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Wald Revisited: The Optimal Level of Experimentation

Author

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  • Giuseppe Moscarini
  • Lones Smith

Abstract

This paper revisits Wald's (1947) sequential experimentation paradigm, now assuming that an impatient decision maker can run variable-size experiments each period at some increasing and strictly convex cost before finally choosing an irreversible action. We translate this natural discrete time experimentation story into a tractable control of variance for a continuous time diffusion. Here we robustly characterize the optimal experimentation level: It is rising in the confidence about the project outcome, and for not very convex cost functions, the random process of experimentation levels has a positive drift over time. We also explore several parametric shifts unique to our framework. Among them, we discover what is arguably an 'anti-folk' result: Where the experimentation level is positive, it is often higher for a more impatient decision maker. This paper more generally suggests that a long-sought economic paradigm that delivers a sensible law of demand for information is our dynamic one namely, allowing the decision maker an eternal repurchase (resample) option.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Giuseppe Moscarini & Lones Smith, 1998. "Wald Revisited: The Optimal Level of Experimentation," Working papers 98-4, Massachusetts Institute of Technology (MIT), Department of Economics.
    • Handle: RePEc:mit:worpap:98-4
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    Cited by:

    1. Manuel Tong Koecklin, . "Experimenting in Export Markets," Economics PhD Theses, Department of Economics, University of Sussex Business School, number 0918, December.
    2. Cristina Mitaritonna & Zhanar Akhmetova, 2013. "A Model of Firm Experimentation under Demand Uncertainty: an Application to Multi-Destination Exporters," Working Papers 2013-10, CEPII research center.
    3. Rauch, James E. & Watson, Joel, 2003. "Starting small in an unfamiliar environment," International Journal of Industrial Organization, Elsevier, vol. 21(7), pages 1021-1042, September.
    4. Hector Chade & Edward E. Schlee, 2000. "Increasing Returns in the Value of Information," Econometric Society World Congress 2000 Contributed Papers 1715, Econometric Society.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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