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Energy Demand in Industry: What Factors Are Important? (Green Energy and Technology)

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en Limba Engleză Hardback – 19 Aug 2015
The book presents a stochastic analysis based on production risk and application of this method in the industrial sector under production risk where energy use is an input factor. Using South Korea as a case study, the book empirically models energy demand at the industrial level and analyzes the results to identify key determinants of energy demand, productions level, productions risk and energy usage efficiency.
Particular attention is paid to the factors that enhance production risk or increase variations in energy input during production. A dynamic panel model is specified and applied to 25 Korean industrial sectors over the period 1970-2007. The determinants of energy usage are identified and their effects in the form of elasticities of energy usage are estimated. In addition the structural changes in the energy demand pattern are explored. Stochastic production technology is applied to create two primary models: A production model where the energy usage is a determinant of output and an energy demand model based on an inverted factor demand model where demand is a key determinant of the level of energy usage.
The findings reveal that: First, there are large variations in the degree of overuse or inefficiency in energy usage among the individual industries and over time; second, ICT (information and communication technology) capital and labor are substituting energy; third, ICT capital and value added services are two input factors decreasing the variability of energy demand while non-ICT capital, material and labor are increasing the variability of energy demand.  Finally, the results suggest that technical progress contributes more to the increase of mean of energy demand than to the reduction of the level of risk. An emerging recommendation is that industries increase the level of ICT capital and digitalization and invest more in R&D activities and value added services to reduce the uncertainty related to their demand for energy. This study forms the structure of the demand for energy under stochastic production risk for the South Korean industrial sector. Public research programs aimed at the industrial sector should be concerned about both mean and risk properties in research on new technologies and in the investigation of possible alternative energy inputs.
This book describes the state of the art in energy usage analysis and production risk, applying factor requirement methodology. It will be of use as a main or supplementary text in the teaching of advanced graduate courses but also as a reference for those working on empirically advanced research. The book is an important addition to the existing literature on industrial development, with its focus on energy as a core production input.
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Specificații

ISBN-13: 9789401799522
ISBN-10: 9401799520
Pagini: 196
Ilustrații: 35 schwarz-weiße Tabellen, Bibliographie
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.47 kg
Ediția: 1st ed. 2015
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria Green Energy and Technology

Locul publicării: Dordrecht, Netherlands

Public țintă

Research

Cuprins

1 OVERVIEW.
1.1 Introduction. 1.2 Problem Description. 1.3 Purpose of Research. 1.4 Significance of the Study. 1.5 Research Design. 1.6 Empirical Motivations. 1.7 Assumptions and Limitations. 1.8 Operational Definitions. 1.9 Expected Results. 1.10 The Structure of the Book. 1.11 References.
2 HISTORY OF ECONOMIC DEVELOPMENT IN SOUTH KOREA.
2.1 Introduction. 2.2 Stages of the Industrial and Technological Polices. 2.3 Energy Consumption. 2.4 Energy Conservation and Structural Changes in the South Korean Economy. 2.5 Energy efficiency.       2.6 Summary. 2.7 References.
3 SURVEY OF EXISTING RESEARCHES RELATED TO ENERGY DEMAND.   
3.1 Introduction. 3.2 Inter-Factor Substitutability and Complementarity. 3.3 Energy Efficiency. 3.4 Energy Demand. 3.5 The Elasticity of Demand.      3.6 Critique of Previous Researches. 3.7 Summary. 3.8 References.  
4 SURVEY OF EXISTING RESEARCHES RELATED TO PRODUCTION RISK.
4.1 Introduction. 4.2 Some Concepts in Expected Utility Theory. 4.3 The Argument of the Utility Function. 4.4 Production Risk and the Theory of Firm Behavior. 4.5 The Production Risk. 4.6 Mean Factor Inputs and Output Variance. 4.7 Technical Efficiency. 4.8 Critique of Previous Researches. 4.9 Summary. 4.10 References.         
5 ECONOMETRICS OF PANEL DATA ESTIMATION.    
5.1 Introduction. 5.2 Fixes Effect and Random Effect Models. 5.3 The Characteristics of Panel Data. 5.4 Industry Heterogeneity and Heteroskedasticity. 5.5 Industry Heterogeneity and Panel Data Availability. 5.6 Theoretical Framework. 5.7 Research Questions and Hypothesis. 5.8 The Econometric Model. 5.9 Model Specification. 5.10 Sampling Distribution Properties. 5.11 Summary. 5.12 References.
6 ENERGY DEMAND DATA.         
6.1 Data Source. 6.2 Population and Sampling Strategy. 6.3 Industry Sector Classification. 6.4 The Dependent and the Independent Variables. 6.5 Multicollinearity and Validation of Results. 6.6 Overview of Statistical Analysis.          6.7 Energy Intensity in the Industrial Sector. 6.8 Empirical Test for Heterogeneity. 6.9 Summary. 6.10 References.      
7 ENERGY DEMAND MODELS ESTIMATION.   
7.1 Cobb-Douglas production function. 7.2 The Translog production function. 7.3 Summary. 7.4 References. 7.A Appendix:  Elasticities Estimates for Translog Production Function.
8 ENERGY DEMAND MODEL I.
8.1 Energy Demand not Accounting for Risk. 8.2 The Overall Performance. 8.3 Regularity Conditions Tests. 8.4 Energy Demand Elasticities. 8.5 The Rate of Technical Change. 8.6 Hypotheses Testing. 8.7 Summary. 8.8 References. 8.A Appendix: Elasticities Estimates for Translog Energy Demand.
9 ENERGY DEMAND MODEL II.
9.1 Energy Demand Model Accounting for Risk. 9.2 Empirical Tests for Heteroskedasticity. 9.3 A Three Stage FGLS estimation. 9.4 The Overall Performance. 9.5 The Regularity Conditions Tests. 9.6 Specification Test. 9.7 Energy Demand Elasticities. 9.8 The Marginal Effects. 9.9 Technical efficiency. 9.10 Hypotheses Testing. 9.11 Summary. 9.12 References. 9.A Appendix: Summary Data, Parameter Estimates, and Elasticities for Translog Energy Demand accounting for Risk.
10 SUMMARY AND CONCLUSION.
10.1 Summary of Results. 10.2 Input Elasticities for Production Function. 10.3 Elasticities in Energy Demand Model. 10.4 Return to Scale. 10.5 Marginal Effects. 10.6 Technical Efficiency. 10.7 Conclusion about the Research Questions and Their Hypotheses. 10.8 The Research Questions. 10.9 Overview of Analysis and Hypothesis. 10.10 Implications for Industry and Policy Makers. 10.11 Conclusions and Practical Recommendations.

Notă biografică

Nabaz T. Khayyat, a Kurdish citizen, an Engineering Economist, has a PhD in economics, from Swiss Management University, Zurich, Switzerland and a PhD in Engineering and IT Policy from Seoul National University, South Korea. He worked for the United Nations Mine Action Program for many years where he acquired the knowledge and managerial skills in mine action information systems. His research interest are mainly in the areas of energy economics, demand forecasting, productivity analysis and production risk. He has a number of published books and journal articles.

Textul de pe ultima copertă

The book presents a stochastic analysis based on production risk and application of this method in the industrial sector under production risk where energy use is an input factor.  Using South Korea as a case study, the book empirically models energy demand at the industrial level and analyzes the results to identify key determinants of energy demand, productions level, productions risk and energy usage efficiency.
Particular attention is paid to the factors that enhance production risk or increase variations in energy input during production. A dynamic panel model is specified and applied to 25 Korean industrial sectors over the period 1970-2007. The determinants of energy usage are identified and their effects in the form of elasticities of energy usage are estimated. In addition the structural changes in the energy demand pattern are explored. Stochastic production technology is applied to create two primary models: A production model where the energy usage is a determinant of output, and an energy demand model based on an inverted factor demand model where demand is a key determinant of the level of energy usage.
The findings reveal that: First, there are large variations in the degree of overuse or inefficiency in energy usage among the individual industries and over time; second, ICT (information and communication technology) capital and labor are substituting energy; third, ICT capital and value added services are two input factors decreasing the variability of energy demand while non-ICT capital, material and labor are increasing the variability of energy demand.  Finally, the results suggest that technical progress contributes more to the increase of mean of energy demand than to the reduction of the level of risk.  An emerging recommendation is that industries increase the level of ICT capital and digitalization and invest more in R&D activities and value added services to reduce the uncertainty related to their demand for energy. This study forms the structure of the demand for energy under stochastic production risk for the South Korean industrial sector. Public research programs aimed at the industrial sector should be concerned about both mean and risk properties in research on new technologies and in the investigation of possible alternative energy inputs.
This book describes the state of the art in energy usage analysis and production risk, applying factor requirement methodology. It will be of use as a main or supplementary text in the teaching of advanced graduate courses but also as a reference for those working on empirically advanced research. The book is an important addition to the existing literature on industrial development, with its focus on energy as a core production input.

Caracteristici

Evaluates the structure of energy demand and its related risks in the industrial sectors
Covers important ways in which industries can reduce their energy consumption, applying stochastic production risk with factor demand to form an energy demand model
Demonstrates how increasing the level of ICT capital, high investment in R&D will reduce the variability of energy demand and its related risk
Shows that high-skilled labor reduces the risk of energy use in the production