Journal of Forest Economics > Vol 19 > Issue 3

Monthly wood supply behavior of associated forest owners in Austria—Insights from the analysis of a micro-econometric panel

Sebastian P. Koch, Kompetenzzentrum Holz GmbH, Wood K Plus – Market Analysis and Innovation Research, Austria AND University of Natural Resources and Life Sciences, Austria, koch@boku.ac.at , Peter Schwarzbauer, Kompetenzzentrum Holz GmbH, Wood K Plus – Market Analysis and Innovation Research, Austria AND University of Natural Resources and Life Sciences, Austria, Tobias Stern, Kompetenzzentrum Holz GmbH, Wood K Plus – Market Analysis and Innovation Research, Austria
 
Suggested Citation
Sebastian P. Koch, Peter Schwarzbauer and Tobias Stern (2013), "Monthly wood supply behavior of associated forest owners in Austria—Insights from the analysis of a micro-econometric panel", Journal of Forest Economics: Vol. 19: No. 3, pp 331-346. http://dx.doi.org/10.1016/j.jfe.2013.06.003

Publication Date: 0/8/2013
© 0 2013 Sebastian P. Koch, Peter Schwarzbauer, Tobias Stern
 
Subjects
 
Keywords
JEL Codes:C23C24Q23
Monthly wood supplySeasonalityForest owner associationPanel regressionTobit modelAustria
 

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In this article:
Introduction 
Methodology and data 
Results 
Conclusions 

Abstract

This paper examines the wood supply from non-industrial private forest owners in Austria. The main novelty of this study is threefold. First, the underlying dataset is based on monthly wood supply. This enables an analysis of seasonal supply behavior, which is found to be different in relation to the size of the forestland. Second, it represents an original study with a dataset from a Central European country whose forest owners are apparently much more fragmented than their Scandinavian or North American counterparts. And third, the study introduces a windfall variable that effectively corrects for a market-relevant storm event. With respect to methodology, a random effects Tobit model is applied. Additionally, a Chamberlain-like term is included in the regression to deal with a possible bias generated through the correlation of regressors and unobserved heterogeneity.

DOI:10.1016/j.jfe.2013.06.003