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Virginia Tech

Cost and rents to logging in the Brazilian Amazon

Abstract

dc:description.abstract

The logging industry of the Amazon is a topic that has received little attention in the literature, beyond specific single firm case studies. This has not allowed estimation of cost and production functions that can be used to predict changes in the industry in response to external market factors or government policies. Cost functions and rents are very important to characterize the dynamics of industry behavior, as well as providing important information for future policies. This study relies on a survey of 527 firms to estimate harvest, transportation, and milling cost functions for the logging industry in the Brazilian Amazon, finding variables such as labor cost, distance from the forest to the sawmill, equipment and frontier type to significantly affect the total and marginal cost of each activity. Rents are also estimated for different sampled milling centers, and a cost minimizing mathematical programming model is presented that explains the advance of the logging frontier in Brazil.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Forestry
Department dc:contributor.department
Forestry
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2002

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bauch, Simone Carolina
Chair dc:contributor.committeechair
  • Amacher, Gregory S.
Committee members dc:contributor.committeemember
  • Merry, Frank D.
  • Taylor, Daniel B.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-06092004-112003
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/10048

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Bauch, Simone Carolina. Cost and rents to logging in the Brazilian Amazon. masters thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/10048