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Journal of Forest Research

, Volume 1, Issue 2, pp 67–72 | Cite as

Economic analysis of harvesting behavior using the modified Gentan probability theory

  • Atsushi Yoshimoto
Original Articles

Abstract

In the past studies on the Gentan probability theory, economic factors, such as the price of logs and the interest rate, have not been embedded into the derived stochastic model due to the limitation of the underlying assumptions. This has lead to misleading results of economic analysis for harvesting behavior based on the Gentan probability theory. In this paper, economic analysis of harvesting behavior was conducted by extending the Gentan probability theory. Since the proposed stochastic process can incorporate a nonstationary growth function, economic analysis of harvesting behavior was easily implemented. Experimental analysis of economic factors showed that change in the price of logs, the interest rate and harvest related costs affected the Gentan probability distribution. Although the analysis is still hypothetical, the results imply the potential use of the Gentan probability theory to predict the forest owners' harvesting behavior.

Key words

a counting process forest economics harvesting behavior harvest scheduling statistical model 

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Literature cited

  1. Amano, M., Noda, I., and Kumazaki, M. (1984) Timber supply projection for private forests in Japan. Proc. IUFRO Symp. For. Manage. Plan. Manage. Econ: 285–292.Google Scholar
  2. Blandon, P. (1985) Forest economics and the Gentan probability distribution. J. Jpn. For. Soc. 67: 478–485.Google Scholar
  3. Blandon, P. (1991) Gentan probability and censored sample theory (I). J. Jpn. For. Soc. 73: 187–196.Google Scholar
  4. Blandon, P. (1993) Unmanaged forests and forecasting using the Gentan probability distribution. J. Jpn. For. Soc. 75: 484–492.Google Scholar
  5. Blandon, P. (1994) Movements in the parameters of the Gentan probability distribution. J. Jpn. For. Soc. 76: 1–9.Google Scholar
  6. Richards, F.J. (1958) A flexible growth function to empirical use. J. Exp. Bot. 10: 290–300Google Scholar
  7. Rinyacho (1984) Report on the development of the domestic timber supply model. 122pp, Rinyacho Kikakuka, Tokyo, 40–69. (in Japanese) These English titles are tentative translations by the author of this paper from the original Japanese.Google Scholar
  8. Suzuki, T. (1972) Applications of stochastic process in forestry (I). J. Jpn. For. Soc. 54: 234–243. (In Japanese)Google Scholar
  9. Suzuki, T. (1979) Forest management. 197pp, Asakurashoten, Tokyo. (in Japanese) These English titles are tentative translations by the author of this paper from the original Japanese.Google Scholar
  10. Suzuki, T. (1984) The Gentan probability, a model for the improvement of the normal forest concept and of forest planning. Proc. IUFRO Symp. For. Manage. Plan. Manage. Econ.: 12–24.Google Scholar
  11. The Science and Technology Agency (1961) Report on forecast of the timber production. Kagakugijutucho-Shigenkyoku Shiryo No. 45: 116pp. (in Japanese) These English titles are tentative translations by the author of this paper from the original Japanese.Google Scholar
  12. The Science and Technology Agency (1963) Report on forecast of the timber production (II) Mathematical study on harvest scheduling in forestry. Kagakugijutucho-Shigenkyoku Shiryo No.53: 54pp. (in Japanese) These English titles are tentative translations by the author of this paper from the original Japanese.Google Scholar

Copyright information

© Japanese Forestry Society 1996

Authors and Affiliations

  • Atsushi Yoshimoto
    • 1
  1. 1.Department of Agricultural and Forest EconomicsMiyazaki UniversityMiyazakiJapan

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