Verification tools for probabilistic forecasts of continuous hydrological variables

In the present paper we describe some methods for verifying and evaluating probabilistic forecasts of hydrological variables. We propose an extension to continuous-valued variables of a verification method originated in the meteorological literature for the analysis of binary variables, and based on the use of a suitable cost-loss function to evaluate the quality of the forecasts. We find that this procedure is useful and reliable when it is complemented with other verification tools, borrowed from the economic literature, which are addressed to verify the statistical correctness of the probabilistic forecast. We illustrate our findings with a detailed application to the evaluation of probabilistic and deterministic forecasts of hourly discharge value

Naive Bayes and Exemplar-Based approaches to Word Sense Disambiguation Revisited

This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar-based classification, on the Word Sense Disambiguation (WSD) problem. The aim of the work is twofold. Firstly, it attempts to contribute to clarify some confusing information about the comparison between both methods appearing in the related literature. In doing so, several directions have been explored, including: testing several modifications of the basic learning algorithms and varying the feature space. Secondly, an improvement of both algorithms is proposed, in order to deal with large attribute sets. This modification, which basically consists in using only the positive information appearing in the examples, allows to improve greatly the efficiency of the methods, with no loss in accuracy. The experiments have been performed on the largest sense-tagged corpus available containing the most frequent and ambiguous English words. Results show that the Exemplar-based approach to WSD is generally superior to the Bayesian approach, especially when a specific metric for dealing with symbolic attributes is used.Comment: 5 page

The impact of alcohol and drug use on employment: A labor market study using the National Longitudinal Survey of Youth

The purpose of this study was, first, to estimate of the impact of alcohol and drug use on the employment status of men and women, and second, to examine whether a history of past use, as opposed to current use, adversely affects the propensity to be employed. Using data from the National Longitudinal Survey of Youth we conducted a cross-sectional and a longitudinal analysis with logistic regression estimation to model the probability that a person was employed in 1992. In addition to usual regressors, interactions between substance use measures, between substance use measures and human capital variables, and between substance use measures and race dummies were included in the equation. The longitudinal analysis utilized a conditional likelihood method based on employment data in 1992 and 1988 and included the difference between 1992 regressors and their 1988 counterparts. A comparison was made between the prediction accuracy of the logit choice model, linear discriminant analysis, k-nearest neighbor analysis, and three modern classification methods that are used extensively in the area of machine learning. Results showed that the logit model performs relatively well in classifying individuals into employed and unemployed categories based on individual attributes. Results of the cross-sectional and longitudinal analysis were mixed, but not inconsistent with our prior expectations that use of alcohol or drug has a negative impact on a person's propensity to be employed. Cross-sectional results show a clear negative impact of past substance use on a person's employment probability among all demographic groups examined (by gender: all persons, blacks, Hispanics, families with income below the poverty line, and high users of alcohol or drugs). However, when current and past use are considered together, only women seem to experience negative impacts. The results of the longitudinal analysis are less clear, although they do indicate that negative impacts are associated with the interaction between substance use measures and human capital variables. Limitations of the study are pointed out and suggestions are made for future research.

Regional disparities in electrification of India – do geographic factors matter?

Modern energy sources are important input factors for human development. Although official estimates indicate that 85% of Indian villages are electrified, fewer than 60% of Indian households actually consume electricity. Therefore, one observes a considerable spatial heterogeneity in electrification rate. This paper examines the factors that influence household and village electrification, with particular attention given to the influence of geographic factors. The analysis shows that village electrification is constrained by state area and village structure. In addition, a high share of agricultural areas seems to have a positive effect. Household electrification depends on household characteristics, the degree of community electrification, and the quality of electricity supply, and it is independent of geographic factors. Surprisingly, household expenditure and, in particular, the electricity tariff show only a relatively small effect on a household‘s choice for electricity.

Reconsidering the calculation and role of environmental footprints

Following the recent Copenhagen Climate Change conference, there has been discussion of the methods and underlying principles that inform climate change targets. Climate change targets following the Kyoto Protocol are broadly based on a production accounting principle (PAP). This approach focuses on emissions produced within given geographical boundaries. An alternative approach is a consumption accounting principle (CAP), where the focus is on emissions produced globally to meet consumption demand within the national (or regional) economy1. Increasingly popular environmental footprint measures, including ecological and carbon footprints, attempt to measure environmental impacts based on CAP methods. The perception that human consumption decisions lie at the heart of the climate change problem is the impetus driving pressure on policymakers for a more widespread use of CAP measures. At a global level of course, emissions accounted for under the production and consumption accounting principles would be equal. It is international trade that leads to differences in emissions under the two principles. This paper, the second in this special issue of the Fraser Commentary, examines how input-output accounting techniques may be applied to examine pollution generation under both of these accounting principles, focussing on waste and carbon generation in the Welsh economy as a case study. However, we take a different focus, arguing that the ‘domestic technology assumption’, taken as something of a mid-point in moving between production and consumption accounting in the first paper, may actually constitute a more useful focus for regional policymakers than full footprint analyses

A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations

This is the post-print version of the final paper published in 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 @ 2012 Elsevier B.V.Adoption of IT in organizations is influenced by a wide range of factors in technology, organization, environment, and individuals. Researchers have identified several factors that either facilitate or hinder innovation adoption. Studies have produced inconsistent and contradictory outcomes. We performed a meta-analysis of ten organizational factors to determine their relative impact and strength. We aggregated their findings to determine the magnitude and direction of the relationship between organizational factors and IT innovation adoption. We found organizational readiness to be the most significant attribute and also found a moderately significant relationship between IT adoption and IS department size. Our study found weak significance of IS infrastructure, top management support, IT expertise, resources, and organizational size on IT adoption of technology while formalization, centralization, and product champion were found to be insignificant attributes. We also examined stage of innovation, type of innovation, type of organization, and size of organization as moderator conditions affecting the relationship between the organizational variables and IT adoption

The electricity generation mix in Scotland : the long and windy road?

This article reports on research funded by the Engineering and Physical Sciences Research Council (EPSRC) at the University of Strathclyde

Combining revealed and stated preference methods to assess the private value of agrobiodiversity in Hungarian home gardens:

" Hungarian home gardens are small-scale farms managed by farm households using traditional management practices and family labor. They generate private benefits for farmers by enhancing diet quality and providing food when costs of transacting in local markets are high. Home gardens also generate public benefits for society by supporting long-term productivity advances in agriculture. In this paper, we estimate the private value to farmers of agrobiodiversity in home gardens. Building on the approach presented in EPTD Discussion Paper 117 (2004), we combine a stated preference approach (a choice experiment model) and a revealed preference approach (a discrete-choice, farm household model). Both models are based on random utility theory. To combine the models, primary data were collected from the same 239 farm households in three regions of Hungary. Combining approaches leads to a more efficient and robust estimation of the private value of agrobiodiversity in home gardens. Findings can be used to identify those farming communities, which would benefit most from agri-environmental schemes that support agrobiodiversity maintenance, at least public cost." Authors' abstractHome gardens, Small-scale farmers, Diet quality, Agricultural productivity, Agrobiodiversity, Household surveys, Private value, Choice experiment model, Farm household model, Revealed and stated preference methods,