Forecasting Technological Progress

26. Forecasting Technological Progress

Author: François Lafond, University of Oxford

 

Abstract

After a brief history of technological forecasting, I synthesize our work at the Institute for New Economic Thinking (INET) over the last decade developing time-series models for performance curves. I conclude with ongoing efforts and a research agenda.

Keywords: performance curves, learning curves, experience curves, diffusion curves, patent networks

Bibliography

Acemoglu, D., U. Akcigit, and W. R. Kerr. 2016. “Innovation Network.” Proceedings of the National Academy of Sciences 113 (41): 11483–11488. https://doi.org/10.1073/pnas.1613559113.

Albright, R. E. 2002. “What Can Past Technology Forecasts Tell Us about the Future?” Technological Forecasting and Social Change 69 (5): 443–464. https://doi.org/10.1016/S0040-1625(02)00186-5.

Alstott, J., G. Triulzi, B. Yan, and J. Luo. 2017. “Mapping Technology Space by Normalizing Patent Networks.” Scientometrics 110: 443–479. https://doi.org/10.1007/s11192-016-2107-y.

Argote, L., and D. Epple. 1990. “Learning Curves in Manufacturing.” Science 247 (4945): 920–924. https://doi.org/10.1126/science.247.4945.920.

Arrow, K. J. 1962. “The Economic Implications of Learning by Doing.” The Review of Economic Studies 29 (3): 155–173. https://doi.org/10.2307/2295952.

Arrow, K. J., R. Forsythe, M. Gorham, R. Hahn, R. Hanson, J. O. Ledyard, S. Levmore, et al. 2008. “The Promise of Prediction Markets.” Science 320 (5878): 877–878. https://doi.org/10.1126/science.1157679.

Arthur, W. B. 1989. “Competing Technologies, Increasing Returns, and Lock-In by Historical Events.” The Economic Journal, 116–131. https://doi.org/10.2307/2234208.

—. 2010. The Nature of Technology: What It Is and How It Evolves. New York, NY: Free Press.

—. 2025. “Combinatorial Evolution.” In The Economy as an Evolving Complex System IV, edited by R. M. del Rio-Chanona, M. Pangallo, J. Bednar, E. D. Beinhocker, J. Kaszowska-Mojsa, F. Lafond, P. Mealy, A. Pichler, and J. D. Farmer. Santa Fe, NM: SFI Press.

Ayres, R. U. 1969. Technological Forecasting and Long-Range Planning. Maidenhead, NY: McGraw-Hill Book Company. https://archive.org/details/technologicalfor0000ayre_l4a1/.

Baumgärtner, L., and J. D. Farmer. n.d. “Empirical Basis for National Renewable Cost Forecasts.” In progress.

Bengio, Y., S. Russell, E. Musk, S. Wozniak, Y. N. Harari, E. Mostaque, A. Yang, et al. 2023. Pause Giant AI Experiments: An Open Letter. Future of Life Institute. https://futureoflife.org/open-letter/pause-giant-ai-experiments/.

Benson, C. L., G. Triulzi, and C. L. Magee. 2018. “Is There a Moore’s Law for 3D Printing?” 3D Printing and Additive Manufacturing 5 (1): 53–62. https://doi.org/10.1089/3dp.2017.0041.

Ciarli, T., A. Coad, and I. Rafols. 2016. “Quantitative Analysis of Technology Futures: A Review of Techniques, Uses and Characteristics.” Science and Public Policy 43 (5): 630–645. https://doi.org/10.1093/scipol/scv059.

Clements, M., and D. F. Hendry. 1998. Forecasting Economic Time Series. Cambridge, UK: Cambridge University Press.

Diane, C. 2025. “Why Are New Ideas Getting Harder to Use?” In The Economy as an Evolving Complex System IV, edited by R. M. del Rio-Chanona, M. Pangallo, J. Bednar, E. D. Beinhocker, J. Kaszowska-Mojsa, F. Lafond, P. Mealy, A. Pichler, and J. D. Farmer. Santa Fe, NM: SFI Press.

Entorf, H. 1997. “Random Walks with Drifts: Nonsense Regression and Spurious Fixed-Effect Estimation.” Journal of Econometrics 80 (2): 287–296. https://doi.org/10.1016/S0304-4076(97)00041-9.

Érdi, P., K. Makovi, Z. Somogyvári, K. Strandburg, J. Tobochnik, P. Volf, and L. Zalányi. 2013. “Prediction of Emerging Technologies Based on Analysis of the US Patent Citation Network.” Scientometrics 95 (1): 225–242. https://doi.org/10.1007/s11192-012-0796-4.

Farmer, J. D., and F. Lafond. 2016. “How Predictable Is Technological Progress?” Research Policy 45 (3): 647–665. https://doi.org/10.1016/j.respol.2015.11.001.

Foerster, A. T., P.-D. G. Sarte, and M. W. Watson. 2011. “Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production.” Journal of Political Economy 119 (1): 1–38. https://doi.org/10.1086/659311.

Frenken, K., and F. Neffke. 2025. “Economic Geography and Complexity Theory.” In The Economy as an Evolving Complex System IV, edited by R. M. del Rio-Chanona, M. Pangallo, J. Bednar, E. D. Beinhocker, J. Kaszowska-Mojsa, F. Lafond, P. Mealy, A. Pichler, and J. D. Farmer. Santa Fe, NM: SFI Press.

Funk, J. L., and C. L. Magee. 2015. “Rapid Improvements with No Commercial Production: How Do the Improvements Occur?” Research Policy 44 (3): 777–788. https://doi.org/10.1016/j.respol.2014.11.005.

Gilfillan, S. C. 1937. “The Prediction of Inventions.” Journal of the Patent and Trademark Office Society 19: 623.

Goldin, I., P. Koutroumpis, F. Lafond, and J. Winkler. 2024. “Why Is Productivity Slowing Down?” Journal of Economic Literature 62 (1): 196–268. https://doi.org/10.1257/jel.20221543.

Gordon, R. J. 1990. The Measurement of Durable Goods Prices. Chicago, IL: University of Chicago Press.

Grace, K., H. Stewart, J. F. Sandkühler, S. Thomas, B. Weinstein-Raun, J. Brauner, and R. C. Korzekwa. 2024. “Thousands of AI Authors on the Future of AI.” arXiv preprint 2401.02843. https://doi.org/10.48550/arXiv.2401.02843.

Grübler, A., N. Nakićenović, and D. G. Victor. 1999. “Dynamics of Energy Technologies and Global Change.” Energy Policy 27 (5): 247–280. https://doi.org/10.1016/S0301-4215(98)00067-6.

Halawi, D., F. Zhang, C. Yueh-Han, and J. Steinhardt. 2024. “Approaching Human-Level Forecasting with Language Models.” arXiv preprint 2402.18563. https://doi.org/10.48550/arXiv.2402.18563.

Harper, J. C. 2013. Impact of Technology Foresight. Compendium of Evidence on the Effectiveness of Innovation Policy Intervention Project, Nesta Working Paper no. 13/16. Compendium of Evidence on the Effectiveness of Innovation Policy Intervention, Manchester Institute of Innovation Research. https://www.nesta.org.uk/wp13-16.

Jantsch, E. 1967. Technological Forecasting in Perspective. OECD.

Kahn, H., and A. J. Wiener. 1967. “The Next Thirty-Three Years: A Framework for Speculation.” Daedalus 96 (3): 705–732. https://www.jstor.org/stable/20027066.

Kim, D., D. B. Cerigo, H. Jeong, and H. Youn. 2016. “Technological Novelty Profile and Invention’s Future Impact.” EPJ Data Science 5: 1–15. https://doi.org/10.1140/epjds/s13688-016-0069-1.

Koh, H., and C. L. Magee. 2006. “A Functional Approach for Studying Technological Progress: Application to Information Technology.” Technological Forecasting and Social Change 73 (9): 1061–1083. https://doi.org/10.1016/j.techfore.2006.06.001.

—. 2008. “A Functional Approach for Studying Technological Progress: Extension to Energy Technology.” Technological Forecasting and Social Change 75 (6): 735–758. https://doi.org/10.1016/j.techfore.2007.05.007.

Lafond, F., A. G. Bailey, J. D. Bakker, D. Rebois, R. Zadourian, P. McSharry, and J. D. Farmer. 2018. “How Well Do Experience Curves Predict Technological Progress? A Method for Making Distributional Forecasts.” Technological Forecasting and Social Change 128: 104–117. https://doi.org/10.1016/j.techfore.2017.11.001.

Lafond, F., D. Greenwald, and J. D. Farmer. 2022. “Can Stimulating Demand Drive Costs Down? World War II as a Natural Experiment.” The Journal of Economic History 82 (3): 727–764. https://doi.org/10.1017/S0022050722000249.

Lafond, F., and D. Kim. 2019. “Long-Run Dynamics of the US Patent Classification System.” Journal of Evolutionary Economics 29 (2): 631–664. https://doi.org/10.1007/s00191-018-0603-3.

Malhotra, A., and T. S. Schmidt. 2020. “Accelerating Low-Carbon Innovation.” Joule 4 (11): 2259–2267. https://doi.org/10.1016/j.joule.2020.09.004.

Mandelbrot, B. 1997. “A Case Against the Lognormal Distribution.” In Fractals and Scaling in Finance: Discontinuity, Concentration, Risk, 252–269. New York, NY: Springer. https://doi.org/10.1007/978-1-4757-2763-0_9.

Mariani, M. S., M. Medo, and F. Lafond. 2019. “Early Identification of Important Patents: Design and Validation of Citation Network Metrics.” Technological Forecasting and Social Change 146: 644–654. https://doi.org/10.1016/j.techfore.2018.01.036.

Markowitz, H. 1952. “Portfolio Selection.” Journal of Finance 7 (1): 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x.

Martino, J. P. 1993. Technological Forecasting for Decision Making. New York, NY: McGraw-Hill, Inc.

Meng, J., R. Way, E. Verdolini, and L. Díaz Anadón. 2021. “Comparing Expert Elicitation and Model-Based Probabilistic Technology Cost Forecasts for the Energy Transition.” Proceedings of the National Academy of Sciences 118 (27): e1917165118. https://doi.org/10.1073/pnas.1917165118.

Nagy, B., J. D. Farmer, Q. M. Bui, and J. E. Trancik. 2013. “Statistical Basis for Predicting Technological Progress.” PLOS One 8 (2): 1–7. https://doi.org/10.1371/journal.pone.0052669.

Nagy, B., J. D. Farmer, J. E. Trancik, and J. P. Gonzales. 2011. “Superexponential Long-Term Trends in Information Technology.” Technological Forecasting and Social Change 78 (8): 1356–1364. https://doi.org/10.1016/j.techfore.2011.07.006.

Napolitano, L., E. Evangelou, E. Pugliese, P. Zeppini, and G. Room. 2018. “Technology Networks: The Autocatalytic Origins of Innovation.” Royal Society Open Science 5 (6): 172445. https://doi.org/10.1098/rsos.172445.

Neffke, F., A. Sbardella, U. Schetter, and A. Tacchella. 2025. “Economic Complexity Analysis.” In The Economy as an Evolving Complex System IV, edited by R. M. del Rio-Chanona, M. Pangallo, J. Bednar, E. D. Beinhocker, J. Kaszowska-Mojsa, F. Lafond, P. Mealy, A. Pichler, and J. D. Farmer. Santa Fe, NM: SFI Press.

Nordhaus, W. D. 2014. “The Perils of the Learning Model for Modeling Endogenous Technological Change.” The Energy Journal 35 (1): 1–14. https://doi.org/10.5547/01956574.35.1.1.

Pfeiffer, A., C. Hepburn, A. Vogt-Schilb, and B. Caldecott. 2018. “Committed Emissions from Existing and Planned Power Plants and Asset Stranding Required to Meet the Paris Agreement.” Environmental Research Letters 13 (5): 054019. https://doi.org/10.1088/1748-9326/aabc5f.

Philippon, T. 2023. Additive Growth. Technical report. Leonard N. Stern School of Business. https://pages.stern.nyu.edu/~tphilipp/papers/AddGrowth_macro.pdf.

Pichler, A. 2021. “Network-Dependent Dynamics of Innovation and Production.” PhD diss., University of Oxford.

Pichler, A., F. Lafond, and J. D. Farmer. 2020. “Technological Interdependencies Predict Innovation Dynamics.” arXiv preprint 2003.00580. https://doi.org/10.48550/arXiv.2003.00580.

Porter, A. L., and S. W. Cunningham. 2005. “Tech Mining.” Competitive Intelligence Magazine 8 (1): 30–36.

Sahal, D. 1979. “A Theory of Progress Functions.” AIIE Transactions 11 (1): 23–29. https://doi.org/10.1080/05695557908974396.

Sampson, M. 1991. “The Effect of Parameter Uncertainty on Forecast Variances and Confidence Intervals for Unit Root and Trend Stationary Time-Series Models.” Journal of Applied Econometrics 6 (1): 67–76. https://doi.org/10.1002/jae.3950060106.

Schoenegger, P., I. Tuminauskaite, P. S. Park, and P. E. Tetlock. 2024. Wisdom of the Silicon Crowd: LLM Ensemble Prediction Capabilities Match Human Crowd Accuracy. https://doi.org/10.48550/arXiv.2402.19379.

Shi, F., and J. Evans. 2023. “Surprising Combinations of Research Contents and Contexts Are Related to Impact and Emerge with Scientific Outsiders from Distant Disciplines.” Nature Communications 14 (1): 1641. https://doi.org/10.1038/s41467-023-36741-4.

Solé, R. V., S. Valverde, M. R. Casals, S. A. Kauffman, J. D. Farmer, and N. Eldredge. 2013. “The Evolutionary Ecology of Technological Innovations.” Complexity 18 (4): 15–27. https://doi.org/10.1002/cplx.21436.

Strumsky, D., and J. Lobo. 2015. “Identifying the Sources of Technological Novelty in the Process of Invention.” Research Policy 44 (8): 1445–1461. https://doi.org/10.1016/j.respol.2015.05.008.

Tacchella, A., A. Napoletano, and L. Pietronero. 2020. “The Language of Innovation.” PLOS One 15 (4): e0230107. https://doi.org/10.1371/journal.pone.0230107.

Tankwa, B. 2024. Is Technology Diffusion Accelerating? In progress.

Tetlock, P. E., and D. Gardner. 2016. Superforecasting: The Art and Science of Prediction. New York, NY: Random House.

Triulzi, G., J. Alstott, and C. L. Magee. 2020. “Estimating Technology Performance Improvement Rates by Mining Patent Data.” Technological Forecasting and Social Change 158: 120100. https://doi.org/10.1016/j.techfore.2020.120100.

Verdolini, E., L. Díaz Anadón, E. Baker, V. Bosetti, and L. A. Reis. 2018. “Future Prospects for Energy Technologies: Insights from Expert Elicitations.” Review of Environmental Economics and Policy. https://doi.org/10.1093/reep/rex028.

Wagenvoort, B., J. Dyer, F. Lafond, and J. D. Farmer. 2025. “Universality and Predictability of Technology Diffusion.” In progress.

Way, R., M. C. Ives, P. Mealy, and J. D. Farmer. 2022. “Empirically Grounded Technology Forecasts and the Energy Transition.” Joule 6 (9): 2057–2082. https://doi.org/10.1016/j.joule.2022.08.009.

Way, R., F. Lafond, F. Lillo, V. Panchenko, and J. D. Farmer. 2019. “Wright Meets Markowitz: How Standard Portfolio Theory Changes When Assets Are Technologies Following Experience Curves.” Journal of Economic Dynamics and Control 101: 211–238. https://doi.org/10.1016/j.jedc.2018.10.006.

Youn, H., D. Strumsky, L. M. A. Bettencourt, and J. Lobo. 2015. “Invention as a Combinatorial Process: Evidence from US Patents.” Journal of the Royal Society Interface 12 (106): 20150272. https://doi.org/10.1098/rsif.2015.0272.

Zadourian, R. 2018. “Model-Based and Empirical Analyses of Stochastic Fluctuations in Economy and Finance.” PhD diss., Technische Universität Dresden.

Zadourian, R., and A. Klümper. 2018. “Exact Probability Distribution Function for the Volatility of Cumulative Production.” Physica A: Statistical Mechanics and Its Applications 495: 59–66. https://doi.org/10.1016/j.physa.2017.12.003.

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