Douglas J. Miller

An Econometric Analysis of the Costs of Sequestering Carbon in Forests

The Kyoto Protocol and the U.S. Climate Change Plan recognize afforestation as a potential means of reducing atmospheric CO 2 concentrations. To examine the cost-effectiveness of afforestation, we use econometric land use models to estimate the marginal costs of carbon sequestration in Maine, South Carolina, and Wisconsin. Our findings include the following: (a) earlier studies of afforestation programs tend to underestimate carbon sequestration costs, (b) afforestation still appears to be a relatively low-cost approach to reducing CO 2 concentrations, (c) Wisconsin offers the lowest-cost opportunties for carbon sequestration, and (d) projected population changes have the largest effect on costs in South Carolina. Copyright 1999, Oxford University Press.

Agricultural Land Values and the Value of Rights to Future Land Development

We investigate the influence of future land development on current agricultural land values. From a theoretical model of land markets, we derive a reduced-form expression for agricultural land values in terms of observable variables. This result dictates the specification of our econometric model and we find strong support for the model in an application to New York State. The estimated model, together with a spatial interpolation algorithm, is used to generate a surface of estimated development rights values for Orange County. This approach overcomes several problems that arise with the use of standard appraisal methods to value conservation easements. (JEL Q24)

Modeling Land Use Decisions with Aggregate Data

In this article, we develop land use models to study the impact of changes in decision variables on soil erosion or other environmental outcomes. From an underlying behavioral model, we use maximum entropy to recover a parametric model of county-level land use shares as a function of decision variables such as output prices, input costs, and land quality. The statistical model may be extended to estimate subcounty land use shares and to incorporate data from federal land use surveys. We use the procedure to analyze the impact of changes in livestock inventories on soil erosion rates in three Iowa counties.

Price Cycles and Asymmetric Price Transmission in the U.S. Pork Market

Economists have proposed several plausible explanations for observed price transmission asymmetries in commodity markets. Unfortunately, the econometric methods commonly used in such studies cannot empirically distinguish pricing behavior under the competing theories. We argue that the theories may be classified by firm responses to high- and low-frequency price cycles and use Engles band spectrum regression to test the symmetry of high- and low-frequency cycles in weekly pork prices. The findings indicate that changes in wholesale prices are asymmetrically transmitted to retail prices in relatively low-frequency cycles, which does not support search costs and other high-frequency explanations. Conversely, wholesale pork prices asymmetrically adjust to changes in farm prices at all frequencies. Copyright 2001, Oxford University Press.

Transaction Costs and the Present Value Model of Farmland: Iowa, 1900–1994

The present study investigates whether the farmland “constant-discount-rate present-value-model (CDR-PVM) puzzle” is due to transaction costs. The theoretical implications of transaction costs for the CDR-PVM of farmland are discussed, and two bootstrap tests of such implications are introduced and applied to Iowa farmland prices and rents. Empirical results regarding the validity of the CDR-PVM in the presence of typical transaction costs are ambiguous. Econometric tests indicate that the CDR-PVM is consistent with typical transaction costs assuming a one-period holding horizon, but not when an infinite-holding horizon is hypothesized. Copyright 1999, Oxford University Press.

Recovering Output-Specific Inputs from Aggregate Input Data: A Generalized Cross-Entropy Approach

For multiproduct firms, data on aggregate input usage are typically available but data on activity-specific inputs are not. The present study proposes a generalized cross-entropy approach to estimate activity-specific input allocations that are consistent with the aggregate information. The proposed method does not require behavioral assumptions (e.g., profit maximization) but does accommodate behavioral restrictions as well as nonsample information about the plausible factor shares across enterprises. Monte Carlo experiments using simulated data for multifactor-multiproduct firms are used to evaluate the performance of the proposed method.