Monthly wood supply behavior of associated forest owners in Austria-Insights from the analysis of a micro-econometric panel
被引:10
|
作者:
Koch, Sebastian P.
论文数: 0引用数: 0
h-index: 0
机构:
Kompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
Univ Nat Resources & Life Sci, Vienna, AustriaKompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
Koch, Sebastian P.
[1
,2
]
Schwarzbauer, Peter
论文数: 0引用数: 0
h-index: 0
机构:
Kompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
Univ Nat Resources & Life Sci, Vienna, AustriaKompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
Schwarzbauer, Peter
[1
,2
]
Stern, Tobias
论文数: 0引用数: 0
h-index: 0
机构:
Kompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, AustriaKompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
Stern, Tobias
[1
]
机构:
[1] Kompetenzzentrum Holz GmbH, Wood Plus Market Anal & Innovat Res K, Vienna, Austria
[2] Univ Nat Resources & Life Sci, Vienna, Austria
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. (C) 2013 Department of Forest Economics, Swedish University of Agricultural Sciences, Umea. Published by Elsevier GmbH. All rights reserved.