OPTIMAL SEQUENTIAL SAMPLING OF NATURAL RESOURCE STOCKS: AN APPLICATION OF KALMAN FILTERING

Bruce L. Dixon and Richard E. Howitt

No 277607, 1979 Annual Meeting, July 29-August 1, Pullman, Washington from American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association)

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.

Keywords: Productivity; Analysis (search for similar items in EconPapers)
Pages: 15
Date: 1979-07
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea79:277607

DOI: 10.22004/ag.econ.277607

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