8 resultados para ordinal regression
em Repositório digital da Fundação Getúlio Vargas - FGV
Resumo:
Este trabalho tem por motivação evidenciar a eficiência de redes neurais na classificação de rentabilidade futura de empresas, e desta forma, prover suporte para o desenvolvimento de sistemas de apoio a tomada de decisão de investimentos. Para serem comparados com o modelo de redes neurais, foram escolhidos o modelo clássico de regressão linear múltipla, como referência mínima, e o de regressão logística ordenada, como marca comparativa de desempenho (benchmark). Neste texto, extraímos dados financeiros e contábeis das 1000 melhores empresas listadas, anualmente, entre 1996 e 2006, na publicação Melhores e Maiores – Exame (Editora Abril). Os três modelos foram construídos tendo como base as informações das empresas entre 1996 e 2005. Dadas as informações de 2005 para estimar a classificação das empresas em 2006, os resultados dos três modelos foram comparados com as classificações observadas em 2006, e o modelo de redes neurais gerou o melhor resultado.
Resumo:
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.
Resumo:
A utilização de artefatos de Tecnologias da Informação Móveis e Sem Fio (TIMS) traz consigo alguns paradoxos tecnológicos associados, já identificados na literatura. O aumento do uso de TIMS e suas evoluções acabam por permitir novos tipos de uso e interação junto aos usuários. Tendo como base teorias sobre a existência de paradoxos associados ao uso de equipamentos tecnológicos, mormente TIMS, este estudo buscou aprofundar a relação entre smartphones e profissionais. A partir da coleta de dados por meio de questionário estruturado, esta pesquisa utilizou a análise quantitativa e teve como objetivo determinar a presença e medir a intensidade dos paradoxos tecnológicos, identificados na literatura, quando do uso profissional de smartphones. Outro ponto observado no presente trabalho foi a associação estatística entre esses paradoxos tecnológicos e, ainda, a identificação de fatores que poderiam impactar a percepção desses paradoxos associados ao uso do smartphone pelos profissionais que os utilizam. A análise dos dados permitiu verificar quais dos quatorze paradoxos tecnológicos apresentados por Mick e Fournier (1998), Jarvenpaa e Lang (2005) e Mazmanian et al. (2006) foram percebidos por mais respondentes, com destaque para o paradoxo de autonomia e vício, que foi vivenciado por mais de 85% daqueles que responderam à pesquisa. Usando como base o percentual de respondentes que percebem os paradoxos tecnológicos e considerando suas intensidades, esta dissertação também apresenta um ranking das forças dos paradoxos, determinado pela taxa relativa da força dos paradoxos. Esse ranking traz nas primeiras posições as seguintes ambiguidades: autonomia / vício, engajamento / desengajamento e liberdade / escravidão, respectivamente. Outro apontamento dessa pesquisa foi que nenhum dos paradoxos analisados é estatisticamente independente. Por fim, a realização de uma regressão logística ordinal levou à conclusão que apenas dois dos paradoxos em questão sofrem impacto das variáveis independentes observadas.
Resumo:
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).
Resumo:
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.
Resumo:
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.
Resumo:
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.