Spatial Spillover Effects of Pine Sawtimber Stumpage Prices in the US South

Author:

Lamichhane Sabhyata1ORCID,Mei Bin1,Siry Jacek1ORCID

Affiliation:

1. Warnell School of Forestry and Natural Resources, University of Georgia , Athens, GA 30602 , USA

Abstract

Abstract Timberland returns have three main drivers: biological growth, timber price, and land value. Among three of these drivers, timber price is the most volatile. Therefore, modeling and predicting timber prices has been of great concern for timberland investors and other stakeholders. In this study, the spatial dependency and spillover effect of sawtimber prices were investigated across 11 southern states with three different spatial panel models. The findings revealed a strong positive spatial dependency in sawtimber prices across these states, and the observed spillover effect for significant independent variables was over 35% of the total effect. Similarly, pulpwood prices not only have positive impact on the sawtimber prices of a given state but also on its contiguous states. In addition, the impact of COVID-19 pandemic on sawtimber prices was positive and significant. These results would facilitate the valuation of timberland investments as well as predict future timber prices. Study Implications: The sawtimber prices of one state positively affect the future sawtimber prices of neighboring states in addition to its own. Similarly, a shock in a given state also affects the sawtimber prices of its neighbors. Given the volatile nature of timber prices, gaining a better understanding of spatial integration of timber markets improves prediction of sawtimber price fluctuations and trends that ultimately help timberland investors to make effective decisions.

Publisher

Oxford University Press (OUP)

Subject

Ecological Modeling,Ecology,Forestry

Reference31 articles.

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3. “Testing For Serial Correlation, Spatial Autocorrelation And Random Effects Using Panel Data.”;Baltagi;Journal of Econometrics,2007

4. “Market Structure in U. S. Southern Pine Roundwood.”;Bingham;Journal of Econometrics,2003

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