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A Markov Model of the Learning Curve

Author

Listed:
  • Larsen, Harry

Abstract

A learning curve is the labor hours per unit of production in the production sequence. Before its cost realization, it is typically forecast using the power function, hours(unit) = a unitb, with a and b derived from historical data via regressions. After the first unit’s cost is realized, future costs can be projected from the sequence of actualized units. This paper transforms the power function into a Markov model and applies a Kalman Filter to estimate the expected value, slope, and variance of a learning curve projection. To exemplify the solution, the parameters of the Kalman Filter are estimated from a set of twenty 1000-unit learning curves derived from The Theory of Complex Work. For those responsible for predicting future values of an ongoing production program, this procedure provides optimal estimates of unit labor hours and their variances.

Suggested Citation

  • Larsen, Harry, 2026. "A Markov Model of the Learning Curve," MPRA Paper 128435, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:128435
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    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L6 - Industrial Organization - - Industry Studies: Manufacturing
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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