https://orcid.org/0000-0001-7000-5016
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ABSTRACT
This study examines the impacts of political competition on eco-efficiency. We first develop a theoretical model in which local government officials compete against each other to maximise their own political score. We find that after an initial stage of decline, eco-efficiency eventually turns upwards, once environmental performance becomes a meaningful component of local government officials’ annual assessment. Eco-efficiency also exhibits a pattern of convergence. Lastly, the level of political competition is found to be negatively correlated with eco-efficiency. For the empirical analysis, we use a data envelopment analysis (DEA) model to compute the eco-efficiency level for 191 Chinese cities from 2003 to 2015. Our empirical evidence presents a ‘U’-shape pattern in the trend of eco-efficiency and identifies two peer effects that work in opposite directions: the incentivising effect arising from higher performing neighbours, and the disincentivising effect when a city outperforms its competitors. Both peer effects lead to convergence in eco-efficiency, and our spatial econometric modeling analysis suggests that the net peer effect is significantly positive. We also find evidence of political competition reducing eco-efficiency, as predicted in the theoretical model. Our findings are robust to alternative measures of eco-efficiency.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
Notes
1 This body of research, known as the environmental Kuznets curve (EKC) literature, has been enormously influential. The work by Grossman and Krueger (Citation1995) is widely regarded as one of the earliest attempts at EKC hypotheses. For an extensive overview of theoretical studies and empirical evidence regarding EKC, see Kaika and Zervas (Citation2013).
2 The term ‘eco-efficiency’ is a concept and philosophy geared toward sustainability, combining ecological and economic efficiency.
3 The pollution haven hypothesis was first developed by Pethig (Citation1976) and McGuire (Citation1982), and later improved by Copeland and Taylor (Citation1994) and Levinson and Taylor (Citation2008), among others.
4 For example, in its National 10th Five-Year Plan (2001–05), released in 2001, the central government for the first time added environmental protection and pollution reduction to its list of ‘national strategic goals’, and set a target to reduce pollutant discharges by 10% by the end of 2005. Under the new regulation framework, each province was assigned a specific target, and the provincial government officials were to be evaluated on, among other things, how well these targets were met. However, little improvement in environmental quality has been observed in China based on data between 1998 and 2008, because the pollution mandates imposed by the central government have triggered strategic polluting responses from the provinces (Cai et al., Citation2016).
5 For example, one can collect China’s provincial energy intensity data from the National Bureau of Statistics, but information on the country’s urban energy intensity is not consistently reported. China’s urban energy consumption will be overestimated if we multiply provincial energy intensity statistics and prefecture gross domestic product (GDP). To overcome this shortcoming, Huang et al. (Citation2018b) have collected China’s urban energy intensity and estimated primary energy consumption using a bottom-up rather than a top-down approach.
6 Economic growth has always been, and will continue to be, of paramount status in China. Friedman (Citation2009) wrote that for Chinese officials trying to move up the system, their success is rewarded in two ways. Formally, annual performance evaluations are tied primarily to GDP growth in each jurisdiction. Informally, local officials personally benefit financially from that growth by ‘investing in or holding positions in key firms, by assigning relatives to management positions, by engaging in plain vanilla corruption, and so on’ (p. 408). This helps justify the observation that economic growth enters twice the public official’s objective function.
7 To normalize the outside influence upon each city, the weights matrix is subject to standardization, so that elements in the same row sum to 1. We use this spatial weighting matrix because a city is more likely to compare itself and compete against its peers in the same province.
8 The Hausman test suggests we cannot reject the null hypothesis that the average political intensity is exogenous. Besides, we employ the maximum likelihood procedure to estimate the spatial Durbin model so to address the potential endogeneity concern.
9 We use data from 2003 to 2015 due to availability of information about public officials in China.
10 Since the 1980s, local GDP growth has been employed as the major indicator to evaluate the performance of local government officials (Li & Zhou, Citation2005).
11 For two decades, the coastal regions of eastern China were the only beneficiaries of the economic reform starting in 1978, and as a result, the western regions lagged behind severely. Around the turn of the century, Chinese leaders announced a change in the regional development strategy by launching the Great Western Development Strategy. Starting in 2001, the Chinese government has offered preferential policies to the western regions on development of infrastructure, foreign investment, environmental protection, promotion of education, etc.