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Karlsson, Olov. "Volatility forecasting under structural breaks." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-302398.
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Sobreira, Nuno. "Three essays on structural breaks." Doctoral thesis, NSBE - UNL, 2012. http://hdl.handle.net/10362/11853.
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Zhang, Dayong. "Structural breaks in empirical modelling of stock markets." Thesis, University of Birmingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433631.
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Nazare, Ronaldo. "Essays in applied factor analysis with structural breaks." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/360375/.
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Malki, Issam. "A structural breaks approach to modelling United States inflation." Thesis, University of Dundee, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505641.
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Banerjee, Abhisek. "Essays on semiparametric estimation of models with structural breaks." Thesis, London School of Economics and Political Science (University of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538732.
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Kartsaklas, Aris. "Long memory, structural breaks and the volatility-volume relationship." Thesis, University of York, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495883.
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Lazarova, Stepana. "Long memory and structural breaks in time series models." Thesis, London School of Economics and Political Science (University of London), 2006. http://etheses.lse.ac.uk/1927/.
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This thesis examines structural breaks in time series regressions where both regressors and errors may exhibit long range dependence. Statistical properties of methods for detecting and estimating structural breaks are analysed and asymptotic distribution of estimators and test statistics are obtained. Valid bootstrap methods of approximating the limiting distribution of the relevant statistics are also developed to improve on the asymptotic approximation in finite samples or to deal with the problem of unknown asymptotic distribution. The performance of the asymptotic and bootstrap methods are compared through Monte Carlo experiments. A background of the concepts of structural breaks, long memory and bootstrap is offered in Introduction where the main contribution of the thesis is also outlined. Chapter 1 proposes a fluctuation-type test procedure for detecting instability of slope coefficients. A first-order bootstrap approximation of the distribution of the test statistic is proposed. Chapter 2 considers estimation and testing of the time of the structural break. Statistical properties of the estimator are examined under a range of assumptions on the size of the break. Under the assumption of shrinking break, a bootstrap approximation of the asymptotic test procedure is proposed. Chapter 3 addresses a drawback of the assumption of fixed size of break. Under this assumption, the asymptotic distribution of the estimator of the breakpoint depends on the unknown underlying distribution of data and thus it is not available for inference purposes. The proposed solution is a bootstrap procedure based on a specific type of deconvolution.
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Mendonça, Francisco António Teixeira. "Double unit tests in the presence of structural breaks." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14894.
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Mestrado em Econometria Aplicada e Previsão<br>Apresentam-se dois testes estatísticos que permitem averiguar a existência de duas raízes unitárias numa série temporal univariada que contenha um quebra estrutural na função determinística.
Os testes foram aplicados a várias séries económicas, e encontrou-se evidência estatística que suporta a hipótese nula.<br>We present two statistical tests that to verify the existence of two unit roots in a univariate time series that contains a structural break in the deterministic function.
The tests were applied to several economic series, and statistical evidence supporting the null hypothesis was found.<br>info:eu-repo/semantics/publishedVersion
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Wang, Bruce Chang-Ming. "Structural breaks and regime switching models : theoretical extensions and applications /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/7476.
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ALMEIDA, ALEXANDRA RIBEIRO MENDES DE. "STRUCTURAL BREAKS DETECTION: AN APPLICATION TO THE BRAZILIAN HEDGE FUNDS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2010. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=16317@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>A estacionariedade sempre desempenhou um papel importante no tratamento
teórico de séries temporais. Contudo muitas séries demonstram um
comportamento não-estacionário. Em muitos casos, técnicas simples como
a diferenciação não são suficientes. Neste contexto, e considerando a mais
frequente suposição de instabilidade nas características estocásticas dos retornos
financeiros, assim como as consequências em se assumir estacionariedade
quando esta não é uma característica razoável, que utilizamos a
metodologia proposta por Picard (1985) (37), estendida por Kluppelberg e
Mikosch (1996)(23) e posteriormente resgatada por Starica e Granger (2005)
(41) em 2005, cujo objetivo é identificar períodos estacionários em séries
globalmente não-estacionárias, e aproximá-las localmente por modelos estacionários. Objetivando ampliar a compreensão da utilidade da estatística utilizada na metodologia, fizemos um estudo via simulação envolvendo mudanças estruturais ou pontuais no processo gerador, e avaliando o desempenho da metodologia na detecção dessas mudanças. Essa metodologia de
identificação de períodos homogêneos foi aplicada no contexto dos hedge funds brasileiros, instrumentos financeiros onde tradicionalmente observa-se significativa auto-correlação, inclusive para defasagens de longo prazo, característica esta, justificada na literatura como resultado da falta de liquidez, como em Getmansky et al (2003) (14). Motivada pelas evidências empíricas
envolvendo a influência das mudanças no segundo momento não-condicional
de séries financeiras no comportamento da função de auto-correlação serial,
discutido em Mikosch e Starica (2004) (32), aplicamos a metodologia de
identificação dos períodos de estacionariedade na série de volatilidade dos
hedge funds que apresentaram não-estacionariedade global.<br>Stationarity has always played an important role in the theoretical treatment
of time series. However many series show a nonstationary behavior.
In many cases, simple techniques such as differentiation is not enough. In
this context, and considering the most frequent assumption of instability
in the stochastic characteristics of financial returns as well as the consequences
of assume stationarity when this feature is not reasonable, we use
the methodology proposed by Picard (1985) (37), extended by Kluppelberg
and Mikosch (1996) (23) and later by Starica and Granger (2005) (41),
whose goal is to identify stationary periods in globally non-stationary series,
and locally approximate them by stationary models. Aiming to broaden
the understanding of the usefulness of the statistical methodology used, we
made a simulation study involving structural or point changes in the generating
process, and evaluating the performance of the methodology to detect
these changes. This method of identifying homogeneous periods was applied
in the context of Brazilian hedge funds, financial instruments where
traditionally we see significant autocorrelation, even for long-term lags, feature
explained in the literature as a result of illiquidity, as in Getmansky et
al (2003) (14). Motivated by empirical evidence involving the influence of
changes in non-conditional second moment of financial time series behavior
of the function of serial correlation, discussed in Mikosch and Starica (2004)
(32), we apply the methodology aiming identifying stationary periods in the
hedge funds volatility series that had global non-stationarity.
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Ortez, Amador Mario Amado. "Forecasting volatility in agricultural commodities markets considering market structural breaks." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/18995.
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Master of Science<br>Department of Agricultural Economics<br>Glynn Tonsor<br>This decade has seen movements in commodity futures markets never seen before. There are many factors that have intensified price movements and volatility behavior. Those factors likely altering supply and demand include governmental policy within and outside of the U.S, weather shocks, geopolitical conflicts, food safety concerns etc. Whatever the reasons are for price movements it is clear that the volatility behavior in commodity markets constantly change, and risk managers need to use current and efficient tools to mitigate price risk.
This study identified market structural breaks of realized volatility in corn, wheat, soybeans, live cattle, feeder cattle and lean hogs futures markets. Furthermore, this study analyzes the forecasting performance of implied volatility, historical volatility, a composite approach and a naïve approach as forecasters of realized volatility. The forecasting performance of these methods was analyzed in the full period of time of our weekly data from January 1995 to April 2014 and in each identified market regime for each commodity. Previous research has analyzed forecasting performance of implied volatility, a time series alternative and a composite method. However, to the best of my knowledge, they have not worried about market structural breaks in the data that might influence the performance of the mentioned forecasting methods in different periods of time.
Overall, results indicate that indeed there are multiple market structural breaks present in the volatility datasets across all six commodities. We found differences in the forecasting performance of the analyzed methods when individual market regimes were analyzed. There seems to be evidence that corroborates the idea in the literature about the superiority of implied volatility over a historical volatility, a composite approach and a naïve approach. Additionally, implied volatility encompassed all the information contained in the historical volatility and the
naïve measure across each identified market regime in all six commodities. Our results show that when both implied volatility and historical volatility are available, the benefit of combining those measures into a composite forecasting approach is very limited. Our results hold true for a short term 1 week ahead realized volatility forecast. It would be of interest to see how results vary for longer forecasting time horizons.
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Li, Chenlu. "Structural breaks in hedge fund performance and foreign exchange liquidity." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/27065.
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Hedge fund managers are characterised as either market timers or asset pickers . Their superior performance can be attributed to either timing skill, selection ability or a combination of both. In the existing literature, average hedge fund performance across the entire time span under investigation is usually investigated and measured, and hence, potentially certain subtle but important features exhibited in different time periods can be averaged out in the analysis. This thesis investigates the structural breaks in the selection ability and timing skill of hedge fund managers. This research issue is of particular importance when the hedge fund performance before, during and after the recent financial crisis is compared and contrasted. This thesis conducts a structural break analysis of hedge fund managers performance in relation to market-wide liquidity and liquidity commonality in the foreign exchange (FX) market. Liquidity commonality captures the co-movement of individual asset liquidities. The measure adopted in the existing literature has several limitations. This thesis proposes a new measure, termed the Beta Index, which is derived from the time-varying exposure of individual liquidities to market liquidity movements. It is shown that the developed Beta Index is more able to identify the level of liquidity commonality in the FX market. It is also more flexible in measuring commonality with different data sampling frequency. The obtained empirical results have some practical implications. They show that the selection skill and timing ability of hedge fund managers are subject to regime switches. Under severe market conditions, most hedge fund managers possess the skill to time FX market-wide liquidity and are able to reduce losses from the FX market by reducing their funds FX exposure prior to the FX market-wide liquidity deteriorations. In the meantime, most hedge fund managers are able to deliver excess returns from time to time due to their selection ability. However, when sudden shocks of crisis occur, they fail to forecast the unexpected behaviour in the price of individual assets underlying the funds and display unsuccessful selection ability. In addition, the results suggest that many hedge funds are exposed to the FX liquidity commonality risk which impairs hedging strategies and diversification performance.
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Houndetoungan, Elysée Aristide. "Essays on Social Networks and Time Series with Structural Breaks." Doctoral thesis, Université Laval, 2021. http://hdl.handle.net/20.500.11794/69494.
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Cette thèse, structurée en trois (03) essais, développe de nouveaux modèles économétriques pour l’analyse des interactions sociales et des séries temporelles. Le premier chapitre (coécrit avec le Professeur Vincent Boucher) étudie une méthode d’estimation des effets de pairs à travers les réseaux sociaux lorsque la structure du réseau n’est pas observée. Nous supposons que nous connaissons (avons une estimation convergente de) la distribution du réseau. Nous montrons que cette hypothèse est suffisante pour l’estimation des effets de pairs en utilisant un modèle linéaire en moyennes. Nous proposons un estimateur de variables instrumentales et un estimateur bayésien. Nous présentons et discutons des exemples importants où notre méthodologie peut être appliquée. Nous présentons également une application avec la base de données Add Health largement utilisée et qui comporte de nombreux liens non observés. Nous estimons un modèle des effets de pairs sur la réussite scolaire des élèves. Nous montrons que notre estimateur bayésien reconstruit les liens manquants et permet d’obtenir une estimation valide des effets de pairs. En particulier, nous montrons qu’ignorer les liens manquants sous-estime l’effet endogène des pairs sur la réussite scolaire. Dans le deuxième chapitre, je présente un modèle structurel des effets de pairs dans lequel la variable dépendante est de type comptage (nombre de cigarettes fumées, fréquence des visites au restaurant, fréquence de participation aux activités). Le modèle est basé sur un jeu statique à information incomplète dans lequel, les individus interagissent à travers un réseau dirigé et sont influencés par leur croyance sur la décision de leurs pairs. Je présente des conditions suffisantes sous lesquelles l’équilibre du jeu est unique. Je montre que l’utilisation du modèle spatial autorégressif (SAR) linéaire-en-moyennes ou du modèle Tobit SAR pour estimer les effets de pairs sur des variables de comptage générées à partir du jeu sous-estime asymptotiquement les effets de pairs. Le biais d’estimation diminue lorsque la dispersion de la variable de comptage augmente. Je propose également une application empirique. J’estime les effets de pairs sur le nombre d’activités parascolaires auxquelles les étudiants sont inscrits. En contrôlant l’endogénéité du réseau, je trouve que l’augmentation du nombre d’activités dans lesquelles les amis d’un étudiant sont inscrits d’une unité implique une augmentation du nombre d’activités dans lesquelles l’étudiant est inscrit de 0,295. Je montre également que les effets de pairs sont sous-estimés à 0,150 lorsqu’on ignore la nature de comptage de la variable dépendante. Le troisième chapitre (coécrit avec le Professeur Arnaud Dufays et le Professeur Alain Coen) présente une approche de modélisation de séries temporelles. Les processus avec changements structurels sont une approche flexible pour modéliser des longues séries chronologiques. En considérant un modèle linéaire en moyennes, nous proposons une méthode qui relâche l’hypothèse selon laquelle une cassure structurelle dans une série temporelle implique un changement de tous les paramètres du modèle. Pour ce faire, nous estimons d’abord les dates de cassures potentielles présentées par la série, puis nous utilisons une régression pénalisée pour détecter les paramètres du modèle qui changent à chaque date de cassure. Étant donné que certains segments de la régression peuvent être courts, nous optons pour une fonction de pénalité(presque) non biaisée, appelée fonction de pénalitéseamless-L0(SELO). Nous montrons que l’estimateur SELO détecte de manière convergente les paramètres qui varient à chaque cassure et nous proposons d’utiliser un algorithme de maximisation d’espérance de recuit déterministe(DAEM) pour traiter la multimodalité de la fonction objectif. Étant donné que la fonction de pénalité SELO dépend de deux paramètres, nous utilisons un critère pour choisir les meilleurs paramètres et par conséquent le meilleur modèle. Ce nouveau critère présente une interprétation bayésienne qui permet d’évaluer l’incertitude des paramètres ainsi que l’incertitude du modèle. Les simulations de Monte Carlo montrent que la méthode fonctionne bien pour de nombreux modèles de séries temporelles, y compris des processus hétéroscédastiques. Pour un échantillon de 14 stratégies de hedge funds (HF), utilisant un modèle de tarification basé sur l’actif, nous mettons en exergue la capacité prometteuse de notre méthode à détecter la dynamique temporelle des expositions au risque ainsi qu’à prévoir les rendements HF.<br>This dissertation, composed of three (03) separate chapters, develops new econometric modelsfor peer effects analysis and time series modelling.The first chapter (a joint work with Professor Vicent Boucher) studies a method for estimatingpeer effects through social networks when researchers do not observe the network structure. We assume that researchers know (a consistent estimate of) the distribution of the network. We show that this assumption is sufficient for the estimation of peer effects using a linear-in-means model. We propose an instrumental variables estimator and a Bayesian estimator. We present and discuss important examples where our methodology can be applied. We also present an application with the widely used Add Health database which presents many missing links. We estimate a model of peer effects on students’ academic achievement. We show that our Bayesian estimator reconstructs these missing links and leads to a valid estimate of peer effects. In particular, we show that disregarding missing links underestimates the endogenous peer effect on academic achievement. In the second chapter, I present a structural model of peer effects in which the dependent variable is counting (Number of cigarettes smoked, frequency of restaurant visits, frequency of participation in activities). The model is based on a static game with incomplete information in which individuals interact through a directed network and are influenced by their belief over the choice of their peers. I provide sufficient conditions under which the equilibrium of the game is unique. I show that using the standard linear-in-means spatial autoregressive (SAR) model or the SAR Tobit model to estimate peer effects on counting variables generated from the game asymptotically underestimates the peer effects. The estimation bias decreases when the range of the dependent counting variable increases. I estimate peer effects on the number of extracurricular activities in which students are enrolled. I find that increasing the number of activities in which a student’s friends are enrolled by one implies an increase in the number of activities in which the student is enrolled by 0.295, controlling for the endogeneity of the network. I also show that the peer effects are underestimated at 0.150 when ignoring the counting nature of the dependent variable. The third chapter (a joint work with Professor Arnaud Dufays and Professor Alain Coen) presents an approach for time series modelling. Change-point (CP) processes are one flexible approach to model long time series. Considering a linear-in-means models, we propose a method to relax the assumption that a break triggers a change in all the model parameters. To do so, we first estimate the potential break dates exhibited by the series and then we use a penalized likelihood approach to detect which parameters change. Because some segments in the CP regression can be small, we opt for a (nearly) unbiased penalty function, called the seamless-L0 (SELO) penalty function. We prove the consistency of the SELO estimator in detecting which parameters indeed vary over time and we suggest using a deterministic annealing expectation-maximisation (DAEM) algorithm to deal with the multimodality of the objective function. Since the SELO penalty function depends on two tuning parameters, we use a criterion to choose the best tuning parameters and as a result the best model. This new criterion exhibits a Bayesian interpretation which makes possible to assess the parameters’ uncertainty as well as the model’s uncertainty. Monte Carlo simulations highlight that the method works well for many time series models including heteroskedastic processes. For a sample of 14 Hedge funds (HF) strategies, using an asset based style pricing model, we shed light on the promising ability of our method to detect the time-varying dynamics of risk exposures as well as to forecast HF returns.
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Zhu, Chuanqi. "Essays on macroeconometrics." Thesis, Boston College, 2013. http://hdl.handle.net/2345/bc-ir:104398.
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Thesis advisor: Zhijie Xiao<br>This dissertation contains three chapters in theoretical Macroeconometrics and applied Macroeconometrics. This first chapter addresses the issues related to the estimation, testing and computation of ordered structural breaks in multivariate linear regressions. Unlike common breaks, ordered structural breaks are those breaks that are related across equations but not necessarily occurring at the same dates. A likelihood ratio test assuming normal errors is proposed in this chapter in order to detect the ordered structural breaks in multivariate linear regressions. The estimation of ordered structural breaks uses quasi-maximum likelihood and adopts the efficient algorithm of Bai and Perron (2003). I also provide results about the consistency and rate of convergence when searching for ordered structural breaks. Finally, these methods are applied to one empirical example: the mean growth rate of output in three European countries and United States. This second chapter focuses on the parameter stability of dynamic stochastic general equilibrium (DSGE) models. To this end, I solve and estimate a representative New Keynesian model using both linear and nonlinear methods. I first examine how nonlinearities affect the parameter stability of the New Keynesian model. The results show that parameter instabilities still exist even using nonlinear solutions, and also highlight differences between two nonlinear solution methods: perturbation method and projection method. In addition, I propose a sequential procedure for searching for multiple structural breaks in nonlinear models, and apply it to the New Keynesian model. Two common structural breaks among these estimated parameters are identified for all the five solutions considered in this chapter. One structural break is in the early 1970s, while another one locates around the middle 1990s. In the third chapter, we investigate changes in long run productivity growth in the United States. In particular, we approach productivity growth from a sectoral perspective, and decompose the whole economy into two broad sectors: investment goods-producing sector and consumption goods-producing sector. Although the evidence of changes in the aggregate productivity growth is far from obvious at conventional test size, we find evidence of structural breaks in the sectoral productivity growth using both growth accounting and DSGE model based measures. There are two structural breaks in investment goods-producing sector using growth accounting measures, which indicates that the era of investment and productivity boom in the middle 1990s may have ended before the Great Recession. In addition, our results show there is one structural break in consumption goods-producing sector around the 1970s and attribute the aggregate productivity slowdown at that time to consumption goods-producing sector. These results are broadly consistent with Ireland and Schuh (2008). Our results offer up with a modestly pessimistic outlook on future productivity growth and, therefore, potential output<br>Thesis (PhD) — Boston College, 2013<br>Submitted to: Boston College. Graduate School of Arts and Sciences<br>Discipline: Economics
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Sögner, Leopold. "Okun's Law. Does the Austrian unemployment-GDP relationship exhibit structural breaks?" SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/1446/1/document.pdf.
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Okun's Law postulates an inverse relationship between movements of the unemployment rate and the real gross domestic product (GDP). Empirical estimates for US data indicate that a two to three percent GDP growth rate above the natural or average GDP growth rate causes unemployment to decrease by one percentage point and vice versa. In this investigation we check whether this postulated relationship exhibits structural breaks by means of Markov-Chain Monte Carlo methods. We estimate a regression model, where the parameters are allowed to switch between different states and the switching process is Markov. As a by-product we derive an estimate of the current state within the periods considered. Using quarterly Austrian data on unemployment and real GDP from 1977 to 1995 we infer only one state, i.e. there are no structural breaks. The estimated parameters demand for an excess GDP growth rate of 4.16% to decrease unemployment by one percentage point. Since only one state is inferred, we conclude that the Austrian economy exhibits a stable relationship between unemployment and GDP growth. (author's abstract)<br>Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
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Santos, Carlos. "Structural breaks and outliers in economic time series : modelling and inference." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433296.
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Han, Lu. "Statistical analysis of structural breaks in discrete valued time series processes." Thesis, University of Liverpool, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539614.
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White, Sava P. "Thermo-mechanical modeling of thermal breaks in structural steel point transmittances." Thesis, University of Alaska Anchorage, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10103669.
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<p> Thermal bridging through structural steel members in building envelopes poses issues with heat loss and condensation in cold regions. Structural steel thermal breaks, taking the form of low-thermal conductivity, high-strength and stiffness materials placed between the faying surfaces of a steel connection, serve to reduce heat flow through the steel element and have seen extensive use in the construction industry. However, current steel construction code provisions in the US prohibit the use of compressible materials in a steel connection. While the practical benefits of thermal breaks in structural steel beams and columns have been well demonstrated, there is a lack of guidance on the structural design of these thermal breaks, as well as a yet undetermined thermal efficacy of thermal break design parameters.</p><p> The objective of this thesis was to determine the thermal and mechanical behavior of structural steel beam thermally broken connections and continuous beam thermal bridges. Heat flow through a thermally broken steel end-plate connection was determined experimentally using a calibrated hot box. Results were used to validate a finite element heat transfer model, which was used to perform a parametric analysis on the thermal break using different break and bolt materials. From the analyses, it was determined that the thickness of the break is effective in reducing heat flow and condensation potential. The use of stainless steel or fiber-reinforced bolts provides a significant reduction in heat flow and condensation potential. The mechanical behavior of the thermally-broken connection was analyzed using cantilever bending tests and shear tests on an identical set of connections using three different thicknesses of neoprene pad. Results showed that the rotational stiffness of the connection was reduced approximately linearly with increasing neoprene pad thickness. Shear deflection stiffness was reduced exponentially with increased pad thickness. Structural experimental results were validated against a finite element model which was used to investigate stresses in the end-plate and the bolt. Bolt rupture was found to occur at a reduced applied bending moment due to the increased rotation of the end-plate due to the soft intermediate layer of neoprene between the end-plate and the connection member.</p>
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Banafea, Waheed A. "Essays on structural breaks and stability of the money demand function." Diss., Kansas State University, 2012. http://hdl.handle.net/2097/14869.
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Doctor of Philosophy<br>Department of Economics<br>Steven P. Cassou<br>This dissertation consists of three chapters. The first chapter surveys recent studies on the stability of the money demand function in selected developing countries. This chapter presents specific details about modeling and estimating the money demand function. Also, reasons behind the mixed results in the literature on the stability of the money demand function are explored as well as providing a guideline for future research on the stability of the money demand function in developing countries.
The second chapter empirically investigates the stability of the money demand function in South Korea and Malaysia. The conventional money demand specification and cointegration framework with a single unknown structural break are conducted. The results of the residual-based tests for cointegration reveal that the M1, M2, and M3 demand are stable in the long run in Malaysia. However, there is no evidence of the stability for all three measures of the money demand in South Korea. The results of the residual-based tests suggest that structural breaks in the cointegration vectors are important and need to be accounted for in the specification of the M1, M2, and LF demand in South Korea, where LF includes M2 in addition to the reserves of nonbanking financial institutions and long-term deposits.
The third chapter complements the previous chapter. It aims to evaluate the stability of the money demand function in South Korea and Malaysia using a cash in advance model and cointegration framework with one unknown structural break. This theoretical model adds short-term foreign interest rates and real exchange rates in addition to short-term domestic interest rates and real income. Also, the Granger causality and currency substitution analysis are conducted in this chapter. The results of the residuals-based tests indicate that the M2 and LF demand in South Korea, and M1, M2, and M3 demand in Malaysia are stable in the long run. The structural breaks may not be fairly absorbed when a cash in advance model is used for M1 in South Korea. Thus, the residual-based tests suggest that the structural break is still important and needs to be included in the specification of the M1 demand in South Korea.
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Mazlan, Nur Syazwani. "A study of the dynamics of structural breaks in real time." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.681544.
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This thesis explores the real-time dynamics of learning about breaks by utilising different datasets, i.e. simulated and actual (aggregate and firm-level). I am interested in the real-time identification because of its relevance for forecasting. Essentially, I raise three main empirical questions: How often do we encounter mistakes in real-time identification of breaks? How soon do mistakes get corrected in real time? How soon do we learn about the breaks in real time? I compare the effectiveness of different break models and techniques for optimal (discrete) break identification. I find that mistakes are encountered when the true breaks are not observed and when the breaks that are not the true breaks are observed in real time. By using simulated and (actual) aggregate-level datasets for the processes related to the growth rate, mistakes are encountered more often for the break model of unit root. As for the (actual) firm-level dataset of dividend series of (selected) V .S. firms, I observe that mistakes are encountered more often for the break model of trend stationary. Consistently, sequential hypothesis testing for optimal breaks are shown to make fewer mistakes compared to the information criteria used in this study. Moreover, I show that it takes several years to find the true breaks and the collection time for mistakes is usually less than a year. The learning time about the breaks and correction time for mistakes in real time are shown to be longer for the unit root model in the processes related to the growth rate for simulated and (actual) aggregate-level datasets. For the firm-level dataset, the learning and correction time are longer for the trend stationary model in the quarterly compounded process of the firm-level dividend. The learning and correction time by sequential hypothesis testing for optimal breaks are consistently shown to be shorter compared to the information criteria.
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Altansukh, Gantungalag. "International inflation linkages and forecasting in the presence of structural breaks." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/international-inflation-linkages-and-forecasting-in-the-presence-of-structural-breaks(bee20ed1-6af2-4b8b-a199-5f3b445d07db).html.
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This PhD thesis consists of three related chapters; each contributes to the study of inflation dynamics by examining different issues that have previously been raised in the relevant literature. In particular, the first chapter is concerned with the nature of different changes that have taken place in the conditional mean and variance of inflation. To shed light on this question, an iterative structural break testing methodology is developed which allows the possibility of distinct changes in the conditional mean and variance components by iterating tests between them, with outliers also identified in relation to regimes. This methodology is applied to models that link domestic and foreign inflation, and uncovers a positive and strengthening contemporaneous relationship between domestic and foreign inflation, adding to the literature that provides evidence of increasing globalization of inflation. The second chapter sheds further light on the nature of the globalization of inflation by separating core, energy and food components of aggregate inflation, analyzing changes in the international links in these separate components. Comparison with the aggregate inflation reveals that the overall globalization is driven largely by the mean levels of core inflation being very similar across countries, especially from the early 1990s. Further, an increased synchronization of short-run movements in non-core (energy and food) components contribute to the overall globalization effect, but such short-run synchronization is less evident in core inflation. The first and second chapters show that structural breaks either in the conditional mean or variance parameters of inflation are a common feature. Therefore, the third chapter focuses on the problem of forecasting in the presence of structural breaks. Specifically, chapter 3 proposes a forecast method which allows for break date uncertainty by employing a confidence interval estimate of the break date. A Monte Carlo simulation study and an empirical application to inflation time series demonstrate the usefulness of this approach. This chapter also proposes an algorithm that re-orders time series data based on the similarity of regimes. It is shown that such re-ordering can improve forecast accuracy when estimation exploits the additional information provided by the re-ordered series. These improvements are significant when there are multiple breaks which have the form of reverting coefficients.
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Asare, Nyamekye. "Essays on Time-Varying Volatility and Structural Breaks in Macroeconomics and Econometrics." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37179.
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This thesis is comprised of three independent essays. One essay is in the field of macroeconomics and the other two are in time-series econometrics. The first essay, "Productivity and Business Investment over the Business Cycle", is co-authored with my co-supervisor Hashmat Khan. This essay documents a new stylized fact: the correlation between labour productivity and real business investment in the U.S. data switching from 0.54 to -0.1 in 1990. With the assistance of a bivariate VAR, we find that the response of investment to identified technology shocks has changed signs from positive to negative across two sub-periods: ranging from the time of the post-WWII era to the end of 1980s and from 1990 onwards, whereas the response to non-technology shocks has remained relatively unchanged. Also, the volatility of technology shocks declined less relative to the non-technology shocks. This raises the question of whether relatively more volatile technology shocks and the negative response of investment can together account for the decreased correlation. To answer this question, we consider a canonical DSGE model and simulate data under a variety of assumptions about the parameters representing structural features and volatility of shocks. The second and third essays are in time series econometrics and solely authored by myself. The second essay, however, focuses on the impact of ignoring structural breaks in the conditional volatility parameters on time-varying volatility parameters. The focal point of the third essay is on empirical relevance of structural breaks in time-varying volatility models and the forecasting gains of accommodating structural breaks in the unconditional variance. There are several ways in modeling time-varying volatility. One way is to use the autoregressive conditional heteroskedasticity (ARCH)/generalized ARCH (GARCH) class first introduced by Engle (1982) and Bollerslev (1986). One prominent model is Bollerslev (1986) GARCH model in which the conditional volatility is updated by its own residuals and its lags. This class of models is popular amongst practitioners in finance because they are able to capture stylized facts about asset returns such as fat tails and volatility clustering (Engle and Patton, 2001; Zivot, 2009) and require maximum likelihood methods for estimation. They also perform well in forecasting volatility. For example, Hansen and Lunde (2005) find that it is difficult to beat a simple GARCH(1,1) model in forecasting exchange rate volatility. Another way of modeling time-varying volatility is to use the class of stochastic volatility (SV) models including Taylor's (1986) autoregressive stochastic volatility (ARSV) model. With SV models, the conditional volatility is updated only by its own lags and increasingly used in macroeconomic modeling (i.e.Justiniano and Primiceri (2010)). Fernandez-Villaverde and Rubio-Ramirez (2010) claim that the stochastic volatility model fits better than the GARCH model and is easier to incorporate into DSGE models. However, Creal et al. (2013) recently introduced a new class of models called the generalized autoregressive score (GAS) models. With the GAS volatility framework, the conditional variance is updated by the scaled score of the model's density function instead of the squared residuals. According to Creal et al. (2013), GAS models are advantageous to use because updating the conditional variance using the score of the log-density instead of the second moments can improve a model's fit to data. They are also found to be less sensitive to other forms of misspecification such as outliers. As mentioned by Maddala and Kim (1998), structural breaks are considered to be one form of outliers. This raises the question about whether GAS volatility models are less sensitive to parameter non-constancy. This issue of ignoring structural breaks in the volatility parameters is important because neglecting breaks can cause the conditional variance to exhibit unit root behaviour in which the unconditional variance is undefined, implying that any shock to the variance will not gradually decline (Lamoureux and Lastrapes, 1990). The impact of ignoring parameter non-constancy is found in GARCH literature (see Lamoureux and Lastrapes, 1990; Hillebrand, 2005) and in SV literature (Psaradakis and Tzavalis, 1999; Kramer and Messow, 2012) in which the estimated persistence parameter overestimates its true value and approaches one. However, it has never been addressed in GAS literature until now. The second essay uses a simple Monte-Carlo simulation study to examine the impact of neglecting parameter non-constancy on the estimated persistence parameter of several GAS and non-GAS models of volatility. Five different volatility models are examined. Of these models, three --the GARCH(1,1), t-GAS(1,1), and Beta-t-EGARCH(1,1) models -- are GAS models, while the other two -- the t-GARCH(1,1) and EGARCH(1,1) models -- are not. Following Hillebrand (2005) who studied only the GARCH model, this essay examines the extent of how biased the estimated persistence parameter are by assessing impact of ignoring breaks on the mean value of the estimated persistence parameter. The impact of neglecting parameter non-constancy on the empirical sampling distributions and coverage probabilities for the estimated persistence parameters are also studied in this essay. For the latter, studying the effect on the coverage probabilities is important because a decrease in coverage probabilities is associated with an increase in Type I error. This study has implications for forecasting. If the size of an ignored break in parameters is small, then there may not be any gains in using forecast methods that accommodate breaks. Empirical evidence suggests that structural breaks are present in data on macro-financial variables such as oil prices and exchange rates. The potentially serious consequences of ignoring a break in GARCH parameters motivated Rapach and Strauss (2008) and Arouri et al. (2012) to study the empirical relevance of structural breaks in the context of GARCH models. However, the literature does not address the empirical relevance of structural breaks in the context of GAS models. The third and final essay contributes to this literature by extending Rapach and Strauss (2008) to include the t-GAS model and by comparing its performance to that of two non-GAS models, the t-GARCH and SV models. The empirical relevance of structural breaks in the models of volatility is assessed using a formal test by Dufour and Torres (1998) to determine how much the estimated parameters change over sub-periods. The in-sample performance of all the models is analyzed using both the weekly USD trade-weighted index between January 1973 and October 2016 and spot oil prices based on West Texas Intermediate between January 1986 and October 2016. The full sample is split into smaller subsamples by break dates chosen based on historical events and policy changes rather than formal tests. This is because commonly-used tests such as CUSUM suffer from low power (Smith, 2008; Xu, 2013). For each sub-period, all models are estimated using either oil or USD returns. The confidence intervals are constructed for the constant of the conditional parameter and the score parameter (or ARCH parameter in GARCH and t-GARCH models). Then Dufour and Torres's union-intersection test is applied to these confidence intervals to determine how much the estimated parameter change over sub-periods. If there is a set of values that intersects the confidence intervals of all sub-periods, then one can conclude that the parameters do not change that much. The out-of-sample performance of all time-varying volatility models are also assessed in the ability to forecast the mean and variance of oil and USD returns. Through this analysis, this essay also addresses whether using models that accommodate structural breaks in the unconditional variance of both GAS and non-GAS models will improve forecasts.
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Yen, Meng-Feng. "GARCH modelling and forecasting in the context of structural breaks or periodicities." Thesis, University of Reading, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431031.
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Bergamelli, Michele. "Structural breaks and outliers detection in time-series econometrics : methods and applications." Thesis, City University London, 2015. http://openaccess.city.ac.uk/14868/.
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This thesis contributes to the econometric literature on structural breaks analysis and outliers detection in parametric linear models. The focus is on the development of new econometric tools as well as on the analysis of novel but largely unexplored approaches. The econometric methods under analysis are illustrated using macroeconomic and financial relationships. The thesis is organised in three main chapters. In Chapter 2, we consider two novel methods to detect multiple structural breaks affecting the deterministic component of a linear system. The first is an extension of the dummy saturation method whereas the second method deals with a sequential bootstrapping procedure based on the sup-F statistic. Through an extensive Monte Carlo exercise, we explore the ability of the two approaches to detect the correct number and the correct location of the breaks. Additionally, we illustrate how to apply empirically the two procedures by investigating the stability of the Fisher relationship in the United States. In Chapter 3, we consider testing for multiple structural breaks in the vector error correction framework. First, we study the role of weak exogeneity when testing for structural breaks in the cointegrating matrix. Second, we extend the existing likelihood ratio test of Hansen (2003) to the case of unknown break dates through the specification of a minimum p-value statistic with critical values approximated by bootstrapping. Monte Carlo simulations show that the proposed statistic has good finite sample properties whilst three small empirical applications illustrate how the minimum p-value statistic can be used in practice. In Chapter 4, we tackle the purchasing power parity puzzle developing a robust estimator for the half-life of the real exchange rate. Specifically, we propose to identify outlying observations by means of a dummy saturation type algorithm designed for ARMA processes which enables to detect additional and innovative outliers as well as level shifts. An empirical application involving US dollar real exchange rates shows that the estimated half-lives are considerably shorter when outlying observations are correctly modelled, therefore shedding some light on the purchasing power parity puzzle.
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Cardosa, João. "Health expenditures in the OECD: a political economy analysis using structural breaks." Master's thesis, NSBE - UNL, 2010. http://hdl.handle.net/10362/11847.
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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics<br>We write this paper with the main purpose of investigating whether or not political factors influence the structural changes in health expenditure. We are not concerned about shocks as most researchers do; but instead we search for significant structural break dates and try to find a correlation between them and political changes. We choose to study health expenditure due to its relevance in terms of share on GDP and share on public expenditure and because of the continuous growth it shows over the last decades. We use probit models for our
empirical tests. Public health expenditure share on GDP is found to have a statistically significant higher probability of breaking in election years which is a
clear indication of possible political effects. By opposition break dates on Private
health expenditure share on GDP show no correlation with elections. In addition,
the probability of occurrence of breaks in public current health expenditure
significantly increases in election years and the coefficients are higher and more
significant in this case than the case of total public health expenditure. However,
this is not verified in investment expenditure which means that elections seem to have a higher impact on short term expenses. Majority governments show a
lesser probability of inducing breaks during their term in office but a higher probability before elections. Although we sometimes found statistically significant differences depending on the ideology of the respective government (i.e. left or right) we failed to achieve consistent and coherent results to allow us to establish a clear conclusion. We based our study on a data set of 23 OECD countries between the years 1960 and 2006.
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Wessollek, Christine, and Pierre Karrasch. "Monitoring structural breaks in vegetation dynamics of the nature reserve Königsbrücker Heide." SPIE, 2017. https://tud.qucosa.de/id/qucosa%3A34984.
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Nowadays remote sensing is a well-established method and technique of providing data. The current development shows the availability of systems with very high geometric resolution for the monitoring of vegetation. At the same time, however, the value of temporally high-resolution data is underestimated, particularly in applications focusing on the detection of short-term changes. These can be natural processes like natural disasters as well as changes caused by anthropogenic interventions. These include economic activities such as forestry, agriculture or mining but also processes which are intended to convert previously used areas into natural or near-natural surfaces. The Königsbrücker Heide is a former military training site located about 30 km north of the Saxon state capitol Dresden. After the withdrawal of the Soviet forces in 1992 and after nearly 100 years of military use this site was declared as nature reserve in 1996. The management of the whole protection area is implemented in three different management zone. Based on MODIS-NDVI time series between 2000 and 2016 different developments are apparent in the nature development zone and the zone of controlled succession. Nevertheless, the analyses also show that short-term changes, so called breaks in the vegetation development cannot be described using linear trend models. The complete understanding of vegetation trends is only given if discontinuities in vegetation development are considered. Structural breaks in the NDVI time series can be found simultaneously in the whole study area. Hence it can be assumed that these breaks have a more natural character, caused for example by climatic conditions like temperature or precipitation. Otherwise, especially in the zone of controlled succession structural breaks can be detected which cannot be traced back to natural conditions. Final analyses of the spatial distribution of breakpoints as well as their frequency depending on the respective protection zone allow a detailed view to vegetation development in the Köonigsbrüucker Heide.
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Rönningsberg, Olle, and Hove Sander ten. "COVID-19 and structural breaks : The case of the Swedish Housing Market." Thesis, Högskolan Dalarna, Institutionen för information och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-37703.
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This paper analyzes how the COVID-19 pandemic has affected the Swedish housing market, and in particular prices and shifts in trends. Different classes of housing objects in various counties are investigated. Combining web scraped housing data for the entirety of Sweden between 2016-01-01 and 2021-03-31, including economic, demographic, socioeconomic and locational data, a hedonic regression model is used to estimate how different variables influence the housing price. The base model is subsequently used to investigate if statistically significant structural breaks exist in relation to the COVID-19 pandemic for the different object types in the entire Swedish market and in certain specific counties. Structural breaks are found for the housing object types ‘Fritidshus’, ‘Lägenhet’ and ‘Radhus’ in the entire Swedish market and for “Villa” in Stockholm county shortly after the pandemic outbreak, suggesting there is evidence for a pandemic infused shift in housing price regime on the Swedish housing market for these object types in stated areas. Splitting the hedonic regression model into three, one pooled regression, one before and one after the identified breaks, and comparing the shifts in impact of the housing price determinants suggests different pandemic effects on different object types. The result indicates that for the object types ‘Lägenhet’ in the entire country and for ‘Villa’ in Stockholm county, living area has an increased impact on the price while the locational variable population density has a decreased impact after the breakpoint date compared to before. This could suggest that for permanent housing objects in these regions, living area might have become increasingly valued over location during the pandemic. The results further indicate the direct opposite effect on the shifted impact in living area and the population density for the price of the temporary housing type Fritidshus in entire Sweden. However, an indication for increased impact of the areas socioeconomic level is noted for all these three object types. These results hold as a ground for further research in the subject.
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Khalil, Ashraf. "ATM-Dependent ERK Signaling in Response to DNA Double Strand Breaks." VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/760.
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Ionizing radiation (IR) triggers many signaling pathways stemming from DNA damage, and, independently, from extra-nuclear events. To generate radio-mimetic DNA double-strand breaks (DSBs) without and minimizing the effects on extra-nuclear radiation targets, human (p53+) glioma and carcinoma cells containing bromodeoxyuridine (BrdU)- substituted DNA were treated with Hoechst 33258 followed by long wave-length UV (UV-A) (BrdU photolysis). BrdU photolysis resulted in well-controlled, dose-dependent generation of DSBs equivalent to 0.2 - 20 Gy of IR, as detected by pulse-field gel electrophoresis, accompanied by dose-dependent H2AX phosphorylation at ser-139 and ATM phosphorylation at ser-1981, indicating ATM activation. Furthermore, BrdU photolysis increased phosphorylation of Chk2 (at thr-68) and p53 (at ser-15). p53 phosphorylation was reduced by the ATM inhibitor caffeine, and H2AX phosphorylation was greatly reduced in AT cells, confirming that phosphorylation was primarily ATM-dependent. We also examined the effects of BrdU photolysis on the major cellular signaling ERK pathways. Interestingly, low-dose (≤ 2 Gy-equivalents) BrdU photolysis stimulated ERK1/2 phosphorylation whereas higher doses (≥ 5 Gy eq.) resulted in Em1/2 dephosphorylation. ERK1/2 phosphorylation was ATM-dependent, whereas dephosphorylation was ATM-independent and DSBs dose-dependent. Thus ERK1/2 appear to be both positively and negatively regulated by ATM depending on the severity of the insult to DNA. In summary, few DSBs trigger ATM-dependent ERK1/2 pro-survival signals whereas more DSBs result in ERK1/2 dephosphorylation consistent with a switch from pro-survival to anti-survival signaling that might affect DSBs repair.
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Cai, Xinhua. "Froecast the USA Stock Indices with GARCH-type Models." Thesis, Uppsala universitet, Statistiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-175432.
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Rea, William Stanley. "The Application of Atheoretical Regression Trees to Problems in Time Series Analysis." Thesis, University of Canterbury. Mathematics and Statistics, 2008. http://hdl.handle.net/10092/1715.
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This thesis applies Atheoretical Regression Trees (ART) to the
problem of locating changes in mean in a time series where the
number and location of those changes are unknown. We undertook
an extensive simulation study into ART's performance on a range
of time series. We found ART to be a useful addition to currently
established structural break methodologies such as the CUSUM and
that due to Bai and Perron. ART was found to be useful in the
analysis of long time series which are not practical to analyze
with the optimal procedure of Bai and Perron.
ART was applied to a long standing problem in the analysis of
long memory time series.
We propose two new methods based on ART
for distinguishing between true long memory
and spurious long memory due to structural breaks. These methods
are fundamentally different from current tests and procedures
intended to discriminate between the two sets of competing
models.
The methods were
subjected to a simulation study and shown to be effective in
discrimination between simple regime switching models and
fractionally integrated processes.
We applied the new methods to 16 realized volatility series and
concluded they were not fractionally integrated series. All 16
series had mean shifts, some of which could be identified with
historical events.
We applied the new methods to a range of geophysical time series
and concluded they were not fractional Gaussian noises. All
of the series examined had mean shifts, some of which could
be identified with known climatic changes.
We conclude that our new methods are a significant advance in
model discrimination in long memory series.
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Wegener, Christoph [Verfasser]. "Essays on empirical finance in times of crises : fractional integration, structural breaks, and explosiveness / Christoph Wegener." Hannover : Technische Informationsbibliothek (TIB), 2016. http://d-nb.info/1122040881/34.
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Huber, Florian. "Structural breaks in Taylor rule based exchange rate models - Evidence from threshold time varying parameter models." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5461/1/wp244.pdf.
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In this note we develop a Taylor rule based empirical exchange rate model for eleven major currencies that endogenously determines the number of structural breaks in the coefficients. Using a constant parameter specification and a standard time-varying parametermodel as competitors reveals that our flexible modeling framework yields more precise density forecasts for all major currencies under scrutiny over the last 24 years.<br>Series: Department of Economics Working Paper Series
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Yfanti, Stavroula. "Non-linear time series models with applications to financial data." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/9247.
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The purpose of this thesis is to investigate the financial volatility dynamics through the GARCH modelling framework. We use univariate and multivariate GARCH-type models enriched with long memory, asymmetries and power transformations. We study the financial time series volatility and co-volatility taking into account the structural breaks detected and focusing on the effects of the corresponding financial crisis events. We conclude to provide a complete framework for the analysis of volatility with major policy implications and benefits for the current risk management practices. We first investigate the volume-volatility link for different investor categories and orders, around the Asian crisis applying a univariate dual long memory model. Our analysis suggests that the behaviour of volatility depends upon volume, but also that the nature of this dependence varies with time and the source of volume. We further apply the vector AR-DCC-FIAPARCH and the UEDCC-AGARCH models to several stock indices daily returns, taking into account the structural breaks of the time series linked to major economic events including crisis shocks We find significant cross effects, time-varying shock and volatility spillovers, time-varying persistence in the conditional variances, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks and the power of returns that best fits the volatility pattern. We observe higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets, a continuous herding investors’ behaviour, as the in-crisis correlations remain high, and a higher level of correlations during the recent financial crisis than during the Asian. Finally, we study the High-frEquency-bAsed VolatilitY (HEAVY) models that combine daily returns with realised volatility. We enrich the HEAVY equations through the HYAPARCH formulation to propose the HYDAP-HEAVY (HYperbolic Double Asymmetric Power) and provide a complete framework to analyse the volatility process.
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Ullmann, Daniel [Verfasser], Peter [Akademischer Betreuer] Posch, and Walter [Gutachter] Krämer. "Essays in finance: aggregating distributions and detecting structural breaks / Daniel Ullmann ; Gutachter: Walter Krämer ; Betreuer: Peter Posch." Dortmund : Universitätsbibliothek Dortmund, 2017. http://d-nb.info/1150960620/34.
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Ullmann, Daniel [Verfasser], Peter N. [Akademischer Betreuer] Posch, and Walter [Gutachter] Krämer. "Essays in finance: aggregating distributions and detecting structural breaks / Daniel Ullmann ; Gutachter: Walter Krämer ; Betreuer: Peter Posch." Dortmund : Universitätsbibliothek Dortmund, 2017. http://d-nb.info/1150960620/34.
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Wingert, Simon [Verfasser]. "Essays on long memory estimation and testing for structural breaks under long-range dependent errors / Simon Wingert." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2020. http://d-nb.info/1214367062/34.
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Marczak, Martyna [Verfasser], and Thomas [Akademischer Betreuer] Beissinger. "Four essays in the empirical analysis of business cycles and structural breaks / Martyna Marczak. Betreuer: Thomas Beißinger." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2015. http://d-nb.info/1069159743/34.
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Muhsal, Birte Chantal Simone [Verfasser]. "Change-Point Methods for Multivariate Autoregressive Models and Multiple Structural Breaks in the Mean / Birte Chantal Simone Muhsal." Karlsruhe : KIT-Bibliothek, 2013. http://d-nb.info/1036681300/34.
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Ferreira, Tiago Toledo. "Arranjos institucionais e investimento em infra-estrutura no Brasil." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/12/12140/tde-30012010-162648/.
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Ao recuperar dados da década de 60 ao momento atual, o estudo acompanha a evolução do investimento no setor sob diferentes arranjos institucionais. A análise é circunscrita aos segmentos rodoviário, ferroviário, energia elétrica e telecomunicações. As séries são submetidas a testes econométricos propostos em Bai e Perron (1998, 2003b) que, em última instância, procuram identificar eventuais quebras estruturais, associando-as às mudanças institucionais. As quebras encontradas demarcam o ápice e o esgotamento do padrão anterior de organização do setor. Apenas no segmento de telecomunicações é encontrada quebra relacionada ao novo arranjo setorial. Além de acompanhar a evolução dos segmentos abordados, o trabalho apresenta base conceitual para fundamentar a análise dos fenômenos ocorridos nos últimos anos.<br>This work follows the investment evolution in the infrastructure sector since the 60s. The investigated series are subjected to econometric tests proposed by Bai and Perron (1998, 2003b) that, ultimately, seek to identify possible structural breaks and try to link them to institutional changes. The follow segments were: road, rail, electric power and telecommunications. The tests found breaks related to the peak and the collapse of the former arrangement reforms, respectively in mid-70s and in late 80s. The only break associated with recent changes was found in the telecommunications segment. Additionally, this work presents conceptual basis to support the analysis of the recent developments in the infrastructure sector.
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Jiang, Yu. "Inference and prediction in a multiple structural break model of economic time series." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/244.
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This thesis develops a new Bayesian approach to structural break modeling. The focuses of the approach are the modeling of in-sample structural breaks and forecasting time series allowing out-of-sample breaks. Our model has some desirable features. First, the number of regimes is not fixed and is treated as a random variable in our model. Second, our model adopts a hierarchical prior for regime coefficients, which allows for the regime coefficients of one regime to contain information about regime coefficients of other regimes. However, the regime coefficients can be analytically integrated out of the posterior distribution and therefore we only need to deal with one level of the hierarchy. Third, the implementation of our model is simple and the computational cost is low. Our model is applied to two different time series: S&P 500 monthly returns and U.S. real GDP quarterly growth rates. We linked breaks detected by our model to certain historical events.
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Pouliot, William. "Two applications of U-Statistic type processes to detecting failures in risk models and structural breaks in linear regression models." Thesis, City University London, 2010. http://openaccess.city.ac.uk/1166/.
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This dissertation is concerned with detecting failures in Risk Models and in detecting structural breaks in linear regression models. By applying Theorem 2.1 of Szyszkowicz on U-statistic type process, a number of weak convergence results regarding three weighted partial sum processes are established. It is shown that these partial sum processes share certain invariance properties; estimation risk does not affect their weak convergence results and they are also robust to asymmetries in the error process in linear regression models. There is also an application of the methods developed here to a four factor Capital Asset Pricing model where it is shown via the methods developed in Chapter 3 that manager stock selection abilities vary over time.
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Reckrühm, Kerstin [Verfasser], and Claudia [Gutachter] Kirch. "Estimating multiple structural breaks in time series - a generalized MOSUM approach based on estimating functions / Kerstin Reckrühm ; Gutachter: Claudia Kirch." Magdeburg : Universitätsbibliothek Otto-von-Guericke-Universität, 2019. http://d-nb.info/121996638X/34.
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Grote, Claudia [Verfasser]. "Essays on testing for nonlinearity in time series : issues in nonlinear cointegration, structural breaks and changes in persistence / Claudia Grote." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2020. http://d-nb.info/1208387936/34.
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Granemark, Elin. "Minskar införandet av skattetillägg benägenheten att begå skattebrott? : En tidsseriestudie om vilken effekt skattetillägg har på självrättelser av inkomstdeklarationer." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-449070.
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Vilken effekt har skattetillägg på självrättelser av inkomstdeklarationer för individers benägenhet att begå skattebrott? Enligt grundteorin inom 'economics of crime' bör benägenheten att begå skattebrott minska för en rationell individ av en ökad sannolikhet och kostnad att bli straffad. Studien är en tidsseriestudie som undersöker beteendeförändringar av individers självrättelser av sina inkomstdeklarationer i samband med införandet av skattetillägg som tillkom av Skatteförfarandelagens (2011:1244) reform år 2018. Studien finner statistiskt signifikanta 'structural breaks' år 2019 (med hänsyn till 'first lag') vilket indikerar på ett förändrat beteendemönster i samband med införandet av skattetillägget. Andra faktorer kan dock inte uteslutas.
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Hellsten, Mark. "GDP per capita and the privatization of copper mines in Zambia : a time series analysis of unit root with structural breaks." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-80704.
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Tran, Amy V. "Do BHA and BHT Induce Morphological Changes and DNA Double-Strand Breaks in Schizosaccharomyces pombe?" Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/scripps_theses/152.
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Butylated Hydroxyanisole, BHA, and Butylated Hydroxytoluene, BHT, are commonly used as preservatives for our food as well as additives in many products such as cosmetics, petroleum, and medicine. Although their use has been approved by the Food and Drug Administration (FDA), there have been controversies and debates on whether these phenol derivatives or antioxidants are safe to use. Their accumulative toxicology and side effects need to be thoroughly investigated as we continue to consume them on a daily basis. Data obtained by genomic analysis in Tang lab suggested the involvement of DNA damage checkpoint/repair pathways in the response network to these phenol stress factors. The aims of this thesis are to examine the morphological changes and potential DNA damage induced by exposing cells to BHA and BHT using fission yeast Schizosaccharomyces pombe as a model organism. Fluorescence microscopy was used to assess DNA double-strain breaks (DSBs) by monitoring the nuclear foci formation of Rad22, a DNA repair protein, in the presence of BHA and BHT. Changes in cell morphology were also studied under microscope. Preliminary data showed that cells treated with BHA and BHT exhibited morphological changes. In addition, for the first time in S. pombe cells, Rad22 foci in the nucleus of BHA and BHT treated cells were observed. Further investigation is needed to optimal the experimental condition to continue the study. These results will not only help us to better understand the effect of these phenol derivatives in the cells, but can also establish an experimental system for future studies on the interaction of the cells with stress factors and therapeutic drugs for human-related diseases such as cancer.
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Schuler, Eric Robert. "When the Levee Breaks: An SEM Approach to Understanding the Narrative and the Anxiety-Buffer Disruption on PTSD Symptoms." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984252/.
Full textAbstract:
The purpose of the present study was to assess if combining the two frameworks would account for more variance in PTSS than could be accounted for using the frameworks separately. An online community sample from Amazon.com's Mechanical Turk (N = 437), who reported experiencing a prior traumatic event, completed measures that reflected the constructs of narrative centrality, negative affectivity, and death concerns, along with a measure of PTSS. PTSS was regressed on the latent variables of death concerns, narrative centrality, and negative affectivity, along with the latent variable interactions between narrative centrality*death concerns and narrative centrality*negative affectivity. Death concerns was not be predictive of PTSS, whereas narrative centrality and negative affectivity were found to uniquely and interactively account for 77% of the variance in PTSS. Death concerns was found to be a separate construct from negative affectivity. The implications of these findings for the two frameworks are discussed along with future directions. By considering aspects of narrative centrality and negative affectivity, substantial portions of PTSS can be accounted for.
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Wu, Qian. "Structural studies of human DNA double-strand breaks repair non-homologous end joining protein complex XLF-XRCC4 : dance in a helical way." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610376.
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MARCHESI, SILVIA. "Screening and Signalling in Debt Strategies: Theory and Empirics." Doctoral thesis, University of Warwick, 2001. http://hdl.handle.net/10281/4658.
Full textAbstract:
This thesis focuses on public debt under asymmetry of information. The first part of the thesis deals with foreign debt while the second part with domestic debt.
In the first part of this work (Chapter 1 and 2) a theoretical model is developed in which adoption of an IMF programme signals a country's productivity. It is assumed that there are two types of country, one with a high return on investment and the other with a low return. The country's type is known only to itself. In the presence of a debt overhang, the high productivity country may choose not to undertake the investment, despite it being socially efficient to do so. In this case the creditor would like to offer the country some debt reduction, but the low productivity type will also benefit from the debt reduction. This problem can be avoided if the country has sufficient resources to engage in a debt buyback in order to gain the debt relief: only the high productivity type would be prepared to sacrifice current resources for the debt reduction, and thus a separation of the two types is achieved. (This is similar to an argument found in Acharya and Diwan, 1993). We argue, however, that it is unlikely that a heavily indebted country will have sufficient resources for a buyback. If the country is credit constrained, an alternative screening mechanism is to undertake an IMF programme in return for debt reduction and possibly an IMF loan. This mechanism can be the equilibrium outcome even if the programme creates only disutility for the country's policy makers.
The existence of an empirical relationship between the adoption of an IMF programme and the concession of a debt rescheduling by commercial and official creditors is tested in Chapter 3 using a bivariate probit model (to control for the endogeneity of the choice "IMF adoption"). If countries who have arrangements with the IMF are more likely than others to obtain a rescheduling of their external debt we could conclude that the adoption of an IMF programme could work as a sort of signal of a country's "good intent", which is thus rewarded with the debt relief. The results confirm the existence of a significant effect of the adoption of an IMF programme on the subsequent concession of a debt rescheduling by creditors.
In the second part of the thesis we have investigated some of the consequences due to the existence of a large public debt (as it is the case in some of the European countries, e.g., Belgium, Greece, Ireland and Italy). More specifically, a theoretical model is developed, in Chapter 4, to examine whether buybacks of domestic debt may signal a government type. In the model it is assumed that the government could be of two types: a dry type and a wet type, according to its willingness to implement a fiscal stabilisation (in this model this basically means reducing fiscal spending). Asymmetry of information between the government and private investors is assumed. In particular interest rates are assumed to incorporate a risk premium which reflect the expectation that the inability to implement a stabilisation programme may result in more inflation and/or taxation, or debt default. In particular, during a fiscal stabilisation, private investors would lack confidence in the stabilisation programme and interest rates would be too high, reflecting this lack of credibility. Thus, a dry type who has to finance new spending may want to signal her resolution in order to lower the interest costs and one way to do that would be to repurchase a fraction of the outstanding debt. The wet type could also decide to buy-back some of his debt in order to pretend to be dry and to (possibly) lower his interest payments. It is showed that a critical amount of buyback exists such that the two types could be separated.
Finally, in Chapter 5, evidence is provided in favour of the hypothesis that the repurchase of public debt is actually perceived as a good signal by private investors, consistently with the theoretical model. According to our results, the initial impact of the repurchase was to make the prices of the remaining bonds rise. This was consistent with our theory as we can interpret an increase in bonds price (and correspondingly a decrease in their rates of returns) as a signal that the buyback operation has positively affected the credibility of a government.