D. F. Abell and J. S. Hammond, Cost Dynamics: Scale and Experience Effects. Strategic Planning: Problems and Analytical Approaches, 1979.

S. Alberth, Forecasting technology costs via the experience curve ? Myth or magic? Technological Forecasting & Social Change, pp.75-952, 2008.

L. Argote and D. Epple, Learning Curves in Manufacturing, Science, vol.247, issue.4945, 1990.
DOI : 10.1126/science.247.4945.920

K. J. Arrow, The Economic Implications of Learning by Doing, The Review of Economic Studies, vol.29, issue.3, pp.155-173, 1962.
DOI : 10.2307/2295952

A. D. Little, Potential cost reduction in PV systems, 2001.

L. Barreto and S. Kypreos, Endogenizing R&D and market experience in the ???bottom-up??? energy-systems ERIS model, Technovation, vol.24, issue.8, pp.615-629, 2004.
DOI : 10.1016/S0166-4972(02)00124-4

J. E. Bartlett, R. M. Margolis, and C. E. Jennings, The Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from, 2008.

J. Barton, Intellectual Property and Access to Clean Energy Technologies in Developing Countries. An Analysis of Solar Photovoltaic, Biofuel and Wind Technologies, ICTSD Programme on Trade and Environment, issue.2, 2007.

D. A. Belsley, E. Kuh, and R. E. Welsch, Regression Diagnostics: Identifying Influential Data and Sources of Collinearity, 1980.
DOI : 10.1002/0471725153

A. V. Benthem, K. Gillingham, and J. Sweeney, Learning-by-Doing and the Optimal Solar Policy in California, The Energy Journal, vol.29, issue.3, pp.131-152, 2008.
DOI : 10.5547/ISSN0195-6574-EJ-Vol29-No3-7

E. R. Berndt, The Practice of Econometrics: Classical and Contemporary, 1991.

V. Bosetti, M. Catenacci, G. Fiorese, and E. Versolini, The future prospect of PV and CSP solar technologies: An expert elicitation survey, FEEM Working Paper, 2012.

K. Branker, M. J. Pathaka, and J. M. Pearce, A review of photovoltaic levelized cost of electricity. Renewable and sustainable energy review, pp.15-4470, 2011.

R. Brown, J. Durbin, and J. Evans, Techniques for testing the constancy of regression relationships over time, J. R. Stat. Soc. Series B, vol.37, pp.149-172, 1975.

L. Butler and K. Neuhoff, Comparison of feed-in tariff, quota and auction mechanisms to support wind power development, Renewable Energy, vol.33, issue.8, pp.1854-1867, 2008.
DOI : 10.1016/j.renene.2007.10.008

G. D. Cody and T. Tiedje, A learning curve approach to projecting cost and performance for photovoltaic technologies, Proceedings of the First Conference on Future Generation Photovoltaic Technologies, 1997.

W. M. Cohen, R. R. Nelson, and J. P. Walsh, Protecting their Intellectual Assets: Appropriability Conditions and Why U.S. Manufacturing Firms Patent (or Not) NBER Working Paper no, 2000.

T. Couture and Y. Gagnon, An analysis of feed-in tariff remuneration models: Implications for renewable energy investment, Energy Policy, vol.38, issue.2, pp.955-965, 2010.
DOI : 10.1016/j.enpol.2009.10.047

P. Criqui, G. Klaassen, and L. Schrattenholzer, The Efficiency of Energy R&D Expenditures. Economic Modelling of Environmental Policy and Endogenous Technological Change Workshop. Institute for Environmental Studies, pp.16-17, 2000.

S. B. Darling, F. You, T. Veselka, and A. Velosa, Assumptions and the levelized cost of energy for photovoltaics. Energy environment science, pp.3133-3139, 2011.

A. De-la-tour, M. Glachant, and Y. Ménière, Innovation and international technology transfer: The case of the Chinese photovoltaic industry, Energy Policy, vol.39, issue.2, pp.761-770, 2011.
DOI : 10.1016/j.enpol.2010.10.050
URL : https://hal.archives-ouvertes.fr/hal-00498578

A. Dechezleprêtre, M. Glachant, and Y. Ménière, What Drives the International Transfer of Climate Change Mitigation Technologies? Empirical Evidence from Patent Data, 2010.

A. Dechezleprêtre, M. Glachant, I. Ha??i?, N. Johnstone, and Y. Ménière, Invention and Transfer of Climate Change-Mitigation Technologies: A Global Analysis, Review of Environmental Economics and Policy, vol.5, issue.1, 2011.
DOI : 10.1093/reep/req023

J. Dutton and A. Thomas, Treating progress functions as a managerial opportunity, The Academy of Management Review, vol.9, issue.2, pp.235-247, 1984.

F. Ferioli, K. Schoots, and B. C. Van-der-zwaan, Use and limitations of learning curves for energy technology policy: A component-learning hypothesis, Energy Policy, vol.37, issue.7, pp.2525-2535, 2009.
DOI : 10.1016/j.enpol.2008.10.043

D. Finon and P. Menanteau, The Static and Dynamic Efficiency of Instruments of Promotion of Renewables, Energy Studies Review, vol.12, issue.1, 2004.
DOI : 10.15173/esr.v12i1.453
URL : https://hal.archives-ouvertes.fr/halshs-00001300

C. W. Granger, Investigating Causal Relations by Econometric Models and Cross-spectral Methods, Econometrica, vol.37, issue.3, pp.424-438, 1969.
DOI : 10.2307/1912791

W. H. Greene, Econometric Analysis, 2000.

A. Grübler and A. Gritsevskyi, A Model of Endogenous Technological Change Through Uncertain Returns on Learning (R&D and Investments) Paper presented at the International Workshop on induced Technical Change and the Environment International Institute for Applied Systems Analysis, pp.26-27, 1997.

H. Grüber, Learning by doing and spillovers: further evidence for the semiconductor industry, Review of Industrial Organization, vol.13, pp.697-711, 1998.

G. Hall and S. Howell, The experience curve from the economist's perspective, Strategic Management Journal, vol.10, issue.3, p.197, 1985.
DOI : 10.1002/smj.4250060302

J. A. Hausman, Specification Tests in Econometrics, Econometrica, vol.46, issue.6, pp.1251-1271, 1978.
DOI : 10.2307/1913827

N. Iea, Projected cost of generating electricity, Intarnational Enargy. Agency and OECD Nuclear Energy Agency, 2010.

S. Isoard and A. Soria, Technical change dynamics: evidence from the emerging renewable energy technologies, Energy Economics, vol.23, issue.6, pp.23-2001, 2001.
DOI : 10.1016/S0140-9883(01)00072-X

A. Jäger-waldau, M. Szabó, F. Monforti-ferrario, H. Bloem, T. Huld et al., Renewable Energy Snapshots, 2011.

T. Jamasb, Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies, The Energy Journal, vol.28, issue.3, 2007.
DOI : 10.5547/ISSN0195-6574-EJ-Vol28-No3-4

P. Joskow, Comparing the Costs of Intermittent and Dispatchable Electricity Generating Technologies, American Economic Review, vol.101, issue.3, pp.238-241, 2011.
DOI : 10.1257/aer.101.3.238

M. Junginger, A. Faaij, and W. C. Turkenburg, Global experience curves for wind farms, Energy Policy, vol.33, issue.2, pp.133-150, 2005.
DOI : 10.1016/S0301-4215(03)00205-2

M. Junginger, P. Lako, S. Lensink, W. Van-sark, and M. Weiss, Technological learning in the energy sector, CLIMATE CHANGE SCIENTIFIC ASSESSMENT AND POLICY ANALYSIS, 2008.
DOI : 10.4337/9781849806848

S. Kahouli-brahmi, Technological learning in energy-environment-economy modelling: A survey, Energy Policy, pp.138-162, 2008.

S. Kahouli-brahmi, Testing for the presence of some features of increasing returns to adoption factors in energy system dynamics: An analysis via the learning curve approach, Ecological Economics, vol.68, issue.4, 2009.
DOI : 10.1016/j.ecolecon.2008.08.013

L. M. Kamp, E. H. Ruud, C. D. Smits, and . Andriesse, Notions on learning applied to wind turbine development in the Netherlands and Denmark, Energy Policy, vol.32, issue.14, pp.1625-1637, 2004.
DOI : 10.1016/S0301-4215(03)00134-4

W. Keller, International Technology Diffusion, Journal of Economic Literature, vol.423, pp.752-782, 2004.

W. Keller, Diffusion of Technology, New Palgrave Dictionary of Economics, 2008.

J. F. Kirkegaard, T. Hanemann, and L. Weischer, It Should Be a Breeze: Harnessing the Potential of Open Trade and Investment Flows in the Wind Energy Industry, SSRN Electronic Journal, 2009.
DOI : 10.2139/ssrn.1521651

P. H. Kobos, J. D. Erickson, and T. Drennen, Technological learning and renewable energy costs: implications for US renewable energy policy, Energy Policy, vol.34, issue.13, pp.1645-1658, 2006.
DOI : 10.1016/j.enpol.2004.12.008

J. Köhler, M. Grubb, D. Popp, and O. Edenhofer, The Transition to Endogenous Technical Change in Climate-Economy Models: A Technical Overview to the Innovation Modeling Comparison Project Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching, the Energy Journal Kouvaritakis, N. International Journal of Global Energy Issues, vol.14, pp.1-4, 2000.

M. B. Lieberman, The Learning Curve and Pricing in the Chemical Processing Industries, The RAND Journal of Economics, vol.15, issue.2, 1984.
DOI : 10.2307/2555676

M. B. Lieberman, The learning curve, diffusion, and competitive strategy, Strategic management journal, pp.441-452, 1987.

J. Lipp, Lessons for effective renewable electricity policy from Denmark, Germany and the United Kingdom, Energy Policy, vol.35, issue.11, pp.5481-5495, 2007.
DOI : 10.1016/j.enpol.2007.05.015

S. Macdonald, Learning rates for energy technologies, Energy Policy, pp.255-261, 2001.

N. Marigo, The Chinese Silicon Photovoltaic Industry and Market: A Critical Review of Trends and Outlook, Progress in Photovoltaic: Research and application, pp.143-162, 2007.

K. E. Maskus, Encouraging technology transfer, UNCTAD-ICTSD Project on IPRs and Sustainable Development, 2004.

P. D. Maycock and G. F. Wakefield, Business analysis of solar photovoltaic conversion, The Conference Record of the 11th IEEE Photovoltaic Specialists Conference, pg, 1975.

. P. Maycock, World Photovoltaic Markets, Report, 2002.
DOI : 10.1016/B978-185617390-2/50039-8

P. D. Maycock, PV technology, performance, 1995.

P. D. Maycock and T. Bradford, PV technology, performance, and cost, 2007.

P. Menanteau, D. Finon, and M. Lamy, Prices versus quantities: choosing policies for promoting the development of renewable energy, Energy Policy, vol.31, issue.8, pp.31-799, 2003.
DOI : 10.1016/S0301-4215(02)00133-7

A. Midttun and K. Gautesen, Feed in or certificates, competition or complementarity? Combining a static efficiency and a dynamic innovation perspective on the greening of the energy industry, Energy Policy, vol.35, issue.3, pp.1419-1422, 2007.
DOI : 10.1016/j.enpol.2006.04.008

H. Mo-lin and Z. Dan-wei, Lessons from photovoltaic policies in China for future development, Energy Policy, vol.51, 2012.

S. Messner, Endogenized technological learning in an energy systems model, Journal of Evolutionary Economics, vol.7, issue.3, pp.291-313, 1997.
DOI : 10.1007/s001910050045

G. F. Nemet, Interim monitoring of cost dynamics for publicly supported energy technologies, Energy Policy, vol.37, issue.3, pp.825-835, 2006.
DOI : 10.1016/j.enpol.2008.10.031

H. Köhler and J. , Technological change in energy systems: Learning curves, logistic curves and input?output coefficients, OECD Ecological Economics, pp.63-749, 2007.

M. Papineau, An economic perspective on experience curves and dynamic economies in renewable energy technologies, Energy Policy, vol.34, issue.4, pp.422-432, 2004.
DOI : 10.1016/j.enpol.2004.06.008

V. Parente, Comments on Experience Curves for PV Modules, Progress in photovoltaics: research and applications, pp.571-574, 2002.

D. Poponi, Analysis of diffusion paths for photovoltaic technology based on experience curves, Solar Energy, vol.74, issue.4, pp.331-340, 2003.
DOI : 10.1016/S0038-092X(03)00151-8

D. Popp, ENTICE: endogenous technological change in the DICE model of global warming, Journal of Environmental Economics and Management, vol.48, issue.1, pp.742-768, 2004.
DOI : 10.1016/j.jeem.2003.09.002

J. Rigter and G. Vidican, Cost and optimal feed-in tariff for small scale photovoltaic systems in China, Energy Policy, vol.38, issue.11, pp.6989-7000, 2010.
DOI : 10.1016/j.enpol.2010.07.014

D. Ruoss, Global Photovoltaics Business and PV in Malaysia, 2007.

G. J. Schaeffer, A. J. Seebregts, L. W. Beurskens, H. H. Moor, E. A. Alsema et al., Learning from the Sun; Analysis of the use of experience curves for energy policy purposes: The case of photovoltaic power, Final report of the Photex project, 2004.

A. Seebregts, T. Kram, G. J. Schaeffer, and A. Bos, Endogenous learning and technology clustering: analysis with MARKAL model of the Western European energy system, International Journal of Global Energy Issues, vol.14, issue.1/2/3/4, pp.1-4, 2000.
DOI : 10.1504/IJGEI.2000.004430

P. Söderholm and G. Klassen, Wind Power in Europe: A Simultaneous Innovation???Diffusion Model, Environmental and Resource Economics, vol.24, issue.12, pp.163-190, 2007.
DOI : 10.1007/s10640-006-9025-z

P. Söderholm and T. Sundqvist, Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies, Renewable Energy, vol.32, issue.15, pp.32-2559, 2007.
DOI : 10.1016/j.renene.2006.12.007

. Strategies-unlimitated, Photovoltaic five-year market forecast, 2002.

&. Sun and . Energy, Z Oversupply ahead, The Solar Silicon Conference, 2011.

R. M. Swanson, A vision for crystalline silicon photovoltaics, Progress in Photovoltaics: Research and Applications, pp.443-453, 2006.
DOI : 10.1002/pip.709

H. Tsuchiya, Photovoltaic cost analysis based on the learning curve, Report, Research Institute for Systems Technology, 1992.

H. Tsuchiya, Learning curve cost analysis for model building of renewable energy in Japan, Proceedings IEA Workshop on Experience Curve for Policy Making?the Case of Energy Technologies, pp.10-11, 1999.

U. Doe, $1/W Systems: A Grand Challenge for Electricity from Solar, 2010.

W. G. Van-sark, Introducing errors in progress ratios determined from experience curves, Technological Forecasting and Social Change, vol.75, issue.3, pp.405-415, 2008.
DOI : 10.1016/j.techfore.2007.03.006

W. G. Van-sark, E. A. Alsema, H. M. Junginger, H. H. De-moor, and G. J. Schaeffer, Accuracy of Progress Ratios Determined From Experience Curves: The Case of Crystalline Silicon Photovoltaic Module Technology Development, Progress in photovoltaics: research and applications, pp.441-453, 2008.

R. Wand and F. Leuthold, Feed-in tariffs for photovoltaics: Learning by doing in Germany? Applied Energy, pp.4387-4399, 2011.

C. Watanabe, K. Wakabayashi, and T. Miyazawa, Industrial dynamism and the creation of a ''virtuous cycle'' between R&D market growth and price reduction. The case of photovoltaic power generation (PV) development in Japan, pp.299-312, 2000.

M. L. Weitzman, Prices vs. Quantities, The Review of Economic Studies, vol.41, issue.4, pp.477-491, 1974.
DOI : 10.2307/2296698

R. H. Williams and G. Terzian, A benefit/cost analysis of accelerated development of photovoltaic technology, 1993.

R. M. Winegarner, Report 1 Silicon Industry A comprehensive report on the use of silicon wafers, silicon ingot, and polysilicon in the semiconductor industry on a fab by fab basis, 2008.

T. P. Wright, Factors Affecting the Cost of Airplanes, Journal of the Aeronautical Sciences, vol.3, issue.4, pp.122-128, 1936.
DOI : 10.2514/8.155

Y. Yang and E. Williams, Theoretical efficiency and asymptotic cost of grid-connected photovoltaic systems, issst, IEEE International Symposium on Sustainable Systems and Technology, 2009.

H. Yanga, H. Wanga, H. Yub, J. Xib, R. Cui et al., Status of photovoltaic industry in China, Energy Policy, vol.31, issue.8, pp.31-703, 2003.
DOI : 10.1016/S0301-4215(02)00121-0

C. F. Yu, How to incorporate input price changes and scale effects into the learning curve? A PV case study, 2008.

C. F. Yu, W. G. Van-sark, and E. A. Alsema, Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects, Renewable and Sustainable Energy Reviews, vol.15, issue.1, pp.324-337, 2011.
DOI : 10.1016/j.rser.2010.09.001