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In 2005, nearly $30 billion of American forest land in the hands of institutional investors may suggest that timberland is a good portfolio diversifier. However, this statement may be overstated because forestry investments may have correlations with non-forestry assets in the long run. In addition, timberland investment is largely determined by stumpage market. Moreover, the differentiated ownerships make the analysis of the stumpage market more complicated. This study investigates the relationships between forestry and non-forestry instruments in the US while examining pulpwood market and stumpage supply by differentiated ownerships in the US South. Chapter 1 the introduction identifies research problems and presents research objectives. Chapter 2 presents a literature review focusing on the major empirical analyses of timberland investment and stumpage market. Chapter 3 investigates the short-run and long-run correlations between forestry and non-forestry assets in the US using quarterly data from January 1992 to July 2006. The results of capital asset pricing model (CAPM) show that the eight investment vehicles (timberland, timber, farmland, national property index, treasury bill for 3-month, deposit, government bond for 30 years, and gold) have lower risk and lower relationship with S&P 500 in the short run. The results of cointegration analysis show that cointegrated relationships exist between timberland, timber price, and the financial assets. Chapter 4 examines the determinants of pine pulpwood supply and demand in the southern US using annual data from 1950 to 2002 with three-stage least squares (3SLS) regression techniques. The results of SSE model show that price elasticities of supply of and demand for pine pulpwood are relatively small, which is consistent with previous studies for the US South. In addition, the significant substitution between pulpwood stumpage and energy use was found with an elasticity of -0.35. Chapter 5 focuses on the short run price elasticities for stumpage market by comparing forest industry (FI) and non-industrial private forest (NIPF) using a two-stage least squares (2SLS) techniques with time series data from 1953 to 2002. The estimated results show that supply price elasticities of 0.70 for sawtimber and 0.90 for pulpwood for FI owners are larger than those of 0.29 for sawtimber and 0.32 for pulpwood for NIPF owners, which, in general, are within the price elasticity range from previous studies. Finally, chapter 6 summarizes the major findings of this study and some policy implications. Recommendations for further research are also addressed in this chapter. Key words: Timberland return, capital asset pricing model, co-integration, simultaneous system of equations, profit maximization model, price elasticity