Productivity Growth-Accounting for Undesirable Outputs and Its Influencing Factors: The Case of China

Abstract

Abstract:Presently, China's social development is facing the dilemma of supporting economic growth and reducing emissions. Therefore, it is crucial to analyse productivity growth and examine its relationship with influencing factors in China. This study evaluated the total factor productivity (TFP) growth of 30 provinces in China by adopting the Malmquist-Luenberger (ML) productivity index and incorporating undesirable outputs from 2011-2014. Then, a Tobit regression model was employed to explore the factors that influence China's TFP growth. The results show that the average annual growth of the Malmquist-Luenberger productivity index was lower than that of the traditional Malmquist (M) productivity index growth during the research period. The findings reveal several key conclusions: First, the true TFP growth in China will be overestimated if undesirable outputs are ignored. Second, technical changes are the main contributor to TFP growth. Third, there are huge regional disparities of productivity growth in China. Fourth, coal intensity, environmental regulations, and industrial structure have significantly negative effects on productivity growth, while real per capita gross domestic product (GDP) and foreign direct investment (FDI) have strongly positive effects on productivity growth.

Impact of Foreign Direct Investment on Environmental Performance

“…This study measures the EP of developed and developing countries. According to existing literature, we can know that labor, capital and energy consumption are the most frequently used input indicators, and gross domestic product (GDP) and carbon dioxide emission are the most frequently used desirable and undesirable outputs respectively in measuring environmental efficiency [15]. In this paper, we also employ input indicators (labor input, capital input and energy input), desirable output (real GDP) and undesirable output (carbon dioxide emission) to measure the EP.…”

“…They found that regardless of the industry under the high and low environmental regulations, capital-based FDI has a significantly positive spillover effect. Zhang et al [15] indicated that FDI has a significantly positive correlation with GTFP growth. On the other hand, FDI has a negative effect on GTFP.…”

Eco-Efficiency of the English and Welsh Water Companies: A Cross Performance Assessment

“…Because the eco-efficiency score is a truncated variable with values between zero and one, Tobit regression was used to derive robust estimates. Several studies in the past used Tobit analysis to understand the drivers of inefficiency in the production process (see for instance [ 4 , 12 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]). The model employed was defined as follows: where is the cross eco-efficiency score of each water company at any time obtained from Equation (7), is the intercept term, is a set of environmental variables and π k are its related parameters to be estimated, denotes firm-specific unobserved heterogeneity (e.g., managerial inability), and is the error term which fulfils the normal distribution, .…”

A Dynamic Analysis to Evaluate the Environmental Performance of Cities in China

“…Compared with the traditional DEA model, the Malmquist-Luenberger (ML) model is an efficient method to analyze undesirable outputs [18]. The main difference is that directional distance functions are used to construct the ML index but the Shepherd distance functions are used in the traditional DEA model [19]. In this paper, to identify the undesirable environmental impact, the meta-frontier ML index was used to develop a dynamic evaluation model of urban environmental performance in China [20].…”