Mean and dispersion modelling for policy claims costs

A model for the statistical analysis of the total amount of insurance paid out on a policy is developed and applied. The model simultaneously deals with the number of claims (zero or more) and the amount of each claim. The number of claims is from a Poisson-based discrete distribution. Individual claim sizes are from a continuous right skewed distribution. The resulting distribution of total claim size is a mixed discrete-continuous model, with positive probability of a zero claim. The means and dispersions of the claim frequency and claim size distribution are modeled in terms of risk factors. The model is applied to a car insurance data set.     

Untersuchung über die Kränklichkeit in den staatlich unterstützten Krankenkassen Schwedens

Abstract

Von den Vorschriften, die für die staatlich unterstützten Krankenkassen gelten, werde ich hier nur so viel mitteilen, was für den Aufbau der mathematiscben Formeln notwendig ist, sowie einige Tatsachen, die bei Vergleichen mit anderen Kränklichkeitsmaterialien von Bedeutung sind. Im übrigen wird auf das Gesetz über Krankenkassen hingewiesen.     

Volatility forecasts and at-the-money implied volatility: a multi-component ARCH approach and its relation to market models

This article explores the relationships between several forecasts for the volatility built from multi-scale linear ARCH processes, and linear market models for the forward variance. This shows that the structures of the forecast equations are identical, but with different dependencies on the forecast horizon. The process equations for the forward variance are induced by the process equations for an ARCH model, but postulated in a market model. In the ARCH case, they are different from the usual diffusive type. The conceptual differences between both approaches and their implication for volatility forecasts are analysed. The volatility forecast is compared with the realized volatility (the volatility that will occur between date t and t + ΔT), and the implied volatility (corresponding to an at-the-money option with expiry at t + ΔT). For the ARCH forecasts, the parameters are set a priori. An empirical analysis across multiple time horizons ΔT shows that a forecast provided by an I-GARCH(1) process (one time scale) does not capture correctly the dynamics of the realized volatility. An I-GARCH(2) process (two time scales, similar to GARCH(1,1)) is better, while a long-memory LM-ARCH process (multiple time scales) replicates correctly the dynamics of the implied and realized volatilities and delivers consistently good forecasts for the realized volatility.     

Process System Modelling of Production Technology Alternatives using Input– Output Tables with Sector Specific Units

Input–output analysis is usually based on tables of accounts expressed in uniform monetary or physical units. However, from a process system modelling perspective, tables of accounts in sector specific units may be more useful for evaluating the effectiveness of new production technologies on reducing pollutant emissions. Using the sector specific unit conceptualization of an IO table, one can consider the effect of changes in direct input coefficients for a particular sector on the complete set of total input coefficients independently from the other direct input coefficients. A process system modelling based method for calculating the total industrial outputs from a new technology matrix together with the new relative prices for each sector output is presented. The method is then used to study the effect of technology changes in the steel making industry in Liaoning Province, China on prices and pollutant emissions.     

Cost-effectiveness of a continuous glucose monitoring system with trending and rate information to predict hypoglycaemia and hyperglycaemia in pregnant women with insulin-dependent diabetes mellitus

Summary

This study seeks to determine the cost-effectiveness of the FreeStyle Navigator? continuous glucose monitoring system compared with self-monitoring of blood glucose (SMBG) when predicting hypoglycaemia and hyperglycaemia in pregnant women with insulin-dependent diabetes mellitus. A Markov model was constructed, and initial model analysis demonstrates that use of the FreeStyle Navigator? by a patient who is trained in diabetes management is more cost-effective than SMBG, resulting in an incremental cost-effectiveness ratio of $267 per quality-adjusted life-month ($3,204 per quality-adjusted life-year). The real-time glucose level rate of change and trend information provided by the FreeStyle Navigator? allows appropriately trained patients to improve upon decisions regarding self-treatment to prevent hypoglycaemic and hyperglycaemic episodes, resulting in a lower treatment cost and higher effectiveness than untrained patients. Based on current performance attributes, a device such as the FreeStyle Navigator? would be more cost-effective than other glucose-monitoring devices, meeting the $50,000/QALY willingness-to-pay threshold used by payers for adoption of new technology.     

Operational efficiency analysis of Beijing multi-airport terminal airspace

Multi-airport systems are growing in number and size globally, despite being afflicted by known inefficiencies due to the interferences between the flows of neighbouring airports. A macroscopic empirical approach is proposed in this paper to estimate the capacity penalties and demonstrated by a numerical case study for Beijing, which is projected to become one of the busiest metroplexes in Asia. The Pareto envelopes of the theoretical and observed peak hour capacities are statistically analysed to quantify the penalties in a comparable metroplex and are subsequently modulated by a sigmoid correlation function. The analysis predicts the practical capacity of Daxing, the penalty incurred by the pre-existing Capital airport and by the total multi-airport system. Various findings are drawn and discussed, highlighting the needs for further research.     

All hype or the real deal? Investigating user engagement with virtual influencers in tourism

Virtual influencer (VI) marketing has become increasingly prevalent on social media with the evolving landscape of digitalisation. However, the use of VIs in tourism has received limited attention in the literature. This study examines salient source and content attributes that stimulate Instagram users’ engagement with VIs in a tourism context. An online discrete choice experiment was designed using key attributes (i.e. source realness, image composition and caption discourse) identified from online focus groups. Survey responses from 309 adult Instagram users in Australia were analysed through discrete choice modelling. The findings indicate that humanlike VIs are preferred over 3D animated VIs and the least preferred influencers are 2D animated VIs. Instagram posts from humanlike VIs that combine images of tourism settings with rational messages attract the most engagement from the audience. Theoretical and practical implications are provided with recommendations for how tourism practitioners can harness VI marketing effectively.     

Modelling airline flight cancellation decisions

In order to predict airline responses to Traffic Management Initiatives (TMIs), and reveal the underlying preference structures that shape these responses, we study US domestic airlines’ cancellation decisions in response to the Federal Aviation Administration (FAA)’s TMIs, in particular, to Ground Delay Programs (GDPs). By observing the actual flight-cancellation choices made by airline dispatchers, the airlines’ cancellation utility functions can be inferred through the use of binary choice models. The model captures how delays to a given flight and potential delay savings to other flights affect flight cancellation decisions. We also find larger, fuller, less frequent, shorter-distance, and spoke-bound flights are less likely to be cancelled, and that there is inter-airline variation in flight cancellation behaviour.     

Assessing the welfare effects of congestion charges in a real world setting

The standard textbook analysis shows that drivers as a group lose from congestion charges. However, it omits taste heterogeneity, shorter travel times far out in the larger network arising from less blocking back of upstream links and the possibility for drivers to reschedule. Taking account of these factors, using a dynamic scheduling model with heterogeneous users we find that all three add significantly to the benefit of the Stockholm congestion charges and that drivers as a group benefit from these charges even without recycling of revenues. This paper also provides an update on the consumer benefits of the Stockholm charges.     

System dynamics modelling and forecasting health tourism demand: the case of Russian resorts

This article presents the results of the system dynamics modelling of the regional market of health tourism in the Krasnodar region of Russia. The research was based on various indicators characterizing the supply and demand for this type of tourism for years 2006–2012. The medium-term forecast made by constructed model shows a possible decrease in number of health tourists and income of sanatorium organizations. Price competition of inexpensive foreign resorts was a key factor influencing the market of tourist services; therefore ruble devaluation to US dollar may improve the prognostic indicators.