Challenges in macro-finance modeling

This article discusses various challenges in the specification and implementation of "macro-finance" models in which macroeconomic variables and term structure variables are modeled together in a no-arbitrage framework. The author classifies macro-finance models into pure latent-factor models ("internal basis models") and models that have observed macroeconomic variables as state variables ("external basis models") and examines the underlying assumptions behind these models. Particular attention is paid to the issue of unspanned short-run fluctuations in macroeconomic variables and their potentially adverse effect on the specification of external basis models. The author also discusses the challenge of addressing features such as structural breaks and time-varying inflation uncertainty. Empirical difficulties in the estimation and evaluation of macro-finance models are also discussed in detail.Econometric models ; Macroeconomics

A Characterization of Completely Reachable Automata

A complete deterministic finite automaton in which every non-empty subset of the state set occurs as the image of the whole state set under the action of a suitable input word is called completely reachable. We characterize completely reachable automata in terms of certain directed graphs.Comment: 12 pages, 3 figures, submitted to DLT 201

The Evolution and Expansion of Risk Management Education Programs in the United States

A rapidly changing business environment has dictated a need for farmers to improve their risk management skills. The 1996 Federal Agricultural Improvement and Reform Act (FAIR) also created a new environment for American farmers by eliminating planting restrictions and deficiency payments. Congress recognized the changing environment by mandating the Secretary of Agriculture to initiate a risk management education program. A memorandum of understanding specified the responsibilities of the federal agencies involved in risk management services and education. A work group representing all public and private organizations concerned with risk management services and strategies was convened. The work group established a set of objectives, the five major areas of risk to address and an overall educational plan. Five regional extension coordinating offices were established to coordinate activities with federal agencies and the private sector and to distribute funding for extension based educational programs. The initiative originally received funding of $5M in 1997. In 2000, the Agricultural Risk Protection Act, which primarily revised the crop insurance program, provided an additional$5M for risk management education for the 2001 fiscal year and the succeeding four years. The initiative has provided an impetus to look a risk management in a broad and comprehensive manner. This has resulted in the development of very creative and innovative programs, in terms of materials and methods of delivery. The working partnerships between public and private sector organizations have been a key to the success of the programs.Farm Management, Risk and Uncertainty, Teaching/Communication/Extension/Profession,

New Inhomogeneous Einstein Metrics on Sphere Bundles Over Einstein-Kahler Manifolds

We construct new complete, compact, inhomogeneous Einstein metrics on S^{m+2} sphere bundles over 2n-dimensional Einstein-Kahler spaces K_{2n}, for all n \ge 1 and all m \ge 1. We also obtain complete, compact, inhomogeneous Einstein metrics on warped products of S^m with S^2 bundles over K_{2n}, for m>1. Additionally, we construct new complete, non-compact Ricci-flat metrics with topologies S^m times R^2 bundles over K_{2n} that generalise the higher-dimensional Taub-BOLT metrics, and with topologies S^m \times R^{2n+2} that generalise the higher-dimensional Taub-NUT metrics, again for m>1.Comment: Latex, 14 pages. Errors and typos corrected, and related references adde

Accuracy assessment, using stratified plurality sampling, of portions of a LANDSAT classification of the Arctic National Wildlife Refuge Coastal Plain

An application of a classification accuracy assessment procedure is described for a vegetation and land cover map prepared by digital image processing of LANDSAT multispectral scanner data. A statistical sampling procedure called Stratified Plurality Sampling was used to assess the accuracy of portions of a map of the Arctic National Wildlife Refuge coastal plain. Results are tabulated as percent correct classification overall as well as per category with associated confidence intervals. Although values of percent correct were disappointingly low for most categories, the study was useful in highlighting sources of classification error and demonstrating shortcomings of the plurality sampling method