Informational Efficiency of Markets for Stumpage

Abstract

This paper examines the weak-form informational efficiency of markets for pine sawtimber stumpage in the U.S. South. Analyses of annual and quarterly rates of price change generally indicate that stumpage markets are efficient. When viewed over monthly intervals, stumpage markets do not pass the tests for weak-form efficiency. This failure is attributed to friction in the market due to the time and cost involved in consumating timber sales. The results have implications for price-responsive timber harvest scheduling, for the application of asset pricing models to forestry investments, and for policies governing sales of timber from public lands.Are markets for stumpage informationally efficient (Samuelson 1965, Fama 1970? This question attends several of the most important problems in forest economics. Stumpage market efficiency is a maintained, yet untested, hypothesis in most econometric analyses of timber supply (e.g., Berek, Adams and Haynes). Recent applications of the capital asset pricing model to forestry investments (e.g., Thomson; Binkley and Washburn 1988a, b; Redmond and Cubbage) assume that stumpage markets are efficient. Conversely, several recent papers rely on predictable departures from equilibrium price levels-market inefficiency-to argue that timber owners can make economic gains by adopting marketing policies which exploit stochastic variations in stumpage prices (Norstrom, Brazee and Mendelsohn 1988b, Lohmander 1988).This paper examines the informational efficiency of markets for sawtimber stumpage. We determine whether the current price of sawtimber stumpage incorporates all of the information obtainable by studying past departures from equilibrium rates of price change. This is known Courtland L. Washburn and Clark S. Binkley are a Ph.D. candidate and a professor, respectively, School of Forestry and Environmental Studies, Yale University.This research is part of a larger project on the evaluation of investments in southern pine forestry which is sponsored jointly by Yale University, the USDA Forest Service Southeastern Forest Experiment Station, Scott Paper Company, Weyerhaeuser Company, South Carolina National Bank, and First Wachovia Bank and Trust.The authors wish to thank two anonymous Journal reviewers for many useful comments on earlier drafts. None of these organizations or individuals is responsible for the data, analysis, or conclusions presented here. as a test of "weak-form" market efficiency (Fama 1970).In the next section the theory of storage (Working 1948(Working , 1949Brennan;Telser) is used to derive a rational expectations equilibrium (Muth, Kohn, Scheinkman and Schechtman) for stumpage markets. In equilibrium, the current price of stumpage will equal its expected future price, less expected capital costs and storage expenses (e.g., land rental and protection from fire and pests) plus the expected value of its physical growth. If new information alters expectations, then stumpage flows in or out of storage until the equilibrium is restored. As long as the store of stump...

Theoretical Reserve Price in Forestry

“…Following [3]- [8], [12], I assume that the stumpage prices ( t P ) are exogenous and follow an autoregressive process AR(q) that is stationary 3 . I will discuss the case of a random walk process follow.…”

“…Denoted by * * t t R P δ = − , the optimal reservation price where the optimal cut-off cost * δ satisfies Equation (12). Equation (12) deserves some comments.…”

“…The stumpage prices are assumed to follow a stationary autoregressive process. [12] pointed out that the stumpage market price is best described by a first-order autoregressive process. A stationary autoregressive process has the feature that it is attracted by the long-run mean price (mean-reverting).…”

Appropriate Stochastic Price Models for the Finnish Stumpage Market

“…Unit root tests are the main tools for defining market efficiency. Washburn and Binkley (1990) used a unit root test for the timber market of the south-eastern United States and used monthly, quarterly and annual data. They found that the timber mar-ket was efficient (non-stationary).…”

“…So the assumption of time series behaviour for the same time-span depends on the time interval of the data. Hultkrantz (1993) found that the pooled quarterly data are stationary and the market of timber stumpage price in the south-eastern United States is inefficient when he applied the DickeyFuller test to Washburn and Binkley's (1990) quarterly and annual data. Hultkrantz (1995) to 1996 as well as expert judgment, and due to their low number of observations modelled data as AR (1) process.…”