Estimating Directional Shadow Prices of Air Pollutant Emissions by Road Transportation Modes

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林佳瑩(Jia_Ying Lin) 查詢紙本館藏

畢業系所

土木工程學系

論文名稱

(Estimating Directional Shadow Prices of Air Pollutant Emissions by Road Transportation Modes)

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摘要(中)

本研究針對2010年及2013年之台灣公路運輸運具為研究對象，透過方向邊際生產力模型探討其生產力之變化，並進一步估算其陰影價格。其中考量一個投入變量(能源消耗)、一項期望產出變量(行駛里程數)以及三項非期望產出變量(二氧化碳、硫氧化物、氮氧化物)，並用以探討九種運具分類18個運具(2011及2013年)之陰影價格變化。結果顯示，由於政府已要求台塑和中國石油進行除硫措施，相較於二氧化碳以及氮氧化物，硫氧化物的排放量相當的低；其中，二氧化碳為排放最多的汙染物，但陰影價格卻為三種汙染物中最低，因此，決策者須著重於二氧化碳的減排，建立完善的大眾運具使用環境以及擬定和擴大對於電動汽機車的補助方案等等。

摘要(英)

This paper applies directional marginal productivity model to study the shadow price of emissions for transportation modes in the year of 2011 and 2013 with the aim that the findings can be a reference for policy makers to improve the emission of pollutants. One input variable (i.e., energy consumption), one desirable output variable (i.e., vehicle kilometers traveled) and three undesirable output variables generated by road transportation modes (i.e., carbon dioxide, sulfur oxides and nitrogen oxides) were used to evaluate directional marginal productivity and directional shadow price for 18 transportation modes. The results show that the DSP of SOx is much higher than CO2 and NOx, nevertheless, the emission of CO2 is the largest among the three kinds of pollutants. To improve the air quality, the government should pay more attention to the emission of CO2 and apply the alternative solution such as promoting the public transportation modes and subsidizing to the electric vehicles to constrain the private modes.

關鍵字(中)

★ 陰影價格
★ 邊際生產力
★ 非期望產出
★ 公路運輸運具

關鍵字(英)

★ shadow price
★ marginal productivity
★ undesirable outputs
★ road transportation modes

論文目次

中文摘要 p.i
Abstract p.ii
誌謝 p.iii
Table of Contents p.iv
List of figures p.v
List of tables p.vi
1 Introduction p.1
1.1 Problem description p.1
1.2 Research motivation p.2
2 Literature Review p.5
2.1 Performance evaluation p.5
2.2 Undesirable outputs p.7
2.3 The estimation of shadow price p.8
3 Methodology p.11
3.1 Directional marginal productivity p.11
3.1.1 Single output marginal productivity p.11
3.1.2 Multi-product marginal productivity p.13
3.1.3 Marginal productivity for undesirable outputs p.15
3.2 Directional shadow prices p.22
4 Empirical Result p.24
4.1 Data collection p.24
4.2 Result analysis p.24
5 Conclusion and Implications p.37
6 Limitations and Future Work p.39
References p.40
Appendix A: The road transportation data p.44

參考文獻

[1] Banker, R.D., Charnes, A.A., and Cooper, W.W., 1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis, Management Science, 30(9), pp. 1078-1092.
[2] Boyd, G.A., Molburg, J.C., Prince, R., 1996. Alternative methods of marginal abatement cost estimation: Nonparametric distance functions. In: Proceedings of the USAEE/IAEE 17th Conference, pp. 86–95.
[3] Charnes, A., Cooper, W.W., and Rhodes, E.L., 1978. Measuring the efficiency of decision making units, European Journal of Operational Research, 2, pp. 429-444.
[4] Cherchye, L., Rock, B. D., and Walheer, B., 2015. Multi-output efficiency with good and bad outputs. European Journal of Operational Research, 240(3), pp. 872-881.
[5] Chung, Y.H., Fare, R., Grosskopf, S., 1997. Productivity and undesirable outputs: a directional distance function approach, Journal of Environmental Management, 51, pp. 229-240.
[6] Coase, R.H., 1960. The problem of social costs, The Journal of Law and Economics, 3, pp. 1-44.
[7] Coelli, T., Rao, D. S. P. and Battese, G. E., 2005. An Introduction to Efficiency and Productivity Analysis, 2nd Ed., Springer, USA.
[8] Coggins, J.S. and Swinton, J.R., 1996. The price of pollution: A dual approach to valuing SO2 allowances. Journal of Environmental Economics and Management. 30, pp. 58–72.
[9] European Environment Agency (EEA), 2015. Transport GHG emissions. https://www.eea.europa.eu/data-and-maps/indicators/transport-emissions-of-greenhouse-gases/transport-emissions-of-greenhouse-gases-10.
[10] Fare, R., Grosskopf, S., Lovell, C.A.K. and Yaisawarng, S., 1993. Derivation of shadow prices for undesirable outputs: a distance function approach. The Review of Economics and Statistics, 75(2), pp. 374-380.
[11] Fare, R., Grosskopf, S., 2000. Theory and application of directional distance functions. Journal of Productivity Analysis, 13, pp. 93–103.
[12] Fare, R., Grosskopf, S., Noh, D.W., Weber, W., 2005. Characteristics of a polluting technology: theory and practice. Journal of Econometrics, 126(2), pp. 469–492.
[13] Fare, R., Grosskopf, S., and Pasurka, C.A., 2007. Environmental production functions and environmental directional distance functions, Energy, 32, pp. 1055-1066.
[14] Fare, R., Grosskopf, S. and Whittaker, G., 2013. Directional output distance function: endogenous directions based on exogenous normalization constraints, Journal of Productivity Analysis, 40(3), pp. 267-269.
[15] Guo X.D., Zhu L., Fan Y. and Xie B.C., 2011. Evaluation of potential reductions in carbon emissions in Chinese provinces based on environmental DEA. Energy Policy, 39(5), pp. 2352-2360.
[16] Hailu A, Veeman TS., 2000. Environmentally sensitive productivity analysis of the Canadian pulp and paper industry, 1959–1994: an input distance function approach. Journal of Environmental Economics and Management, 40(3), pp. 251–274.
[17] Johnson, A.L. and T. Kuosmanen, 2014. An Introduction to CNLS and StoNED Methods for Efficiency Analysis: Economic Insights and Computational Aspects, in S. Ray, S. Kumbhakar, and P. Dua (Eds) Benchmarking for Performance Evaluation: A Production Frontier Approach, Springer.
[18] Kuosmanen, T., 2005. Weak disposability in nonparametric production analysis with undesirable outputs. Agricultural & Applied Economics Association, 87(4), pp. 1077-1082.
[19] Kuosmanen, T., 2008. Representation theorem for convex nonparametric least squares. Econometrics Journal, 11(2), pp. 308–325.
[20] Kuosmanen, T. and Podinovski, V., 2009. Weak disposability in nonparametric production analysis: reply to Fare and Grosskopf. Agricultural & Applied Economics Association, 91(2), pp. 539-545.
[21] Lee, C.Y., 2013. Multi-product marginal productivity of efficient frontiers in data envelopment analysis. Working paper at SSRN. .
[22] Lee, C.Y., 2014. Meta-data envelopment analysis: finding a direction towards marginal profit maximization, European Journal of Operational Research, 237, pp. 207-216.
[23] Lee, M., 2005. The shadow price of substitutable sulfur in the US electric power plant: a distance function approach. Journal of Environmental Management, 77, pp. 104–10.
[24] Lee, C.Y. and Zhou, P., 2015. Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990-2010, Energy Economics, 51, pp. 493-502.
[25] Lee, J.D., Park, J.B., and Kim, T.Y., 2002. Estimation of the shadow prices of pollutants with production/environment inefficiency taken into account: a nonparametric directional distance function approach. Journal of Environmental Management, 64, pp. 365-375.
[26] Lee, S.C., Oh, D.H., Lee, J.D., 2014. A new approach to measuring shadow price: reconciling engineering and economic perspectives. Energy Economics, 46, pp. 66–77.
[27] Mekaroonreung, M. and Johnson, A. L., 2012. Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach, Energy Economics, 34, pp. 723-732.
[28] Montgomery, D.W., 1972. Markets in licenses and efficient pollution control programs, Journal of Economic Theory, 5, pp. 395-418.
[29] Morrow, W.R., Gallagher, K.S., Collantes, G., Lee, H., 2010. Analysis of policies to reduce oil consumption and greenhouse-gas emissions from the US transportation sector, Energy Policy, 38, pp. 1305-1320.
[30] Park, H. & Lim, J., 2009. Valuation of marginal CO2 abatement options for electric power plants in Korea, Energy Policy, 37(5), pp. 1834–1841.
[31] Podinovski, V. V. and Forsund, F. R., 2010. Differential characteristics of efficient frontiers in data envelopment analysis, Operations Research, 58(6), pp. 1743-1754.
[32] Morales Sarriera, J., Serebrisky, T., Araya, G., Briceno-Garmendia, C. and Schwartz, J., 2013. Benchmarking container port technical efficiency in Latin America and the Caribbean, IDB Working Paper Series No. IDB-WP-474.
[33] Tietenberg, T.H., 1985. Emission Trading: An Exercise in Reforming Pollution Policy, Resources for the Future, Washington, D.C.
[34] Turner, J., 1995. Measuring the Cost of Pollution Abatement in the US Electric Utility Industry: A Production Frontier Approach Ph.D. dissertation. University of North Carolina, Chapel Hill.
[35] Wang, X., Westerdahl, D., Chen, L.C., Wu, Y., Hao, J., Pan, X., Guo, X., Zhang, K. M., 2009. Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles, Atmospheric Environment, 43, pp. 4535-4543.
[36] Zhou, P., Zhou, X., Fan, L.W., 2014. On estimating shadow prices of undesirable outputs with efficiency models: a literature review. Applied Energy, 130, pp. 799–806.
[37] Zhou, X., Fan, L.W., Zhou, P., 2015. Marginal CO2 abatement costs: findings from alternative shadow price estimates for Shanghai industrial sectors, Energy Policy, 77, pp. 109–117.
[38] Zofio, J.L. and Prieto, A.M., 2001. Environmental efficiency and regulatory standards: The case of CO2 emissions from OECD Industries, Resource and Energy Economics, 23, pp. 63-83.
[39] 陳惠國，2010年，研究方法–理論與實務，滄海書局。
[40] 交通部，2012年7月，運輸政策白皮書綠運輸篇。
[41] 環保署，2017年5月，台灣空氣汙染排放量[TEDS9]線源—排放量推估手冊。
[42] 經濟部，2018年4月，能源轉型白皮書初稿。

指導教授

陳惠國(Huey_Kuo Chen)

審核日期

2018-8-22

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