The term ‘tipping event’ is used to describe a certain class of phenomena as observed in many different fields of science. It refers to an event where a gradual change of external forcing causes a sudden, large, often unwanted, transition to the state of the system. Some examples of known tipping events in science include: Arctic sea ice melting (climate), epileptic seizures (biology), collapse of ecosystems and populations (ecology) and market crashes (finance). Three mathematical mechanisms for tipping events have been proposed in the literature: bifurcation-, noise- or rate-induced tipping. Recent research has focused on developing early-warning indicators to potentially offer forewarning, which can extract from output time series whether the external forcing approaches a critical level at which tipping occurs. Two commonly used early-warning indicators are an increase of autocorrelation and variance in the time series data for the system’s output. The theory behind the presence of these indicators is the loss of stability of the system’s current state known as ‘critical slowing down’ for the approach of a bifurcation-induced tipping. Rate-induced tipping occurs when the external forcing reaches a critical rate instead of level. For rate-induced tipping there is no loss of stability of the system’s current state and therefore it is not clear if the early-warning indicators should exist. In this thesis we investigate the presence of early-warning indicators for models that show rate-induced tipping with additive noise. We also explore a technique for determining the most likely time of tipping using optimal paths for escape. Research has mainly focussed on testing the early-warning indicators for examples of known tipping events in the past. The ultimate aim of early-warning indicators would be to have the ability to predict future tipping events. Using the early-warning indicators in isolation is susceptible to incurring false alarms and missed alarms. We present a method for approximating the probability of experiencing rate-induced tipping with noise for slow to moderate drift speeds.

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Background: HIV drug resistance is presumed to be inevitable due to the error-prone nature of the virus. However, poor adherence to the antiretroviral drugs is proven to be an impending factor for HIV drug resistance development. Of these two explanations, which is the most common reason for HIV drug resistance?Method: A total of 40 published studies about HIV drug resistance, were retrospectively collected in Pubmed (May 2017), from 36 different countries for this paper. From each study was participants, percentage of HIV drug resistance and HIV-1 subtype extracted for analysis. All studies were than classified by either high-income, middle-income or low-income, based on a country income status, defined by the World Bank. HIV drug resistance was tested against: continents, HIV-1 subtypes, number of study participants, income levels, GDP per capita and EWI’s. All statistical analysis was performed in R: The R project for statistical computing.Result: This paper show, that HIV drug resistance primarily is caused by poor adherence which is closely associated with drug stock out. Highest HIV drug resistance levels was found in middle-income countries. However, number of participants enrolled per study was important for the outcome and this indicates that HIV drug resistance would be higher in low-income countries if larger studied had been carried out in these settings. This means that there is a large unrecorded prevalence of HIV drug resistance in low-income countries.

This thesis develops an early warning system framework for assessing systemic risks and for predicting systemic events, i.e. periods of extreme financial instability with potential real costs, over the short horizon of six quarters and the long horizon of twelve quarters on the panel of 14 countries both advanced and developing. Firstly, Financial Stress Index is built aggregating indicators from equity, foreign exchange, security and money markets in order to identify starting dates of systemic financial crises for each country in the panel. Secondly, the selection of early warning indicators for assessment and prediction of systemic risks is undertaken in a two- step approach; relevant prediction horizons for each indicator are found by means of a univariate logit model followed by the application of Bayesian model averaging method to identify the most useful indicators. Next, logit models containing useful indicators only are estimated on the panel while their in-sample and out-of-sample performance is assessed by a variety of measures. Finally, having applied the constructed EWS for both horizons to the Czech Republic it was found that even though models for both horizons perform very well in-sample, i.e. both predict 100% of crises, only the long model attains the maximum utility of 0,5 as...

Submitted by Thiago Lombardi Terra (thiagolombarditerra@gmail.com) on 2014-08-15T01:46:43Z No. of bitstreams: 1 DISSERTACAO_INDICADORES_DE_VULNERABILIDADE_APLICADOS_AO_BRASIL_UMA_ABORDAGEM_EMPIRICA.pdf: 1032629 bytes, checksum: b0fb2ce1f3e5486520e29b253189bc38 (MD5) / Rejected by JOANA MARTORINI (joana.martorini@fgv.br), reason: Thiago, bom dia. Os agradecimentos deve estar no formato "justificado" no mesmo formato do seu resumo. Por gentileza fazer os ajustes listados acima. Aguardo Joana Martorini on 2014-08-15T12:16:47Z (GMT) / Submitted by Thiago Lombardi Terra (thiagolombarditerra@gmail.com) on 2014-08-15T13:35:18Z No. of bitstreams: 1 DISSERTACAO_INDICADORES_DE_VULNERABILIDADE_APLICADOS_AO_BRASIL_UMA_ABORDAGEM_EMPIRICA.pdf: 1032701 bytes, checksum: c8f544861f8509c50b19ab2bd37c61fa (MD5) / Rejected by JOANA MARTORINI (joana.martorini@fgv.br), reason: Aguardo os ajustes nos agradecimentos. on 2014-08-15T13:39:04Z (GMT) / Submitted by Thiago Lombardi Terra (thiagolombarditerra@gmail.com) on 2014-08-15T13:44:43Z No. of bitstreams: 1 DISSERTACAO_INDICADORES_DE_VULNERABILIDADE_APLICADOS_AO_BRASIL_UMA_ABORDAGEM_EMPIRICA.pdf: 1032816 bytes, checksum: 2eae63d37c58ea9666b2ad8013879033 (MD5) / Approved for entry into archive by JOANA MARTORINI (joana.martorini@fgv.br) on 2014-08-15T13:46:25Z (GMT) No. of bitstreams: 1 DISSERTACAO_INDICADORES_DE_VULNERABILIDADE_APLICADOS_AO_BRASIL_UMA_ABORDAGEM_EMPIRICA.pdf: 1032816 bytes, checksum: 2eae63d37c58ea9666b2ad8013879033 (MD5) / Made available in DSpace on 2014-08-15T13:49:38Z (GMT). No. of bitstreams: 1 DISSERTACAO_INDICADORES_DE_VULNERABILIDADE_APLICADOS_AO_BRASIL_UMA_ABORDAGEM_EMPIRICA.pdf: 1032816 bytes, checksum: 2eae63d37c58ea9666b2ad8013879033 (MD5) Previous issue date: 2014-08-05 / Along the economic history, financial instabilities have instigated the interests of the researchers that aimed to comprehend the reasons that an economy became vulnerable in certain situations. Others researchers sought to unravel the reasons that have caused the financial instability and, moreover, they sought to relate the variables that had greater exploratory power in periods of instability. This dissertation focuses on early warning indicators’ research applied in the Brazilian economy, in order to estimate which are the most adherent indicators in explaining the movements of the economy. To achieve this, this work is divided as follows: The first chapter is an introduction of this work. In the second chapter, we will focus on theoretical frameworks of authors who studied the reasons for financial instabilities. This chapter also included a review of early warning indicators and exchange market pressure applied to the Brazilian economy. After, inside the third chapter, is presented the econometric analysis and it is highlighted the criteria used to choose the indicators. Besides this selection, impacts are estimated for models of early warning indicators inside the Brazilian economy. Still in this chapter, the exchange market pressure model was estimated for the Brazilian economy. Although the models of early warning indicators are not as adherent for the Brazilian reality, their statistical relevance is important for the monitoring the trends of the economy. / Ao longo da história econômica, as instabilidades financeiras sempre despertaram interesses dos pesquisadores, que visavam entender os motivos pelos quais uma economia se tornava vulnerável em determinadas situações. Outros estudiosos procuravam desvendar as razões que levavam às instabilidades e, além do mais, procuravam relacionar as variáveis que tinham maior poder de explicação nos períodos de instabilidade. O presente trabalho focará nas pesquisas dos early warning indicators aplicados à economia brasileira, com o intuito de estimar quais são os indicadores mais aderentes na explicação dos movimentos da economia. Para tal, o trabalho está dividido da seguinte maneira: No primeiro capítulo, será abordada uma introdução do trabalho. Já no segundo capítulo, serão abordados os referenciais teóricos de autores que estudaram os motivos das instabilidades financeiras. Também consta a revisão dos estudos dos early warning indicators e do exchange market pressure aplicado à economia brasileira. Posteriormente, no terceiro capítulo, é feita uma análise econométrica, com os critérios de seleção dos indicadores. Além da justificativa das escolhas dos indicadores, serão estimados modelos dos impactos dos early warning indicators na economia brasileira. Após isto, também foi calculado o exchange market pressure para a economia brasileira. Por fim, concluí-se que, apesar dos modelos de early warning indicators não serem tão aderentes à realidade brasileira, a sua determinação estatística é de grande importância para o acompanhamento das tendências na economia.

L’objectif de cette thèse est la mise en place d’un Système d’Alerte Précoce comme instrument de prévision de la survenance des crises bancaires et des crises de la dette souveraine dans 48 pays de 1977 à 2010. Il s’agit à la fois d’identifier les facteurs capables de prédire ces événements et ceux annonçant leurs interactions éventuelles. La présente étude propose une approche à la fois originale et robuste qui tient compte de l’incertitude des modèles et des paramètres par la méthode de combinaison bayésienne des modèles de régression ou Bayesian Model Averaging (BMA). Nos résultats montrent que les avoirs étrangers nets en pourcentage du total des actifs, la dette à court terme en pourcentage des réserves totales et enfin la dette publique en pourcentage du PIB ont un pouvoir prédictif élevé pour expliquer les crises de la dette souveraine pour plusieurs pays. De plus, la croissance de l’activité et du crédit bancaire, le degré de libéralisation financière et le poids de la dette extérieure sont des signaux décisifs des crises bancaires. Notre approche offre le meilleur compromis entre les épisodes manqués et les fausses alertes. Enfin, nous étudions le lien entre les crises bancaires et les crises de la dette souveraine pour 62 pays de 1970 à 2011, en développant une approche basée sur un modèle Vecteur Auto-Régressif (VAR). Nos estimations montrent une relation significative et bidirectionnelle entre les deux types d’évènements. / The main purpose of this thesis is the development of an Early Warning System to predict banking and sovereign debt crises in 48 countries from 1977 to 2010. We are interested in identifying both factors that predict these events and those announcing their possible interactions. In particular, our empirical works provide an original and robust approach accounting for model and parameter uncertainty by means of the Bayesian Model Averaging method. Our results show that: Net foreign assets to total assets, short term debt to total reserves, and public debt to GDP have a high predictive power to signal sovereign debt crises in many countries. Furthermore, the growth rates of economic activity and credit, financial liberalization, and the external indebtedness are decisive signals of banking crises. Our approach offers the best compromise between missed episodes and false alarms. Finally, we study the link between banking and sovereign debt crises for 62 countries from 1970 to 2011 by developing an approach based on a Vector Autoregressive model (VAR). Our estimates show a significant two-way relationship between the two types of events.

This dissertation is composed of four essays that empirically investigate three topics in financial economics; financial stress and its leading indicators, the relationship between bank competition and financial stability, and the link between management board composition and bank risk. In the first essay we examine which variables have predictive power for financial stress in 25 OECD countries, using a recently constructed financial stress index. We find that panel models can hardly explain FSI dynamics. Although better results are achieved in country models, our findings suggest that financial stress is hard to predict out-of- sample despite the reasonably good in-sample performance of the models. The second essay develops an early warning framework for assessing systemic risks and predicting systemic events over two horizons of different length on a panel of 14 countries. We build a financial stress index to identify the starting dates of systemic financial crises and select crisis-leading indicators in a two-step approach; we find relevant prediction horizons for each indicator and employ Bayesian model averaging to identify the most useful predictors. We find superior performance of the long-horizon model for the Czech Republic. The theoretical literature gives conflicting predictions on how bank...