Energy, Environment and Transitional Green Growth in China (eBook)

Ruizhi Pang (PhD in Economics, 2002, Nankai University; Professor of Institute of Industrial Economics at Nankai University). Dr. Pang’s fields of research are Industrial Organization, Performance Evaluation and Industrial Development. In the past 10 years, she has published more than 40 academic papers and 5 monographs, some influential papers has been reprinted by Xinhua Digest (TOP 1 journal in social science in China). Dr. Pang has chaired 7 research projects from Social Science Fund, the Ministry of Education Fund etc. She has also finished more than 20 research reports which sponsored by national government agencies and provincial government institutions. She also serves as anonymous reviewer of well-known academic journals, such as Empirical Economics, Economic Research etc.Dr. Xuejie Bai, professor in economics at Nankai University, is the vice dean of College of Economic and Social Development at Nankai University, and a member of China Society of Industrial Economics. Dr Bai Xuejie has engaged in the teaching and research of industrial economics for more than 20 years, whose fields of research are industrial development and industrial policy, productivity and efficiency, and Japanese economy and Japanese industrial development. In recent years, she has published 5 monographs and several influential papers in industrial economics and industrial development. She has also presided more than 20 research projects in the areas of industrial planning, regional industry analysis, and industrial development strategy, which were sponsored by government agencies at central level and provincial levels.Knox Lovell is Honorary Professor with the Centre for Efficiency and Productivity Analysis in the School of Economics at the University of Queensland. He has served as Editor-in-Chief of the Journal of Productivity Analysis, and he has co-authored several books, including Production Frontiers (with Färe&Grosskopf), Stochastic Frontier Analysis (with Kumbhakar), and Productivity Accounting (with Grifell-Tatje), all for Cambridge University Press. He also hosts The Jazz Show on radio station 4zzz, 102.1 Fm, in Brisbane, Australia.

Contents 5
The Expert Overviews 7
1 Editors’ Introduction 8
1 Background 8
1.1 Background for the Volume 8
1.2 Background on China’s Economic Growth Model and Its Transition 9
2 Part I: The Expert Overviews 14
2.1 Chapter 2 14
2.2 Chapter 3 15
2.3 Chapter 4 15
3 Part II: Studies in Energy and Environment 16
4 Part III: Studies in Transitional Growth 18
Some Useful References and Links 18
2 Composite Indicators for Sustainability Assessment: Methodological Developments 20
1 Introduction 20
2 Generic Procedure of Constructing CSI 22
3 MADM Methods 23
3.1 Normalization Methods 24
3.2 Aggregation Methods 25
3.2.1 Simple Additive Weighting 26
3.2.2 Weighted Product Method 26
3.2.3 Weighted Displaced Ideal 27
3.2.4 Social Multi-criterion Evaluation Method 27
3.3 Weighting Methods 28
3.3.1 Exogenous Methods 28
3.3.2 Endogenous Methods 29
3.3.3 Hybrid Methods 29
4 BOD Methods 30
4.1 Basic BOD Model 30
4.2 Weight Restriction in Basic BOD Model 31
4.3 Extensions of Basic BOD Model 32
5 The CSI Robustness and Beyond 34
5.1 Selection Principle 34
5.2 Uncertainty and Sensitivity Analysis 35
5.3 Beyond Rankings 36
6 Conclusions 37
Acknowledgements 37
References 37
3 Pollution Meets Efficiency: Multi-equation Modelling of Generation of Pollution and Related Efficiency Measures 42
1 Introduction 42
2 Environmental Economics 43
2.1 Environmental Economics Post Externality Models 44
2.2 The Materials Balance 45
2.3 Literature on Modelling Production of Goods and Generation of Waste 47
3 Joint Production 52
3.1 The Historical Background 52
3.2 Frisch on Joint Production 54
3.3 Restrictions on Production Models 57
4 Multi-equation Models for Desirable and Undesirable Outputs 58
4.1 The Frisch Multi-equation Model 59
4.2 Substitution Possibilities 60
4.3 The Materials Balance and the Multi-equation Model 62
5 End-of-Pipe Abatement and Regulation 63
5.1 End-of-Pipe 63
5.2 Imposing a Constraint on Emission 66
6 Allowing for Inefficient Operations 67
6.1 Defining Inefficiency 67
6.2 The Production Possibility Set 69
6.3 Weak Disposability 69
6.4 Recent Attempts to Improve the Single-Equation Model 71
7 Efficiency Measures and Their Estimation in the Multi-equation Model 73
7.1 The Production Possibility Sets of the Factorially Determined Multi-equation Model 73
7.2 The Multi-equation By-Product Model 74
7.3 The Efficiency Measures 75
8 Conclusions 79
Acknowledgment 81
References 81
4 Environmental Productivity Growth in Consumer Durables 85
1 Introduction 85
2 Particular Features of Consumer Durables 87
2.1 Typical Example 90
3 Conceptual Modeling of Consumer Durables 92
3.1 Conventional Specification of Polluting Technology 92
3.2 Direct Proportionality and Materials Balance 95
4 Measurement of Environmental Productivity 97
4.1 Brief Overview of Conventional Measures 97
4.2 Malmquist-type Index for Consumer Durables 100
5 Empirical Case: New Passenger Cars in Finland 104
6 Concluding Remarks 107
Acknowledgements 108
References 108
Studies in Energy and Environment 112
5 Revisiting Reasons for Ten Years of Power Shortages in China 113
1 Introduction 113
2 Literature Review 116
3 Methodology on Decomposition of Productivity Change 119
3.1 Non-parametric Approach of Decomposing Productivity Change 119
3.2 Non-parametric Approach of Calculating Productivity Change 120
3.3 Parametric Approach of Decomposing Productivity Change in the Case of Production Function 121
3.4 Parametric Approach of Calculating Productivity Change 123
4 Data Selection and Model Specification 124
4.1 Model Specification 124
4.2 Data Description 127
5 Estimation Results and Analysis 129
5.1 Technical Efficiency 129
5.2 TFP Change and Its Sources 132
5.3 Reasons for Low Utilisation Rates of Installed Capacity 134
6 Concluding Remarks 136
Acknowledgements 137
References 137
6 Allocation Schemes and Efficiencies of China’s Carbon and Sulfur Emissions 141
1 Introduction 141
2 Research Method and Data Processing 143
2.1 Existing Research on Allocation Mechanism 143
2.2 Zero-Sum Gain Model 144
2.3 Variable Selection and Data Sources 147
3 Empirical Analysis 149
3.1 Comparison Between ZSG Allocation, National Administrative Allocation, and Actual Emissions in 2010 149
3.1.1 Twenty Provinces or Cities Were Assigned an Excessively High Administrative Sulfur-Emission Quota 149
3.1.2 Significant Provincial Difference in the Completion Degree of Sulfur-Dioxide-Emission Reduction 151
3.1.3 The Middle and Western Regions Should Shoulder More Responsibilities in Terms of Reducing Sulfur Emission 152
3.2 Comparison Between the ZSG Allocation and Administrative Allocation in 2015 154
3.2.1 Under the ZSG Allocation Scheme, There Were 16 Provinces and Cities in China that Must Lower Their Administrative Quota of Carbon Emission 154
3.2.2 When Allocating Emission with an Administrative Scheme, the Chinese Government Adopted a Unified Standard to Fit All Regions 154
3.2.3 Nationwide, 19 Provinces and Cities Were Being Granted an Excessively High Administrative Sulfur-Emission Quota 156
4 Conclusions 159
Acknowledgments 160
References 160
7 Carbon Productivity and Carbon Shadow Price in China’s Power Industry: An Endogenous Directional Distance Function Approach 163
1 Introduction 163
2 Methodologies 165
2.1 Endogenous Directional Distance Function 165
2.2 Shadow Price Estimation of Unintended Output 166
2.3 Global Luenberger Productivity Indicator 168
3 Data 169
4 Empirical Analyses 170
4.1 Carbon Productivity Change Analysis 170
4.2 Relative Shadow Price of CO2 Emissions 172
5 Conclusions and Policy Implications 175
Acknowledgements 177
References 177
8 The Context-Dependent Total-Factor Energy Efficiency of China’s Regions 179
1 Introduction 179
2 Methodology 180
3 Context-Dependent DEA and TFEE 180
4 Russell-Based Directional Distance Function (RDDF) with Undesirable Outputs 181
5 Data Sources and Variables 183
6 Frontier Levels by CD-DEA and CD-TFEE 183
7 Concluding Remarks 188
References 188
9 Was Economic Growth in China Environmentally Friendly? A Case Study of the Chinese Manufacturing Sector 190
1 Introduction 190
2 Protecting the Environment Versus the Production of Goods 191
3 Technical Efficiency Measures with Undesirable Outputs 193
4 Data and Results 194
5 The Environmentally Unfriendly Provinces 202
6 Conclusion 206
References 207
10 Environmental and Energy Efficiencies Using the Stochastic Frontier Cost  Function Type 209
1 Introduction 209
2 Theoretic Model 211
3 Empirical Test Results 214
4 Conclusions 220
References 221
11 Evaluating Performance of New Energy—Evidence from OECD 222
1 Introduction 222
2 Literature Review 224
3 Research Method 227
3.1 DEA Model 227
3.2 Dynamic DEA 228
3.3 Meta-Frontier DN-DEA 229
3.3.1 Meta-Frontier (MF) 229
3.3.2 Group-Frontier (GF) 230
3.3.3 Technology Gap Ratio (TGR) 231
4 Empirical Result and Discussion 231
5 Conclusions 239
References 240
Studies in Transitional Green Growth 244
12 Factor Price Distortion, Technological Innovation Pattern and the Biased Technological Progress of Industry in China: An Empirical Analysis Based on Mediating Effect Model 245
1 Introduction 245
2 Literature Review 246
3 Mechanism Analysis of How Factor Price Distortion Affects Industrial Technological Progress Direction 248
3.1 Direct Effect Mechanism of Factor Price Distortion on Technological Progress Bias 249
3.1.1 Relative Distortion Degrees of Capital and Labor Prices Determine the Bias of Technological Progress 249
3.1.2 Industrial Difference of Factor Price Distortion—Based on the Law of Diminishing Factor Marginal Returns 249
3.2 Indirect Effect Mechanism of Factor Price Distortion on Technological Progress Bias 250
3.2.1 The More Factor Price Is Distorted, the More Technological Innovation Pattern Is Biased Towards Technology Introduction 250
3.2.2 When the Factor Price Is Distorted, the Higher the Proportion of Technology Introduction, More Capital-Biased the Technological Progress Is—Based on “Transnational Technology Diffusion Theory” 251
3.2.3 Differences Among Industries: The Indirect Effects of Factor Price Distortion on Technological Progress Bias on Capital-Intensive Industries Are Bigger Than that of Labor-Intensive Industries 252
4 Empirical Methods and Variable Description 252
4.1 Calculation Method of Industrial Technological Progress Bias 252
4.2 Calculation Method of Factor Price Distortion Degree 255
4.3 Design of Regression Model—Mediating Effect Model 256
4.4 Description of Variables and Data 257
5 Analysis of Measured Results of China’s Industrial Technological Progress Bias and Factor Price Distortion 258
5.1 China’s Current Industrial Technological Progress Is Generally Biased Towards Capital 258
5.2 Factor Prices in China’s Industries Is Seriously Negatively Distorted and Have not Been Mitigated yet 260
5.3 China’s Capital-Intensive Industrial Technological Progress Is Strongly Biased Towards Capital 261
5.4 Factor Intensity of an Industry Determines the Price Distortion Degrees of Different Factors 262
6 Empirical Analysis of Mediating Effect Model 263
6.1 Estimate of the Benchmark Model 263
6.2 Endogenous Problems and the Regression of Instrumental Variable 2SLS 265
6.3 Examination of the Mediating Effect 267
6.4 Analysis of Estimated Results Based on Characteristics of Industries 268
7 Conclusion and Perspective 269
References 271
13 Environmental Innovation and Green Transformation of Economic Growth Pattern: Evidence from China 274
1 Introduction 274
2 Literature Review 275
3 Empirical Model and Variables 276
3.1 Specifications of Empirical Model 276
3.2 Variables and Data Sources 277
3.2.1 The Indicator of Green Transformation of Economic Growth Pattern 277
3.2.2 Environmental R& D and Traditional R&
3.2.3 Control Variables 278
4 Empirical Results and Discussions 279
4.1 Effect on the Green Transformation of Economic Growth Pattern 279
4.2 Robustness Analysis 280
5 Conclusions 281
Acknowledgements 282
Appendix A. The Estimated Results of Eq. (2) 282
References 283
14 Study of Regional Efficiency in China: Perspectives of FDI and Green Development 285
1 Introduction 285
2 Hypotheses 287
3 Methodology 289
4 Empirical Analysis 293
4.1 Data Sources and Input-Output Variables 293
4.2 Empirical Results 294
4.3 Discussion 298
5 Conclusions 300
References 301
15 Emissions Cost and Value-Added Benefit of Exports in China: An Analysis Based on a Global Input-Output Model 303
1 Introduction 303
2 Methodology 305
2.1 Measurement of Emissions and Value-Added Created by Exports 305
2.2 Decomposition of Differences in PIVE Across Countries 307
3 Data 309
4 Main Results 309
4.1 Value-Added and Emissions Generated by Export Production in China 309
4.2 Pollution Intensities of Value-Added Exports in China 312
4.3 Decomposition of Gaps in Pollution Intensities of Value-Added Exports Across Countries 313
5 Conclusion and Policy Implications 316
Acknowledgements 318
References 318