Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Is there Descriminatory Mortgage Pricing against Immigrants in the Spanish Lending Market?

In this paper, we investigate whether evidence of discriminatory treatment against immigrants in the Spanish mortgage market exists. More specifically, we test whether, ceteris paribus, immigrant borrowers tend to be charged with higher interest rates on their mortgages than their Spanish born counterparts. To do so, we use a unique dataset on granted mortgages that contains information not only regarding the conditions of the loan but also the socio-economic characteristics of the mortgagors. We observe that immigrants are systematically charged with higher interest rates. We apply the well known Oaxaca-Blinder decomposition to measure the extent to which this disparate treatment of lenders in mortgage pricing against immigrants is due to discrimination. Our results indicate that approximately two thirds of the gap in the interest rate between Spanish born and immigrant borrowers can be attributed to discriminatory treatment. Key words: Immigration, discrimination, mortgage pricing, housing market. JEL codes: R21, G21, J14

An empirical analysis of a merger between a network and low-cost airlines

We use a difference-in-difference estimator to examine the effects of a merger involving three airlines. The novelty lies in the examination of this operation in two distinct scenarios: (1) on routes where two low-cost carriers and (2) on routes where a network and one of the low-cost airlines had previously been competing. We report a reduction in frequencies but no substantial effect on prices in the first scenario, while in the second we report an increase in prices but no substantial effect on frequencies. These results may be attributed to the differences in passenger types flying on these routes.

Climate-based empirical models show biased predictions of butterfly communities along environmental gradients

A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Policy Credibility and Delegation to Independent Regulatory Agencies: A Comparative Empirical Analysis

Independent regulatory agencies are one of the main institutional features of the 'rising regulatory state' in Western Europe. Governments are increasingly willing to abandon their regulatory competencies and to delegate them to specialized institutions that are at least partially beyond their control. This article examines the empirical consistency of one particular explanation of this phenomenon, namely the credibility hypothesis, claiming that governments delegate powers so as to enhance the credibility of their policies. Three observable implications are derived from the general hypothesis, linking credibility and delegation to veto players, complexity and interdependence. An independence index is developed to measure agency independence, which is then used in a multivariate analysis where the impact of credibility concerns on delegation is tested. The analysis relies on an original data set comprising independence scores for thirty-three regulators. Results show that the credibility hypothesis can explain a good deal of the variation in delegation. The economic nature of regulation is a strong determinant of agency independence, but is mediated by national institutions in the form of veto players.

High Growth Firms and Innovation: an empirical analysis for Spanish firms

This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30

Neither dashboard nor 'mashup' indices: an empirical wealth approach as a pathway to a comprehensive measure of development

The article is composed of two sections. The first one is a critical review of the three main alternative indices to GDP which were proposed in the last decades – the Human Development Index (HDI), the Genuine Progress Indicator (GPI), and the Happy Planet Index (HPI) – which is made on the basis of conceptual foundations, rather than looking at issues of statistical consistency or mathematical refinement as most of the literature does. The pars construens aims to propose an alternative measure, the composite wealth index, consistent with an approach to development based on the notion of composite wealth, which is in turn derived from an empirical common sense criterion. Arguably, this approach is suitable to be conveyed into an easily understandable and coherent indicator, and thus appropriate to track development in its various dimensions: simple in its formulation, the wealth approach can incorporate social and ecological goals without significant alterations in conceptual foundations, while reducing to a minimum arbitrary weighting.

Model-based appraisal of minimum unit pricing for alcohol in Northern Ireland

In 2009, the Sheffield Alcohol Research Group (SARG) at Sheffield University developed the Sheffield Alcohol Policy Model version 2.0 (SAPM) to appraise the potential impact of alcohol policies, including different levels of MUP, for the population of England. In 2013, SARG were commissioned by the DHSSPS and the Department for Social Development to adapt the Sheffield Model to NI in order to appraise the potential impact of a range of alcohol pricing policies. The present report represents the results of this work. Estimates from the Northern Ireland (NI) adaptation of the Sheffield Alcohol Policy Model - version 3 - (SAPM3) suggest: 1. Minimum Unit Pricing (MUP) policies would be effective in reducing alcohol consumption, alcohol related harms (including alcohol-related deaths, hospitalisations, crimes and workplace absences) and the costs associated with those harms. 2. A ban on below-cost selling (implemented as a ban on selling alcohol for below the cost of duty plus the VAT payable on that duty) would have a negligible impact on alcohol consumption or related harms. 3. A ban on price-based promotions in the off-trade, either alone or in tandem with an MUP policy would be effective in reducing alcohol consumption, related harms and associated costs. 4. MUP and promotion ban policies would only have a small impact on moderate drinkers at all levels of income. Somewhat larger impacts would be experienced by increasing risk drinkers, with the most substantial effects being experienced by high risk drinkers. 5. MUP and promotion ban policies would have larger impacts on those in poverty, particularly high risk drinkers, than those not in poverty. However, those in poverty also experience larger relative gains in health and are estimated to marginally reduce their spending due to their reduced drinking under the majority of policies åÊ

Authors' response to 'Limitless longevity': the contribution of rectangularization to the secular increase in life expectancy: an empirical study.

Related article : Letter to the Editor: Karin Modig, Sven Drefahl, and Anders Ahlbon.Limitless longevity: Comment on the Contribution of rectangularization to the secular increase of life expectancy

Report of the Independent Body on Pharmacy Contract Pricing

Report of the Independent Body on Pharmacy Contract Pricing On 18 February 2008 the Minister for Health and Children announced the appointment of an Independent Body to recommend a new, interim community pharmacy dispensing fee for the General Medical Service (GMS), Drugs Payment Scheme (DPS) and other community drug schemes.The Terms of Reference for the Independent Body on Pharmacy Contract Pricing are as follows: â?oTo advise the Minister for Health and Children on the appropriate level of dispensing fee to be paid to community pharmacists for existing services provided under the GMS and community drug schemes having regard to: Click here to download PDF: 110kb