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.

Master of Science