مقاله سال ۲۰۱۶

The Poyang Lake Eco-economic Zone Planning was officially approved by the State Council of China on December 12th, 2009, indicating that the construction of the Poyang Lake Eco-economic Zone (PLEEZ) was a national-level strategy. The PLEEZ is based on the Poyang lake urban circle and is intended to become an ecological economic demonstration zone and a low-carbon economy development priority zone in China.1 The increasing interest in and strategic importance of the PLEEZ have heightened the need for investigating its effects on regional environmental performance.

Therefore this study investigates the effect of the PLEEZ’s establishment on regional environmental productivity growth after 2009. A significant growth of the environmental productivity of the PLEEZ after 2009 indicates that the PLEEZ policy is effective. Two kinds of indices are widely used for measuring productivity growth, i.e. the Malmquist index and the Luenberger indicator. The Malmquist index, empirically presented by Färe et al. (1994), is widely used for measuring productivity change growth. Taking the environmental factors into account, Chung et al. (1997) proposed the Malmquist–Luenberger index for measuring environmentally sensitive productivity growth. Empirical studies applying the Malmquist–Luenberger index include Weber and Domazlicky (2001), Färe et al. (2001), Yörük and Zaim (2005), Kumar (2006) and Zhang and Choi (2013a,b), for measuring environmental performance change.

The Luenberger productivity indicator is an alternative for measuring productivity growth. Compared with the Luenberger indicator, the Malmquist index appears to overestimate productivity changes (Boussemart et al., 2003). Recent work also suggests that the Luenberger index is more robust than the Malmquist index (Fujii et al., 2014). Thus, this study employs the Luenberger indicator as its main methodology. However, the basic Luenberger indicator cannot deal with the non-zero slack variable problem because it adopts the radial method for measuring performance (Zhou et al., 2012; Zhang et al., 2014). To handle this shortcoming, Fujii et al. (2014) proposed the nonradial Luenberger indicator with undesirable outputs. To incorporate cross-group heterogeneity into this indicator, Zhang and Wei (2015) introduced a metafrontier non-radial Luenberger carbon emission performance index; unlike Zhang and Wei (2015), who focused on singlefactor carbon emission performance change, we propose a metafrontier non-radial Luenberger productivity indicator to measure the totalfactor environmentally sensitive productivity growth. Compared with the methodologies adopted in existing energy and environmental studies (e.g. Wang et al., 2013, 2015; Zhang and Wei, 2015),2 the key innovativeness of the proposed approach is that it can handle both non-zero slack variables and cross-group heterogeneity simultaneously. We then use the proposed approach to measure environmental productivity growth and its patterns in the PLEEZ at a county level.