Energy Conservation and Emissions Reduction (ECER) has become a global goal, and many countries and organizations have conducted technological, engineering, policy and economic research to promote ECER in developing countries [1
]. In reality, ECER has become a crucial national policy in China [2
]. The Chinese regulation CPG (2006) [3
], which first proposed the ECER concept, set the goal that energy consumption per unit of GDP should be reduced by 20% and the total discharge of major pollutants should be reduced by 10% during the period of the 11thfive-year plan. CPG (2012) [4
] stated that by 2015, CO2
emissions per unit of GDP were required to be reduced by 17% from 2010 levels. According to the two above regulations, this paper considers ECER policies to be those focused on energy conservation, water conservation, SO2
emissions reduction and the comprehensive utilization of industrial solid waste.
As the largest developing country in the world, China has become the world’s largest consumer of energy and the world’s largest emitter of SO2
. Faced with the serious situation of ECER, dire energy supply shortages and increasing environmental pollution have made it challenging to maintain sustainable economic growth in China. If China wants to achieve sustainable economic development, ECER must be enforced [5
]. Even though a series of ECER policies and measures has been enacted since the late 1970s, the current state is still far from the desired goals outlined in the ECER objectives. Significant improvements are required to standardize systems and government policies for full ECER implementation. However, ECER cannot be achieved through market mechanisms alone [6
]. The government must enforce ECER implementation through the promulgation of effective policies. As ECER crosses multiple areas, ECER policies are beyond the boundaries of a single policy area or the responsibilities of an individual government agency. If a single policy is overemphasized, it may have detrimental effects on sustainable economic development. Therefore, to achieve better results, different policy means need to be coordinated when implementing ECER [7
According to traditional neoclassical economic theory, in order to achieve the goal of ECER, the implementation of ECER policies will inevitably bring negative impact on economic growth [8
]. However, according to the environmental Porter hypothesis, ECER policies will not increase the cost of production, but can stimulate business innovation, resulting in an increase in environmental technology efficiency and a further increase in corporate output [9
], which will eventually promote economic growth, leading to win-win results between ECER and economic growth [10
]. Based on the above two points of view, it is necessary for us to analyze which PMCs in ECER promote economic growth, and which PMCs in ECER hinder economic growth.
The rest of this paper is organized as follows. Section 2
presents the review of the present literature on policy coordination and ECER policies; Section 3
describes the methods of policy quantization, selected variables, modified model and methodology used in this paper. Section 4
reports on the results of a unit root test, cointegration test and stability test with estimated cointegration equation. Section 5
discusses the differences between usage rankings for policy means coordination (PMC) and consequent effect on economic growth. Section 6
presents the major conclusions and policy implications.
2. Literature Review
Present ECER policy studies in China have focused mainly on dealing with existing ECER policy implementation problems and solutions (Yuan et al. [11
]; Zhao et al. [12
]; Zhao and Ortolano [13
]), evaluating the effect and policy welfare in ECER policies (Fang et al. [14
]; Geng et al. [15
]; Price et al. [16
]), discussing the potential and actual costs of ECER under different policy scenarios, and determining optimum ECER implementation (Wang et al. [17
]; Hao et al. [18
]; Xi et al. [19
]), investigating the key factors, departments and areas that influence the effect of the ECER and making policy suggestions according to those factors (Zhu et al. [20
]; Fujii et al. [21
]; Zhang et al. [22
]), and outlining ECER policies in other countries and discussing the implications and references for China (Hu and Monroy [23
]; Tanaka [24
]; Yuan et al. [25
]). These studies have relied on discussions about object, content, significance, effect, or the future direction of one group or one class of ECER policies, and most took a logical and analytical approach. Because of policy uncertainty and subjectivity, imbalances in levels of political power, and supply and demand levels, some policies may not function coherently, thereby reducing the effectiveness of ECER. To date, however, there have been few studies on policy coordination in ECER field.
There are plenty of studies researching policy coordination from at least four various aspects: definition, necessity, functions and department coordination. About the definition of policy coordination, Mulford and Rogers [26
] defined policy coordination as a joint process between two or more organizations dealing with similar tasks which develops new rules or uses existing decision rules; Meijers and Stead [27
] saw policy coordination as the management of multiple policies from multiple functional areas, or the management of the multiple aspects of a single functional area; Rostaing [28
] stated that policy coordination has three coordination dimensions: “horizontal,” “vertical” and “time,” respectively; there are also two levels: “policy conformity” and “policy integration,” respectively. As for the necessity of policy coordination, Camarero and Tamarit [29
] postulated that policy coordination was required in situations in which there was conflict or competition between the policy objectives; Herzog [30
] examined the necessity of international policy coordination issues when dealing with common international problems; Hughes et al. [31
] pointed out that coordination between policy formulation and evaluation needs to be efficient and consistent. About the functions of policy coordination, Hoel [32
] concluded that positive policy coordination can be beneficial to improve policy implementation efficiency to achieve a Pareto optimal state; Lee et al. [7
] found that mixed policy coordination was more effective than using a single policy coordination approach; Effective policy coordination has been shown to achieve a greater level of performance [33
] and create greater benefits [34
]. As for department coordination, Iglesias et al. [35
] pointed out that governments need to coordinate different departments when formulating public policies to balance the possible conflicts of interest between them; Vakili and Khorsandi [36
] suggested that to improve policy implementation, policy coordination must be strengthened among the government, public welfare organizations, and nongovernment organizations; Huang et al. [37
] analyzed different organizations and frameworks for Chinese innovation policies, and emphasized that policy development also needed to be coordinated. These policy coordination studies have discussed the importance and superiority of policy coordination mainly from a policy effectiveness perspective, which has shown that policy coordination is of great importance to successful policy implementation and the achievement of social and economic goals. As governments begin to pay increasing attention to PMC, dealing with the coordination between the different policies means is likely to become one of the greatest policy formulation challenges in the future. However, they have focused less on policy content and the PMC effect on economic growth.
Starting from the method of quantitative content analysis of Krippendorff [38
], many policy studies have investigated policy content. Srebotnjak [39
] conducted a quantitative investigation into the environment policy objectives of Canada and Japan. Cools et al. [40
] conducted a quantitative analysis on Flemish transport policy means. Zhang et al. [41
] investigated Chinese industries to measure the institutional factors affecting enterprise ECER based on several indexes. These quantitative studies have further motivated the policy documents quantization in this paper. Once PMC in ECER field can be studied from a policy content perspective, the results could be used to guide ECER policy formulation in China. Therefore, it is imperative to focus on policy content when seeking to elaborate on PMC and the effect on economic growth, so that the findings can assist governments in using PMC to promote economic growth in the process of ECER.
Analysis models of institutional policy have been used in the academic studies. Eggertsson [42
] introduced institutional policy factors into the Cobb−Douglas production function and proposed a production function which included capital, labor and policy factors. Bjorn and Danny [43
] also introduced institutional policy factors into the Cobb−Douglas production function, and analyzed the effect of these factors on financial globalization. It can thus be seen that introducing policy factors into the Cobb−Douglas production function has become a normative research paradigm. PMC based on policy document quantization is introduced into the Cobb−Douglas production function, which will require some innovation.
As economic growth is still the main focus in China because of the current relatively low income per capita and the low urbanization rate, sustainable economic development requires the Chinese government to promote PMC vigorously in the ECER field. Institutional PMC has significant effects on economic growth in the process of implementing ECER. Clarifying how PMC in the ECER field affects economic growth can assist in ensuring constant improvements in the ECER policy system, while maintaining stable economic development. The negative effect of PMC on economic growth indicates the government’s economic cost when they use different PMC methods to promote ECER. Therefore, the implementation of an improved ECER at a less economic cost is a problem that needs to be urgently addressed by government officials, which is the primary motivation for this study.
5.1. Analysis of Cointegration Equation Results
shows the estimated cointegration equation results for the effect the administrative means and other means coordination had on economic growth. The controlling variables of capital stock (K
), employed people (L
) and technological advancement (T
) have significantly positive effects on GDP
. The coefficients of K
are the largest of all the variable coefficients, which is consistent with reality, illustrating that the estimated results are able to better explain the variables in a real-life situation. Specific statements can be concluded as follows.
The coordination between administrative means and fiscal and tax means (LnCAT) has a significantly negative effect on economic growth. The reason for this is that the government offered ECER subsidies or tax incentives, which inevitably reduces government investment in other areas, thereby somewhat reducing economic output. The government mainly uses the coordination of fiscal and tax means and administrative means, which infers excessive government intervention in the ECER guidance process, thereby reducing the guidance role of the fiscal and tax means, which is not conducive to economic growth.
The coordination between administrative means and financial means (LnCAF) has a significantly positive effect on economic growth, which indicates that as long as the government increases coordination between financial means and administrative means at the ECER policy level, both ECER policy objectives and economic growth can be realized at the same time.
The coordination between administrative means and personnel means (LnCAP
) has a significantly positive effect on economic growth. This denotes that increasing the penalties for offenders and increasing the cultivation or training of talent have important significance for the promotion of economic growth and ECER. At the same time, it also shows that at the ECER policy level, the government can realize greater ECER compliance while promoting economic growth by increasing the coordination between the personnel means and the administrative means. As the ECER pressure gradually increases, this should be the first choice for the Chinese government, which could promote ECER under the “Strategy of Strengthening the Country on Human Resource Development (2002)” [66
] to increase the coordination between the personnel means and administrative means.
The coordination between administrative means and guidance means (LnCAG) has a significantly negative effect on economic growth. This may be related to the imperfect use of the administrative means and guidance means by the Chinese government, which indicates that at the ECER policy level, the government pays a higher economic cost when promoting ECER through administrative means and guidance means coordination.
Through the above analysis, it can be seen that there are two kinds of effects on economic growth for different PMCs. For one thing, the administrative means and financial means coordination (LnCAF) and the administrative means and personnel means coordination (LnCAP) have significantly positive effects on economic growth, which demonstrate that when formulating ECER policy, the above two PMCs should be used to promote ECER and economic growth at the same time. For the other thing, the administrative means and fiscal and tax means coordination (LnCAT) and the administrative means and guidance means coordination (LnCAG) have significantly negative effects on economic growth, which show that when formulating ECER policy, the above two PMCs can be used to slow down economic growth so as to promote ECER.
In a word, these economic effects demonstrate two kinds of explanation for PMC. On one hand, the effect of the PMC on economic growth reflects the influence on economic development when a certain type of PMC is used by the government in ECER policy formulation. On the other hand, it also reflects the economic cost when the government uses more severe PMC to promote ECER.
5.2. Discussions on Usage Ranking and Policy Means Coordination (PMC) Effects
presents the difference between the usage rankings and effects on economic growth for PMC of ECER policies in China from 1978 to 2013. Based on Equation (1), the PMC degree for a policy is calculated by using the policy’s power score multiplied by the policy means score. The PMC degree per year is calculated by using the sum of the corresponding PMC degree. Therefore, the higher a policy’s PMC degree, the higher the Chinese government’s use of the PMC.
As shown in Table 9
, the administrative means together with the fiscal and tax means, financial means, personnel means and guidance means are coordinated differently, which demonstrate that the Chinese government has used various policy means to promote ECER by the method of PMC at the ECER policy level. Specifically, in the ECER policies from 1978 to 2013, the Chinese government frequently used the administrative means and guidance means coordination (LnCAG
), the administrative means and personnel means coordination (LnCAP
), and the administrative means and fiscal and tax means coordination (LnCAT
); however, use of the administrative means and financial means coordination (LnCAF
) was less frequent.
According to the comparisons between different economic effects and various usage rankings, several findings can be shown as follows. First, the administrative means and personnel means coordination (LnCAP
) has positive effects on economic growth, and is also frequently used by the government (the usage ranking of 2nd), which illustrates that training and educating people are the main means the Chinese government uses to deal with the implementation of the “Strategy of Developing the Country by Science and Education (1995)” [67
] and the “Strategy of Strengthening the Country on Human Resource Development (2002)” [66
Second, the administrative means and fiscal and tax means coordination (LnCAT) and the administrative means and guidance means coordination (LnCAG) have significant negative effects on economic growth, but the government tends to use these frequently (usage rankings of 3rd and 1st, respectively). The government’s excessive administrative intervention in ECER has hindered economic growth, especially when using fiscal and tax means or guidance means at the same time.
Third, while the administrative means and financial means coordination (LnCAF) significantly promoted economic growth, the use from the government is the least frequent (4th place). This fact illustrates that the Chinese government has not yet grasped the essence of the use of financial means when seeking to promote both ECER and economic growth, showing that the Chinese government has a certain blindness in their frequent use of PMC.
In summary, there are two ways to read the results of comparisons between different economic effects and various usage rankings. From the standpoint of policy means, first of all, the Chinese government is supposed to think about which kinds of policy means should be adopted since the economic growth development trends are expected to remain unchanged in China over the long term. Therefore, as pressure to both ensure consistent growth in the Chinese market economy and increase ECER compliance, the Chinese government is expected to increase the use of personnel means and especially financial means rather than rely on the use of other policy means in subsequent ECER policy formulation processes.
Second of all, when using PMC, the Chinese government should increase the administrative means and personnel means coordination (LnCAP), specifically the administrative means and financial means coordination (LnCAF), and reduce the administrative means and fiscal and tax means coordination (LnCAT) and especially the administrative means and guidance means coordination (LnCAG), so as to give full play to the basic role of economic leverage to ensure ECER compliance and extension.
6. Conclusions and Policy Implications
Based on identifying the Energy Conservation and Emissions Reduction (ECER) policies formulated by the central Chinese government from 1978 to 2013 and quantifying them from two dimensions of policy power and policy means, this paper develops policy means coordination(PMC) degrees as independent variables which are incorporated into a modified Cobb−Douglas production model, and then conducts a cointegration equation to discuss the economic growth effects of PMC in China while determining the cointegration relationship using the unit root, cointegration and stability tests. Furthermore, this paper analyzes the government’s PMC usage ranking in China based on the PMC in the ECER field. The main conclusions can be drawn as follows.
First of all, a long-term cointegration relationship is found among the eight variables of GDP, capital stock, employed people, technological advancement and coordination between administrative means and other means from 1978 to 2013. Enhancing capital stock, employed people and technological advancement is conducive to increasing GDP in China as expected in this paper, which illustrates the real-life situation that capital stock, employed people and technological advancement are three important factors affecting the growth of GDP.
Moreover, the effects of the different PMCs on economic growth are found to have significant discrepancies. For instance, the administrative means and financial means coordination and the administrative means and personnel means coordination have significant positive effects on economic growth, which have shown that the government can realize both ECER policy objectives and economic growth by increasing these two kinds of coordination. Meanwhile, the administrative means and fiscal and tax means coordination and the administrative means and guidance means coordination have significantly negative effects on economic growth because of the imperfect use of these two kinds of coordination.
Last but not least, the situation for each PMC is significantly different, thereby indicating that the usage ranking for each PMC is significantly different, also indicating that the Chinese government synthetically uses various policy means at the policy level to promote ECER by using PMC. In China’s ECER policies from 1978 to 2013, the Chinese government uses the administrative means and guidance means coordination, the administrative means and personnel means coordination and the administrative means and fiscal and tax means coordination most frequently, but uses the administrative means and financial means coordination less frequently.
From these conclusions and the situation of PMC, some important policy implications can be summarized as follows. First and foremost, the Chinese government should think about adopting different means cautiously when implementing ECER through policies. Specifically, financial means and personnel means should be given more focus than guidance means and fiscal and tax means because of their different economic effects.
Second, the Chinese government is expected to further increase the use of the administrative means and financial means coordination which contributes to economic growth due to the comparisons between usage ranking and economic effect when the Chinese government implements ECER by applying policy different means at the same time. It has been demonstrated that using administrative means and financial means coordination and administrative means and personnel means coordination is conducive to economic growth while implementing ECER if administrative means and financial means coordination is used less than the administrative means and personnel means coordination.
Finally, the Chinese government is supposed to reduce the use of administrative means and fiscal and tax means coordination and the administrative means and guidance means coordination which are harmful to economic growth because of the comparisons between usage ranking and economic effect while implementing ECER by applying different policy means together. The fact which brings up the conflicts is that the administrative means and fiscal and tax means coordination and the administrative means and guidance means coordination are not conducive to economic growth, especially when these two kinds of coordination are used more frequently than the administrative means and financial means coordination.
There are some limitations to this study, such as in the aspect of data feasibility. The data pool used in this paper mainly relied on national-level data, which may have a negative impact on the precision of the econometric results due to the lack of provincial-level data. Moreover, for the sake of brevity, this paper does not discuss the effect of all PMCs on economic growth. In the future, the authors will collect panel data at the provincial level to provide more explanations of the effects of other PMCs. This will be the focus of our later research, which will also use an econometric model.