Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

Is Mortality Spatial or Social?

Mortality modelling for the purposes of demographic forecasting and actuarial pricing is generally done at an aggregate level using national data. Modelling at this level fails to capture the variation in mortality within country and potentially leads to a mis-specification of mortality forecasts for a subset of the population. This can have detrimental effects for pricing and reserving in the actuarial context. In this paper we consider mortality rates at a regional level and analyse the variation in those rates. We consider whether variation in mortality rates within a country can be explained using local economic and social variables. Using Northern Ireland data on mortality and measures of deprivation we identify the variables explaining mortality variation. We create a population polarisation variable and find that this variable is significant in explaining some of the variation in mortality rates. Further, we consider whether spatial and non-spatial models have a part to play in explaining mortality differentials.

Structural Breaks in Mortality Models and their Consequences

In recent years, the issue of life expectancy has become of upmost importance to pension providers, insurance companies and the government bodies in the developed world. Significant and consistent improvements in mortality rates and, hence, life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data in order to anticipate future life expectancy and, hence, quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age and cohort, and forecast these trends into the future using standard statistical methods. The modeling approaches used failed to capture the effects of any structural change in the trend and, thus, potentially produced incorrect forecasts of future mortality rates. In this paper, we look at a range of leading stochastic models of mortality and test for structural breaks in the trend time series.

Bandwidth selection by cross-validation for forecasting long memory financial time series

The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates

Reducible diffusions (RDs) are nonlinear transformations of analytically solvable Basic Diffusions (BDs). Hence, by construction RDs are analytically tractable and flexible diffusion processes. Existing literature on RDs has mostly focused on time-homogeneous transformations, which to a significant extent fail to explore the full potential of RDs from both theoretical and practical points of view. In this paper, we propose flexible and economically justifiable time variations to the transformations of RDs. Concentrating on the Constant Elasticity Variance (CEV) RDs, we consider nonlinear dynamics for our time-varying transformations with both deterministic and stochastic designs. Such time variations can greatly enhance the flexibility of RDs while maintaining sufficient tractability of the resulting models. In the meantime, our modeling approach enjoys the benefits of classical inferential techniques such as the Maximum Likelihood (ML). Our application to the UK and the US short-term interest rates suggests that from an empirical point of view time-varying transformations are highly relevant and statistically significant. We expect that the proposed models can describe more truthfully the dynamic time-varying behavior of economic and financial variables and potentially improve out-of-sample forecasts significantly.

In situ electron holography of the dynamic magnetic field emanating from a hard-disk drive writer

The proliferation of mobile devices in society accessing data via the ‘cloud’ is imposing a dramatic increase in the amount of information to be stored on hard disk drives (HDD) used in servers. Forecasts are that areal densities will need to increase by as much as 35% compound per annum and by 2020 cloud storage capacity will be around 7 zettabytes corresponding to areal densities of 2 Tb/in2. This requires increased performance from the magnetic pole of the electromagnetic writer in the read/write head in the HDD. Current state-of-art writing is undertaken by morphologically complex magnetic pole of sub 100 nm dimensions, in an environment of engineered magnetic shields and it needs to deliver strong directional magnetic field to areas on the recording media around 50 nm x 13 nm. This points to the need for a method to perform direct quantitative measurements of the magnetic field generated by the write pole at the nanometer scale. Here we report on the complete in situ quantitative mapping of the magnetic field generated by a functioning write pole in operation using electron holography. Opportunistically, it points the way towards a new nanoscale magnetic field source to further develop in situ Transmission Electron Microscopy.

Identifying Structural Breaks in Stochastic Mortality Models

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

Células solares de Cu2ZnSnS4 por sulfurização de camadas metálicas

As energias renováveis têm estado em destaque desde o fi nal do século XX. São vários os motivos para que isto esteja a acontecer. As previsões apontam para problemas de depleção das reservas de combustíveis fósseis, nomeadamente o petróleo e gás natural, durante o presente século. O carvão, ainda abundante, apresenta problemas ambientais signi cativos. Os perigos associados à energia nuclear estão fazer com que os governos de vários países repensem as suas políticas energéticas . Todas estas tecnologias têm fortes impactos ambientais. Considerando o conjunto das energias renováveis, a energia solar fotovoltaica tem ainda um peso menor no panorama da produção energética actual. A explicação para este facto deve-se ao custo, ainda elevado, dos sistemas fotovoltaicos. Várias iniciativas governamentais estão em curso, a SET for 2020 (UE) e a Sunshot (EUA), para o desenvolvimento de tecnologias que façam frente a este problema. A fatia de mercado que a tecnologia de filmes fi nos representa ainda é pequena, mas tem vindo a aumentar nos últimos anos. As vantagens relativamente à tecnologia tradicional baseada em Si são várias, como por ex. os custos energéticos e materiais para a fabricação das células. Esta dissertação apresenta um processo de fabricação de células solares em fi lmes finos usando como camada absorvente um novo composto semicondutor, o Cu2ZnSnS4, que apresenta como grande argumento, relativamente aos seus predecessores, o facto de ser constituído por elementos abundantes e de toxicidade reduzidas. Foi realizado um estudo sobre as condições termodinâmicas de crescimento deste composto, bem como a sua caracterização e das células solares finais. Este trabalho inclui um estudo dos compostos ternários, CuxSnSx+1 e compostos binários SnxSy, justi cado pelo facto de surgirem como fases secundárias no crescimento do Cu2ZnSnS4. Em seguida são descritos resumidamente os vários capítulos que constituem esta tese. No capítulo 1 é abordada de forma resumida a motivação e o enquadramento da tecnologia no panorama energético global. A estrutura da célula solar adoptada neste trabalho é também descrita. O capítulo 2 é reservado para uma descrição mais detalhada do composto Cu2ZnSnS4, nomeadamente as propriedades estruturais e opto-electrónicas. Estas últimas são usadas para explicar as composições não estequiométricas aplicadas no crescimento deste composto. São também descritas as várias técnicas de crescimento apresentadas na literatura. A última secção deste capítulo apresenta os resultados da caracterização publicados pelos vários grupos que estudam este composto. O método que foi implementado para crescer a camada absorvente, bem como os efeitos que a variação dos vários parâmetros têm neste processo são abordados no capítulo 3. Neste é também incluída uma descrição detalhada dos equipamentos usados na caraterização da camada absorvente e das células solares finais. As fases calcogêneas binária e ternárias são estudadas no capítulo 4. É apresentada uma descrição do método de crescimento, quer para as fases do tipo CuxSnSx+1, quer para as fases do tipo SnxSy e a sua caracterização básica, nomeadamente a sua composição e as propriedades estruturais, ópticas e eléctricas. No caso dos compostos binários são também apresentados os resultados de uma célula solar. No capítulo 5 são reportados os resultados da caracterização dos fi lmes de Cu2ZnSnS4. Técnicas como a dispersão Raman, a fotoluminescência, a efi ciência quântica externa e a espectroscopia de admitância são usadas para analisar as propriedades quer da camada absorvente quer da célula solar. No capítulo 6 é apresentada uma conclusão geral do trabalho desenvolvido e são referidas sugestões para melhorar e complementar os estudos feitos.

Prevenção e detecção de incêndios

Os fogos florestais, embora possam ser encarados como um fenómeno natural, constituem igualmente uma ameaça com impactos negativos a vários níveis. A alteração dos regimes naturais do fogo por acção antrópica tem vindo a maximizar o potencial catastrófico do fenómeno em diferentes regiões do planeta, destacando-se, em particular, a Região Mediterrânica, onde o fogo constitui uma perturbação recorrente associada, por um lado, às características climáticas desta região e, por outro, às práticas tradicionais decorrentes da presença humana nessa área, numa extensão temporal de milhares de anos. Em Portugal, o problema dos fogos florestais assume uma expressividade de particular relevo, colocando-o entre os países do sul da Europa mais atingidos pelo fogo a cada Verão. Reconhecendo o papel das condições meteorológicas nas interacções envolvidas no processo de deflagração e propagação de incêndios, a identificação de condições meteorológicas propícias à ocorrência de incêndios, expressa sob a forma de índices de risco reveste-se de crucial importância para as operações de prevenção e combate aos incêndios, para além da mais-valia que constituem para os restantes sectores da sociedade. Adicionalmente, a detecção e monitorização de ocorrências de incêndios a partir de satélites tem vindo a assumir um papel preponderante, revelando-se fundamental enquanto fonte de alerta e pelas potencialidades que as bases de dados resultantes da observação contínua da Terra pelos satélites oferecem, no que às mais diversas áreas de investigação diz respeito. O presente trabalho explora, nas vertentes da prevenção de incêndios, a utilização de previsões de tempo de alta resolução espacial obtidas com o modelo WRF para a determinação das componentes do sistema FWI canadiano e sua disponibilização operacional. Os resultados apontam para um impacto positivo, em virtude do incremento da resolução espacial, da representação espacial do risco meteorológico de incêndio no território português. Paralelamente, apresentam-se os resultados do desenvolvimento de produtos de detecção de incêndios activos a partir da infra-estrutura de recepção de dados de satélite implementadas na Universidade de Aveiro, destacando a sua adequabilidade para a monitorização e identificação, em tempo quase-real, da ocorrência de fogos florestais em Portugal Continental.

Development of an operational tool for oil spill forecast: application to oil exposed regions

Tese de doutoramento, Ciências do Mar, da Terra e do Ambiente (Modelação), Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Acoustic-oceanographic data fusion for prediction of oceanic acoustic elds

Tese de doutoramento, Engenharia Electrónica e Telecomunicações (Processamento de Sinal), Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Hotel Valuation Software, Version 4.0

[Updated August 2016] The Hotel Valuation Software, freely available from Cornell’s Center for Hospitality Research, has been updated to reflect the many changes in the 11th Edition of the Uniform System of Accounts for the Lodging Industry (USALI). Version 4.0 of the Hotel Valuation Software provides numerous enhancements over the original tool from 2011. In addition to a significant increase in functionality and an update to reflect the 11th edition of the USALI, Version 4.0 takes advantage of the power of the latest release of Microsoft Excel®. Note that Version 4.0 works only on a PC running Microsoft Windows, it does not work on a Mac running OS X. Users desiring an OS X compatible version should click here (Labeled as Version 2.5). 酒店评估软件手册和三个程序（点击这里 ) Users desiring a Mandarin version of the Hotel Valuation Software should click here The Hotel Valuation Software remains the only non-proprietary computer software designed specifically to assist in the preparation of market studies, forecasts of income and expense, and valuations for lodging property. The software provides an accurate, consistent, and cost-effective way for hospitality professionals to forecast occupancy, revenues and expenses and to perform hotel valuations. Version 4.0 of the Hotel Valuation Software includes the following upgrades – a complete update to reflect the 11th edition of the USALI – the most significant change to the chart of accounts in a generation, an average daily rate forecasting tool, a much more sophisticated valuation module, and an optional valuation tool useful in periods of limited capital liquidity. Using established methodology, the Hotel Valuation Software is a sophisticated tool for lodging professionals. The tool consists of three separate software programs written as Microsoft Excel files and a software users' guide. The tool is provided through the generosity of HVS and the School of Hotel Administration. The three software modules are: Room Night Analysis and Average Daily Rate: Enables the analyst to evaluate the various competitive factors such as occupancy, average room rate, and market segmentation for competitive hotels in a local market. Calculates the area-wide occupancy and average room rate, as well as the competitive market mix. Produce a forecast of occupancy and average daily rate for existing and proposed hotels in a local market. The program incorporates such factors as competitive occupancies, market segmentation, unaccommodated demand, latent demand, growth of demand, and the relative competitiveness of each property in the local market. The program outputs include ten-year projections of occupancy and average daily rate. Fixed and Variable Revenue and Expense Analysis: The key to any market study and valuation is a supportable forecast of revenues and expenses. Hotel revenue and expenses are comprised of many different components that display certain fixed and variable relationships to each other. This program enables the analyst to input comparable financial operating data and forecast a complete 11-year income and expense statement by defining a small set of inputs: The expected future occupancy levels for the subject hotel Base year operating data for the subject hotel Fixed and variable relationships for revenues and expenses Expected inflation rates for revenues and expenses Hotel Capitalization Software: A discounted cash flow valuation model utilizing the mortgage-equity technique forms the basis for this program. Values are produced using three distinct underwriting criteria: A loan-to-value ratio, in which the size of the mortgage is based on property value. A debt coverage ratio (also known as a debt-service coverage ratio), in which the size of the mortgage is based on property level cash flow, mortgage interest rate, and mortgage amortization. A debt yield, in which the size of the mortgage is based on property level cash flow. By entering the terms of typical lodging financing, along with a forecast of revenue and expense, the program determines the value that provides the stated returns to the mortgage and equity components. The program allows for a variable holding period from four to ten years The program includes an optional model useful during periods of capital market illiquidity that assumes a property refinancing during the holding period

The Long Range Transport of Birch (Betula) Pollen from Poland and Germany Causes Significant Pre-season Concentrations in Denmark

Background Birch pollen is highly allergic and has the potential for episodically long range transport. Such episodes will in general occur out of the main pollen season. During that time allergy patients are unprotected and high pollen concentrations will therefore have a full allergenic impact. Objective To show that Denmark obtains significant quantities of birch pollen from Poland or Germany before the local trees start to flower. Methods Simultaneous observations of pollen concentrations and phenology in the potential source area in Poland as well as in Denmark were performed in 2006. The Danish pollen records from 2000-2006 were analysed for possible long range transport episodes and analysed with trajectories in combination with a birch tree source map. Results In 2006 high pollen concentrations were observed in Denmark with bi-hourly concentrations above 500 grains/ m3 before the local trees began to flower. Poland was identified as a source region. The analysis of the historical pollen record from Copenhagen shows significant pre-seasonal pollen episodes almost every year from 2000-2006. In all episodes trajectory analysis identified Germany or Poland as source regions. Conclusion Denmark obtains significant pre-seasonal quantities of birch pollen from either Poland or Germany almost every year. Forecasting of birch pollen quantities relevant to allergy patients must therefore take into account long-range transport. This cannot be based on measured concentrations in Denmark. The most effective way to improve the current Danish pollen forecasts is to extend the current forecasts with atmospheric transport models that take into account pollen emission and transport from countries such as Germany and Poland. Unless long range transport is taken into account pre-seasonal pollen episodes will have a full allergic impact, as the allergy patients in general will be unprotected during that time.

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials.

Long-term and Short-term Forecast Models for Poaceae (Grass) Pollen in Poznan, Poland, Constructed Using Regression Analysis

Airborne concentrations of Poaceae pollen have been monitored in Poznań for more than ten years and the length of the dataset is now considered sufficient for statistical analysis. The objective of this paper is to produce long-range forecasts that predict certain characteristics of the grass pollen season (such as the start, peak and end dates of the grass pollen season) as well as short-term forecasts that predict daily variations in grass pollen counts for the next day or next few days throughout the main grass pollen season. The method of forecasting was regression analysis. Correlation analysis was used to examine the relationship between grass pollen counts and the factors that affect its production, release and dispersal. The models were constructed with data from 1994-2004 and tested on data from 2005 and 2006. The forecast models predicted the start of the grass pollen season to within 2 days and achieved 61% and 70% accuracy on a scale of 1-4 when forecasting variations in daily grass pollen counts in 2005 and 2006 respectively. This study has emphasised how important the weather during the few weeks or months preceding pollination is to grass pollen production, and draws attention to the importance of considering large-scale patterns of climate variability (indices of the North Atlantic Oscillation) when constructing forecast models for allergenic pollen.