EPA Guidelines for Regulatory Impact Analysis

On February 17, 1981, the President issued Executive Order 12291 mandating that regulatory agencies must prepare regulatory impact analyses (RIAs) on all major regulations. Before taking action, the agencies must send all RIAs and proposed regulations to the Office of Management and Budget (OMB) for review. These guidelines discuss the analytical techniques that may be used and the information to be developed by the U.S. Environmental Protection Agency when (l) stating the need for the proposed regulatory action; (2) examining alternative approaches to the problem; (3) quantifying benefits and costs and valuing them in dollar terms (where feasible); and (4) evaluating the findings on benefits, costs, and distributional effects. This document provides guidance for preparing Regulatory Impact Analyses. It includes four appendices and one supplement in addition to the main document.

A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Economism and its Limits

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Electronic information sharing in local government authorities: Factors influencing the decision-making process

This is the post-print version of the final paper published in International Journal of Information Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Local Government Authorities (LGAs) are mainly characterised as information-intensive organisations. To satisfy their information requirements, effective information sharing within and among LGAs is necessary. Nevertheless, the dilemma of Inter-Organisational Information Sharing (IOIS) has been regarded as an inevitable issue for the public sector. Despite a decade of active research and practice, the field lacks a comprehensive framework to examine the factors influencing Electronic Information Sharing (EIS) among LGAs. The research presented in this paper contributes towards resolving this problem by developing a conceptual framework of factors influencing EIS in Government-to-Government (G2G) collaboration. By presenting this model, we attempt to clarify that EIS in LGAs is affected by a combination of environmental, organisational, business process, and technological factors and that it should not be scrutinised merely from a technical perspective. To validate the conceptual rationale, multiple case study based research strategy was selected. From an analysis of the empirical data from two case organisations, this paper exemplifies the importance (i.e. prioritisation) of these factors in influencing EIS by utilising the Analytical Hierarchy Process (AHP) technique. The intent herein is to offer LGA decision-makers with a systematic decision-making process in realising the importance (i.e. from most important to least important) of EIS influential factors. This systematic process will also assist LGA decision-makers in better interpreting EIS and its underlying problems. The research reported herein should be of interest to both academics and practitioners who are involved in IOIS, in general, and collaborative e-Government, in particular

Designing requirements engineering research

Engineering sciences study different different topics than natural sciences, and utility is an essential factor in choosing engineering research problems. But despite these differences, research methods for the engineering sciences are no different than research methods for any other kind of science. At most there is a difference in emphasis. In the case of requirements engineering research - and more generally software engineering research - there is a confusion about the relative roles of research and about design and the methods appropriate for each of these activities. This paper analyzes these roles and provides a classification of research methods that can be used in any science—engineering or otherwise

Forecasting the demand for privatized transport - What economic regulators should know, and why

Forecasting has long been a challenge, and will remain so for the foreseeable future. But the analytical instruments and data processing capabilities available through the latest technology, and software, should allow much better forecasting than transport ministries, or regulatory agencies typically observe. Privatization brings new needs for demand forecasting. More attention is paid to risk under privatization, than when investments are publicly financed. And regulators must be able to judge traffic studies done by operators, and to learn what strategic behavior influenced these studies. Many governments, and regulators avoid good demand, modeling out of lack of conviction that theory, and models can do better than the"old hands"of the sector. This is dangerous when privatization changes the nature of business. For projects amounting to investments of $100-200 million, a cost of$ 100,000-200,000 is not a reason to reject a reasonable modeling effort. And some private forecasting firms are willing to sell guarantees, or insurance with their forecasts, to cover significant gaps between forecasts, and reality.Markets and Market Access,Environmental Economics&Policies,Economic Theory&Research,Decentralization,Banks&Banking Reform,Markets and Market Access,Economic Theory&Research,Banks&Banking Reform,Access to Markets,Environmental Economics&Policies