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Closing the Gap between Risk Estimation and Decision Making: Efficient Management of Trade-Related Invasive Species Risk

Author

Listed:
  • Robert P. Lieli

    (Central European University)

  • Michael Springborn

    (University of California)

Abstract

This paper examines the implications of a binary action, binary outcome decision problem for estimating risk. We use data on the invasiveness of biological imports to develop the first comparison of two classical methods—maximum likelihood and Bayesian—against a third, the recently developed maximum utility (MU) approach. MU estimation uniquely takes advantage of the structure of the decision problem, which depends on a local rather than global fit to the model. Extending methods to account for an endogenously stratified sample, we show that the MU approach is less sensitive to specification error and can offer significant economic gains under model uncertainty. © 2013 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Robert P. Lieli & Michael Springborn, 2013. "Closing the Gap between Risk Estimation and Decision Making: Efficient Management of Trade-Related Invasive Species Risk," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 632-645, May.
  • Handle: RePEc:tpr:restat:v:95:y:2013:i:2:p:632-645
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    Citations

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    Cited by:

    1. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    3. Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger, 2016. "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 505-562, June.
    4. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Best subset binary prediction," CeMMAP working papers 50/17, Institute for Fiscal Studies.

    More about this item

    Keywords

    maximum utility estimation; Bayesian decision theory; endogenous stratified sample; risk assessment; invasive species;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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