The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
Modeling endogenous technological change for climate policy analysis
Open accessAbstract
The approach used to model technological change in a climate policy model is a critical determinant of its results in terms of the time path of CO2 prices and costs required to achieve various emission reduction goals. We provide an overview of the different approaches used in the literature, with an emphasis on recent developments regarding endogenous technological change, research and development, and learning. Detailed examination sheds light on the salient features of each approach, including strengths, limitations, and policy implications. Key issues include proper accounting for the opportunity costs of climate-related knowledge generation, treatment of knowledge spillovers and appropriability, and the empirical basis for parameterizing technological relationships. No single approach appears to dominate on all these dimensions, and different approaches may be preferred depending on the purpose of the analysis, be it positive or normative.
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Cites
On the mechanics of economic development
Lucas, R. E. (1988) · Journal of Monetary Economics · doi:10.1016/0304-3932(88)90168-7 · Cited by 24,085
Endogenous Technological Change
Romer, P. M. (1990) · Journal of Political Economy · doi:10.1086/261725 · Cited by 17,711
Endogenous Technological Change
Romer, P. (1989) · National Bureau of Economic Research · doi:10.3386/w3210 · Cited by 13,303
The Economic Implications of Learning by Doing
Arrow, K. J. (1962) · The Review of Economic Studies · doi:10.2307/2295952 · Cited by 7,202
The Economic Implications of Learning by Doing
Arrow, K. J. (1971) · Readings in the Theory of Growth · doi:10.1007/978-1-349-15430-2_11 · Cited by 6,605
Econometric policy evaluation: A critique
Lucas, R. E. (1976) · Carnegie-Rochester Conference Series on Public Policy · doi:10.1016/s0167-2231(76)80003-6 · Cited by 6,110
(1985) · American Economic Review · Cited by 6,056
Zilibotti, F., Aghion, P., Howitt, P., & Garcia-Penalosa, C. (1999) · The Canadian Journal of Economics / Revue canadienne d'Economique · doi:10.2307/136487 · Cited by 3,655
Factors Affecting the Cost of Airplanes
WRIGHT, T. P. (1936) · Journal of the Aeronautical Sciences · doi:10.2514/8.155 · Cited by 2,958
Inside the Black Box: Technology and Economics
Morgan, M. G., & Rosenberg, N. (1983) · Journal of Policy Analysis and Management · doi:10.2307/3324062 · Cited by 2,326
Cited by
Energy Efficiency Economics and Policy
Gillingham, K., Newell, R. G., & Palmer, K. (2009) · Annual Review of Resource Economics · doi:10.1146/annurev.resource.102308.124234 · Cited by 871
Self-citationAir Pollution and Manufacturing Firm Productivity: Nationwide Estimates for China
Fu, S., Viard, V. B., & Zhang, P. (2021) · The Economic Journal · doi:10.1093/ej/ueab033 · Cited by 373
Assessing Transformation Pathways
(2015) · Climate Change 2014: Mitigation of Climate Change · doi:10.1017/cbo9781107415416.012 · Cited by 159
Popp, D. (2010) · Annual Review of Resource Economics · doi:10.1146/annurev.resource.012809.103929 · Cited by 217
A global stocktake of the Paris pledges: Implications for energy systems and economy
Vandyck, T., Keramidas, K., Saveyn, B., Kitous, A., & Vrontisi, Z. (2016) · Global Environmental Change · doi:10.1016/j.gloenvcha.2016.08.006 · Cited by 186
Metadata
- Authors
- Gillingham, K., Newell, R. G., & Pizer, W. A.
- Venue
- Energy Economics
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 30
- Issue
- 6
- Pages
- 2734-2753
- ISSN
- 0140-9883 (ISSN-L)
- OpenAlex
- W2128846935
- Cited by
- 294
- References
- 88
- FWCI
- 49.29
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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