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Optimal Sequential Sampling Of Natural Resource Stocks: An Application Of Kalman Filtering

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  • Dixon, Bruce L.
  • Howitt, Richard E.

Abstract

For sequential estimation of resource stocks, partial replacement sampling is conventionally thought to give stock estimates with lower standard errors than estimators using simple random samples. Viewing resource production scheduling as dynamic, stochastic optimization, partial replacement sampling.is shown to be inefficient In certain instances compared with simple random sampling.

Suggested Citation

  • Dixon, Bruce L. & Howitt, Richard E., 1979. "Optimal Sequential Sampling Of Natural Resource Stocks: An Application Of Kalman Filtering," 1979 Annual Meeting, July 29-August 1, Pullman, Washington 278370, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea79:278370
    DOI: 10.22004/ag.econ.278370
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    References listed on IDEAS

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    1. Michael Athans, 1972. "The Discrete Time Linear-Quadratic-Gaussian Stochastic Control Problem," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 449-491, National Bureau of Economic Research, Inc.
    2. Burt, Oscar R & Cummings, Ronald G, 1970. "Production and Investment in Natural Resource Industries," American Economic Review, American Economic Association, vol. 60(4), pages 576-590, September.
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    Resource /Energy Economics and Policy;

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