15 resultados para EU Data Protection Framework

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We present the results of a study that collected, compared and analyzed the terms and conditions of a number of cloud services vis-a-vis privacy and data protection. First, we assembled a list of factors that comprehensively capture cloud companies' treatment of user data with regard to privacy and data protection; then, we assessed how various cloud services of different types protect their users in the collection, retention, and use of their data, as well as in the disclosure to law enforcement authorities. This commentary provides comparative and aggregate analysis of the results.

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A coleta e o armazenamento de dados em larga escala, combinados à capacidade de processamento de dados que não necessariamente tenham relação entre si de forma a gerar novos dados e informações, é uma tecnologia amplamente usada na atualidade, conhecida de forma geral como Big Data. Ao mesmo tempo em que possibilita a criação de novos produtos e serviços inovadores, os quais atendem a demandas e solucionam problemas de diversos setores da sociedade, o Big Data levanta uma série de questionamentos relacionados aos direitos à privacidade e à proteção dos dados pessoais. Esse artigo visa proporcionar um debate sobre o alcance da atual proteção jurídica aos direitos à privacidade e aos dados pessoais nesse contexto, e consequentemente fomentar novos estudos sobre a compatibilização dos mesmos com a liberdade de inovação. Para tanto, abordará, em um primeiro momento, pontos positivos e negativos do Big Data, identificando como o mesmo afeta a sociedade e a economia de forma ampla, incluindo, mas não se limitando, a questões de consumo, saúde, organização social, administração governamental, etc. Em seguida, serão identificados os efeitos dessa tecnologia sobre os direitos à privacidade e à proteção dos dados pessoais, tendo em vista que o Big Data gera grandes mudanças no que diz respeito ao armazenamento e tratamento de dados. Por fim, será feito um mapeamento do atual quadro regulatório brasileiro de proteção a tais direitos, observando se o mesmo realmente responde aos desafios atuais de compatibilização entre inovação e privacidade.

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Using the Pricing Equation, in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) mimicking portfolio which relies on the fact that its logarithm is the ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences, making it suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

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The purpose of this article is to discuss the relations between regulation, competition policy and consumer protection these relations in three key sectors of Brazil’s infrastructure: telecommunications, electricity and water supply. A study of the literature points to two general principles. First, the need for consumer protection depends on the “degree of sovereignty” enjoyed by consumers, defined in terms of the cost of consumer organization, consumers’ ability to evaluate services, and the level of competition in each sector. Second, the less sovereignty consumers enjoy the more consumer protection institutions are involved with regulation agencies. The evidence for the Brazilian case apparently corroborates these points. In addition, it is important to stress that consumer complaints in regulated sectors seem to have increased more intensely than in others. The article is divided into three sections. Section 1 presents theoretical elements and aspects of the relations between regulation, competition policy and consumer protection evidenced by international experience. Section 2 analyzes the Brazilian experience and in particular the available statistics on consumer complaints about telecommunications, electricity and water supply, submitted to Fundação Procon-SP during the nineties. The last section points to possible configurations of the institutional relations between competition policy, regulation and consumer protection, showing how the existing configuration of these areas in the three infrastructure sectors discussed confirms that the theoretical framework proposed has reasonable predictive power.

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This paper analyses the equilibrium structure of protection in Mercosul, developing empirical analyses based on the literature ensuing from the sequence of models set forth by Grossman and Helpman since 1994. Not only Mercosul’s common external tariff (CET) may be explained under a political economy perspective, but the existence of deviations, both at the level of the external tariffs and at that of the internal ones, make it interesting to contrast several structures under this approach. Different general equilibrium frameworks, in which governments are concerned with campaign contributions and with the welfare of the average voter, while organized special-interest groups care only about the welfare of their members, are used as the theoretical basis of the empirical tests. We build a single equation for explaining the CET and two fourequations systems (one equation for each member) for explaining deviations from the CET and from the internal free trade between members. The results (at the two-digit level) shed an interesting light on the sectoral dynamics of protection in each country; notably, Brazil seems to fit in better in the model framework, followed by Uruguay. In the case of the CET, and of deviations from it, the interaction between the domestic lobbies in the four countries plays a major role. There is also suggestion that the lobby structure that bid for deviations, be they internal or external, differs from the one which bid for the CET.

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This paper develops a framework to test whether discrete-valued irregularly-spaced financial transactions data follow a subordinated Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates not only the irregular spacing of transactions data, but also price discreteness. Further, it turns out that, under such an observation rule, the current price duration is independent of previous price durations given the current price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Finally, we investigate whether or not bid-ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid-ask spread. The results are mixed in the sense that the Markov assumption is rejected for three out of the five stocks we have analyzed.

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Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the "common feature" in every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences. The techniques discussed in this paper were applied to two relevant issues in macroeconomics and finance: the first asks what type of parametric preference-representation could be validated by asset-return data, and the second asks whether or not our SDF estimator can price returns in an out-of-sample forecasting exercise. In formal testing, we cannot reject standard preference specifications used in the macro/finance literature. Estimates of the relative risk-aversion coefficient are between 1 and 2, and statistically equal to unity. We also show that our SDF proxy can price reasonably well the returns of stocks with a higher capitalization level, whereas it shows some difficulty in pricing stocks with a lower level of capitalization.

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The objective of this paper is to test for optimality of consumption decisions at the aggregate level (representative consumer) taking into account popular deviations from the canonical CRRA utility model rule of thumb and habit. First, we show that rule-of-thumb behavior in consumption is observational equivalent to behavior obtained by the optimizing model of King, Plosser and Rebelo (Journal of Monetary Economics, 1988), casting doubt on how reliable standard rule-of-thumb tests are. Second, although Carroll (2001) and Weber (2002) have criticized the linearization and testing of euler equations for consumption, we provide a deeper critique directly applicable to current rule-of-thumb tests. Third, we show that there is no reason why return aggregation cannot be performed in the nonlinear setting of the Asset-Pricing Equation, since the latter is a linear function of individual returns. Fourth, aggregation of the nonlinear euler equation forms the basis of a novel test of deviations from the canonical CRRA model of consumption in the presence of rule-of-thumb and habit behavior. We estimated 48 euler equations using GMM, with encouraging results vis-a-vis the optimality of consumption decisions. At the 5% level, we only rejected optimality twice out of 48 times. Empirical-test results show that we can still rely on the canonical CRRA model so prevalent in macroeconomics: out of 24 regressions, we found the rule-of-thumb parameter to be statistically signi cant at the 5% level only twice, and the habit ƴ parameter to be statistically signi cant on four occasions. The main message of this paper is that proper return aggregation is critical to study intertemporal substitution in a representative-agent framework. In this case, we fi nd little evidence of lack of optimality in consumption decisions, and deviations of the CRRA utility model along the lines of rule-of-thumb behavior and habit in preferences represent the exception, not the rule.

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Esta tese é composta por três ensaios sobre o mercado de crédito e as instituições que regem bancarrota corporativa. No capítulo um, trazemos evidências que questionam a ideia de que maiores níveis de proteção ao credor sempre promovem desenvolvimento do mercado de crédito. Desde a publicação dos artigos seminais de La Porta et al (1997,1998), a métrica de proteção ao credor que os autores propuseram -- o índice de proteção ao credor -- tem sido amplamente utilizada na literatura de Law and Finance como variável explicativa em modelos de regressão linear em forma reduzida para determinar a correlação entre proteção ao credor e desenvolvimento do mercado de crédito. Neste artigo, exploramos alguns problemas com essa abordagem. Do ponto de vista teórico, essa abordagem geralmente supõe uma relação monotônica entre proteção ao credor e expansão do crédito. Nós apresentamos um modelo teórico para um mercado de crédito com seleção adversa em que um nível intermediário de proteção ao credor é capaz de implementar equilíbrios first best. Este resultado está de acordo com diversos outros artigos teóricos, tanto em equilíbrio geral quanto em equilíbrio parcial. Do ponto de vista empírico, tiramos proveito das reformas realizadas por alguns países durante as décadas de 1990 e 2000 para implementar uma estratégia inspirada na literatura de treatment effects e estimar o efeito sobre o valor de mercado e sobre a dívida de: i) permitir automatic stay a firmas em recuperação; e ii) conceder aos credores o direito de afastar os administradores. Os resultados que obtivemos apontam para um impacto positivo de automatic stay sobre todas as variáveis que dependem do valor de mercado da firma. Não encontramos efeito sobre dívida, e não encontramos efeitos significativos do direito de afastar administradores sobre valor de mercado ou dívida. O capítulo dois avalia as consequências empíricas de uma reforma na lei de falências sobre um mercado de crédito pouco desenvolvido. No início de 2005, o Congresso Nacional brasileiro aprovou uma nova lei de falências, a lei 11.101/05. Usando dados de firmas brasileiras e não-brasileiras, nós estimamos, usando dois modelos diferentes, o efeito da reforma falimentar sobre variáveis contratuais e não-contratuais de dívida. Ambos os modelos produzem resultados similares. Encontramos um aumento no volume total de dívida e na dívida de longo prazo, e uma redução no custo de dívida. Não encontramos efeitos significativos sobre a estrutura de propriedade da dívida. No capítulo três, desenvolvemos um modelo estimável de equilíbrio em search direcionado aplicado ao mercado de crédito, modelo este que pode ser usado para realizar avaliações ex ante de mudanças institucionais que afetem o crédito (como reformas em leis de falência). A literatura em economia há muito reconhece uma relação causal entre instituições (como leis e regulações) e desenvolvimento dos mercados financeiros. Essa conclusão qualitativa é amplamente reconhecida, mas há pouca evidência de sua importância quantitativa. Com o nosso modelo, é possível estimar como contratos de dívida mudam em resposta a mudanças nos parâmetros que descrevem as instituições da economia. Também é possível estimar o impacto sobre investimentos realizados pelas firmas, bem como caracterizar a distribuição do tamanho, idade e produtividade das firmas antes e depois da mudança institucional. Como ilustração, realizamos um exercício empírico em que usamos dados de firmas brasileiras para simular o impacto de variações na taxa de recuperação de créditos sobre os valores médios e totais de dívida e capital das firmas. Encontramos dívida crescente e capital quase sempre também crescente na taxa de recuperação.

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This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.

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Using the theoretical framework of Lettau and Ludvigson (2001), we perform an empirical investigation on how widespread is the predictability of cay {a modi ed consumption-wealth ratio { once we consider a set of important countries from a global perspective. We chose to work with the set of G7 countries, which represent more than 64% of net global wealth and 46% of global GDP at market exchange rates. We evaluate the forecasting performance of cay using a panel-data approach, since applying cointegration and other time-series techniques is now standard practice in the panel-data literature. Hence, we generalize Lettau and Ludvigson's tests for a panel of important countries. We employ macroeconomic and nancial quarterly data for the group of G7 countries, forming an unbalanced panel. For most countries, data is available from the early 1990s until 2014Q1, but for the U.S. economy it is available from 1981Q1 through 2014Q1. Results of an exhaustive empirical investigation are overwhelmingly in favor of the predictive power of cay in forecasting future stock returns and excess returns.

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This thesis contains three chapters. The first chapter uses a general equilibrium framework to simulate and compare the long run effects of the Patient Protection and Affordable Care Act (PPACA) and of health care costs reduction policies on macroeconomic variables, government budget, and welfare of individuals. We found that all policies were able to reduce uninsured population, with the PPACA being more effective than cost reductions. The PPACA increased public deficit mainly due to the Medicaid expansion, forcing tax hikes. On the other hand, cost reductions alleviated the fiscal burden of public insurance, reducing public deficit and taxes. Regarding welfare effects, the PPACA as a whole and cost reductions are welfare improving. High welfare gains would be achieved if the U.S. medical costs followed the same trend of OECD countries. Besides, feasible cost reductions are more welfare improving than most of the PPACA components, proving to be a good alternative. The second chapter documents that life cycle general equilibrium models with heterogeneous agents have a very hard time reproducing the American wealth distribution. A common assumption made in this literature is that all young adults enter the economy with no initial assets. In this chapter, we relax this assumption – not supported by the data – and evaluate the ability of an otherwise standard life cycle model to account for the U.S. wealth inequality. The new feature of the model is that agents enter the economy with assets drawn from an initial distribution of assets. We found that heterogeneity with respect to initial wealth is key for this class of models to replicate the data. According to our results, American inequality can be explained almost entirely by the fact that some individuals are lucky enough to be born into wealth, while others are born with few or no assets. The third chapter documents that a common assumption adopted in life cycle general equilibrium models is that the population is stable at steady state, that is, its relative age distribution becomes constant over time. An open question is whether the demographic assumptions commonly adopted in these models in fact imply that the population becomes stable. In this chapter we prove the existence of a stable population in a demographic environment where both the age-specific mortality rates and the population growth rate are constant over time, the setup commonly adopted in life cycle general equilibrium models. Hence, the stability of the population do not need to be taken as assumption in these models.