5 resultados para POISSON REGRESSION APPROACH

em Repositório digital da Fundação Getúlio Vargas - FGV


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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.

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O presente artigo estuda a relação entre corrupção e discricionariedade do gasto público ao responder a seguinte pergunta: regras de licitação mais rígidas, uma proxy para discricionariedade, resultam em menor prevalência de corrupção nos municípios brasileiros? A estratégia empírica é uma aproximação de regressões em dois estágios (2SLS) estimadas localmente em cada transição de regras de licitação, cuja fonte de dados de corrupção é o Programa de Fiscalização por Sorteio da CGU e os dados sobre discricionariedade são derivados da Lei 8.666/93, responsável por regular os processos de compras e construção civil em todas as esferas de governo. Os resultados mostram, entretanto, que menor discricionariedade está relacionada com maior corrupção para quase todos os cortes impostos pela lei de licitações.

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This paper examines the evolution of wage inequality in Brazil in the 1980s and 1990s . It tries to investigate the role played by changing economic returns to education and to experience over this period together with the evolution of within-group inequality. It applies a quantile regression approach on grouped data to the Brazilian case. Results using repeated cross-sections of a Brazilian annual household survey indicate that : i) Male wage dispersion remained basically constant overall in the 1980's and 1990' s but has increased substantially within education and age groups. ii) Returns to experience increased significantly over this period, with the rise concentrated on the iliterate/primary school group iii) Returns to college education have risen over time, whereas return to intermediate and high-school education have fallen iv) The apparent rise in within-group inequality seems to be the result of a fall in real wages, since the difference in wage leveIs has dec1ined substantially over the period, especially within the high-educated sample. v) Returns to experience rise with education. vi) Returns to education rise over the life-cycle. vii) Wage inequality increases over the life-cycle. The next step i~ this research will try to conciliate all these stylised facts.

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The thesis at hand adds to the existing literature by investigating the relationship between economic growth and outward foreign direct investments (OFDI) on a set of 16 emerging countries. Two different econometric techniques are employed: a panel data regression analysis and a time-series causality analysis. Results from the regression analysis indicate a positive and significant correlation between OFDI and economic growth. Additionally, the coefficient for the OFDI variable is robust in the sense specified by the Extreme Bound Analysis (EBA). On the other hand, the findings of the causality analysis are particularly heterogeneous. The vector autoregression (VAR) and the vector error correction model (VECM) approaches identify unidirectional Granger causality running either from OFDI to GDP or from GDP to OFDI in six countries. In four economies causality among the two variables is bidirectional, whereas in five countries no causality relationship between OFDI and GDP seems to be present.

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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).