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The incidence and extent of the CDM across developing countries

Published online by Cambridge University Press:  22 January 2016

Shaikh M. Rahman ,
Ariel Dinar  and
Donald F. Larson
Shaikh M. Rahman
Affiliation:
Agricultural and Applied Economics, Texas Tech University, Box 42132, Lubbock 79409, TX, USA. E-mail: shaikh.m.rahman@ttu.edu
Ariel Dinar
Affiliation:
School of Public Policy, University of California, Riverside, CA, USA. E-mail: adinar@ucr.edu
Donald F. Larson
Affiliation:
Development Research Group, The World Bank, Washington, DC, USA. E-mail: dlarson@worldbank.org
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Abstract

This paper empirically examines the factors that determine the incidence and extent of the Clean Development Mechanism (CDM) in developing countries. Estimation results show that the incidence and extent of the CDM is greater for the developing countries with larger mitigation potential and greater capacity to manage the projects. Developing countries with faster economic growth and past experience with activities implemented jointly (AIJ) projects are more likely to host renewable energy projects, although this is not the case for other project types. The incidence and extent of foreign investment projects in energy efficiency, CO2 reduction and non-CO2 gas reduction projects are higher for the countries with lower per capita GDP, most likely due to capital constraints. There is no evidence that the number of sub-regional projects impinged on investment flows. Countries in Sub-Saharan Africa appear to face special obstacles under the CDM even after the strength of institutions and energy-related mitigation opportunities are accounted for.

Type
Research Article
Information
Environment and Development Economics , Volume 21 , Issue 4 , August 2016 , pp. 415 - 438
Copyright
Copyright © Cambridge University Press 2016 

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References

Bass, F.M. (1969), ‘A new product growth model for consumer durables’, Management Science 15: 215–217.Google Scholar
Bayer, P., Urpelainen, J., and Wallace, J. (2013), ‘Who uses the Clean Development Mechanism? An empirical analysis of projects in Chinese provinces’, Global Environmental Change 23: 512–521.Google Scholar
Bewley, R. and Fiebig, D.G. (1988), ‘A flexible logistic growth model with application in telecommunications’, International Journal of Forecasting 4: 177–192.Google Scholar
Buys, P., Deichmann, U., Meisner, C., That, T., and Wheeler, D. (2007), ‘Country stakes in climate change negotiations: two dimensions of vulnerability’, World Bank Policy Research Working Paper No. 4300, World Bank, Washington, DC.Google Scholar
Caselli, F. and Coleman, W.J. (2001), ‘Cross-country technology diffusion: the case of computers’, American Economic Review 91(2): 328–335.Google Scholar
Comin, D. and Hobijn, B. (2004), ‘Cross-country technology adoption: making the theories face the facts’, Journal of Monetary Economics 51: 39–83.Google Scholar
Davies, S. (1979), The Diffusion of Innovations, Cambridge: Cambridge University Press.Google Scholar
Dinar, A. and Yaron, D. (1992), ‘Adoption and abandonment of irrigation technologies’, Agricultural Economics 6: 315–332.CrossRefGoogle Scholar
Dinar, A., Rahman, S.M., Larson, D.F., and Ambrosi, P. (2011), ‘Local actions, global impacts: international cooperation and the CDM’, Global Environmental Politics 11(4): 108–133.Google Scholar
Dixon, R. (1980), ‘Hybrid corn revisited’, Econometrica 48: 1451–1461.CrossRefGoogle Scholar
Doessel, D.P. and Strong, S.M. (1991), ‘A neglected problem in the analysis of the diffusion process’, Applied Economics 23: 1335–1340.Google Scholar
Dolsak, N. and Crandall, E.B. (2013), ‘Do we know each other? Bilateral ties and the location of clean development mechanism projects’, Climatic Change 118: 521–536.Google Scholar
Feder, G. and Umali, D.L. (1993), ‘The adoption of agricultural innovations: a review’, Technological Forecasting and Social Change 43: 215–239.Google Scholar
Flues, F. (2010), ‘Who hosts the Clean Development Mechanism? Determinants of CDM project distribution’, CIS Working Paper No. 53, Center for Comparative and International Studies, Zurich.Google Scholar
Griliches, Z. (1957), ‘Hybrid corn: an exploration in the economics of technological change’, Econometrica 25: 501–522.Google Scholar
Griliches, Z. (1980), ‘Hybrid corn revisited: a reply’, Econometrica 48: 1451–1461.Google Scholar
Henisz, W.J. (2002), ‘The institutional environment for infrastructure investment’, Industrial and Corporate Change 11(2): 355–389.Google Scholar
IRAI (2010), ‘Country policy and institutional assessments: 2010 assessment questionnaire’, International Development Association Resource Allocation Index, World Bank, Washington, DC, [Available at] http://www.worldbank.org/ida/IRAI/2010/CPIA-criteria-2010.pdf.Google Scholar
Jung, M. (2006), ‘Host country attractiveness for CDM non-sink projects’, Energy Policy 34(15): 2173–2184.Google Scholar
Kaufmann, D., Kraay, A., and Mastruzzi, M. (2010), ‘Governance matters VI: aggregate and individual governance indicators 1996–2006’, World Bank Policy Research Working Paper No. 4280, Washington, DC.CrossRefGoogle Scholar
Knudson, M.K. (1991), ‘Incorporating technological change in diffusion models’, American Journal of Agricultural Economics 73: 724–733.Google Scholar
KPMG International Cooperative (2011), Energy and Natural Resources: Taxes and Incentives for Renewable Energy, Amstelveen: KPMG, [Available at] http://www.kpmg.com/Global/en/IssuesAndInsights/ArticlesPublications/Documents/Taxes-Incentives-Renewable-Energy-2011.pdf.Google Scholar
Lal, R. (2004), ‘Soil carbon sequestration impacts on global climate change and food security’, Science 304(5677): 1623–1627.Google Scholar
Larson, D.F. and Breustedt, G. (2009), ‘Will markets direct investments under the Kyoto Protocol?’, Environmental and Resource Economics 43(3): 433–456.Google Scholar
Larson, D.F., Ambrosi, P., Dinar, A., Rahman, S.M., and Entler, R. (2008), ‘A review of carbon market policies and research’, International Review of Environmental and Resource Economics 2(3): 177–236.Google Scholar
Larson, D.F, Dinar, A., and Frisbie, J.A. (2011), ‘The present and future role for agricultural projects under the Clean Development Mechanism’, inDinar, A. and Mendelsohn, R. (eds), Handbook on Climate Change and Agriculture, Cheltenham: Edward Elgar.Google Scholar
Lecocq, F. and Ambrosi, P. (2007), ‘The Clean Development Mechanism: history, status, and prospects’, Review of Environmental Economics and Policy 1(1): 134–151.Google Scholar
Lekvall, P. and Wahlbin, C. (1973), ‘A study of some assumptions underlying innovation diffusion function’, Swedish Journal of Economics 75: 362–377.CrossRefGoogle Scholar
Maddala, G.S. (1977), Econometrics, New York: McGraw-Hill.Google Scholar
Mahajan, V. and Schoeman, M.E.F. (1977), ‘Generalized model for the time pattern of the diffusion process’, IEEE Transactions of Engineering Management 24: 12–18.Google Scholar
Mansfield, E. (1961), ‘Technical change and the rate of imitation’, Econometrica 29: 741–765.Google Scholar
Metcalfe, J.S. (1981), ‘Impulse and diffusion in the study of technical change’, Futures 13: 347–359.Google Scholar
Michalakelis, C., Varoutas, D., and Sphicopoulos, T. (2008), ‘Diffusion models of mobile telephony in Greece’, Telecommunications Policy 32 (3–4): 234–245.Google Scholar
Murray, M.P. (2006), ‘Avoiding invalid instruments and coping with weak instruments’, Journal of Economic Perspectives 20: 111–132.Google Scholar
Oleschak, R. and Springer, U. (2007), ‘Measuring host country risk in CDM and JI projects: a composite indicator’, Climate Policy 7: 470–487.Google Scholar
Olsen, K.H. (2007), ‘The Clean Development Mechanism's contribution to sustainable development: a review of the literature’, Climatic Change 84: 59–73.Google Scholar
Carbon, Point (2009), ‘CDM host countr ratings’, [Available at] http://www.pointcarbon.com.Google Scholar
Risoe, (2013), ‘CDM/JI pipeline analysis and database’, UNEP Risoe Center, January, [Available at] http://cdmpipeline.org/.Google Scholar
Rogers, E.M. (2003), Diffusion of Innovations, 5th edn, New York: Free Press.Google Scholar
Samuelson, W. and Zeckhauser, R. (1988), ‘Status quo bias in decision making’, Journal of Risk and Uncertainty 1: 7–59.CrossRefGoogle Scholar
Winkelman, A.G. and Moore, M.R. (2011), ‘Explaining the differential distribution of Clean Development Mechanism projects across host countries’, Energy Policy 39: 1132–1143.Google Scholar
WDI (2014), World Development Indicators, Washington, DC: World Bank.Google Scholar
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