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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 277607, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea79:277607
    DOI: 10.22004/ag.econ.277607
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    References listed on IDEAS

    as
    1. 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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