbon technology output of pulp-andpaper industry, helping them reduce carbon-emissions (Cohen and Miller, 2015). Second, stimulating effect of the EU ETS on technological innovation will be stable, because regulated enterprises have been required to monitor CO2 emissions and report about carbon abatement costs in consolidated financial statements. Moreover, as the media and public become more involved with climate change issues, the ETS may be viewed as an important measure of market-oriented control over carbon emissions across the international community, and the ETS will continue to drive regulated enterprises to seek technological innovation to reduce carbon emissions. For instance, Gulbrandsen and Stenqvist (2013) found that the ETS increased the entire pulp and paper industry's awareness of climatic change issues in Sweden and Norway. Once the EU set its carbon-emission targets, the enterprises set internal carbon-reduction goals and implementation schedules. Finally, regardless of whether ETS-induced pressures are strong, technological innovation is always a key intermediary factor leading to a positive effect of the ETS. Correspondingly, regulated enterprises would be driven to invest in low-carbon technologies and production processes and to explore new energy sources. To this end, governments should strengthen the accumulation of patented technology through creating a set of supporting policies and operational mechanisms that encourage enterprises to intensify technical innovation. Therefore, revenues generated from auctioning carbon emissions allowances and from fines on regulated enterprises for excessive carbon emissions can be used to subsidize enterprises in improving their technical capabilities (Río, 2017). They can also be used to provide technical guidance and training for enterprises (Engels, 2009). Further, governments should establish low-carbon consumption markets to ensure that enterprises can obtain the economic benefits of realizing carbon reduction by means of technological innovation (Lin et al., 2017). Additionally, governments should encourage enterprises to voluntarily seek technological innovation that realize carbon reductions through the marketoriented forces of economic interests and spontaneous environmental protection (Meleo, 2014). Higher rate of allocation by auctioning and

higher carbon price are important incentives for enterprises to invest in new (low-carbon) technologies (EU Commission, 2014). However, this study has some shortcomings. First, due to the limitations of our data, we could not cover all the factors that may affect the international competitiveness of the pulp and paper industry. Fortunately, the system GMM can mitigate generating estimation bias resulting from omitting heterogeneous variables to ensure the validity of estimated results (see Section 4 for details). Second, the pulp and paper industry covers a variety of production technologies, products, and raw materials. For example, while chemical pulping technologies are not reliant on energy supplies, mechanical pulping technologies are reliant on significant external supplies of energy. So, further research will investigate the heterogeneity of the EU ETS's effects on the international competitiveness of different paper products based on the firm level data. Acknowledgements This work is supported by the National Natural Science Foundation of China [71703024], the Outstanding Young Scientists Program of Fujian Agriculture and Forestry University [xjq201733], and Innovation and Entrepreneurship Training Program for College Students (201814046002). References Abadie, A., Diamond, A., Hainmueller, J., 2010. Synthetic control methods for comparative case studies: estimating the effect of california’s tobacco control program. J. Am. Stat. Assoc. 105, 493–505. Abrell, J., Rausch, S., Yonezawa, H., 2017. Higher price, lower costs? minimum prices in the eu emissions trading scheme. Working Paper of Center of Economic Research at ETH Zurich 16, 243. Aichele, R., Felbermayr, G., 2013. Estimating the effects of Kyoto on bilateral trade flows using matching econometrics. World Econ. 36 (3), 303–330. Allevi, E., Oggioni, G., Riccardi, R., et al., 2018. An equilibrium model for the cement sector: EU-ETS analysis with power contracts. Ann. Oper. Res. 255 (1–2), 1–31. Anger, N., Oberndorfer, U., 2008. Firm performance and employment in the EU emissions trading scheme: an empirical assessment for Germany. Energy Policy 36 (1), 12–22. Antweiler, W., Copeland, B.R., Taylor, M.S., 2001. Is free trade good for the environment? Am. Econ. Rev. 91 (4), 877–908. Arellano, M., Bond, S., 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58 (2), 277–297. Arellano, M., Bover, O., 1995. Another look at the instrumental variable estimation of error-components models. J. Econ. 68 (1), 29–51. Baum, C.F., Schaffer, M.E., Stillman, S., 2003. Instrumental variables and GMM: estimation and testing. Stata J. 3 (1), 1–31. Bednar-Friedl, B., Kulmer, V., Schinko, T., 2012. The effectiveness of anti-leakage policies in the European union: results for Austria. Empirica 39 (2), 233–260. Blundell, R., Bond, S., 1998. Initial conditions and moment restrictions in dynamic panel data models. J. Econ. 87 (1), 115–143. Borghesi, S., Cainelli, G., Mazzanti, M., 2015. Linking emission trading to environmental innovation: evidence from the Italian manufacturing industry. Res. Policy 44 (3), 669–683. Boutabba, M.A., Lardic, S., 2017. EU emissions trading scheme, competitiveness and carbon leakage: new evidence from cement and steel industries. Ann. Oper. Res. 255 (1), 1–15. Branger, F., Quirion, P., Chevallier, J., 2016. Carbon leakage and competitiveness of cement and steel industries under the EU ETS: much ado about nothing. Energy J. 37, 109–135. Calel, R., Dechezleprêtre, A., 2016. Environmental policy and directed technological change: evidence from the European carbon market. Rev. Econ. Stat. 98 (1), 173–191. Cohen, S., Miller, A., 2015. Climate change 2011: a status report on US policy. Bull. At. Sci. 68 (1), 39–49. Costantini, V., Mazzanti, M., 2012. On the green and innovative side of trade competitiveness? The impact of environmental policies and innovation on EU exports. Res. Policy 41 (1), 132–153. Cui, J.B., Zhang, J.J., Zheng, Y., 2018. Carbon pricing induces innovation: evidence from China’s regional carbon market pilots. AEA Papers and Proceedings 108, 453–457. Demailly, D., Quirion, P., 2008. European emission trading scheme and competitiveness: a case study on the iron and steel industry. Energy Econ. 30 (4), 2009–2027. Ellerman, A.D., Convery, F.J., Perthuis, C., 2010. Pricing Carbon: The European Union Emissions Trading Scheme. Cambridge University Press, Cambridge. Engels, A., 2009. The European emissions trading scheme: an exploratory study of how companies learn to account for carbon. Acc. Organ. Soc. 34 (3–4), 488–498. EU Commission, 2014. Impact Assessment. (Staff Working Document, Brussels, 22.1.2014, SWD(2014) 17). Retrieved from. http://ec.europa.eu/clima/policies/ ets/reform/docs/swd_2014_17_en.pdf.

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