An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

The link between public support and private R&D effort: What is the optimal subsidy?

The effectiveness of R&D subsidies can vary substantially depending on their characteristics. Specifically, the amount and intensity of such subsidies are crucial issues in the design of public schemes supporting private R&D. Public agencies determine the intensities of R&D subsidies for firms in line with their eligibility criteria, although assessing the effects of R&D projects accurately is far from straightforward. The main aim of this paper is to examine whether there is an optimal intensity for R&D subsidies through an analysis of their impact on private R&D effort. We examine the decisions of a public agency to grant subsidies taking into account not only the characteristics of the firms but also, as few previous studies have done to date, those of the R&D projects. In determining the optimal subsidy we use both parametric and nonparametric techniques. The results show a non-linear relationship between the percentage of subsidy received and the firms’ R&D effort. These results have implications for technology policy, particularly for the design of R&D subsidies that ensure enhanced effectiveness.

Comparison of the Proportion Method With Mycobacteria Growth Indicator Tube and E-test for Susceptibility Testing of Mycobacterium tuberculosis

The aim of this study was to investigate the correlation between proportion method with mycobacteria growth indicator tube (MGIT) and E-test for Mycobacterium tuberculosis. Forty clinical isolates were tested. MGIT and E-test with the first line antituberculous drugs correlated with the proportion method. Our results suggested that MGIT and E-test methods can be routinely used instead of the proportion method.

Changing Diets in China’s Cities: Empirical Fact or Urban Legend, November 2006

China’s economic reforms, which began in 1978, resulted in remarkable income growth, and urban Chinese consumers have responded by dramatically increasing their consumption of meat, other livestock products, and fruits and by decreasing consumption of grain-based foods. Economic prosperity, a growing openness to international markets, and domestic policy reforms have changed the food marketing environment for Chinese consumers and may have contributed to shifts in consumer preferences. The objective of this paper is to uncover evidence of structural change in food consumption among urban residents in China. Both parametric and nonparametric methods are used to test for structural change in aggregate household data from 1981 to 2004. The tests provided a reasonably clear picture of changing food consumption over the study period.

Developing a Simple and Rapid Test for Monitoring the Heat Evolution of Concrete Mixtures for Both Laboratory and Field Applications, January 2006

Various test methods exist for measuring heat of cement hydration; however, most current methods require expensive equipment, complex testing procedures, and/or extensive time, thus not being suitable for field application. The objectives of this research are to identify, develop, and evaluate a standard test procedure for characterization and quality control of pavement concrete mixtures using a calorimetry technique. This research project has three phases. Phase I was designed to identify the user needs, including performance requirements and precision and bias limits, and to synthesize existing test methods for monitoring the heat of hydration, including device types, configurations, test procedures, measurements, advantages, disadvantages, applications, and accuracy. Phase II was designed to conduct experimental work to evaluate the calorimetry equipment recommended from the Phase I study and to develop a standard test procedure for using the equipment and interpreting the test results. Phase II also includes the development of models and computer programs for prediction of concrete pavement performance based on the characteristics of heat evolution curves. Phase III was designed to study for further development of a much simpler, inexpensive calorimeter for field concrete. In this report, the results from the Phase I study are presented, the plan for the Phase II study is described, and the recommendations for Phase III study are outlined. Phase I has been completed through three major activities: (1) collecting input and advice from the members of the project Technical Working Group (TWG), (2) conducting a literature survey, and (3) performing trials at the CP Tech Center’s research lab. The research results indicate that in addition to predicting maturity/strength, concrete heat evolution test results can also be used for (1) forecasting concrete setting time, (2) specifying curing period, (3) estimating risk of thermal cracking, (4) assessing pavement sawing/finishing time, (5) characterizing cement features, (6) identifying incompatibility of cementitious materials, (7) verifying concrete mix proportions, and (8) selecting materials and/or mix designs for given environmental conditions. Besides concrete materials and mix proportions, the configuration of the calorimeter device, sample size, mixing procedure, and testing environment (temperature) also have significant influences on features of concrete heat evolution process. The research team has found that although various calorimeter tests have been conducted for assorted purposes and the potential uses of calorimeter tests are clear, there is no consensus on how to utilize the heat evolution curves to characterize concrete materials and how to effectively relate the characteristics of heat evolution curves to concrete pavement performance. The goal of the Phase II study is to close these gaps.

Trade credit: Suppliers as debt collectors and insurance providers

There are two fundamental puzzles about trade credit: why does it appearto be so expensive,and why do input suppliers engage in the business oflending money? This paper addresses and answers both questions analysingthe interaction between the financial and the industrial aspects of thesupplier-customer relationship. It examines how, in a context of limitedenforceability of contracts, suppliers may have a comparative advantageover banks in lending to their customers because they hold the extrathreat of stopping the supply of intermediate goods. Suppliers may alsoact as lenders of last resort, providing insurance against liquidityshocks that may endanger the survival of their customers. The relativelyhigh implicit interest rates of trade credit result from the existenceof default and insurance premia. The implications of the model areexamined empirically using parametric and nonparametric techniques on apanel of UK firms.

Inferring transport characteristics in a fractured rock aquifer by combining single-hole ground-penetrating radar reflection monitoring and tracer test data

Investigations of solute transport in fractured rock aquifers often rely on tracer test data acquired at a limited number of observation points. Such data do not, by themselves, allow detailed assessments of the spreading of the injected tracer plume. To better understand the transport behavior in a granitic aquifer, we combine tracer test data with single-hole ground-penetrating radar (GPR) reflection monitoring data. Five successful tracer tests were performed under various experimental conditions between two boreholes 6 m apart. For each experiment, saline tracer was injected into a previously identified packed-off transmissive fracture while repeatedly acquiring single-hole GPR reflection profiles together with electrical conductivity logs in the pumping borehole. By analyzing depth-migrated GPR difference images together with tracer breakthrough curves and associated simplified flow and transport modeling, we estimate (1) the number, the connectivity, and the geometry of fractures that contribute to tracer transport, (2) the velocity and the mass of tracer that was carried along each flow path, and (3) the effective transport parameters of the identified flow paths. We find a qualitative agreement when comparing the time evolution of GPR reflectivity strengths at strategic locations in the formation with those arising from simulated transport. The discrepancies are on the same order as those between observed and simulated breakthrough curves at the outflow locations. The rather subtle and repeatable GPR signals provide useful and complementary information to tracer test data acquired at the outflow locations and may help us to characterize transport phenomena in fractured rock aquifers.

Effect of the environment inside and outside the cage on the activity and behaviour test performance of silver foxes

Selostus: Kasvatushäkin ympäristön vaikutus hopeakettujen käyttäytymiseen

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

Investigation of cytotoxic and mutagenic effects of Malpighia glabra L. (barbados cherry) fruit pulp and vitamin C on plant and animal test systems

Fruits are important sources of nutrients in human diet, and Barbados Cherry (Malpighia glabra L.) is of particular interest due to its high content of antioxidants. Diets rich in fruits and vegetables protect individuals against diseases and cancer, but excessive intake of vitamins may act as pro-oxidant and generate changes in DNA. To evaluate the effect of different in natura (BAN) and frozen (BAF) Barbados Cherry pulp concentrations and synthetic vitamin C in liquid form (VC) on the chromosome level and the cell cycle division, root meristeme cells of Allium cepa L. and bone marrow cells of Wistar rats Rattus norvegicus, were used as test system. In Allium cepa L., BAN, at the highest concentration (0.4 mg.mL-1) and BAF, at the lowest concentration (0.2 mg.mL-1), inhibited cell division, and there was recovery of cell division after the recovery period in water only for BAN. In the Wistar rats, all treatments with Barbados Cherry, either acute or subchronic, were not cytotoxic or mutagenic; only the highest concentration of VC increased significantly the rate of chromosomal abnormalities. The data obtained are important to reinforce the use of Barbados Cherry fruit in the diet.

Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.