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Economic Model Building and Computers in Forestry Research

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Although most past research in forestry economics was characteristically descriptive in nature, recent research is more diagnostic. Formal model building is used more extensively when diagnostic studies are undertaken. Models are classified as: (1) either verbal or mathematical; (2) within mathematical models - either deterministic or econometric; (3) microeconomic or macroeconomic; (4) static, comparative static, or dynamic; and (5) within dynamic models, either continuous or discrete dynamic. Steps in the model building process are indicated, with emphasis on the interrelations between the steps, feedbacks, and the division between the real and symbolic worlds. Criteria for testing adequacy of models partly depend on the model type. The role that data processing equipment can play in each stage of the model building process is pointed out. A computer can be a fundamental tool in the research process, best understood as an integral part of the model building process.

Document Type: Journal Article

Affiliations: Economist, Pacific Northwest Forest and Range Expt. Sta., Forest Serv., U.S. Dept. Agric., Portland, Ore.

Publication date: May 1, 1966

More about this publication?
  • The Journal of Forestry is the most widely circulated scholarly forestry journal in the world. In print since 1902, the Journal has received several national awards for excellence. The mission of the Journal of Forestry is to advance the profession of forestry by keeping forest management professionals informed about significant developments and ideas in the many facets of forestry: economics, education and communication, entomology and pathology, fire, forest ecology, geospatial technologies, history, international forestry, measurements, policy, recreation, silviculture, social sciences, soils and hydrology, urban and community forestry, utilization and engineering, and wildlife management. The Journal is published bimonthly: January, March, May, July, September, and November.

    2015 Impact Factor: 1.476
    Ranking: 22 of 66 in forestry

    Also published by SAF:
    Forest Science
    Other SAF Publications
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