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Learning-by-Doing under Uncertainty

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  • Alvarez, Francisco
  • Amman, Hans

Abstract

Empirical research indicates that learning-by-doing may be one of the main causes of falling production costs. A number of authors like Arrow, Fudenberg and Tirole, Dasgupta and Stiglitz, have focused on the theoretical implications of learning-by-doing. However, a complete framework incorporating learning, stock building as well as uncertainty, is lacking in the literature. In this paper we broaden earlier theoretical work in two ways. First, we present a theoretical model of learning-by-doing in which the unit-cost structure is not fully known to the firm. The firm has to estimate its stochastic cost structure during the production process. Second, the model allows for the firm to keep a stock which adds to the complexity of the learning process. Through Monte Carlo techniques we derive the optimal production and sales quantities for multiple cost structures. Citation Copyright 1999 by Kluwer Academic Publishers.

Suggested Citation

  • Alvarez, Francisco & Amman, Hans, 1999. "Learning-by-Doing under Uncertainty," Computational Economics, Springer;Society for Computational Economics, vol. 14(3), pages 255-262, December.
    • Handle: RePEc:kap:compec:v:14:y:1999:i:3:p:255-62
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    Cited by:

    1. Dzhumashev, Ratbek & Mishra, Vinod & Smyth, Russell, 2016. "Exporting, R&D investment and firm survival in the Indian IT sector," Journal of Asian Economics, Elsevier, vol. 42(C), pages 1-19.
    2. Qin Lu & Jingwen Liao & Kechi Chen & Yanhui Liang & Yu Lin, 2024. "Predicting Natural Gas Prices Based on a Novel Hybrid Model with Variational Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 639-678, February.

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