Driving forces of different productivity models

Halkos, George and Bampatsou, Christina (2016): Driving forces of different productivity models.

Abstract

In the present study, Data Envelopment Analysis (DEA) is used for the period spanning from 1980 to 2012 and for a total of 32 countries which are classified into four groups, according to their level of development (Developing, BRICS, Developed, G7). DEA allows us to measure technical efficiency under constant (CRS) and variable (VRS) returns to scale and also the Malmquist index and its components (TECHCH, EFFCH, PECH, SECH). Furthermore, we develop an order-α approach for the determination of partial frontiers. An output oriented model is applied. Labor and capital are used as inputs while the GDP index is used as output. Subsequently, energy is incorporated in the model as an additional input variable and CO2 emissions as undesirable output. A comparison of productivity indices as derived from the analysis, allows us to highlight the different levels of productivity before and after the integration of energy and CO2 emissions as additional variables, for each group of countries and therefore their sustainability gaps.

• Item Type: MPRA Paper
• Language: English
• Keywords: Data Envelopment Analysis; Malmquist Index; Order-α approach; Energy; CO2 emissions.
• Subjects: O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O11 - Macroeconomic Analyses of Economic Development; O - Economic Development, Innovation, Technological Change, and Growth > O5 - Economywide Country Studies > O57 - Comparative Studies of Countries; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q0 - General; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q0 - General > Q01 - Sustainable Development; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q43 - Energy and the Macroeconomy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q50 - General; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R15 - Econometric and Input-Output Models ; Other Models

References

Apergis, N., Aye, G. C., Barros C. P., Gupta, R. and Wanke, P. (2015). Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs, Energy Economics, Vol. 51, pp. 45-53.

Bădin, L., Daraio, C. and Simar, L. (2012). How to measure the impact of environmental factors in a nonparametric production model?, European Journal of Operational Research, Vol. 223, pp. 818–833.

Caves, D., Christensen, L. and Diewert, W.E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity, Econometrica, Vol. 50, pp. 1393–1414.

Chung, Y. H., Färe, R. and Grosskopf, S. (1997)/ Productivity and Undesirable Outputs: A Directional Distance Function Approach/, Journal of Environmental Management, Vol. 51, pp. 229–40.

Coelli, T.J., Rao, D.S.P., O’Donnell, C.J. and Battese, G.E. (2005). An Introduction to Efficiency and Productivity Analysis, 2nd ed., Springer, New York.

Daraio, C. and Simar, L. (2007). Advanced Robust and Nonparametric Methods in Efficiency Analysis, Springer US. New York, USA.

Fare, R., Grosskopf, S. and Lovell, C.A.K. (1994). Production Frontiers, Cambridge University Press, Cambridge.

Fischer, M. M., Scherngell, T. and Reismann, M. (2009). Knowledge spillovers and total factor productivity: evidence using a spatial panel datamodel, Geographical Analysis, Vol. 41 No. 2, pp. 204– 220.

Halkos, G. (2014). The Economics of Climate Change Policy: Critical review and future policy directions, MPRA Paper 56841, University Library of Munich, Germany.

Halkos, G. and Tzeremes, N. (2009). Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis, Ecological Economics, vol. 68 No. 7, pp. 2168-2176.

Halkos, G. and Tsilika, K. (2014). Analyzing and visualizing the synergistic impact mechanisms of climate change related costs, MPRA Paper 55459, University Library of Munich, Germany.

Halkos, G. and Tsilika, K. (2016). Climate change impacts: Understanding the synergetic interactions using graph computing, MPRA Paper 75037, University Library of Munich, Germany.

Halkos, G. and Polemis, M. (2016). The good, the bad and the ugly? Balancing environmental and economic impacts towards efficiency, MPRA Paper 72132, University Library of Munich, Germany.

Kitcher, B., McCarthy, I. P., Turner, S. and Ridgway, K. (2013) ‘Understanding the effects of outsourcing: unpacking the total factor productivity variable’, Production Planning & Control, Vol. 24 No. 4-5, pp.308–317.

Malmquist, S. (1953). Index numbers and indifference surfaces, Trabajos de Estadistica, Vol. 4, pp. 209-242.

Kortelainen, M., (2008). Dynamic environmental performance analysis: A Malmquist index approach, Ecological Economics, Vol.64 No. 4, pp. 701–715.

Long, Xingle, Xicang Zhao, and Faxin Cheng. (2015). The comparison analysis of total factor productivity and eco-efficiency in China's cement manufactures, Energy Policy, Vol.81, pp. 61-66.

Mahlberg, Bernhard, Mikulas Luptacik and Biresh K. Sahoo (2011). Examining the drivers of total factor productivity change with an illustrative example of 14 EU countries, Ecological Economics, Vol. 72, pp. 60-69.

Malmquist, S. (1953). Index numbers and indifference surfaces, Trabajos de Estadistica, 4, 209-242.

Mastromarco, C., Simar, L. (2014). Effect of FDI and time on catching-up: new insights from a conditional nonparametric frontier analysis, Journal of Applied Econometrics, Vol. 30 No. 5, pp.826-847. doi: 10.1002/jae.2382

Simar, L. (2003). Detecting outliers in frontier models: a simple approach, Journal of Productivity Analysis, Vol. 20, pp.391–424.

Wang, K. and Yi-Ming Wei (2016). Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator, Energy Economics, Vol.54, pp. 50-59.