Economic Factorial Analysis of CO2 Emissions: The Divisia Index with Interconnected Factors Approach
This paper presents a method of economic factorial analysis of the CO2 emissions based on the extension of the Divisia index to interconnected factors. This approach, contrary to the Kaya identity, considers three main factors of the CO2 emissions: gross domestic product, energy consumption, and population - as equally important, and allows for accounting of all of them simultaneously. The three factors are included into analysis together with their carbon intensities that allows for obtaining a comprehensive picture of the change in the CO2 emissions. A computer program in R-language that is available for free download serves automation of the calculations. A case study of the U.S. carbon dioxide emissions is used as an example.
[1] Albert, A. Regression and Moore - Penrose Pseudoinverse, Academic
Press, New - York, 1972.
[2] Diewert, W. Index Numbers. In Diewert, W. and Nakamura, A. (Eds.)
Essays in Index Number Theory. Vol. 1, Chapter 5. Elsevier Science
Publishers, 1993.
[3] Divisia, F. L'indice Monetaire et la Theorie de la Monnaie, Revue
d'Economic Politique, 1925; 39(5):980-1020.
[4] International energy outlook 2011. U.S. Bureau of Economic Analysis,
2011. Available at www.eia.gov.
[5] Kaya, Y., Impact of Carbon Dioxide Emission Control on GNP Growth:
Interpretation of Proposed Scenarios. Paper presented to the IPCC
Energy and Industry Subgroup, Response Strategies Working Group,
Paris, 1990. (mimeo).
[6] Laspeyres, E. Die Berechnung einer mittleren Waarenpreissteigerung.
Jahrbücher für Nationalökonomie und Statistik, 1871;16: 296–315.
[7] Lozano, S., Gutiérrez, E.Non-parametric frontier approach to modelling
the relationships among population, GDP, energy consumption andCO2
emissions. Ecological Economics, 2008, 2, 66 (4); 687-699.
[8] Maital, S. and Vaninsky, A. Productivity paradoxes and their resolution.
Journal of Productivity Analysis, 2000, 14(3); 191-207.
[9] Meerovich, V. Turnover of Financial Funds and Efficiency of
Production. (Oborot Sredstv i Effektivnost' Proizvodstva), Financy,
Moscow, 1974. (In Russian.)
[10] Paasche, H. Über die Preisentwicklung der letzten Jahre nach den
Hamburger Börsennotirungen. Jahrbücher für Nationalökonomie und
Statistik 1874; 23:168–178.
[11] Politics. The Economist, 2013, July 13th -19th, 8.
[12] R Development Core Team. R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna,
Austria, 2011. ISBN 3-900051-07-0, URL http://www.R-project.org/.
[13] Sheremet, A. (Ed.) Economic analysis of business activity
(Ekonomicheskii analiz khozyaistvennoi deyatel'nosti). Economika,
1979. (In Russian).
[14] Sheremet, A., Dei, G. and Shapovalov, V. Method of the chain
substitutions and development of the factorial analysis of the economic
indicators (Metod tsepnykh podstanovok i sovershenstvovanie
faktornogo analiza ekonomicheskikh pokazatelei). Vestnik
Moskovskogo Universiteta, Ser. Ekonomika, 1971; 4:62-69. (In
Russian).
[15] Vaninsky, A. Analysis of production efficiency based on the generalized
integral method (Analiz effectivnosti proizvodstva na osnove
obobschennogo ntegral'nogo metoda) In Aksenenko, A. (Ed.)
Accounting and analysis of production efficiency (Uchet i analiz
effectivnosti proizvodstva). 6.1;212-25. Financy i Statistika, Moscow,
1986. (In Russian)
[16] Vaninsky, A. Factorial Analysis of Economic Activity. (Factornyi
Analiz Khozyaistbennoi Deyatel'nosti), Financy i Statistika, Moscow,
1987. (In Russian)
[17] Vaninsky, A. Generalization of the integral method of economic analysis
to interconnected and derived factors. Automation and Remote Control,
184, 44: 8:2, 1074 - 1083.
[18] Vaninsky, A. and Meerovich, V. Problems of the methodology of
analysis of the impact of structural change on the indicators of
production efficiency. (Voprosy metodologii analiza vliyaniya
strukturnykh sdvigov na pokazateli effectivnosti proizvodstva.)
Proceedings of the National Scientific Conference "Economic Leverages
of the Efficiency of Using Material, Labor, Financial, and Natural
Resourses", 2, 105 - 107, Central Economic - Mathematical Institute,
Moscow, 1978. (In Russian)
[19] U.S. Bureau of Economic Analysis (BEA) - www. bea.gov.
[20] U.S. Energy Information Adinistration (EIA) - www.eia.gov.
[1] Albert, A. Regression and Moore - Penrose Pseudoinverse, Academic
Press, New - York, 1972.
[2] Diewert, W. Index Numbers. In Diewert, W. and Nakamura, A. (Eds.)
Essays in Index Number Theory. Vol. 1, Chapter 5. Elsevier Science
Publishers, 1993.
[3] Divisia, F. L'indice Monetaire et la Theorie de la Monnaie, Revue
d'Economic Politique, 1925; 39(5):980-1020.
[4] International energy outlook 2011. U.S. Bureau of Economic Analysis,
2011. Available at www.eia.gov.
[5] Kaya, Y., Impact of Carbon Dioxide Emission Control on GNP Growth:
Interpretation of Proposed Scenarios. Paper presented to the IPCC
Energy and Industry Subgroup, Response Strategies Working Group,
Paris, 1990. (mimeo).
[6] Laspeyres, E. Die Berechnung einer mittleren Waarenpreissteigerung.
Jahrbücher für Nationalökonomie und Statistik, 1871;16: 296–315.
[7] Lozano, S., Gutiérrez, E.Non-parametric frontier approach to modelling
the relationships among population, GDP, energy consumption andCO2
emissions. Ecological Economics, 2008, 2, 66 (4); 687-699.
[8] Maital, S. and Vaninsky, A. Productivity paradoxes and their resolution.
Journal of Productivity Analysis, 2000, 14(3); 191-207.
[9] Meerovich, V. Turnover of Financial Funds and Efficiency of
Production. (Oborot Sredstv i Effektivnost' Proizvodstva), Financy,
Moscow, 1974. (In Russian.)
[10] Paasche, H. Über die Preisentwicklung der letzten Jahre nach den
Hamburger Börsennotirungen. Jahrbücher für Nationalökonomie und
Statistik 1874; 23:168–178.
[11] Politics. The Economist, 2013, July 13th -19th, 8.
[12] R Development Core Team. R: A language and environment for
statistical computing. R Foundation for Statistical Computing, Vienna,
Austria, 2011. ISBN 3-900051-07-0, URL http://www.R-project.org/.
[13] Sheremet, A. (Ed.) Economic analysis of business activity
(Ekonomicheskii analiz khozyaistvennoi deyatel'nosti). Economika,
1979. (In Russian).
[14] Sheremet, A., Dei, G. and Shapovalov, V. Method of the chain
substitutions and development of the factorial analysis of the economic
indicators (Metod tsepnykh podstanovok i sovershenstvovanie
faktornogo analiza ekonomicheskikh pokazatelei). Vestnik
Moskovskogo Universiteta, Ser. Ekonomika, 1971; 4:62-69. (In
Russian).
[15] Vaninsky, A. Analysis of production efficiency based on the generalized
integral method (Analiz effectivnosti proizvodstva na osnove
obobschennogo ntegral'nogo metoda) In Aksenenko, A. (Ed.)
Accounting and analysis of production efficiency (Uchet i analiz
effectivnosti proizvodstva). 6.1;212-25. Financy i Statistika, Moscow,
1986. (In Russian)
[16] Vaninsky, A. Factorial Analysis of Economic Activity. (Factornyi
Analiz Khozyaistbennoi Deyatel'nosti), Financy i Statistika, Moscow,
1987. (In Russian)
[17] Vaninsky, A. Generalization of the integral method of economic analysis
to interconnected and derived factors. Automation and Remote Control,
184, 44: 8:2, 1074 - 1083.
[18] Vaninsky, A. and Meerovich, V. Problems of the methodology of
analysis of the impact of structural change on the indicators of
production efficiency. (Voprosy metodologii analiza vliyaniya
strukturnykh sdvigov na pokazateli effectivnosti proizvodstva.)
Proceedings of the National Scientific Conference "Economic Leverages
of the Efficiency of Using Material, Labor, Financial, and Natural
Resourses", 2, 105 - 107, Central Economic - Mathematical Institute,
Moscow, 1978. (In Russian)
[19] U.S. Bureau of Economic Analysis (BEA) - www. bea.gov.
[20] U.S. Energy Information Adinistration (EIA) - www.eia.gov.
@article{"International Journal of Business, Human and Social Sciences:65483", author = "Alexander Y. Vaninsky", title = "Economic Factorial Analysis of CO2 Emissions: The Divisia Index with Interconnected Factors Approach", abstract = "This paper presents a method of economic factorial analysis of the CO2 emissions based on the extension of the Divisia index to interconnected factors. This approach, contrary to the Kaya identity, considers three main factors of the CO2 emissions: gross domestic product, energy consumption, and population - as equally important, and allows for accounting of all of them simultaneously. The three factors are included into analysis together with their carbon intensities that allows for obtaining a comprehensive picture of the change in the CO2 emissions. A computer program in R-language that is available for free download serves automation of the calculations. A case study of the U.S. carbon dioxide emissions is used as an example.
", keywords = "CO2 emissions, Economic analysis, Factorial analysis, Divisia index, Interconnected factors.", volume = "7", number = "10", pages = "2776-6", }
