Spatial spillovers and political coordination in public health provision

We estimate the impact of the main unconditional federal grant (Fundo de Participaçãodos Municípios - FPM) to Brazilian municipalities as well as its spillover from the neighboring cities on local health outcomes. We consider data from 2002 to 2007 (Brollo et al, 2013) and explore the FPM distribution rule according to population brackets to apply a fuzzy Regression Discontinuity Design (RDD) using cities near the thresholds. In elasticity terms, we nd a reduction on infant mortality rate (-0.18) and on morbidity rate (- 0.41), except in the largest cities of our sample. We also nd an increase on the access to the main program of visiting the vulnerable families, the Family Health Program (Programa Sa ude da Família - PSF). The e ects are stronger for the smallest cities of our sample and we nd increase: (i) On the percentage of residents enrolled in the program (0.36), (ii) On the per capita number of PSF visits (1.59), and (iii) On the per capita number of PSF visits with a doctor (1.8) and nurse (2). After we control for the FPM spillover using neighboring cities near diferent thresholds, our results show that the reduction in morbidity and mortality is largely due to the spillover e ect, but there are negative spillover on preventive actions, as PSF doctors visits and vaccination. Finally, the negative spillover e ect on health resources may be due free riding or political coordination problems, as in the case of the number of hospital beds, but also due to to competition for health professionals, as in the case of number of doctors (-0.35 and -0.87, respectively), specially general practitioners and surgeons (-1.84 and -2.45).

Wald tests for IV regression with weak instruments

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).

Improved combinations of parametric and nonparametric Regression estimators

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.

Unconditional transfers goes to health? Evidence from Brazilian municipalities

This study assesses the impact of unconditional transfer resources on the health indicators of Brazilian municipalities. This transfer refers to the Participation Fund of Municipalities (FPM) where at least 15% of its value should be spent on public health. Based on a discontinuity of the rules of transfers, we explore Regression Discontinuous Design for the years 2002 to 2010, and find: (i) no significant effect of FPM on mortality reduction; (ii) a robust and significant reduction in morbidity, treated municipalities – on the right side of thresholds – on average have a per capita rate of morbidity 0.00821% lower than those on the left side of the cutoff points; (iii) the mechanisms through which a reduction on morbidity could be operated would be due to estimated increases in preventive measures such as consultations and medical and nurses visits, these were bigger for the treated group in, respectively, 0.32%, 0.038% and 0.039%.

Optimal two-sided tests for instrumental variables regression with heteroskedastic and autocorrelated errors

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.

International entry modes in Brazil and the CAGE distances effects

The international entry mode choices have a relevant importance for the impact they have on successful internationalization strategies. Many theories have been developed to describe which entry mode may be better than another according to the particular situation. The CAGE Distances Framework developed by Ghemawat to identify which dimensions companies should look when develop an internationalization strategy, may be useful to identify also how those dimensions impact on the international entry mode decision. The aim of this thesis is to study which kind of relationship exists between Cultural, Administrative, Geographic and Economic Distances and international entry mode choice. It analyzes a sample of companies that have been entered in Brazil through a logistic regression. According to this analysis, a negative and significant relation between Cultural Distance and need of control exists, a positive one exists between Administrative and Geographic, while no significant relationship has been found with the Economic dimension. Those findings are conceivably explainable through the theories found by scholars, but a deeper analysis that may take into account the specificity of every country is highly recommended, like the one developed with Brazil in this thesis.

Assessing global economic activity linkages: an empirical exercise based on global autoregressive regression

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.