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Updated: May 13, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Statistical basis for predicting technological progress.

Béla Nagy1, J Doyne Farmer, Quan M Bui

  • 1Santa Fe Institute, Santa Fe, New Mexico, USA.

Plos One
|March 8, 2013
PubMed
Summary
This summary is machine-generated.

Technological progress is predictable. Wright's law, which states cost decreases with production, best forecasts future technology costs, closely followed by Moore's law predicting exponential improvement over time.

Related Experiment Videos

Last Updated: May 13, 2026

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

Area of Science:

  • Economics of Technology
  • Innovation Studies
  • Technological Forecasting

Background:

  • Forecasting technological progress is crucial for engineers, policymakers, and investors.
  • Existing models like Wright's law (cost vs. production) and Moore's law (improvement vs. time) lack rigorous testing.
  • A comprehensive database of 62 technologies enables robust evaluation of these models.

Purpose of the Study:

  • To rigorously test and compare the predictive performance of six different models of technological progress.
  • To evaluate the accuracy of Wright's law and Moore's law in forecasting future technology costs.
  • To identify regularities in technological advancement and their implications for forecasting.

Main Methods:

  • Utilized an expansive new database covering cost and production data for 62 diverse technologies.
  • Employed hindcasting techniques to assess the predictive accuracy of various technological progress models.
  • Developed a statistical model to rank the performance of postulated laws, including Wright's and Moore's laws.

Main Results:

  • Wright's law demonstrated the highest accuracy in forecasting future technology costs, with Moore's law performing nearly as well.
  • A novel regularity was observed: production tends to increase exponentially over time.
  • The study confirms that technological progress is forecastable, with a predictable error rate.

Conclusions:

  • Wright's and Moore's laws are nearly indistinguishable under observed regularities of exponential cost decrease and production increase.
  • Technological progress can be reliably forecasted, with implications for assessing new technologies and climate change mitigation strategies.
  • The findings support theories of technological change and provide a quantitative basis for future predictions.