A technique for establishing L1 asymptotic unbiasedness of a kernel density estimator in Rd that does not depend on the form of the kernel function will be demonstrated. We will introduce the concept of a region sequence of a sequence of kernel functions and show how this can be used to give necessary and sufficient conditions for L1 asymptotic unbiasedness. These results are then applied to kernel density estimators whose form is given and a number of known and novel results are obtained.

A technique for establishing L1 asymptotic unbiasedness of a kernel density estimator in Rd that does not depend on the form of the kernel function will be demonstrated. We will introduce the concept of a region sequence of a sequence of kernel functions and show how this can be used to give necessary and sufficient conditions for L1 asymptotic unbiasedness. These results are then applied to kernel density estimators whose form is given and a number of known and novel results are obtained.

Der Beitrag analysiert die Präzision der Aufkommensprognose wichtiger Bundesabgaben der Jahre 1976 bis 2002 in Österreich. Dadurch wird eine im Schrifttum bestehende Forschungs- und Informationslücke verringert. Eine Prognose wird dazu als präzise verstanden, wenn sie sowohl unverzerrt als auch im Mittel genau ist. Die Prognose des Steueraufkommens auf Bundesebene ist in Österreich gemessen am Bruttogesamtabgabenaufkommen präzise. Dennoch sind aufgrund der unpräzisen Prognosen wichtiger Einzelsteuern Verbesserungen möglich. Als mögliche Ursachen für die Verschätzungen werden die Organisation der Prognose, die verwendeten Prognosemethoden, der Vorsteuerbetrug, Ausgliederungstendenzen aus dem Staatshaushalt und neue kommunale Finanzierungsformen isoliert. Eine Erhöhung der Präzision sollte durch die Kombination mehrerer unabhängiger Prognosen zu einer Gesamtprognose, durch eine stärkere Dokumentation der Prognose, durch die Verwendung univariater Zeitreihenmethoden für die Prognose des Aufkommens an veranlagter Einkommensteuer und an Körperschaftsteuer und durch die Reduktion (Umsatzsteuer) bzw. Erhöhung (Mineralölsteuer) der verwendeten Aufkommenselastizitäten erreicht werden.

The objective of this dissertation is to verify and explain the forward exchange rate unbiasedness hypothesis in the foreign exchange market. Since in most of the cases the unbiasedness hypothesis fails to hold, we try to provide three different explanations of this puzzling behavior in the three essays. The first essay tries to resolve the forward premium puzzle by addressing the model misspecification issue and thereby adding a time-varying risk premium term in the percentage change specification. The risk premium term is modeled using the GARCH-M representation and the model is estimated by applying a GARCH (1, 1) specification. The second essay attributes the failure of the unbiasedness hypothesis to hold to the nonstationarity of the spot and forward exchange rate. It verifies the existence of a cointegrating relationship between the spot and the forward exchange rates and thus specifies an Error Correction Model to better capture the relation between the spot and the forward rates. Further, a cointegrating or the existence of a long run relationship between the spot and forward exchange rates and the domestic and foreign interest rates is tested. It can be viewed as a robustness check where we ensure whether the cointegrated exchange rates are still related in the long run with the inclusion of the interest rates. The objective of the third essay is to apply the generalized method of moments (GMM) to test the unbiasedness hypothesis in the foreign exchange market. Empirical evidence suggests that the spot and forward rates are nonstationary with unit roots and are cointegrated. Cointegration further suggests that the changes in the spot rate can be modeled by an Error Correction Model. The third essay explicitly derives an ECM from the levels specification and uses the GMM estimation technique to test the unbiasedness hypothesis.

This paper sheds light on the differences and similarities in natural gas trading at the National Balancing Point in the UK and the Henry Hub located in the US. For this, we analyze traders' expectations and implement a mechanical forecasting model that allows traders to predict future spot prices. Based on this, we compute the deviations between expected and realized spot prices and analyze possible reasons and dependencies with other market variables. Overall, the mechanical predictor performs well, but a small forecast error remains which can not be characterized by the explanatory variables included.

Estimating functions have been widely used for parameter estimation in various statistical problems. Regular estimating functions produce parameter estimators which have desirable properties, such as consistency and asymptotic normality. In quasi-likelihood inference, an important example of estimating functions, correct specification of the first two moments of the underlying distribution leads to the information unbiasedness, which states that two forms of the information matrix: the negative sensitivity matrix (negative expectation of the first order derivative of an estimating function) and the variability matrix (variance of an estimating function) are equal, or in other words, the analogue of the Fisher information is equivalent to the Godambe information. Consequently, the information unbiasedness indicates that the model-based covariance matrix estimator and sandwich covariance matrix estimator are equivalent. By comparing the model-based and sandwich variance estimators, we propose information ratio (IR) statistics for testing model misspecification of variance/covariance structure under correctly specified mean structure, in the context of linear regression models, generalized linear regression models and generalized estimating equations. Asymptotic properties of the IR statistics are discussed. In addition, through intensive simulation studies, we show that the IR statistics are powerful in various applications: test for heteroscedasticity in linear regression models, test for overdispersion in count data, and test for misspecified variance function and/or misspecified working correlation structure. Moreover, the IR statistics appear more powerful than the classical information matrix test proposed by White (1982). In the literature, model selection criteria have been intensively discussed, but almost all of them target choosing the optimal mean structure. In this thesis, two model selection procedures are proposed for selecting the optimal variance/covariance structure among a collection of candidate structures. One is based on a sequence of the IR tests for all the competing variance/covariance structures. The other is based on an ``information discrepancy criterion" (IDC), which provides a measurement of discrepancy between the negative sensitivity matrix and the variability matrix. In fact, this IDC characterizes the relative efficiency loss when using a certain candidate variance/covariance structure, compared with the true but unknown structure. Through simulation studies and analyses of two data sets, it is shown that the two proposed model selection methods both have a high rate of detecting the true/optimal variance/covariance structure. In particular, since the IDC magnifies the difference among the competing structures, it is highly sensitive to detect the most appropriate variance/covariance structure.

Estimating functions have been widely used for parameter estimation in various statistical problems. Regular estimating functions produce parameter estimators which have desirable properties, such as consistency and asymptotic normality. In quasi-likelihood inference, an important example of estimating functions, correct specification of the first two moments of the underlying distribution leads to the information unbiasedness, which states that two forms of the information matrix: the negative sensitivity matrix (negative expectation of the first order derivative of an estimating function) and the variability matrix (variance of an estimating function) are equal, or in other words, the analogue of the Fisher information is equivalent to the Godambe information. Consequently, the information unbiasedness indicates that the model-based covariance matrix estimator and sandwich covariance matrix estimator are equivalent. By comparing the model-based and sandwich variance estimators, we propose information ratio (IR) statistics for testing model misspecification of variance/covariance structure under correctly specified mean structure, in the context of linear regression models, generalized linear regression models and generalized estimating equations. Asymptotic properties of the IR statistics are discussed. In addition, through intensive simulation studies, we show that the IR statistics are powerful in various applications: test for heteroscedasticity in linear regression models, test for overdispersion in count data, and test for misspecified variance function and/or misspecified working correlation structure. Moreover, the IR statistics appear more powerful than the classical information matrix test proposed by White (1982). In the literature, model selection criteria have been intensively discussed, but almost all of them target choosing the optimal mean structure. In this thesis, two model selection procedures are proposed for selecting the optimal variance/covariance structure among a collection of candidate structures. One is based on a sequence of the IR tests for all the competing variance/covariance structures. The other is based on an ``information discrepancy criterion" (IDC), which provides a measurement of discrepancy between the negative sensitivity matrix and the variability matrix. In fact, this IDC characterizes the relative efficiency loss when using a certain candidate variance/covariance structure, compared with the true but unknown structure. Through simulation studies and analyses of two data sets, it is shown that the two proposed model selection methods both have a high rate of detecting the true/optimal variance/covariance structure. In particular, since the IDC magnifies the difference among the competing structures, it is highly sensitive to detect the most appropriate variance/covariance structure.

This thesis examines the impact of shocks in spot prices on long-term forward contracts in power markets. A unique comparison of efficiency of German and Hungarian power markets is provided. The risk premium on week-ahead forward contract is scrutinized by both data inspection and by unbiased forward rate hypothesis (UFRH) testing. Additionally, the ex-post market's prediction error for this product is explained by main drivers of spot electricity price, which are presented in section devoted to introduction to power markets. Expectedly, Hungarian forwards with longer time-to-delivery are found to react heavily on spot market shocks after controlling for changes in short-run marginal costs of conventional power plants. Such outcome applies both to intra-day and weekly time horizons. However, this evidence was not found for German market. These results point out to immaturity and the presence of inefficiencies in Hungarian power market. However, Hungarian risk premia on week-ahead and day-ahead forward products turn out to be considerably lower than for Germany. This was confirmed by UFRH tests on week-ahead forward contracts, where a significant risk premium was found in Germany as opposed to Hungarian risk premium. This finding is surprising since Hungarian spot prices are more prone to upward...

Made available in DSpace on 2014-12-17T15:26:38Z (GMT). No. of bitstreams: 1 MarconioSS_DISSERT.pdf: 828358 bytes, checksum: d4bc4c24d61f5cdfad5c76519c34784e (MD5) Previous issue date: 2010-06-28 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / In this work we studied the asymptotic unbiasedness, the strong and the uniform strong consistencies of a class of kernel estimators fn as an estimator of the density function f taking values on a k-dimensional sphere / Nesse trabalho estudamos o n?o-v?cio assint?tico, a consist?ncia forte e a consist?ncia uniformemente forte de um estimador do tipo n?cleo, que como a maioria dos estimadores ? constru?do com base em n observa??es i.i.d. X1,..., Xn de X, para a densidade f(x) de um vetor aleat?rio X que assume valores em uma esfera unit?ria k-dimensional

This thesis provides a thorough analysis of the covered- and uncovered interest parity conditions (CIP, UIP) as well as the forward rate unbiasedness hypothesis (FRUH) for Sweden and the European Economic and Monetary Union (EMU). By studying data on interbank rates in Sweden (STIBOR) and the EMU (EURIBOR) as well as the corresponding spot- and forward exchange rates, monetary integration and country-specific risks are determined and analyzed with direct applications to the potential entry of Sweden into the EMU. As interest rate parity in general gives insight into market efficiency and frictions between the chosen regions, such points are discussed in addition to EMU entry. Drawing on past studies that mainly studied one condition in isolation, a nested formulation of interest rate parity is instead derived and tested using cointegration and robust estimation methods. The results point to a strict rejection of the FRUH for all horizons except the shortest and a case where CIP only holds for the 6-month horizon and partially over one year. This implies, based on the nested formulation, that UIP is rejected for all horizons as well. Ultimately, the study concludes that a Swedish entry into the EMU is not motivated given the lackluster results on UIP and due to the lack of monetary integration. / Den här uppsatsen presenterar en djupgående analys av det kurssäkrade- och icke-kurssäkrade ränteparitetsvillkoret samt den effektiva marknadshypotesen på valutaterminer för Sverige och den europeiska ekonomiska och monetära unionen (EMU). Genom att studera data på interbankräntor i Sverige (STIBOR) och EMU (EURIBOR) samt respektive spot- och valutaterminskurser så skattas och analyseras monetär integration samt landsspecifika risker med en direkt tillämpning på Sveriges eventuella inträde i EMU. Eftersom ränteparitet generellt ger insikt i marknadseffektivitet och friktioner regioner emellan, diskuteras även dessa punkter utöver ett eventuellt EMU-inträde. Genom att bygga på föregående studier som i huvudsak studerar ränteparitetsvillkoren var för sig, härleds en sekventiell formulering av villkoren som sedan testas med kointegration och robusta estimeringsmetoder. Resultaten ger att den effektiva marknadshypotesen strikt förkastas på alla tidshorisonter förutom på en dag respektive en vecka, samt att kurssäkrad ränteparitet håller på 6 och delvis 12 månaders sikt. Baserat på den sekventiella formuleringen så innebär detta att icke-kurssäkrad ränteparitet inte håller på någon tidshorisont. Slutligen, baserat på både resultat och diskussion, är ett svenskt inträde i EMU inte motiverbart givet negativa resultat för icke-kurssäkrad ränteparitet och avsaknaden av fullständig monetär integration mellan regionerna.