Privatisation and Stock Market Efficiency: The British Experience

We present evidence that with its emphasis on wide-share-ownership the British privatisation program created heavy involvement of small investors in privatised stocks. Using standard market efficiency tests and maximum likelihood estimates of stationary fractional ARIMA models, we show that the pricing of privatised stocks in the London Stock Exchange was indeed inefficient, unlike the rest of the market. Together, these two pieces of evidence suggest that small investors, behaving like noise-traders, may be generating this inefficiency. Yet, we cannot rule out alternative explanations.     

Cost-Effective Targeting of Land Retirement to Improve Water Quality with Endogenous Sediment Deposition Coefficients

An integrated framework that combines spatial and biophysical attributes of land with a hydrological model and an economic model is developed to identify cropland for enrollment in the Conservation Reserve Enhancement Program. Sediment deposition coefficients are determined endogenously depending on the land-use decisions on other land parcels. Application of this framework to a watershed in Illinois demonstrates that highly sloping land adjacent to water bodies should be selected for retirement. A marginal value rental payment scheme can achieve program goals of 20% sediment abatement at 39% lower cost than a productivity-based rental scheme.     

Amenity driven price effects and conservation reserve site selection: A dynamic linear integer programming approach

Most conservation reserve design models presented in the literature are static and ignore the dynamic economic aspects of site selection. Typically conservation programs operate under time-related (e.g. annual) budgets and purchase land over time in a sequential manner. The uncertainty of land development has been incorporated in a few dynamic reserve selection formulations using stochastic dynamic programming. However, the existing formulations do not explicitly deal with inter-temporal price and location linkages. We address this issue here and present a two-period linear integer programming model for conservation reserve design that incorporates amenity driven price feedback effects inherent in the reserve development problem. In addition, the model includes spatial and ecological criteria. We then use this model to answer the question “How suboptimal is ignoring amenity driven price effects in reserve design models?” We apply the model to artificially generated data sets and compare the results with the results of an iterated static model that considers only one period at a time. We find that the dynamic model with price feedback effects selects sites at a lower per-site cost. The policy implication of this finding is that conservation programs should avoid purchasing land in the same neighborhood over multiple time periods.     

Optimizing the aerodynamic efficiency of intermodal freight trains

We develop an aerodynamic loading assignment model for intermodal freight trains based on an integer-programming framework to help terminal managers make up more fuel-efficient trains. This is the first use of optimization modeling to address the aerodynamics and energy efficiency of railroad intermodal trains. Several recommendations regarding railway equipment use, operations, and policy are proposed to improve fuel-efficiency and reduce emissions from intermodal transportation. Analysis of one major railroad intermodal route reveals the potential to reduce fuel consumption by 15 million gallons per year with corresponding savings of $28,000,000. Greater benefits are possible through broader implementation of the model.     

Land use and economic effects of alternative biofuel policies in Brazil and the United States

Being the two largest ethanol producers in the world, biofuel policies in Brazil and the United States affect both their domestic markets and the global food and biofuel economy. In this article we develop a price endogenous mathematical programming model to simulate and analyze the impacts of biofuel mandates and trade distortions on land use, agricultural commodity and transportation fuel markets, and global environment. We find that an 80% increase in total biofuel production from its 103 billion liter baseline level to the mandated 183 billion liter level in 2022 can be achieved with less than 2% increase in total cropland use in both countries. In the United States, this would occur with cellulosic biofuels meeting nearly half of the biofuels consumed and produced largely on cropland pasture and corn ethanol meeting the rest of the mandate and resulting in a 2% increase in corn price. In Brazil, the expansion in sugarcane production would be achieved by reducing land under pasture and a marginal increase in intensification of livestock production. In the aggregate, biofuel policies increase economic surplus in both countries by 1% and redistribute the benefits from agricultural consumers to agricultural producers and the fuel sector. Finally, we also find that full implementation of the mandates in North America, China, and the European Union would reduce the global life‐cycle global greenhouse gas emissions by about 5%.     

Is Geographical Targeting Cost-Effective? The Case of the Conservation Reserve Enhancement Program in Illinois

This paper uses economic, hydrologic, and GIS modeling to assess the effectiveness of the Illinois Conservation Reserve Enhancement Program in the Lower Sangamon watershed. Our results show that for a representative five-year storm event, the acres currently enrolled in the program result in a 12% reduction in sediment loading, which is below the program goal of 20% and four times the least-cost solution. We also analyze the design of alternative rental payment instruments for improving the cost-effectiveness of geographical targeting for land retirement. Policy implications for the characteristics of the land parcels that should be targeted for enrollment in the program are discussed.     

Preservation of Species and Genetic Diversity

This article presents a mathematical programming approach to determine a conservation strategy that maximizes preserved species' diversity under limited resource availability. Diversity is defined as the negative of total diversity loss given by the sum of genetic distances between extinct species and their closest surviving relatives. The model incorporates both species richness and genetic diversity as the conservation criteria when determining species preservation and site selection decisions. The article also presents two empirical applications to the conservation of 15 crane species and 208 genera including most of the endangered or threatened North American bird species.     

Exact Aggregation in Mathematical Programming Sector Models

This paper defines the exact aggregation problem in the sector modeling context and develops the theoretical basis of an aggregation procedure based on extreme point representation. Under the assumption of full information on all firms this procedure yields exact aggregation, irrespective of firm heterogeneity, and it also suggests empirical procedures for cases when full information is not present. Although aggregation in such cases is in general not exact, empirical evidence shows that little error is involved, and the aggregate model is rather stable under various parameter changes.
Le présent document définit le problème de l'agrégation exacte dans le contexte de la modélisation d'un secteur et énonce la base théorique d'une méthode d'agrégation fondée sur la représentation des points extrêmes. Si on part de l'hypothèse qu'on détient toutes les informations sur les entreprises, la méthode proposée donne une agrégation exacte de ces dernières, peu importe leur hétérogénéité. Les auteurs suggèrent aussi des méthodes empiriques lorsque certaines données font défaut. Même si, dans ces cas, l'agrégation est rarement exacte, les résultats indiquent que les erreurs sont peu nombreuses et que le modèle agrégé garde sa stabilité meme advenant la modification de divers paramètres.     

Site accessibility and prioritization of nature reserves

Nature reserves not only protect habitat-stressed species but also provide recreation and welfare services to people. Therefore, site accessibility matters in reserve design. This study incorporates public accessibility, determined by urban populations and distances between urban areas and reserve sites, as an additional factor in conservation reserve design besides species representation and economic characteristics of individual sites. An optimization approach is introduced to determine a reserve network with maximum accessibility while satisfying specified representation targets under financial constraints. The paper also presents an empirical application of this approach to endangered/threatened birds in Illinois, USA, and analyzes the tradeoffs between ecological, economic, and social objectives of biological conservation. The results show that: i) the conventional minimal representation approach would result in a small reserve network, but this network would have poor accessibility; ii) public accessibility can be improved significantly by selecting alternative sites with the same amount of conservation budget; iii) further improvement in accessibility can be achieved by enlarging the network, but in this particular case the gains would be insignificant after the first few additional sites; and iv) a regionally integrated conservation plan, as opposed to decentralized conservation efforts, is beneficial for both species protection and social welfare.     

Regional Shifts in Pork Production: Implications for Competition and Food Safety

U.S. pork production and processing is consolidating in larger, more economically efficient units, and shifting from the Midwest into the Southeast. A regional model of farm supply and processing demand shows that smaller Midwest operations can survive only if processing capacity remains concentrated in that region. Salmonella incidence is higher in the Southeast and on larger farms. Restricting salmonella incidence in hogs delivered for processing to the minimum feasible level would increase total industry costs by 3%, due to increased production and delivery costs. It would also increase the comparative advantage of farms and processing firms in the Midwest.