Journal of Economic Structures

The Official Journal of the Pan-Pacific Association of Input-Output Studies (PAPAIOS)

Journal of Economic Structures Cover Image
Open Access

Production analysis in environmental, resource, and infrastructure evaluation

Journal of Economic StructuresThe Official Journal of the Pan-Pacific Association of Input-Output Studies (PAPAIOS)20154:15

https://doi.org/10.1186/s40008-015-0025-4

Received: 13 August 2015

Accepted: 18 August 2015

Published: 2 September 2015

Abstract

Over the past several decades, significant efforts have been made to regulate the use of resource and pollution in most industrialized countries, and the stringency of pollution regulations has continued to increase globally. At the same time, physical and social infrastructures are influenced by changes in the use of resources which contribute to the wealth of many regions. Technical progress plays an important role in maintaining a high standard of living in the face of these increasingly stringent regulations. This thematic series looks at how recent advances in this field to contribute to understanding the evaluation for environment, resource, and infrastructure management.

JEL classification

O10 O13 O18 Q01 Q40 Q50

1 Introduction

Over the past several decades, significant efforts have been made to regulate the use of resources and pollution in most industrialized countries, and the stringency of pollution regulations has continued to increase globally (see example on climate change on Somanathan et al. (2014)). At the same time, physical and social infrastructures are influenced by changes in the use of resources which contribute to the wealth of many regions. Technical progress plays an important role in maintaining a high standard of living in the face of these increasingly stringent regulations (Managi 2011).

Several techniques are able to assess the importance of technical change or productivity change considering environmental or resource performance. Deterministic frontier analysis of data envelopment analysis, or stochastic frontier analysis, in addition to the conventional production function approach is useful tools in this objective (Barros et al. 2013; Managi et al. 2004; Kumar et al. 2015). Furthermore, these techniques are suggested to apply to the evaluation of infrastructure management (Managi 2015a,b). This thematic series looks at how recent advances in this field contribute to understanding the evaluation for environment, resource, and infrastructure management.

2 Results

We solicit papers concerning theory and application into diverse regions and focus. First paper tackles renewable policy planning using long-range energy alternatives planning system (LEAP). Halkos et al. (2015a) utilize the system for forecasting and analyze four long-term renewable energy scenarios for the Greek sectors. They evaluate the efficiency of renewable energy commitments on decreasing greenhouse gas (GHG) emissions. The results find that the efficiency of renewable energy commitments set under the law would not be sufficient to decrease systematically the generated GHG emissions. For the government to have more effective emission reduction, it needs to increase the share of energy consumption produced from renewable resources at least up to 27 % by 2020.

International trade has significant impact on the environment (Managi 2011). Honma (2015) analyzes the impact of international trade on environmental efficiency including carbon dioxide (CO2) emissions. He measures the environmental efficiency of four emissions and finds that trade openness is positively correlated to the environmental efficiency. The study shows that the higher the relative income per capita, the more the benefit of trade on the environmental efficiency.

Infrastructure requires evaluation ex ante and ex post. Commonly, when the decision to what and when to construct is not prepared well, it does not necessarily mean that performance of infrastructure construction is good. However, if it is immediately required, it might be good such as when large damage right after the natural disaster occurred. Halkos et al. (2015b) examine the effect of man-made and natural disaster occurrences on countries’ production efficiency levels. Their empirical findings suggest that the relationship is nonlinear forming an inverted U shape regardless of the countries’ income classification. This implies that a lower number of disaster occurrences has a positive influence on countries’ productivity improvement due to possible stimulation of restructuring and investment policies imposed by governments as counteractions of those events. After a certain threshold level, the effect becomes negative, influencing countries’ production factors.

The wage increases and labor productivity is a common topic that needs to be discussed for cost-competitiveness of industries and countries. Mizobuchi (2015) proposes an alternative decomposition of the change in unit labor cost (ULC) with a measure of a comprehensive wage effect. This fully captures its direct as well as indirect impact. He finds the wage effect to be significantly overestimated under the conventional decomposition.

As more data are available to emerging countries such as China, application study increases over time. Cao et al. (2015) take further step to comprehensively grasp not just environmental pollution but including human health in China. They focus on regional differences in productive inefficiencies and attempts to clarify the determinants of inefficiency, accounting economic, environmental, and health-related factors. After accounting for environmental pollution and health impacts, they find the productive inefficiency reduced.

Another country where emission data such as CO2 emissions are available and require particular attention is an emerging country such as Indonesia. Armundito and Kaneko (2015) provide empirical evidence of changes in the productivities of manufacturing firms in Indonesia over time of total factor productivity (TFP) with and without considering CO2 emissions. They show that TFP with CO2 emissions has grown faster than TFP without CO2 emissions.

3 Discussions

Apart from this special issue, performance analysis now became a common practice not just in academics. Techniques introduced in this special issue are also used in practice such as checking regulatory changes in law and performance improvement, evaluating potential improvements of revenue increase and emission reduction, or resource-saving by catching up with the frontier firm, measuring technological production frontier shift in firm, industry, or country.

In the field of technical aspects, there are still many areas that needed to be developed. Chen et al. (2015) explore approach in the context of environmental policy evaluations, and Kerstens and Managi (2012) show the importance of differentiating convex and non-convex treatment in production function. Wide ranges of applications are also provided empirically using global (Fujii and Managi 2015) or developing country (Fujii et al. 2015). In terms of data disaggregation, firm level or field level analysis started increasing globally in resource and environmental economics field (Managi et al. 2005; Yagi et al. 2015). Formally, lack of disaggregated data such as firm level data makes traditional (aggregated) country level or industry level analysis applied. Future research and practice need to take these developments into account for evaluation.

Declarations

Acknowledgements

SM thanks the funding from the Grant-in-Aid for Young Scientists (B) Specially Promoted Research (26000001) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. The results and conclusions of this introduction or special issue do not necessarily represent the views of the funding agency.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)

References

  1. Armundito E, Kaneko S (2015) Baseline analysis of productivity changes with and without considering carbon dioxide emissions in the major manufacturing sector of Indonesia. The Journal of Economic Structures. doi:10.1186/s40008-015-0018-3 Google Scholar
  2. Barros CP, Chen Z, Managi S, Antunes OS (2013) Examining the cost efficiency of Chinese hydroelectric companies using a finite mixture model. Energy Economics 36(1):511–517View ArticleGoogle Scholar
  3. Cao H, Fujii H, Managi S (2015) A productivity analysis considering environmental pollution and diseases in China. The Journal of Economic Structures. doi:10.1186/s40008-015-0012-9 Google Scholar
  4. Chen P-C, Yu M-M, Chang C-C, Hsu S-H, Managi S (2015) The enhanced Russell-based directional distance measure with undesirable outputs: numerical example considering CO2 emissions. Omega - Int J Manage Sci 53:30–40View ArticleGoogle Scholar
  5. Fujii H, Cao J, Managi S (2015) Decomposition of productivity considering multi-environmental pollutants in Chinese industrial sector. Rev Dev Econ 19(1):75–84View ArticleGoogle Scholar
  6. Fujii H, Managi S (2015) Optimal production resource reallocation for CO2 emissions reduction in manufacturing sectors. Global Environmental Change. doi:10.1016/j.gloenvcha.2015.06.005 Google Scholar
  7. Halkos G, Tzeremes N, Tzeremes P (2015a) A nonparametric approach for evaluating long-term energy policy scenarios: an application to the Greek energy system. The Journal of Economic Structures. doi:10.1186/s40008-015-0011-x Google Scholar
  8. Halkos G, Managi M, Tzeremes N (2015b) The effect of natural and man-made disasters on countries’ production efficiency. The Journal of Economic Structures. doi:10.1186/s40008-015-0019-2 Google Scholar
  9. Honma S (2015) Does international trade improve environmental efficiency? An application of a super slacks-based measure of efficiency. The Journal of Economic Structures. doi:10.1186/s40008-015-0023-6 Google Scholar
  10. Kerstens K, Managi S (2012) Total factor productivity growth and convergence in the petroleum industry: empirical analysis testing for convexity. Int J Prod Econ 139(1):196–206View ArticleGoogle Scholar
  11. Kumar S, Fujii H, Managi S (2015) Substitute or complement? Assessing renewable and nonrenewable energy in OECD countries. Applied Econ 47(14):1438–1459View ArticleGoogle Scholar
  12. Managi S (ed) (2015a) The economics of green growth: new indicators for sustainable societies. Routledge, New York, USAGoogle Scholar
  13. Managi S (ed) (2015b) The Routledge handbook of environmental economics in Asia. Routledge, New York, USAGoogle Scholar
  14. Managi S (2011) Technology, natural resources and economic growth: improving the environment for a greener future. Edward Elgar Publishing Ltd, Cheltenham, UKView ArticleGoogle Scholar
  15. Managi S, Opaluch JJ, Jin D, Grigalunas TA (2004) Technological change and depletion in offshore oil and gas. J Environ Econ Manag 47(2):388–409View ArticleGoogle Scholar
  16. Managi S, Opaluch JJ, Jin D, Grigalunas TA (2005) Environmental regulations and technological change in the offshore oil and gas industry. Land Econ 81(2):303–319View ArticleGoogle Scholar
  17. Mizobuchi H (2015) Measuring the comprehensive wage effect of changes in unit labor cost. The Journal of Economic Structures. doi:10.1186/s40008-015-0017-4 Google Scholar
  18. Somanathan E., T. Sterner, T. Sugiyama, D. Chimanikire, J. Essandoh-Yeddu, S. Fifita, L. Goulder, A. Jaffe, X. Labandeira, S. Managi, C. Mitchell, J.P. Montero, F. Teng, and T. Zylicz (2014) National and sub-national policies and institutions. In: Climate Change 2014: mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Salvolainen, S. Schlömer, C. von Stechow, T. Zwickel and J. Minx (eds.)]. Page 1141–1206. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Google Scholar
  19. Yagi M, Fujii H, Hoang V, Managi S (2015) Environmental efficiency of energy, materials, and emissions. J Environ Manage 161:206–218View ArticleGoogle Scholar

Copyright

© Managi and Halkos. 2015