Assessing commercial timberland assets in the U.S.
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In the past several decades, timberland ownership in the United States has changed dramatically. Traditional vertically-integrated forest products firms have been divesting their timberlands, while timberland investment management organizations (TIMOs) have been active acquirers. As a unique asset class, timberland has three return drivers, namely, the biological growth, timber price, and land price. Biological growth can be consistently estimated, land price is correlated with inflation, while timber price remains most unpredictable. The first part of this dissertation aims to model and forecast timber prices in 12 southern timber regions via different time series models. The results reveal that the vector autoregressive model (VAR) forecasts more accurately for 2009Q1-2009Q4, seven out of the 12 southern timber regions play dominant roles in the long-run equilibrium, and the conditional variances and covariances from the bivariate generalized autoregressive conditional heteroscedasticity (GARCH) model well capture market risks. The second part examines the financial performance of private- and public-equity timberland investments in the U.S. using both parametric and nonparametric asset pricing approaches. The results reveal that private-equity timberland investments outperform the market, and have low systematic risk, whereas public-equity timberland investments fare similarly as the market. The last part investigates real option values of investment, mothballing, reactivation, and abandonment in a hypothetical southern pine plantation using the contingent claims approach. The results reveal that these option values, while ignored by the discounted cash flow (DCF) analysis, do affect timber management decisions. The impacts of changes in the key economic parameters on changes in the option values are examined in the sensitivity analysis.