10 resultados para Ols Regression

em Repositório digital da Fundação Getúlio Vargas - FGV


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Este trabalho visa sistematizar um modelo para previsão e explicação dos movimentos de curto prazo da estrutura a termo de taxas de juros pré-fixada em reais do Brasil, baseado na relação dos movimentos em questão com os níveis e alterações que se processam nas variáveis macroeconômicas relevantes. A metodologia usada foi dividir o procedimento em duas etapas: Na primeira etapa, o modelo de Svensson (1994) é usado para ajustar a Estrutura a Termo de Taxas de Juros de cada data específica para obter os parâmetros daquela data. Isso é conseguido através da maximização da estatística R2 na regressão de mínimos quadrados, como sugerido no artigo original de Nelson e Siegel (1987). Então, as medianas dos dois parâmetros de decaimento utilizados são calculadas e mantidas arbitrariamente constantes para facilitar os cálculos da segunda etapa. Na segunda etapa, uma vez que os estimadores que melhor se ajustam às curvas de juros foram obtidos, outra regressão de MQO é realizada considerando os betas de Svensson dependentes de variáveis macroeconômicas de estado.

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The general idea of this research is to analyze overall firm performance before and after the global financial crisis of 2008. The main question is: What kind of strategies did companies adopt that led to positive business performance after the crisis? Are there any particular competitive advantages that bring better performance in the case of an economic downturn? This research focuses on competitive advantage gained by resource-based view attributes of a product (quality, durability and prestige) and dynamic capabilities (strategic flexibility in product development and technological innovation ability). The economic crisis setting provides a proper background to analyze the competitive advantage strategies in a dynamic, low-probability environment to determine which are most worth adopting in the business world. I employ an OLS regression analysis in order to measure the business performance of 136 Brazilian firms across four years – 2002, 2005, 2008 and 2012. The findings indicate that even though all of the strategic resources and capabilities positively influence firm performance in expansionary periods, only the superior product characteristics are pertinent in surviving an economic downturn.

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We exploit a discontinuity in Brazilian municipal election rules to investigate whether political competition has a causal impact on policy choices. In municipalities with less than 200,000 voters mayors are elected with a plurality of the vote. In municipalities with more than 200,000 voters a run-off election takes place among the top two candidates if neither achieves a majority of the votes. At a first stage, we show that the possibility of runoff increases political competition. At a second stage, we use the discontinuity as a source of exogenous variation to infer causality from political competition to fiscal policy. Our second stage results suggest that political competition induces more investment and less current spending, particularly personnel expenses. Furthermore, the impact of political competition is larger when incumbents can run for reelection, suggesting incentives matter insofar as incumbents can themselves remain in office.

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This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).

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This paper provides a systematic and unified treatment of the developments in the area of kernel estimation in econometrics and statistics. Both the estimation and hypothesis testing issues are discussed for the nonparametric and semiparametric regression models. A discussion on the choice of windowwidth is also presented.

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This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.

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Este estudo tem por objetivo identificar as principais variáveis que afetam o spread de Certificados de Recebíveis Imobiliários (CRI) no mercado nacional no momento da emissão do título. Dentre as principais variáveis estudadas estão o volume de emissão, prazo dos títulos, existência de rating, tipo de emissão, dentre outros. Para o trabalho foi utilizada uma base de dados de acompanhamento do mercado realizado pela ANBIMA e contou com 535 emissões, realizadas entre 2005 e 2015, de CRI indexados ao IGP, IPCA, DI e TR, além de títulos pré-fixados. Foram elaboradas cinco regressões pelo método dos Mínimos Quadrados Ordinários (MQO) stepwise sendo que as amostras foram separadas de acordo com o tipo de indexador (IGP, IPCA, DI e TR) e uma que englobou todas as emissões. Os resultados se mostraram distintos para cada regressão realizada e as variáveis explicativas do spread que se mostraram significativas na maioria das regressões foram o volume de emissão e a variável representativa da percepção internacional do cenário brasileiro. A evolução apresentada por este estudo com relação aos trabalhos disponíveis na literatura é de expandir as análises realizadas com outros títulos mobiliários, como Debentures e Fundos de Investimento em Direito Creditórios, para os CRIs.

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O mercado de securitização através de Fundos de Investimento em Direitos Creditórios (FIDCs) no Brasil ainda não é tão desenvolvido quando comparado aos mercados internacionais. O desenvolvimento desse mercado facultaria a bancos e empresas acesso a fontes de financiamento além da sua geração de caixa ou da emissão de novas ações. Bancos e empresas devem manter a busca por formas alternativas de financiamento, obtendo, assim, diversificação de suas fontes de recursos. O objetivo desse trabalho é avaliar como as características dos FIDCs afetam a taxa de captação de suas cotas sênior. Para isso foram avaliadas 151 séries de cotas, emitidas entre 2002 e 2014. Na análise foram usadas análises multivariadas através da regressão linear múltipla, usando o método de Mínimos Quadrados Ordinários (MQO), para avaliar o efeito das variáveis sobre o spread das cotas. Os resultados apontaram que o volume de emissão afeta a forma como outras variáveis afetam o spread. Os fundos com tamanho de oferta maior têm seu spread influenciado por características de seus cedentes e por características de sua estruturação, enquanto que fundos menores são apreçados por negociações entre emissor e investidores.

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Economic performance increasingly relies on global economic environment due to the growing importance of trade and nancial links among countries. Literature on growth spillovers shows various gains obtained by this interaction. This work aims at analyzing the possible e ects of a potential economic growth downturn in China, Germany and United States on the growth of other economies. We use global autoregressive regression approach to assess interdependence among countries. Two types of phenomena are simulated. The rst one is a one time shock that hit these economies. Our simulations use a large shock of -2.5 standard deviations, a gure very similar to what we saw back in the 2008 crises. The second experiment simulate the e ect of a hypothetical downturn of the aforementioned economies. Our results suggest that the United States play the role of a global economy a ecting countries across the globe whereas Germany and China play a regional role.