What Motivates Local Sustainability Policy Action in China? The Case of Low-Carbon City Pilot Program

Abstract

An increasing volume of literature has sought to identify factors that motivate cities to pursue sustainability and adopt climate policies. However, most empirical studies were done in Western countries, where relatively high local autonomy and low pressure on industrial growth create conditions for spontaneous policy innovations in sustainability. This paper uses China’s Low-Carbon City Pilot Program as a case to investigate motivations for local sustainability actions in an authoritarian context. Our event history analyses confirm the effects of multi-level governance on local sustainability initiatives in China, particularly horizontal competition across jurisdictions, priorities and preferences of upper-level authorities, as well as local determinants including leadership, capacity, politics, and environmental stress. The findings contribute to the comparative urban governance scholarship by highlighting the unique feature of “experimentation under hierarchy” in shaping urban sustainability policymaking in China.

Keywords

sustainability multi-level governance low-carbon city policy experimentation China

Introduction

With the challenge of global climate change looming and international collaboration by national governments largely stalled, scholars and policymakers have turned to local cities as the groundbreaking forces in the pursuit of both local and global sustainability (Bulkeley and Broto 2013; Hoffman 2011). Spontaneous policy innovations by city governments are seen as an effective way to propel new policy ideas and identify policy solutions that address the global climate challenges while ensuring local co-benefits (Bulkeley and Broto 2013; Ostrom 2010). Past observations have shown greater initiatives of city governments in policy innovation in climate change mitigation and adaptation (Broto and Bulkeley 2013).

A growing scholarship has sought to understand the motivations and politics of urban climate policymaking (Hughes 2017; Yeganeh, McCoy, and Schenk 2020). Early studies have attributed variance in local commitment to climate protection to a set of internal determinants, such as government capacity, local leadership, community support and interest group influences, local demographics, and environmental risks (Krause 2011b; Lubell, Feiock, and Handy 2009; Wang 2013; Zahran et al. 2008a, 2008b). More recently, scholars from the multi-level governance perspective argued that local climate policymaking is shaped by external factors, including horizontal learning and diffusion across cities as well as incentives and capacities vertically structured by upper-level authorities (Ehnert et al. 2018; Hawkins, Kwon, and Bae 2016; Homsy and Warner 2015; Hultquist, Wood, and Romsdahl 2017; Krause 2011a, 2012; Lee and Koski 2015).

To date, most existing studies on motivations of local sustainability actions have drawn from empirical analysis of cities in Western Europe and North America, which are primarily post-industrialized, democratic countries with greater local autonomy and less pressure on industrial growth. These studies pointed to locally motivated sustainability actions by cities, which served as laboratories for spontaneous policy innovations and horizontal policy diffusion across jurisdictions in a democratic context (Krause 2011a; Lee and Koski 2015; Lubell, Feiock, and Handy 2009). Relatively less is known about what motivates local climate policy action in developing countries with an authoritarian political system where national governments exert greater influences on local policymaking.

Several characteristics make China a unique case for understanding motivations of local sustainability actions in an authoritarian context. First, after four decades of market-oriented reforms, city governments now enjoy greater autonomy in deciding local agendas, although the central government remains influential in urban policymaking through fiscal and political incentives structured within a hierarchical government system (Su and Tao 2017; Xu 2011). Second, local policy innovation features an “experimentation under hierarchy” model (Heilmann 2008a, 2008b), that is distinctive from spontaneous policy innovation observed in democratic countries. Although local cities are empowered to initiate policy innovations of their own, the central government often leverages local policy experimentation to signal policy reforms and eventually promote national policy transformation (Heilmann 2008a; Mei and Liu 2014). Third, until recently industrialization and economic development had dominated local policy agendas in Chinese cities, leading to widespread implementation gap in environmental policies (Kostka and Mol 2013). In these institutional and political environments, to what extent is local climate policy action by Chinese cities motivated by the unique incentive structure embedded in a context of multi-level sustainability governance and hierarchical experimentation?

This research uses the Low-Carbon City Pilot (LCCP) Program as a case to investigate factors that motivate Chinese cities to adopt sustainability policy action from a multi-level governance perspective. Unlike climate policy innovations in Western cities, which tend to be locally initiated, LCCP is a pilot program initiated by China’s central government in 2010 to stimulate local actions in low-carbon development. After drawing hypotheses from the theoretical perspectives of multi-level sustainability governance (Hawkins, Kwon, and Bae 2016; Homsy and Warner 2015; Krause 2011b; Lee and Koski 2015; Yi et al. 2019) and hierarchical experimentation in China (Heilmann 2008a, 2008b; Mei and Liu 2014; Miao and Lang 2015; Miao and Li 2017; Tsai and Dean 2014), we use event history analysis to test the extent to which a city’s likelihood to apply for LCCP can be predicted by neighboring effects (horizontal diffusion and hierarchical intervention), provincial priority in sustainability and climate protection, as well as local determinants such as leadership, politics, capacity, and environmental stress.

Our research has two intellectual contributions. First, we engage in the comparative urban governance literature on how different political-institutional contexts shape local policymaking for urban sustainability transitions. Our empirical analysis of the LCCP Program reveals that, despite in the authoritarian context, Chinese cities’ commitment to climate protection is motivated by local leadership, capacity, and environmental stress, resembling those that have been found in Western democracies. More importantly, we also find that local commitment is shaped by horizontal competition across jurisdictions and by priorities and preferences of upper-level authorities, reflecting China’s unique dynamics of multi-level governance and hierarchical experimentation. Second, a growing number of case studies have shown the emergence of local pioneers in climate policy innovation among Chinese cities (Khanna, Fridley, and Hong 2014; Li et al. 2018; Liu and Qin 2016; Lo 2014; Miao and Lang 2015; Miao and Li 2017). We contribute to this emerging line of inquiry with a systematic analysis of the motivations of local climate policy innovation in China, which not only is the world’s biggest greenhouse gas emitter but also faces severe environmental problems in multiple fronts on its own, thereby offering more knowledge about urban sustainability policymaking in developing countries.

The rest of the paper proceeds as follows. Based upon a review of previous literature on local and multi-level determinants for urban climate policy actions in Western contexts, we discuss the need to extend the scope of the knowledge to the authoritarian context of China. Next, we outline the origin and development of China’s Low-Carbon City Pilot Program, and research hypotheses based on theoretical perspectives of multi-level sustainability governance to understand LCCP participation of Chinese cities. We then introduce our research design, including data sources and variable specifications. The next section presents our research findings from the descriptive analyses and event history analyses. We discuss theoretical and policy implications of our findings and conclude the paper with possible directions for future research.

Existing Knowledge: Urban Climate Policy Innovation in Democratic Contexts

Local Determinants of Urban Climate Policy Innovation

To date, most existing research on urban sustainability policy innovation, including climate policy, has been conducted in the US context (Hughe 2017; see Yeganeh, McCoy, and Schenk 2020 for a comprehensive meta-analysis). In the absence of federal mandates, city governments are in a polycentric system in which voluntary local innovations function as laboratories for urban climate experiments to reframe global climate protection into local agendas and to demonstrate the viability of climate protection measures in creating local co-benefits while addressing a global public good issue (Bulkeley and Broto 2013; Ostrom 2010). A meta-analysis by Yeganeh, McCoy, and Schenk (2020) concluded that climate policy adoption by US cities is largely driven by internal factors such as government capacity, local leadership and politics (e.g., environmental entrepreneurs, community support, manufacturing dependence), and environmental risk and vulnerability, reflecting the spontaneous nature of local policy innovation in the US (Krause 2011a).

First, city governments are bounded by their fiscal and administrative capacity to adopt sustainability policies and commit to climate change mitigation (Homsy and Warner 2015; Krause 2011a, 2012; Lubell, Feiock, and Handy 2009). More economically advanced and fiscally stronger cities have more material and institutional resources to provide investment and support for sustainability policy innovations to mitigate global climate change (Krause 2011a, 2012; Lubell, Feiock, and Handy 2009). Cities that have a dedicated sustainability unit and more staff support have greater administrative and managerial capacities to engage in climate policy actions (Homsy and Warner 2015; Hultquist, Wood, and Romsdahl 2017; Krause 2011a, 2012; Lubell, Feiock, and Handy 2009; Wang 2013).

Second, local leadership and politics also predict active climate policy adoption (Yeganeh, McCoy, and Schenk 2020). The pluralist local politics in US cities entails strong influence of interest groups in local sustainability policymaking. On one hand, cities that are more dependent on manufacturing or have more powerful development interests are more likely to face stronger oppositions against adopting sustainability policies (Krause 2011a; Lubell, Feiock, and Handy 2009). On the other hand, stronger civic capacity in cities with more educated citizens, stronger public awareness of climate challenges, and the presence of environmental groups may allow the public to effectively counterbalance business interests in their advocacy for sustainability (Homsy and Warner 2015; Lubell, Feiock, and Handy 2009; Sharp, Daley, and Lynch 2011; Wang 2013; Zahran et al. 2008b). Meanwhile, the presence of an environmental policy entrepreneur may help organize diffuse public interests to form a pro-sustainability coalition in local politics and overcome local capacity constraints (Homsy 2018; Lubell, Feiock, and Handy 2009), thus leading to more active climate policies (Hultquist, Wood, and Romsdahl 2017; Krause 2011b, 2012).

Additionally, local environmental risk and stress may drive local climate actions. Although earlier studies found insignificant associations of composite indices of climate change risks (Zahran et al. 2008b), in general scholars agreed that a city’s vulnerability to climate change—for example, being a coastal community, previous extreme weather disasters—prompted active climate protection commitment and policy adoption (Hultquist, Wood, and Romsdahl 2017; Kalafatis 2018; Wang 2013; Zahran et al. 2008a).

Urban Climate Policy Actions in a Multi-Level Governance Structure

Urban climate policymaking does not take place in isolation from broader institutional and political contexts (Betsill and Bulkeley 2006). A growing body of literature has adopted the multi-level governance perspective to understand how vertical and horizontal interactions among government and non-government actors across different levels and territories shaped the incentives, capacity, and opportunities for local innovation in sustainability policies (Betsill and Bulkeley 2006; Bulkeley and Betsill 2005; Hawkins, Kwon, and Bae 2016; Homsy and Warner 2015; Lee and Koski 2015; Zeemering 2012). Yet compared to local motivations, to what extent local climate policy decision is motivated by multi-level governance factors is less well understood, particularly from a comparative lens.

Recent studies in the US have sought to test the effects of inter-governmental relationships on local policy decisions to address sustainability and climate change. Horizontally, policy diffusion studies suggested an inter-jurisdictional learning and imitation process that increases the likelihood of a locality to adopt similar policies that have been adopted by its neighboring localities (Berry and Berry 1990). Adopting the horizontal policy diffusion theory, Krause (2011a) found that cities are more likely to commit to climate protection when more neighboring cities take similar actions (Krause 2011a). Trans-municipal networks form another venue of horizontal information sharing and policy learning across cities. However, while Lee and Koski (2015) found that membership in climate-related city networks prompts a city to take stronger climate mitigation actions, Kalafatis (2018) found that the association is only significant for climate adaptation policy but not for mitigation.

Vertically, higher-level governments may incentivize and enable local sustainability actions by setting up aggressive targets, providing funding and technical assistance, and providing supportive frameworks for innovative actions (Hawkins, Kwon, and Bae 2016; Homsy and Warner 2015). However, previous studies on US cities have shown inconsistent impacts of leadership from higher levels of government on local climate policy adoption by US cities (Yeganeh, McCoy, and Schenk 2020). Homsy and Warner (2015) found that a city tends to adopt more sustainability policy actions if it is located in a state with a supportive policy environment. In climate policy initiatives, however, Krause (2011a, 2012) found no significant impacts of state-level actions (i.e., the presence of statewide GHG targets or climate action plans) on municipal climate commitment or policy adoption. Using a different dependent variable of climate policy performance, Lee and Koski (2015) found that the presence of a state-wide climate action plan—along with energy regulations—contributes to stronger local climate actions. Similarly, Hultquist, Wood, and Romsdahl (2017) found significantly more climate mitigation policies in cities where the state had a Climate Action Plan.

Multi-Level Governance and Hierarchical Policy Experimentation in China

A growing literature has applied the multi-level governance approach to characterize the reforming sustainability governance in China (Balme and Ye 2014; Homsy, Liu, and Warner 2019; Miao and Lang 2015; Miao and Li 2017; Yi et al. 2019), although some may question the extent to which China represents a multi-level governance system (Westman, Broto, and Huang 2019). For instance, local climate policy adoption by US cities is most significantly driven by local community support and interest groups (Yeganeh, McCoy, and Schenk 2020). Yet China’s urban sustainability governance is dominated by authoritarian, top-down decision making where public participation remains limited and often ineffective (Kostka and Mol 2013; Westman, Broto, and Huang 2019). But more scholars argued that four decades of governance reform have fundamentally changed the traditional bureaucratic hierarchy of policymaking in China, allowing for more bottom-up initiatives, societal engagement, and horizontal interactions across jurisdictions to shape local policy decisions (Ongaro, Gong, and Jing 2018) and in local environmental governance in particular (Homsy, Liu, and Warner 2019; Yi et al. 2019).

Nonetheless, China’s multi-level governance structure is authoritarian and thus more top-down than the federal multi-level governance structures in Western democracies, which delegate much legal and political power to state and local governments and prioritize local autonomy (Homsy, Liu, and Warner 2019; Ongaro, Gong, and Jing 2018). The central government remains influential in urban policymaking by restructuring local officials’ incentives and interests from economic growth to sustainability (Balme and Ye 2014; Homsy, Liu, and Warner 2019). The central government also actively incentivizes local climate policy innovation through adopting national climate strategies and initiating experimental programs (Miao and Li 2017). At the same time, local governments engage in horizontal learning and collaboration to promote sustainability, sometimes under vertical pressure of upper-level authorities (Homsy, Liu, and Warner 2019; Yi et al. 2018, 2019).

Policy experimentation in China also exhibits distinctive features under this unique and evolving multi-level governance system. Heilmann (2008a, 2008b) coined the term of “experimentation under hierarchy” to describe the central-local dynamics of policy innovation and transformation in China over the past four decades. Unlike the patterns of spontaneous local innovation in Western democracies, nationwide policy transformation results from a conscious effort of the central government to legitimize and empower bottom-up initiatives of policy innovation, with successful innovations eventually scaled up into national reform policies (Heilmann 2008a). The central government even uses policy experimentation—through controlling the purpose, site, instrument, and even evaluation of pilot programs—to signal new policy ideas and eventually induce nationwide policy transformation (Mei and Liu 2014). In various policy reforms, the central government may purposefully choose a relatively underdeveloped locality to carry out a pilot program in order to reduce political and economic risks (Tsai and Dean 2014), a city most seriously inflicted by certain policy issues in order to seek best solutions (Miao and Lang 2015), or the best performers as exemplars for a new policy idea or instrument (Heilmann 2008a). Like in other policy areas, the central government initiated a series of experimental programs to incentivize local policy innovations that promote urban sustainability transition (Li et al. 2018; Miao and Lang 2015; Miao and Li 2017).

In the authoritarian style of multi-level governance, what motivates Chinese city governments to engage in the hierarchical experimentation in sustainability policies? Do Chinese cities that are more active in climate policy actions have similar characteristics as have been observed in the US? Or, does active involvement of the central government change the determinants of local climate policy actions? We use the Low-Carbon City Pilot Program in China as an empirical case to answer these research questions. Before we discuss our theoretical hypotheses, we first present the contextual information about the LCCP Program, particularly with respect to the application and approval process of low-carbon pilot cities, based on information collected through documentary review and key informant interviews.

The Case: Low-Carbon City Pilot Program in China

As the world’s largest source of greenhouse gas emissions, China has been under increasing pressure from the international community to take greater responsibility in climate change mitigation. In 2007, the Chinese government issued China’s National Climate Change Strategy (zhongguo yingdui qihou bianhua gongzuo fangan, 中国应对气候变化工作方案) that specifies objectives, basic principles, key areas of actions, and policy measures to address climate change. In this context, the National Development and Reform Commission (NDRC), the central government authority in charge of national climate strategy and policymaking, launched the Low-Carbon City Pilot (LCCP) Program in 2010. The purpose of this pilot program was to encourage local cities to explore innovative measures that “both can grow the economy and improve people’s livelihood, as well as combat global climate change, reduce the carbon intensity, and promote green development in China” (Department of Climate Change Strategy, NDRC 2010).

In the first phase, a total of 12 provincial and prefectural cities applied with eight approved by NDRC as the first cohort of low-carbon pilot cities in July 2010. The pilot program was expanded in the subsequent two phases, with 28 provincial and prefectural cities out of 41 applicants approved in December 2012 (refer to Figure 1 for locations of all applicant cities). LCCP itself does not come with funding support from the central government, aside from seed grants to help cities make low-carbon city action plans (interview with NDRC officials, 09/24/2017). In the third phase, NDRC cut this seed grant; nevertheless, even without financial incentives, 41 prefectural cities applied and the central government decided to grant almost all applicants the pilot city titles except six cities with poor quality of application documents (interview with NDRC officials, 09/24/2017).

Figure 1.

Location of LCCP applicant cities, by phase.

Applying for LCCP, like many other pilot programs in China, involved three steps (Figure 2). First, the central government authority in charge of the LCCP Program—that is, the NDRC—issued a call-for-application notice to each provincial-level government, which would subsequently forward the notice to all municipalities in each province. Second, interested municipalities prepared application documents under the guidance of the provincial DRC. In each round of application, each provincial DRC may recommend up to three municipalities as candidates for the LCCP Program (NDRC-DCCS 2010, 2012, 2016). Finally, NDRC’s Department of Climate Change Strategy was in charge of the process of organizing expert review panels and making the final decision on which cities to be approved to join the pilot program. The Program also involved substantial roles of domestic and international experts both in preparing local application documents and in the final review and approval process (interview with an NDRC official, 08/25/2017).

Figure 2.

The application and review process of the LCCP program.

In practice, the whole process of application, review, and approval often involved multiple rounds of formal and informal consultation and negotiation among central, provincial, and municipal agencies (Figure 2). Municipalities often sought guidance from central and provincial authorities and gauged preferences and expectations of NDRC as they prepared their application documents or even as they decided whether or not to apply in the first place (interview with local officials in Jiangsu Province, 08/04/2017). Provincial governments played a pivotal role in coordinating the application process, but it remained up to city governments to decide whether or not to join in and commit to climate change policy innovation. Our interviews with central and provincial officials showed that, although provinces were allowed to recommend up to three candidates, in most cases, fewer cities actually applied. For instance, in Jiangsu Province, no city applied in the first phase, and only three and two cities voluntarily applied in the second and third phases, respectively (written interview with Jiangsu Provincial DRC, August 04, 2017).

Provinces took drastically different approaches to coordinating the low-carbon policy experimentation. Some provinces (such as Jiangsu) took a passive stance by simply forwarding NDRC’s notice and “encouraging voluntary applications” by municipalities (written interview with Jiangsu Provincial DRC, August 04, 2017). Other provinces chose to actively encourage and even provide financial and technical support for their municipalities to apply. Provinces may even signal their preferences when coordinating the application process. For instance, both Shandong and Hunan Provinces, where no cities had voluntarily applied in the first two phases, closely studied the eligibility criteria set out by NDRC and selected three cities to apply in the third phase (written interviews with Shandong and Hunan Provincial DRCs, August 01 and 03, 2017).

Theoretical Framework and Hypotheses

Why did local cities in China decide to apply and become a low-carbon pilot city? LCCP is a signature program launched by the central government to incentivize local policy innovations in climate protection, with the goal to promote nationwide transformation toward low-carbon development. Unlike spontaneous local innovation observed in climate actions by US cities, a city’s decision to apply for the LCCP Program may be affected by its own assessment of the chance of being approved by upper-level governments as well as its horizontal competition with other cities. In other words, local climate policy actions in the authoritarian China should be situated within a multi-level governance structure that is characterized with horizontal diffusion across municipalities, top-down incentives from upper-level governments, as well as local determinants such as capacity, politics, and problem severity.

First, public policy scholars both in the US and China have written about horizontal diffusion of innovations, in which interjurisdictional competition, learning, and imitation increases the probability of a city to adopt similar policy actions that have been adopted by geographically neighboring jurisdictions (Berry and Berry 1990; Zhu and Zhang 2015). But horizontal diffusion is not limited to geographically adjacent jurisdictions in China. Local leaders in China are locked in a fierce competition for political promotion largely controlled by superior governments (Xu 2011). Although early literature has suggested a political tournament model based on economic performance (Li and Zhou 2005), recent studies have shown that being an active policy innovator in issues of top priority for the central government may also be rewarding to local officials in terms of the chance of being promoted (Mei and Wang 2017). As environmental sustainability gradually assumed a higher priority on national policy agenda, it is not surprising to find stronger local enthusiasm in sustainability pilot programs in order to show a local leader’s loyalty and support to the national policy agenda. A city may have even greater enthusiasm if its economic competitors—other cities with similar economic performance in the same province—participate in similar policy innovation.

However, in hierarchical experimentation such as LCCP, the central government’s preference may complicate the horizontal diffusion mechanisms when it closely monitored the selection of pilot cities. Khanna, Fridley, and Hong (2014) found that the central government explicitly sought geographical, social, and economic representativeness of pilot cities to test different paths and policy measures for low-carbon development in different local conditions. Knowing this preference of the central government, a city may intentionally choose not to apply if its neighboring cities have applied or even been awarded LCCP titles. The co-existence of horizontal competition and hierarchical intervention entails two competing hypotheses regarding the neighboring effects:

Horizontal Diffusion Hypothesis (H1a): A city is motivated to apply for LCCP due to peer pressure from similar actions by its geographical neighbors or economic competitors.

Hierarchical Intervention Hypothesis (H1b): Due to the center’s preference for the diversity of pilot cities, a city is less likely to apply for LCCP if its geographic neighbors or economic competitors have joined the LCCP Program.

Second, in multi-level governance, local policy actions are affected by the priority and actions of upper-level governments. In China, as the nexus between the central and local governments, provincial priorities in sustainability can help shape more environment-friendly localities. Under the pressure and empowerment by the central government, provinces may adopt their own climate policy goals and initiatives (Miao and Li 2017). Provinces that prioritize sustainability would provide more financial support for local cities to take actions for environmental protection or even mandate certain actions by cities. Our hypothesis regarding provincial priority is:

Provincial Priority Hypothesis (H2): A city is more likely to apply for LCCP if it is located in a province with stronger commitment and actions in sustainability and climate protection by the provincial government.

Third, local policy innovation in China is also determined by local leadership and capacities (Eaton and Kostka 2014; Zhu and Zhang 2015). In fact, local government interest and capacity are likely to be stronger drivers for local climate policy adoption because local mayors and bureaucratic agencies largely dominated city government decisions to apply to LCCP while public consultation and participation were limited. Local mayors with prior work experience in sustainability-related agencies likely have more understanding of climate change and thus play an entrepreneurial role in promoting a local policy agenda more supportive of climate protection. A city government with greater capacity is more capable of adopting this agenda. Meanwhile, in China’s hierarchical system of cadre management, mayors with greater political leverage have higher ability to negotiate with upper-level governments and thus may be encouraged to apply. Therefore, we derive our three hypotheses regarding local leadership and government capacity:

Local Leadership Hypothesis (H3): A city is more likely to apply for LCCP if its mayor has had prior work experience in sustainability-related agencies.

Local Capacity Hypothesis (H4): A city that has greater fiscal capacity is more likely to apply for LCCP.

Local Political Leverage Hypothesis (H5): A city with more political leverage with upper-level governments are more likely to apply for LCCP.

Fourth, the ways that local interest group politics affects local climate policy actions by Chinese cities may be different from those by post-industrialized western cities. On the one hand, scholars of urban politics in China have suggested the emergence of pro-growth coalitions in Chinese cities (Zhang 2002; Zhu 1999), which indicates a growing influence of local business interests in shaping urban policy decisions. In that case, a strong industrial base may function as a local obstacle for climate policy adoption, similar to observations in the US (Krause 2011b). On the other hand, cities with a larger industrial base, hence a more energy-intensive economy, may consider the LCCP Program an opportunity to pursue other co-benefits such as economic restructuring, energy conservation, and local pollutant reduction. A case study by Shin (2017) found that industries and city governments formed an alliance to lobby for low-carbon piloting programs as a means to facilitate local pursuit of developing more energy-intensive green industries. Our key informant interviews, supplemented with review of policy documents, also suggested that many cities saw economic restructuring—upgrading the industrial base and transition toward a less energy-intensive and more services-oriented economy—as a co-benefit of joining in the LCCP Program. Hence our hypothesis regarding local industrial base is:

Local Industrial Base Hypothesis (H6): The share of the secondary industry in a local economy has an inverted U-shaped relationship with a city’s willingness to apply for LCCP.

Data and Variable Specification

Following the policy diffusion literature (e.g., Berry and Berry 1990, 2018; Zhu and Zhang 2015), we adopt discrete time event history analysis to capture both external diffusion and internal determinants of local government engagement in LCCP, with the period of analysis divided into three distinct units, that is, 2010, 2012, and 2016, the year when the application and review process of each phase was actually carried out, respectively. Thus, our observations include 317 cities in China, excluding cities from two autonomous regions with ethnic minority concentration (Xinjiang and Tibet), where social and political stability are the top priority over other policy agendas and most data are not available.

In China’s hierarchical system, there are four administrative ranks of subnational governments: province, prefecture, county, and township. Subsequently, cities in China may be at the provincial, prefectural, and county-levels. NDRC’s LCCP Program primarily focused on prefecture-level jurisdictions, which directly fall under the authority of a province. Therefore, our research only concerns prefectural-level cities, excluding the four provincial-level municipalities (i.e., Beijing, Shanghai, Tianjin, and Chongqing) because they enjoy the same political power as a province, and county-level cities because they are at a lower administrative level than prefectures and the political dynamics governing local policymaking in these county-cities is different. However, among these prefecture-cities, 15 cities received a special status as deputy-provincial cities, which are typically provincial capitals or cities specifically designated by the central government and thus have stronger political leverage than other prefectures. Therefore, our sample includes 302 prefecture-level cities (including: shi, diqu, zizhizhou, and meng) and 15 deputy-provincial level cities.

Most studies on sustainability policy innovations in China have employed the adoption of innovative programs by local governments as the proxy of local sustainability participation (Li et al. 2015; Zhang and Li 2011). However, such measurement of local participation is problematic as it omits cities that were actively pursuing sustainability policy innovations but were dropped from application to adoption because of central selection. Therefore, our main dependent variable is LCCP application, measured by a dummy variable that equals one if the city applied for LCCP Program in one particular time, and zero otherwise. We also check the robustness of empirical results by replacing LCCP application with LCCP approval as the dependent variable (1 = approved LCCP city; 0 = otherwise). In all three phases, 75.5% of all applicant cities were approved and designated as low-carbon pilot cities.

Based on previous discussions, we included independent variables of both multi-level governance factors (neighboring effects and provincial priority in sustainability) and local determinants (leadership, politics, capacity, and environmental stress). Table 1 introduces all variable definitions and data sources.

Table 1.

Variable Definitions and Data Sources.

Variable names	Variable definition	Data source
Neighbor application	Number of neighboring cities that have applied or are applying for LCCP	Compiled by the authors
Competitor application	Whether at least one economic competitor (cities with GDP rank one above or lower in the same province) has applied or is applying for LCCP (1 = yes; 0 = no)	Compared by the authors
Provincial carbon goal	Whether carbon dioxide emission reduction targets were mentioned in the annual government work report given by governors to provincial People’s Congress (1 = yes; 0 = no)	Compiled by the authors
Provincial environmental budget share	Annual budgetary expenditure on environmental protection as a share of total provincial expenditure in the previous year	China City Statistical Yearbook
Provincial pilot	Whether the province to which the city belongs has currently or previously applied for Low-Carbon Pilot Province (1 = yes; 0 = no)	Compiled by the authors
Local leader’s interest	Whether the city’s mayor previously held a position in charge of sustainability-related policies, for example, environmental protection, forestry conservation, land management, or planning (1 = yes; 0 = no)	China Political Elite Database: http://cpc.people.com.cn/gbzl/index.html
Local political leverage	Administrative ranking (1 = deputy provincial city; 0 = prefectural city)	Compiled by the authors
Secondary industry share in local GDP	Share of secondary industry in total GDP in the previous year	China City Statistical Yearbook
Local fiscal capacity	Per capita revenue (10,000 yuan) in the previous year	China City Statistical Yearbook
Urban population	Number of urban year-end population (10,000 persons) in the previous year	China City Statistical Yearbook
Energy consumption (log)	Amount of energy consumption (10,000 kWh, logged value) in the previous year	China City Statistical Yearbook
SO₂ emission (log)	Amount of SO₂ emission in tons (logged value) in the previous year	China City Statistical Yearbook

Note. Data for most independent variables were collected at three points in time for the event history analysis (2010, 2012, and 2016 for each of the three phases). Variables derived from China City Statistical Yearbook used data from one year prior to each phase (2009, 2011, and 2015, respectively).

Multi-Level Governance Factors

We test the competing hypotheses regarding the neighboring effects (H1a vs. H1b) by measuring low-carbon climate actions of two types of “neighboring” cities: geographical neighbors and economic competitors. Neighbor Application refers to the number of geographically adjacent cities that have previously applied or are applying for LCCP in one particular year. Competitor Application refers to whether at least one economic competitor of the city has applied or is applying for LCCP. Following Yu, Zhou, and Zhu’s (2016) measurement, a city’s economic competitors in this paper are defined as other cities in the same province but with GDP per capita ranked one above or lower than the city.

Three indicators act as the proxy of provincial priority in sustainability and climate protection. The first variable, Provincial Carbon Goal, is a dummy variable capturing whether the province has placed climate actions high on the policy agenda. This was measured through review of annual government work reports given by governors to provincial People’s Congress to see if the report included at least one carbon dioxide emission reduction targets. Second, Provincial Environmental Budget refers to the amount of provincial government budget for environmental protection as a share of total provincial budget. The third variable, Provincial Pilot, is also a dummy variable indicating whether the province has applied or is applying for the low-carbon pilot province program.

Local Determinants: Leadership, Politics, Capacity, and Environmental Stress

Based on previous studies, we control for local determinants of climate commitment including leadership, capacity, politics, and environmental stress. First, we include Leader Interest to capture whether the city’s mayor has worked in any of the following departments: environmental protection, forestry conservation, land resource management, and urban planning. Second, we use the administrative ranking in the governmental hierarchy to proxy a city’s local political leverage, which is a dummy variable with one referring to deputy-provincial cities and zero referring to prefectural-level cities. Deputy-provincial cities have higher political and economic status, thus greater political capability to compete for resources and preferential treatments from provincial and central governments. Because of the hierarchical intervention of the experimental program, cities with greater political leverage with upper-level governments may be more encouraged to apply for LCCP knowing its greater chance of success. Third, we use the share of the secondary industry to local GDP, as well as its square term, to capture the double-edge effects of the industrial base on climate policy commitment. In China, the secondary industry is defined as all industries that are related to “mining and quarrying (not including support activities for mining), manufacturing (not including repair service of metal products, machinery, and equipment), production and supply of electricity, heat, gas and water, and construction.” Fourth, we capture government capacity with local fiscal capacity, measured by per capita revenue, and local administrative capacity, indicated by the number of year-end urban population, both in the year prior to LCCP application. More urban population requires city governments to develop greater capacities in delivering public services and enforcing sustainability policies. Finally, we include two variables of local environmental stress: the amount of energy consumption and the amount of sulfur dioxide emission (SO₂), both using the natural logarithm values to make variables more normally distributed. Higher environmental stress is expected to increase the likelihood of a city to apply for LCCP.

Empirical Findings

Descriptive Analysis

Table 2 presents summary statistics of independent variables comparing LCCP applicant and non-applicant observations, and LCCP approval and non-approval observations in all phases. Results shown in columns 1 to 3 indicate that LCCP applicants have significantly higher mean values for most independent variables than cities that never applied for LCCP. Specifically, LCCP applicants tend to be cities that have stronger local leadership interested in sustainability, higher political leverage as deputy-provincial cities, greater fiscal capacity, and higher level of energy consumption. However, LCCP applicants are not necessarily more manufacturing-dependent or have a larger urban population. Additionally, applicants tend to locate in provinces that have established own targets of carbon emission reduction and have higher provincial expenditure on environmental protection. Similar differences can be observed between approval and non-approval cities (columns 4–6). Furthermore, there is no significant difference in key fiscal, environmental, and political factors between applicant and approval cities (shown in column 7).

Table 2.

Comparing Mean Values of Key Independent Variables by Applicant (Approval) and Non-Applicant (Non-Approval) Cities.

Variables	(1)	(2)	(3)	(4)	(5)	(6)	(7)
	Applicants (all phases)	Non-applicants (all phases)	Mean difference (1) − (2)	Approvals (all phases)	Non-approvals (all phases)	Mean difference (4) − (5)	Mean difference (1) − (4)
Neighbor application	1.289	0.735	0.554***	—	—	—	—
Competitor application	0.277	0.205	0.072	—	—	—	—
Neighbor approval	—	—	—	1.092	0.555	0.538***	—
Competitor approval	—	—	—	0.185	0.165	0.020	—
Provincial carbon goal	0.349	0.191	0.158***	0.369	0.199	0.170***	−0.02
Provincial environmental budget share	1.401	1.234	0.167***	1.404	1.242	0.162**	−0.004
Provincial pilot	0.410	0.409	0.001	0.400	0.411	−0.011	0.010
Local leader’s interest	0.145	0.066	0.079***	0.154	0.067	0.087***	−0.009
Local political leverage	0.157	0.027	0.130***	0.185	0.027	0.158***	−0.028
Secondary industry share in local GDP	50.027	48.280	1.746	49.361	48.424	0.937	0.666
Local fiscal capacity	0.575	0.254	0.321***	0.648	0.258	0.390***	−0.073
Urban population	430.138	388.471	41.667	446.995	387.654	59.340*	−16.857
Energy consumption (log)	13.403	12.771	0.632***	13.544	12.780	0.764***	−0.140
SO₂ Emission (log)	10.712	10.547	0.164	10.719	10.555	0.164	−0.007

Note. Columns 1 and 2 are mean values among cities that applied for LCCP (Column 1) and cities that never applied (Column 2) in all three phases, with Column 3 showing the mean-difference tests between applicants and non-applicants. Columns 4 and 5 are mean values among cities that were approved pilot cities (Column 4) and cities that were never approved (Column 5), with Column 6 showing the mean-difference tests between approval and non-approval cities. Column 7 further shows the mean differences between applicants and approval cities.

Level of significance of the mean difference: *p < .1. **p < .05. ***p < .01.

Event History Analysis: Determinants of LCCP Participation

Table 3 presents results from event history analyses of the determinants of LCCP participation. In Model 1, we only included four multi-level governance variables capturing neighboring effects and provincial priority. Model 2 added local determinants except the two environmental indicators. Model 3 (the full model) further added the environmental indicators, but because of the extensive missing values of these two environmental variables, Model 3 had fewer observations than Model 2. Additionally, in Model 4, we ran the full model with only prefecture-level cities while leaving deputy-provincial cities, which have greater political leverage to compete for resources and preferential treatments.

Table 3.

Determinants of LCCP Application: Results from Event History Analysis.

	Model 1 (full sample)		Model 2 (full sample)		Model 3 (full sample)		Model 4 (only prefecture-cities)
	Coeff.	t-Ratio	Coeff.	t-Ratio	Coeff.	t-Ratio	Coeff.	t-Ratio
Multi-level governance
Neighboring effects
Neighbor application	0.188**	2.155	0.170*	1.867	0.174**	2.133	0.215**	2.385
Competitor application	−0.187	−0.778	−0.293	−1.206	−0.362	−1.442	−0.329	−1.269
Provincial priority
Provincial carbon goal	0.190	0.766	0.311	1.225	0.215	0.797	0.036	0.122
Provincial environmental budget share	0.245	1.325	0.222	1.129	0.511***	2.648	0.619***	3.190
Provincial pilot	−0.035	−0.152	−0.031	−0.131	−0.215	−0.844	−0.071	−0.246
Local capacity, leadership, and problem severity
Local leadership and politics
Local leader’s interest			0.676***	2.747	0.565**	2.338	0.603**	2.035
Local political leverage			1.206***	3.460	1.115***	3.014
Square of secondary industry share			0.000	0.627	−0.000	−0.454	−0.000	−0.297
Secondary industry share in local GDP			−0.029	−0.430	0.062	0.672	0.045	0.479
Local capacity
Local fiscal capacity			0.816***	3.629	0.650***	2.961	0.547*	1.834
Urban population			0.000	0.932	0.000	0.521	0.000	0.406
Problem severity
Energy consumption (log)					0.322**	2.072	0.326**	2.072
SO₂ emission (log)					−0.364**	−2.098	−0.343*	−1.787
Number of observations	903		901		763		728
Chi-square	9.40*		99.85***		102.68***		39.64***
Log likelihood	−468.088		−447.022		−387.673		−324.803

Note. Model 1 only included multi-level governance variables (neighboring effects and provincial priority); Model 2 further included local determinants except two environmental variables that contain extensive missing values; Models 3 and 4 included all variables. Models 1, 2, and 3 included deputy-provincial and prefecture-level cities, while Model 4 excluded deputy-provincial cities (with the local political leverage variable omitted). Standard errors were adjusted for clusters in cities.

p < .1. **p < .05. ***p < .01.

Consistent with descriptive statistics, in all four models, a city is significantly more likely to apply for LCCP if more of its geographical neighboring cities also apply for the program. With all other variables held constant, a city’s odds to apply for LCCP would increase by 19.0% (=exp (0.174) − 1, p < .05, Model 3 in Table 3) with one additional neighboring city that applies or previously applied for LCCP; the likelihood is even higher in Model 4 when only prefecture-level cities are considered. This finding contradicts our hierarchical intervention hypothesis about the central government’s preferences for geographical dispersion of pilot cities (H1b) but rather confirms the horizontal diffusion hypothesis (H1a) that is consistent with previous findings from the policy diffusion literature in the US context (Krause 2011a). One possible explanation is that, although the central government may prefer geographic dispersion of applicant cities, this is primarily achieved through distributing the quota among provinces. At the local level, cities are motivated by strong peer pressure from their geographical neighbors to apply for LCCP. The coefficient of Competitor Application is negative but insignificant in all four models. One possible explanation is that, while competing with other cities with similar economic profile for being a policy innovator, cities may prefer piloting in other policy areas in order to distinguish themselves with unique performance, rather than simply following the same actions by their economic competitors (Zhu 2014).

Regarding the provincial priority variables, provincial environmental budget share is significant and positively predicting the likelihood of LCCP application when all local factors are controlled for (Models 3 and 4; see Table 3), confirming the positive influence of provincial support to incentivize and encourage local sustainability actions (H2). However, provincial carbon goal and provincial pilot are not significant in all four models. The inconsistent results of three provincial priority variables indicate that, compared to making tangible investment in the provincial budgets, simply announcing a commitment to climate goals by a provincial government does not necessarily incentivize climate policy innovation by city governments.

Among the local variables, our analysis found significant and positive effects of local leaders’ interests in sustainability (H3), local fiscal capacity (H4), and local political leverage (H5). As shown in Table 3, all else equal, the odds for a city to apply for LCCP increase by 75.9% if its leaders have previously worked in sustainability-related departments (coefficient = 0.565, p < .05; Model 3). Deputy-provincial cities, which have greater political leverage, are more likely than prefectural cities to apply for the program (coefficient = 1.115, p < .01). Per capita revenue is also highly significant and positive (coefficient = 0.650, p < .01; Model 3), which indicates that local sustainability policy innovations are more likely to occur in cities with healthier fiscal conditions, consistent with previous studies in Western contexts (e.g., Krause 2011a, 2012; Lubell, Feiock, and Handy 2009).

Meanwhile, contrary to our expectations and previous findings in US cities regarding the negative effects of manufacturing dependence (Yeganeh, McCoy, and Schenk 2020), neither the share of the secondary industry in the local economy nor its square term is significant. This probably indicates that co-benefits of climate change policies are not limited to transforming the industrial structure and that cities with a small manufacturing base may pursue their own paths toward low-carbon cities. It may also reflect that the central government intentionally encouraged cities with different economic conditions to explore locally-tailored measures to climate change mitigation.

Finally, event history analysis suggests mixed effects of the two environmental control variables: while more energy consumption increases the propensity of a city to apply for LCCP (coefficient = 0.322, p < .05, Model 3; Table 3), a city’s SO₂ emissions are negatively associated with LCCP application (coefficient = −0.364, p < .05 in model 3). This is probably because SO₂ emissions are less visible to the public attention and governmental agenda, while energy consumption is more directly linked to green-house gas emissions, and hence more directly motivates local participation in LCCP Program.

Robustness Check: Determinants of LCCP Approval

As a robustness test, Table 4 presents model results by replacing the dependent variable of LCCP applicant to LCCP approval, defined as whether a city was ultimately awarded as a pilot city in the LCCP Program.

Table 4.

Robustness Check: Determinants of LCCP Approval (Event History Analysis).

	Model 5 (full sample)		Model 6 (full sample)		Model 7 (full sample)		Model 8 (only prefecture-cities)
	Coeff.	t-Ratio	Coeff.	t-Ratio	Coeff.	t-Ratio	Coeff.	t-Ratio
Multi-level governance
Neighboring effects
Neighbor adoption	0.266***	2.661	0.261**	2.359	0.286***	2.847	0.331***	3.206
Competitor adoption	−0.573**	−1.987	−0.709**	−2.430	−0.870***	−2.937	−0.888***	−2.779
Provincial priority
Provincial carbon goal	0.162	0.554	0.364	1.086	0.280	0.792	0.055	0.147
Provincial environmental budget share	0.185	0.910	0.060	0.261	0.431*	1.916	0.548**	2.217
Provincial pilot	−0.360	−1.097	−0.615*	−1.724	−0.574	−1.420	−0.599	−1.102
Local capacity, leadership, and problem severity
Local leadership and politics
Local leader’s interest			0.626**	2.283	0.640**	2.446	0.752**	2.337
Local political leverage			1.497***	3.691	1.171***	2.771
Square of secondary industry share			−0.000	−0.141	−0.002	−1.160	−0.001	−0.994
Secondary industry share			0.017	0.195	0.171	1.221	0.140	1.038
Local capacity
Local fiscal capacity			0.985***	4.025	0.812***	3.563	0.762**	2.389
Urban population			0.000	0.666	0.000	0.426	0.000	0.606
Problem severity
Energy consumption (log)					0.425**	2.484	0.424**	2.471
SO₂ emission (log)					−0.404**	−2.565	−0.421**	−2.477
Number of observations	914		912		774		739
Chi-square	13.87**		118.90***		154.13***		61.44***
Log likelihood	−365.051		−340.477		−299.462		−244.669

p < .1. **p < .05. ***p < .01.

As shown in Table 4, the neighbor adoption variable is a robust and even stronger predictor of the odds for a city to be approved as a LCCP pilot city would increase by 33.1% if at least one of its geographical neighbors joined the program (coefficient = 0.286, p < .01; Model 7). Moreover, the negative role of competitor adoption becomes statistically significant in all four LCCP adoption models. With all other variables held constant, a city is less likely to be selected as a LCCP pilot city when having at least one economic competitor city also selected to join in the pilot program (coefficient = −0.870, p < .01; Model 7). While this finding does not directly confirm our hierarchical intervention hypothesis (H1b), it does indicate that the central government prefers diversified economic profiles of pilot cities selected to join in the LCCP Program. Results of other independent variables remain robust. Provincial environmental budget, leader interests, administrative ranking, local fiscal capacity, and environmental stress matter for local sustainability actions.

Discussion

The above empirical findings revealed similarities and contrasts in the motivations of urban climate policy action in China compared to Western democracies. Despite being in an authoritarian country, Chinese city governments are similarly motivated by local fiscal capacity, entrepreneurial leaders, and environmental stress to commit to climate protection. Meanwhile, whether using LCCP application or LCCP approval as the dependent variable, our models suggested positive influence of actions by geographic neighbors, resembling the horizontal diffusion mechanism as observed in Western patterns in spite of the central government’s preference for geographical dispersion of piloting cities.

More importantly, our research revealed that, under China’s authoritarian multi-level governance, the hierarchical nature of policy experimentation created unique motivations for local climate policy action. First, although statistically insignificant in the LCCP application models, competitor adoption becomes a significant and negative predictor of LCCP approval, possibly supporting the effect of hierarchical intervention in policy experimentation in China (Heilmann 2008a; Mei and Liu 2014). The central government aims to test different paths and policy measures for low-carbon development in diverse economic, social, and environmental conditions, and thereby reducing the chance of a city to be selected into the LCCP Program if its economic competitors already joined the program. Second, this paper also offered additional empirical evidence from China to support the role of leadership of upper-level governments as a positive trigger of local climate policy action, which had been found to have only weak links to local climate policy adoption in the US (Yeganeh, McCoy, and Schenk 2020). More interestingly, it is less about making a commitment to climate goals than about providing substantive public investment in sustainability by provincial governments that is more likely to incentivize local initiatives on climate protection. Finally, urban climate policymaking is overall authoritarian and non-participatory, dominated by inter-governmental relationship and bureaucratic politics, which is different from US patterns where community support and interest groups play important roles in determining local sustainability actions (Yeganeh, McCoy, and Schenk 2020).

Conclusions

In this paper, we used the LCCP as an empirical case to investigate motivations of city governments in China to participate in sustainability policy innovation in an authoritarian, industrializing context. We conducted event history analyses to evaluate the effects of multi-level governance factors (neighboring effects, provincial priority in sustainability) and local factors (leadership, politics, capacity, and environmental stress)—in determining whether or not city governments applied for being pilots, and then conducted a robustness test by running models on whether cities were eventually approved to become pilots. Our research contributed to the comparative scholarship urban sustainability governance by revealing the uniqueness of motivations for urban climate policy action in non-Western contexts.

However, there are also implications for three major areas of research this paper did not address. First, our research indicated the co-existence of horizontal diffusion and hierarchical intervention as two competing mechanisms underlying the effects of geographic neighbors and economic competitors. More qualitative studies are necessary to specify exactly how these two mechanisms interplay to shape local policy decisions. Second, this paper only captured whether a city participated in an environmental piloting program; we did not assess how the piloting program was actually implemented and which policy instruments were developed in specific policy areas. Substantial variations exist in terms of the implementation of sustainability policy actions as suggested by previous studies (Khanna, Fridley, and Hong 2014; Sharp, Daley, and Lynch 2011). The enduring gap between adoption and implementation of local sustainability actions deserves more discussion, particularly in a comparative context. Finally, given that our research only focuses on the Low-Carbon City Pilot Program, we cannot assess whether motivations behind local innovations in other policy areas follow the same logic. Hence, further empirical studies are needed to support theory and practice in this domain.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Office for Philosophy and Social Sciences, P.R.China (Grant No. 20ZDA042). This research also received support from the Tsinghua University Research Center for Green Economy and Sustainable Development.

ORCID iD

Zhilin Liu

Author Biographies

Zhilin Liu, PhD, is an associate professor in the School of Public Policy and Management, and a joint research fellow at the Hang Lung Center for Real Estate, Tsinghua University. Her main research interests are in urban planning and governance, sustainable development, and affordable housing (email: zhilinliu@tsinghua.edu.cn).

Jie Wang is a PhD student in the Department of Urban Planning and Public Policy, University of California, Irvine. Her main research interests are in environmental policy, water resource management, and collaborative governance (email: jiew35@uci.edu).

Craig W. Thomas, PhD, is a professor in the Daniel J. Evans School of Public Policy and Governance, University of Washington, Seattle. His main research interests are in collaborative governance, public management, policy processes, and environmental and natural resources policy (email: thomasc@washington.edu).

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