4 resultados para Trail riding

em Repositório digital da Fundação Getúlio Vargas - FGV


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We analyze a common agency game under asymmetric information on the preferences of the non-cooperating principals in a public good context. Asymmetric information introduces incentive compatibility constraints which rationalize the requirement of truthfulness made in the earlier literature on common agency games under complete information. There exists a large class of differentiable equilibria which are ex post inefficient and exhibit free-riding. We then characterize some interim efficient equilibria. Finally, there exists also a unique equilibrium allocation which is robust to random perturbations. This focal equilibrium is characterized for any distribution of types.

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The town of Nova Friburgo, in Brazil, was founded in 1820 by swiss immigrants who, as often happens in the majority of migratory flows, crossed the ocean in search of better life conditions. The scope of this paper is to trail the path of a swiss immigrant called Marianne Joset Salusse and then follow on to investigate the mechanisms involved in elaborating family memory and public memory around this woman who would become a symbol of immigration to this town. Thus a series of interviews were held with her descendants, which were fundamental for the understanding of current representations and the main elements which constitute the collective memory around Marianne. Besides oral sources, we had recourse to written documents which allowed a retrieval of relevant information about her life. More than simply adding information, written sources allowed for a more profound analysis of oral accounts, unravelling as well as unveiling selective procedures peculiar to memory construction (Pollak, 1989;1992).

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We analyze a common agency game under asymmetric information on the preferences of the non-cooperating principals. Asymmetric information introduces incentive compatibility constraints which rationalize the requirement of truthfulness made in the earlier literature on common agency games under complete information. There exists a large class of differentiable equilibria which are ex post inefficient and exhibit free-riding. We then characterize some interim efficient equilibria. Finally, there exists also a unique equilibrium allocation which is robust to random perturbations. This focal equilibrium is characterized for any distribution of types.

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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).