Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 60247
Title Quantification of aggregation bias in regional agricultural land use models: application to Guácimo County, Costa Rica
Author(s) Jansen, H.G.P.; Stoorvogel, J.J.
Source Agricultural Systems 58 (1998)3. - ISSN 0308-521X - p. 417 - 439.
DOI https://doi.org/10.1016/S0308-521X(98)00039-0
Department(s) Laboratory of Soil Science and Geology
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 1998
Keyword(s) landgebruik - modellen - costa rica - landbouwbedrijven - classificatie - land use - models - costa rica - farms - classification
Categories Agriculture (General)
Abstract Different specifications of a land use model for Guacimo county in Costa Rica were used to quantify various sources of aggregation bias, including variation in farm resource endowments within and between representative farm classes; spatially variable prices; and labor market inter-dependencies between farm classes. The results indicate that adequate treatment of the farm level in regional land use analysis requires proper classification of individual farms in representative farm classes, as well as explicit modelling of inter-dependencies between such classes. Aggregation bias introduced by the assumption of spatially fixed farm-gate prices is insignificant for regions with reasonable infrastructure quality and relatively small distances between farms and markets. Aggregation bias caused by variation in resource endowments within farm classes cannot be eliminated, but should be minimized, underscoring the importance of a proper farm classification.
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