Nos últimos 50 anos, registrou-se na América Central um dos processos de integração econômica e regional mais antigos do continente americano. O comércio intra-regional aumentou e dinamizou-se significativamente a partir da formação, em 1960, do Mercado Comum Centro-Americano (MCCA), assim como processos de integração de acordos bilaterais, regionais e multilaterais de livre comércio. A partir desses acordos, surge uma nova perspectiva para estudar os efeitos do comércio internacional, segundo a Nova Geografia Econômica (NGE), a qual tenta explicar como a evolução da distribuição do tamanho das cidades pode ser representada por uma distribuição de Pareto, que deriva numa regularidade empírica chamada Lei de Zipf, que brinda uma explicação de como interagem as forças de aglomeração nos centros urbanos, que favorecem a atividade econômica e o comércio internacional em geral. Esta dissertação procura investigar a maneira como as mudanças na política comercial geraram impacto sobre a ordem no tamanho das cidades e a influência no crescimento econômico da Guatemala. Para esse propósito, foi estimado o coeficiente de Pareto no período compreendido entre 1921-2002, e como um valor agregado na proposta original, foram introduzidas duas não-linearidades na distribuição e uma medida de apoio, como o Índice Hirschman-Herfindahl, para medir o grau da concentração urbana. Por outra parte, foi utilizado um modelo de taxas de variação para medir o impacto de abertura comercial no período de 1960-2002 sobre o crescimento econômico resultante. Portanto, pode-se enfatizar que alterações no tamanho da amostra podem conduzir a diferentes interpretações. Os resultados obtidos apontam um leve crescimento na desigualdade e divergência, apesar do índice de concentração urbana mostrar uma queda gradual desde o ano de 1964, na época MCCA, até o ano de 2002. No caso do período de 1973-2002, pode-se verificar a Lei de Gibrat, que indica ser o crescimento das cidades independente do seu tamanho. Também se verifica a hipótese de que a concentração urbana tem uma relação inversa com a abertura comercial, e que ela está correlacionada de forma positiva com o crescimento econômico no período de 1921- 1964. Com esses resultados, pode-se mostrar o caminho futuro da evolução do crescimento urbano, onde as maiores cidades reduziram o seu crescimento e as médias e pequenas cidades cresceram a um ritmo mais acelerado que os grandes centros, impulsionadas pelo crescimento do comércio internacional. / Over the last 50 years, in Central America was developed one of the oldest processes of economic and regional integration of the American Continent. Since the establishment in 1960 of the Central American Common Market (CACM), intra-regional trade significantly increased under multilateral, bilateral and regional free trade agreements of the integration process. Today, a new perspective exists in the study of the effects of international trade offered by the New Economic Geography (NEG) that seeks to explain the evolution and distribution of the size of the cities that can be represented by Pareto's distribution, derived from a well-known empirical regularity known as the Zipf's Law, which promotes an explanation of how the agglomeration forces in the urban centers interact in favor of economic activity and international trade. This dissertation tries to investigate the way in which the changes in trade policy generate changes in the order of the size in the cities, thus influencing the economic growth of Guatemala. To this purpose Pareto's coefficient was estimated for the period between 1921 and 2002 and it was considered as an aggregated value and therefore the original proposal of two not-linealities were introduced in the distribution as support, as the Hirschman-Herfindahl Index to measure the degree of the urban concentration. On the other hand, a model of variation rates was used during the 1960 and 2002 period to measure the trade impact of the trade opening on the resulting economic growth. Therefore, a model of variation rates was used to measure the impact of the trade opening on the resulting economic growth during the 1960-2002 period. For that reason, it is possible to emphasize the alterations in the size of the sample that can achieve different interpretations. The results obtained point to a slight growth in inequality and divergence, even though the index of urban concentration shows a gradual fall from 1964 during the CACM period up to 2002; which otherwise means that small cities grew at a smaller rate than the larger cities did. In the case of the 1973-2002 period, it is possible to verify Gibrat's Law which indicates that the growth of the cities is independent to its size. Also the hypothesis is verified that the urban concentration has an inverse relation with the trade opening and that the urban concentration is correlated in a positive form with the economic growth during the 1921-1964 period. With these results it is possible to show the future way of the evolution of urban growth where major cities would reduce its growth, and the middle and small cities will grow further at a more accelerated rate than the major cities driven by the growth of international trade. / En los últimos 50 años, se registró en Centro América uno de los procesos de integración económica y regional más antiguos del continente. El comercio intra-regional aumento y se dinamizo significativamente a partir de la formación, en 1960, del Mercado Común Centroamericano (MCCA), así como a los procesos de integración como acuerdos bilaterales, regionales y multilaterales de libre comercio. A partir de esos acuerdos, surge una nueva perspectiva para estudiar los efectos del comercio internacional, la Nueva Geografía Económica (NGE) la cual intenta explicar como la evolución de la distribución del tamaño de las ciudades puede ser representada por una distribución de Pareto, que se deriva en una regularidad empírica llamada la Ley de Zipf, que brinda una explicación de como interactúan las fuerzas de aglomeración en los centros urbanos y que favorecen a la actividad económica en el comercio internacional en general. Esta disertación busca investigar como los cambios en la política comercial generaran un impacto sobre el orden en el tamaño de las ciudades y esto a su vez como influencia en el crecimiento económico de Guatemala. Para ese propósito, fue estimado el coeficiente de Pareto en el período comprendido entre 1921-2002 y como un valor agregado en la propuesta original, fueran introducidas dos no-linealidades en la distribución y una medida de apoyo, como el Índice Hirschman-Herfindahl, para medir el grado de concentración urbana. Por otra parte, fue utilizado un modelo de tasas de variación para medir el impacto de apertura comercial en el período de 1960-2002 sobre el crecimiento económico resultante. Por lo tanto, se puede enfatizar que alteraciones en el tamaño de la muestra pueden conducir a diferentes interpretaciones. Los resultados obtenidos apuntan un leve crecimiento en la desigualdad y divergencia, a pesar de que el índice de concentración urbana muestra una caída gradual desde el año de 1964, en la época del MCCA, hasta el año de 2002. En el caso del período de 1973-2002, se puede verificar la Ley de Gibrat, que indica que el crecimiento de las ciudades es independiente de su tamaño. También se verifica la hipótesis de que la concentración urbana tiene una relación inversa con una apertura comercial y que está correlacionada de forma positiva con el crecimiento económico en el período de 1921-1964. Con estos resultados, se puede mostrar el camino futuro de la evolución del crecimiento urbano, donde las mayores ciudades reducirían su crecimiento y las medianas y pequeñas ciudades crecerán a un ritmo más acelerado que los grandes centros, impulsadas por el crecimiento del comercio internacional.

Nos últimos 50 anos, registrou-se na América Central um dos processos de integração econômica e regional mais antigos do continente americano. O comércio intra-regional aumentou e dinamizou-se significativamente a partir da formação, em 1960, do Mercado Comum Centro-Americano (MCCA), assim como processos de integração de acordos bilaterais, regionais e multilaterais de livre comércio. A partir desses acordos, surge uma nova perspectiva para estudar os efeitos do comércio internacional, segundo a Nova Geografia Econômica (NGE), a qual tenta explicar como a evolução da distribuição do tamanho das cidades pode ser representada por uma distribuição de Pareto, que deriva numa regularidade empírica chamada Lei de Zipf, que brinda uma explicação de como interagem as forças de aglomeração nos centros urbanos, que favorecem a atividade econômica e o comércio internacional em geral. Esta dissertação procura investigar a maneira como as mudanças na política comercial geraram impacto sobre a ordem no tamanho das cidades e a influência no crescimento econômico da Guatemala. Para esse propósito, foi estimado o coeficiente de Pareto no período compreendido entre 1921-2002, e como um valor agregado na proposta original, foram introduzidas duas não-linearidades na distribuição e uma medida de apoio, como o Índice Hirschman-Herfindahl, para medir o grau da concentração urbana. Por outra parte, foi utilizado um modelo de taxas de variação para medir o impacto de abertura comercial no período de 1960-2002 sobre o crescimento econômico resultante. Portanto, pode-se enfatizar que alterações no tamanho da amostra podem conduzir a diferentes interpretações. Os resultados obtidos apontam um leve crescimento na desigualdade e divergência, apesar do índice de concentração urbana mostrar uma queda gradual desde o ano de 1964, na época MCCA, até o ano de 2002. No caso do período de 1973-2002, pode-se verificar a Lei de Gibrat, que indica ser o crescimento das cidades independente do seu tamanho. Também se verifica a hipótese de que a concentração urbana tem uma relação inversa com a abertura comercial, e que ela está correlacionada de forma positiva com o crescimento econômico no período de 1921- 1964. Com esses resultados, pode-se mostrar o caminho futuro da evolução do crescimento urbano, onde as maiores cidades reduziram o seu crescimento e as médias e pequenas cidades cresceram a um ritmo mais acelerado que os grandes centros, impulsionadas pelo crescimento do comércio internacional. / Over the last 50 years, in Central America was developed one of the oldest processes of economic and regional integration of the American Continent. Since the establishment in 1960 of the Central American Common Market (CACM), intra-regional trade significantly increased under multilateral, bilateral and regional free trade agreements of the integration process. Today, a new perspective exists in the study of the effects of international trade offered by the New Economic Geography (NEG) that seeks to explain the evolution and distribution of the size of the cities that can be represented by Pareto's distribution, derived from a well-known empirical regularity known as the Zipf's Law, which promotes an explanation of how the agglomeration forces in the urban centers interact in favor of economic activity and international trade. This dissertation tries to investigate the way in which the changes in trade policy generate changes in the order of the size in the cities, thus influencing the economic growth of Guatemala. To this purpose Pareto's coefficient was estimated for the period between 1921 and 2002 and it was considered as an aggregated value and therefore the original proposal of two not-linealities were introduced in the distribution as support, as the Hirschman-Herfindahl Index to measure the degree of the urban concentration. On the other hand, a model of variation rates was used during the 1960 and 2002 period to measure the trade impact of the trade opening on the resulting economic growth. Therefore, a model of variation rates was used to measure the impact of the trade opening on the resulting economic growth during the 1960-2002 period. For that reason, it is possible to emphasize the alterations in the size of the sample that can achieve different interpretations. The results obtained point to a slight growth in inequality and divergence, even though the index of urban concentration shows a gradual fall from 1964 during the CACM period up to 2002; which otherwise means that small cities grew at a smaller rate than the larger cities did. In the case of the 1973-2002 period, it is possible to verify Gibrat's Law which indicates that the growth of the cities is independent to its size. Also the hypothesis is verified that the urban concentration has an inverse relation with the trade opening and that the urban concentration is correlated in a positive form with the economic growth during the 1921-1964 period. With these results it is possible to show the future way of the evolution of urban growth where major cities would reduce its growth, and the middle and small cities will grow further at a more accelerated rate than the major cities driven by the growth of international trade. / En los últimos 50 años, se registró en Centro América uno de los procesos de integración económica y regional más antiguos del continente. El comercio intra-regional aumento y se dinamizo significativamente a partir de la formación, en 1960, del Mercado Común Centroamericano (MCCA), así como a los procesos de integración como acuerdos bilaterales, regionales y multilaterales de libre comercio. A partir de esos acuerdos, surge una nueva perspectiva para estudiar los efectos del comercio internacional, la Nueva Geografía Económica (NGE) la cual intenta explicar como la evolución de la distribución del tamaño de las ciudades puede ser representada por una distribución de Pareto, que se deriva en una regularidad empírica llamada la Ley de Zipf, que brinda una explicación de como interactúan las fuerzas de aglomeración en los centros urbanos y que favorecen a la actividad económica en el comercio internacional en general. Esta disertación busca investigar como los cambios en la política comercial generaran un impacto sobre el orden en el tamaño de las ciudades y esto a su vez como influencia en el crecimiento económico de Guatemala. Para ese propósito, fue estimado el coeficiente de Pareto en el período comprendido entre 1921-2002 y como un valor agregado en la propuesta original, fueran introducidas dos no-linealidades en la distribución y una medida de apoyo, como el Índice Hirschman-Herfindahl, para medir el grado de concentración urbana. Por otra parte, fue utilizado un modelo de tasas de variación para medir el impacto de apertura comercial en el período de 1960-2002 sobre el crecimiento económico resultante. Por lo tanto, se puede enfatizar que alteraciones en el tamaño de la muestra pueden conducir a diferentes interpretaciones. Los resultados obtenidos apuntan un leve crecimiento en la desigualdad y divergencia, a pesar de que el índice de concentración urbana muestra una caída gradual desde el año de 1964, en la época del MCCA, hasta el año de 2002. En el caso del período de 1973-2002, se puede verificar la Ley de Gibrat, que indica que el crecimiento de las ciudades es independiente de su tamaño. También se verifica la hipótesis de que la concentración urbana tiene una relación inversa con una apertura comercial y que está correlacionada de forma positiva con el crecimiento económico en el período de 1921-1964. Con estos resultados, se puede mostrar el camino futuro de la evolución del crecimiento urbano, donde las mayores ciudades reducirían su crecimiento y las medianas y pequeñas ciudades crecerán a un ritmo más acelerado que los grandes centros, impulsadas por el crecimiento del comercio internacional.

Magister Scientiae - MSc / The intention is to draw more specific connections between certain deconvolution methods and also to demonstrate the application of the statistical theory of estimation in the presence of measurement error. A parametric methodology for deconvolution when the underlying distribution is of the Pareto form is developed. Maximum likelihood estimation (MLE) of the parameters of the convolved distributions is considered. Standard errors of the estimated parameters are calculated from the inverse Fisher’s information matrix and a jackknife method. Probability-probability (P-P) plots and Kolmogorov-Smirnov (K-S) goodnessof- fit tests are used to evaluate the fit of the posited distribution. A bootstrapping method is used to calculate the critical values of the K-S test statistic, which are not available. / South Africa

>Magister Scientiae - MSc / Estimation of population distributions, from samples that are contaminated by measurement errors, is a common problem. This study considers the problem of estimating the population distribution of independent random variables Xi, from error-contaminated samples ~i (.j = 1, ... , n) such that Yi = Xi + f·.i, where E is the measurement error, which is assumed independent of X. The measurement error ( is also assumed to be normally distributed. Since the observed distribution function is a convolution of the error distribution with the true underlying distribution, estimation of the latter is often referred to as a deconvolution problem. A thorough study of the relevant deconvolution literature in statistics is reported. We also deal with the specific case when X is assumed to follow a truncated Pareto form. If observations are subject to Gaussian errors, then the observed Y is distributed as the convolution of the finite-support Pareto and Gaussian error distributions. The convolved probability density function (PDF) and cumulative distribution function (CDF) of the finite-support Pareto and Gaussian distributions are derived. The intention is to draw more specific connections bet.ween certain deconvolution methods and also to demonstrate the application of the statistical theory of estimation in the presence of measurement error. A parametric methodology for deconvolution when the underlying distribution is of the Pareto form is developed. Maximum likelihood estimation (MLE) of the parameters of the convolved distributions is considered. Standard errors of the estimated parameters are calculated from the inverse Fisher's information matrix and a jackknife method. Probability-probability (P-P) plots and Kolmogorov-Smirnov (K-S) goodnessof- fit tests are used to evaluate the fit of the posited distribution. A bootstrapping method is used to calculate the critical values of the K-S test statistic, which are not available. Simulated data are used to validate the methodology. A real-life application of the methodology is illustrated by fitting convolved distributions to astronomical data

In many environmental and climate applications, extreme data are spatial by nature, and hence statistics of spatial extremes is currently an important and active area of research dedicated to developing innovative and flexible statistical models that determine the location, intensity, and magnitude of extreme events. In particular, the development of flexible sub-asymptotic models is in trend due to their flexibility in modeling spatial high threshold exceedances in larger spatial dimensions and with little or no effects on the choice of threshold, which is complicated with classical extreme value processes, such as Pareto processes. In this thesis, we develop new flexible sub-asymptotic extreme value models for modeling spatial and spatio-temporal extremes that are combined with carefully designed gradient-based Markov chain Monte Carlo (MCMC) sampling schemes and that can be exploited to address important scientific questions related to risk assessment in a wide range of environmental applications. The methodological developments are centered around two distinct themes, namely (i) sub-asymptotic Bayesian models for extremes; and (ii) flexible marked point process models with sub-asymptotic marks. In the first part, we develop several types of new flexible models for light-tailed and heavy-tailed data, which extend a hierarchical representation of the classical generalized Pareto (GP) limit for threshold exceedances. Spatial dependence is modeled through latent processes. We study the theoretical properties of our new methodology and demonstrate it by simulation and applications to precipitation extremes in both Germany and Spain. In the second part, we construct new marked point process models, where interest mostly lies in the extremes of the mark distribution. Our proposed joint models exploit intrinsic CAR priors to capture the spatial effects in landslide counts and sizes, while the mark distribution is assumed to take various parametric forms. We demonstrate that having a sub-asymptotic distribution for landslide sizes provides extra flexibility to accurately capture small to large and especially extreme, devastating landslides.

<p>In this thesis are extreme value theory used to estimate the probability that large insuranceclaims are exceeding a certain threshold. The expected claim size, given that the claimhas exceeded a certain limit, are also estimated. Two different models are used for thispurpose. The first model is based on maximum domain of attraction conditions. A Paretodistribution is used in the other model. Different graphical tools are used to check thevalidity for both models. Länsförsäkring Kronoberg has provided us with insurance datato perform the study.Conclusions, which have been drawn, are that both models seem to be valid and theresults from both models are essential equal.</p> / <p>I detta arbete används extremvärdesteori för att uppskatta sannolikheten att stora försäkringsskadoröverträffar en vis nivå. Även den förväntade storleken på skadan, givetatt skadan överstiger ett visst belopp, uppskattas. Två olika modeller används. Den förstamodellen bygger på antagandet att underliggande slumpvariabler tillhör maximat aven extremvärdesfördelning. I den andra modellen används en Pareto fördelning. Olikagrafiska verktyg används för att besluta om modellernas giltighet. För att kunna genomförastudien har Länsförsäkring Kronoberg ställt upp med försäkringsdata.Slutsatser som dras är att båda modellerna verkar vara giltiga och att resultaten ärlikvärdiga.</p>

Title: Large deviations and their applications in insurance mathematics Author: Lucia Fuchsová Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Zbyněk Pawlas, Ph.D. Supervisor's e-mail address: Zbynek.Pawlas@mff.cuni.cz Abstract: In the present work we study large deviations theory. We discuss heavy-tailed distributions, which describe the probability of large claim oc- curence. We are interested in the use of large deviations theory in insurance. We simulate claim sizes and their arrival times for Cramér-Lundberg model and first we analyze the probability that ruin happens in dependence on the parameters of our model for Pareto distributed claim size, next we compare ruin probability for other claim size distributions. For real life data we model the probability of large claim size occurence by generalized Pareto distribu- tion. 1

In the present work we deal with the problem of etremal value of time series, especially of maxima. We study times and values of maximum by an approach of point process and we model distribution of extremal values by statistical methods. We estimate parameters of distribution using different methods, namely graphical methods of data analysis and subsequently we test the estimated distribution by tests of goodness of fit. We study the stationary case and also the cases with a trend. In connection with distribution of excesess and exceedances over a threshold we deal with generalized Pareto distribution.

This thesis is focused on the models based on extreme value theory and their practical applications. Specifically are described the block maxima models and the models based on threshold exceedances. Both of these methods are described in thesis theoretically. Apart from theoretical description there are also practical calculations based on simulated or real data. The applications of block maxima models are focused on choice of block size, suitability of the models for specific data and possibilities of extreme data analysis. The applications of models based on threshold exceedances are focused on choice of threshold and on suitability of the models. There is an example of the model used for calculations of reinsurance premium for extreme claims in the case of nonproportional reinsurance.

In the present thesis we will firstly familiarize ourselves with the term of operational risk, it's definition presented in the directives Basel II and Solvency II, and afterwards with the methods of calculation Capital Requirements for Operational Risk, set by these directives. In the second part of the thesis we will concentrate on the methods of modelling operational loss data. We will introduce the Extreme Value Theory which describes possible approaches to modelling data with significant values that occur infrequently; the typical characteristic of operational risk data. We will mainly focus on the model for threshold exceedances which utilizes Generalized Pareto Distribution to model the distribution of those excesses. The teoretical knowledge of this theory and the appropriate modelling will be applied on simulated loss data. Finally we will test the ability of presented methods to model loss data distributions.