Evolução da concentração de renda no Brasil entre 1977 e 2013

Este trabalho procura analisar a evolução da concentração de renda familiar para o Brasil e seus vinte e sete estados entre os anos de 1977 e 2013 através das informações da Pesquisa Nacional por Amostragem de Domicílios (PNAD) do IBGE. Foram consideradas quatro faixas distintas de renda: 1% mais ricos, 10% mais ricos, 10% mais pobres e 50% mais pobres. O resultado do estudo se fundamentou na análise descritiva dos dados, assim como nas informações disponibilizadas pelos testes de componentes não observados e do modelo de mudança de regime de Markov-switching. Em relação às famílias mais ricas do país, foi constatado um movimento divergente entre as duas faixas consideradas neste estudo, sendo registrada uma redução do nível de concentração de renda nas famílias 10% mais ricas, enquanto que as famílias da faixa 1% mais ricas não apresentaram o mesmo movimento, permanecendo praticamente no mesmo patamar ao longo de todo o período analisado. Quando consideradas as famílias mais pobres do país, confirma-se a elevação do nível de apropriação da renda ao longo dos últimos 37 anos de história, embora com grandes indícios que esta trajetória já tenha chegado ao fim. É possível observar, entretanto, que a distribuição dos ganhos recentes não foi uniforme entre as diversas regiões brasileiras, com destaque para o Nordeste, que não registrou elevação consistente da apropriação de renda pelas famílias 10% mais pobres, indicando que os mais pobres da região permanecem em situação vulnerável.

Essays on international macroeconomics and conflict analysis

This dissertation addressed two broad problems in international macroeconomics and conflict analysis. The first problem in the first chapter looked at the behavior of exchange rate and its interaction with industry-level tradable goods prices for three countries, USA, UK and Japan. This question has important monetary policy implications. Here, I computed to what extent changes in exchange rate affected prices of consumer, producer, and export goods. I also studied the timing of these changes in these prices. My results, based on thirty-four industrial prices for USA, UK and Japan, supported the view that changes in exchange rates significantly affect prices of industrial and consumer goods. It also provided an insight to the underlying economic process that led to changes in relative prices. ^ In the second chapter, I explored the predictability of future inflation by incorporating shocks to exchange rates and clearly specified the transmission mechanisms that link exchange rates to industry-level consumer and producer prices. Employing a variety of linear and state-of-the-art nonlinear models, I also predicted growth rates of future prices. Comparing levels of inflation obtained from the above approaches showed superiority of the structural model incorporating the exchange rate pass-through effect. ^ The second broad issue addressed in the third chapter of the dissertation investigated the economic motives for conflict, manifested by rebellion and civil war for seventeen Latin American countries. Based on the analytical framework of Garfinkel, Skaperdas and Syropoulos (2004), I employed ordinal regressions and Markov switching for a panel of seventeen countries to identify trade and openness factors responsible for conflict occurrence and intensity. The results suggested that increased trade openness reduced high intensity domestic conflicts but overdependence on agricultural exports, along with a lack of income earning opportunities lead to more conflicts. Thereafter, using the Cox Proportional Hazard model I studied “conflict duration” and found that over-reliance on agricultural exports explained a major part of the length of conflicts in addition to various socio-political factors. ^

Essays on emissions trading markets

This dissertation is a collection of three economics essays on different aspects of carbon emission trading markets. The first essay analyzes the dynamic optimal emission control strategies of two nations. With a potential to become the largest buyer under the Kyoto Protocol, the US is assumed to be a monopsony, whereas with a large number of tradable permits on hand Russia is assumed to be a monopoly. Optimal costs of emission control programs are estimated for both the countries under four different market scenarios: non-cooperative no trade, US monopsony, Russia monopoly, and cooperative trading. The US monopsony scenario is found to be the most Pareto cost efficient. The Pareto efficient outcome, however, would require the US to make side payments to Russia, which will even out the differences in the cost savings from cooperative behavior. The second essay analyzes the price dynamics of the Chicago Climate Exchange (CCX), a voluntary emissions trading market. By examining the volatility in market returns using AR-GARCH and Markov switching models, the study associates the market price fluctuations with two different political regimes of the US government. Further, the study also identifies a high volatility in the returns few months before the market collapse. Three possible regulatory and market-based forces are identified as probable causes of market volatility and its ultimate collapse. Organizers of other voluntary markets in the US and worldwide may closely watch for these regime switching forces in order to overcome emission market crashes. The third essay compares excess skewness and kurtosis in carbon prices between CCX and EU ETS (European Union Emission Trading Scheme) Phase I and II markets, by examining the tail behavior when market expectations exceed the threshold level. Dynamic extreme value theory is used to find out the mean price exceedence of the threshold levels and estimate the risk loss. The calculated risk measures suggest that CCX and EU ETS Phase I are extremely immature markets for a risk investor, whereas EU ETS Phase II is a more stable market that could develop as a mature carbon market in future years.

Essays on Emissions Trading Markets

This dissertation is a collection of three economics essays on different aspects of carbon emission trading markets. The first essay analyzes the dynamic optimal emission control strategies of two nations. With a potential to become the largest buyer under the Kyoto Protocol, the US is assumed to be a monopsony, whereas with a large number of tradable permits on hand Russia is assumed to be a monopoly. Optimal costs of emission control programs are estimated for both the countries under four different market scenarios: non-cooperative no trade, US monopsony, Russia monopoly, and cooperative trading. The US monopsony scenario is found to be the most Pareto cost efficient. The Pareto efficient outcome, however, would require the US to make side payments to Russia, which will even out the differences in the cost savings from cooperative behavior. The second essay analyzes the price dynamics of the Chicago Climate Exchange (CCX), a voluntary emissions trading market. By examining the volatility in market returns using AR-GARCH and Markov switching models, the study associates the market price fluctuations with two different political regimes of the US government. Further, the study also identifies a high volatility in the returns few months before the market collapse. Three possible regulatory and market-based forces are identified as probable causes of market volatility and its ultimate collapse. Organizers of other voluntary markets in the US and worldwide may closely watch for these regime switching forces in order to overcome emission market crashes. The third essay compares excess skewness and kurtosis in carbon prices between CCX and EU ETS (European Union Emission Trading Scheme) Phase I and II markets, by examining the tail behavior when market expectations exceed the threshold level. Dynamic extreme value theory is used to find out the mean price exceedence of the threshold levels and estimate the risk loss. The calculated risk measures suggest that CCX and EU ETS Phase I are extremely immature markets for a risk investor, whereas EU ETS Phase II is a more stable market that could develop as a mature carbon market in future years.

Dynamic Performance Evaluation of Canadian Fixed-Income Funds using Markov Regime Switching Models

This thesis examines the performance of Canadian fixed-income mutual funds in the context of an unobservable market factor that affects mutual fund returns. We use various selection and timing models augmented with univariate and multivariate regime-switching structures. These models assume a joint distribution of an unobservable latent variable and fund returns. The fund sample comprises six Canadian value-weighted portfolios with different investing objectives from 1980 to 2011. These are the Canadian fixed-income funds, the Canadian inflation protected fixed-income funds, the Canadian long-term fixed-income funds, the Canadian money market funds, the Canadian short-term fixed-income funds and the high yield fixed-income funds. We find strong evidence that more than one state variable is necessary to explain the dynamics of the returns on Canadian fixed-income funds. For instance, Canadian fixed-income funds clearly show that there are two regimes that can be identified with a turning point during the mid-eighties. This structural break corresponds to an increase in the Canadian bond index from its low values in the early 1980s to its current high values. Other fixed-income funds results show latent state variables that mimic the behaviour of the general economic activity. Generally, we report that Canadian bond fund alphas are negative. In other words, fund managers do not add value through their selection abilities. We find evidence that Canadian fixed-income fund portfolio managers are successful market timers who shift portfolio weights between risky and riskless financial assets according to expected market conditions. Conversely, Canadian inflation protected funds, Canadian long-term fixed-income funds and Canadian money market funds have no market timing ability. We conclude that these managers generally do not have positive performance by actively managing their portfolios. We also report that the Canadian fixed-income fund portfolios perform asymmetrically under different economic regimes. In particular, these portfolio managers demonstrate poorer selection skills during recessions. Finally, we demonstrate that the multivariate regime-switching model is superior to univariate models given the dynamic market conditions and the correlation between fund portfolios.

Analysis of contagion from the constant conditional correlation model with Markov regime switching

Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.

Mudanças de regimes na função de reação do Banco Central do Brasil : uma abordagem utilizando Markov Regime Switching

O presente trabalho busca identificar a ocorrência, duração e probabilidades de transição de diferentes regimes na condução da política monetária no Brasil a partir da implantação do sistema de metas de inflação em 1999. A estimação da função de reação do Banco Central do Brasil é realizada a partir de uma Regra de Taylor forward looking para uma economia aberta, onde utilizamos a metodologia Markov Regime Switching para caracterizar de forma endógena os diferentes regimes de política monetária. Os resultados obtidos indicam a ocorrência de três regimes distintos de política monetária a partir da implantação do sistema de metas de inflação no Brasil. O primeiro regime ocorre durante 21% do período estudado e se caracteriza pela não aderência ao princípio de Taylor e discricionariedade da autoridade monetária, que reage demonstrando maior sensibilidade ao hiato do produto. O segundo regime é o de maior duração, ocorre durante 67% do período estudado, e se caracteriza pela aderência ao princípio de Taylor e equilíbrio nos pesos atribuídos pelo Banco Central tanto ao hiato do produto como ao desvio das expectativas de inflação com relação à meta. Já o terceiro regime ocorre durante 12% do período estudado e se caracteriza não somente pela aderência ao princípio de Taylor, como também por uma maior aversão ao desvio das expectativas de inflação com relação à meta.

Universal codes from switching strategies

We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.

Asymptotic analysis of option pricing in a Markov modulated market

We address asymptotic analysis of option pricing in a regime switching market where the risk free interest rate, growth rate and the volatility of the stocks depend on a finite state Markov chain. We study two variations of the chain namely, when the chain is moving very fast compared to the underlying asset price and when it is moving very slow. Using quadratic hedging and asymptotic expansion, we derive corrections on the locally risk minimizing option price.

A reinforcement learning based algorithm for finite horizon Markov decision processes

We develop a simulation based algorithm for finite horizon Markov decision processes with finite state and finite action space. Illustrative numerical experiments with the proposed algorithm are shown for problems in flow control of communication networks and capacity switching in semiconductor fabrication.

A mathematical programming approach to optimal Markovian switching of Poisson arrival streams to queueing systems

Motivated by certain situations in manufacturing systems and communication networks, we look into the problem of maximizing the profit in a queueing system with linear reward and cost structure and having a choice of selecting the streams of Poisson arrivals according to an independent Markov chain. We view the system as a MMPP/GI/1 queue and seek to maximize the profits by optimally choosing the stationary probabilities of the modulating Markov chain. We consider two formulations of the optimization problem. The first one (which we call the PUT problem) seeks to maximize the profit per unit time whereas the second one considers the maximization of the profit per accepted customer (the PAC problem). In each of these formulations, we explore three separate problems. In the first one, the constraints come from bounding the utilization of an infinite capacity server; in the second one the constraints arise from bounding the mean queue length of the same queue; and in the third one the finite capacity of the buffer reflect as a set of constraints. In the problems bounding the utilization factor of the queue, the solutions are given by essentially linear programs, while the problems with mean queue length constraints are linear programs if the service is exponentially distributed. The problems modeling the finite capacity queue are non-convex programs for which global maxima can be found. There is a rich relationship between the solutions of the PUT and PAC problems. In particular, the PUT solutions always make the server work at a utilization factor that is no less than that of the PAC solutions.

Risk Minimizing Option Pricing for a Class of Exotic Options in a Markov-Modulated Market

We address risk minimizing option pricing in a regime switching market where the floating interest rate depends on a finite state Markov process. The growth rate and the volatility of the stock also depend on the Markov process. Using the minimal martingale measure, we show that the locally risk minimizing prices for certain exotic options satisfy a system of Black-Scholes partial differential equations with appropriate boundary conditions. We find the corresponding hedging strategies and the residual risk. We develop suitable numerical methods to compute option prices.