8 resultados para germs of holomorphic generalized functions
em Repositório digital da Fundação Getúlio Vargas - FGV
Resumo:
Considering the importance of the proper detection of bubbles in financial markets for policymakers and market agents, we used two techniques described in Diba and Grossman (1988b) and in Phillips, Shi, and Yu (2015) to detect periods of exuberance in the recent history of the Brazillian stock market. First, a simple cointegration test is applied. Secondly, we conducted several augmented, right-tailed Dickey-Fuller tests on rolling windows of data to determine the point in which there’s a structural break and the series loses its stationarity.
Resumo:
Data available on continuos-time diffusions are always sampled discretely in time. In most cases, the likelihood function of the observations is not directly computable. This survey covers a sample of the statistical methods that have been developed to solve this problem. We concentrate on some recent contributions to the literature based on three di§erent approaches to the problem: an improvement of the Euler-Maruyama discretization scheme, the use of Martingale Estimating Functions and the application of Generalized Method of Moments (GMM).
Resumo:
Data available on continuous-time diffusions are always sampled discretely in time. In most cases, the likelihood function of the observations is not directly computable. This survey covers a sample of the statistical methods that have been developed to solve this problem. We concentrate on some recent contributions to the literature based on three di§erent approaches to the problem: an improvement of the Euler-Maruyama discretization scheme, the employment of Martingale Estimating Functions, and the application of Generalized Method of Moments (GMM).
Resumo:
This paper develops nonparametric tests of independence between two stationary stochastic processes. The testing strategy boils down to gauging the closeness between the joint and the product of the marginal stationary densities. For that purpose, I take advantage of a generalized entropic measure so as to build a class of nonparametric tests of independence. Asymptotic normality and local power are derived using the functional delta method for kernels, whereas finite sample properties are investigated through Monte Carlo simulations.
Resumo:
In this paper, we investigate the nature of income inequality across nations. First, rather than functional forms or parameter values in calibration exercises that can potentially drives results, we estimate, test, and distinguish between types of aggregate production functions currently used in the growth literature. Next, given our panel-regression estimates, we perform several exercises, such as variance decompositions, simulations and counter-factual analyses. The picture that emerges is one where countries grew in the past for different reasons, which should be an important ingredient in policy design. Although there is not a single-factor explanation for the difference in output per-worker across nations, inequality, followed by distortions to capital accumulations and them by human capital accumulation.
Resumo:
This paper considers the general problem of Feasible Generalized Least Squares Instrumental Variables (FG LS IV) estimation using optimal instruments. First we summarize the sufficient conditions for the FG LS IV estimator to be asymptotic ally equivalent to an optimal G LS IV estimator. Then we specialize to stationary dynamic systems with stationary VAR errors, and use the sufficient conditions to derive new moment conditions for these models. These moment conditions produce useful IVs from the lagged endogenous variables, despite the correlation between errors and endogenous variables. This use of the information contained in the lagged endogenous variables expands the class of IV estimators under consideration and there by potentially improves both asymptotic and small-sample efficiency of the optimal IV estimator in the class. Some Monte Carlo experiments compare the new methods with those of Hatanaka [1976]. For the DG P used in the Monte Carlo experiments, asymptotic efficiency is strictly improved by the new IVs, and experimental small-sample efficiency is improved as well.
Resumo:
Nessa tese, é buscado um maior entendimento sobre a importância das funções operacionais nas startups francesas. Uma grande flexibilidade das tarefas a ser coberta e uma gestão horizontal caracterizam as startups. Desse jeito, não é muito comum para as empresas recentemente criadas como as startups ter uma politica clara de recursos humanos. Na verdade, cada participante na start-up pode ser levado a pensar de forma diferente em termos de vendas desenvolvimento de negócios, comercialização, marketing, tecnologia ou desenvolvimento de produto. Essa tese não vai explorar cada uma dessas tarefas. Mas vai procurar para identifcar a percepção sobre a alocação ótima de recursos para cada função chave da nova empresa. Qualquer seja o setor de mercado em consideração ou o estágio de amadurecimento da startup, funções chaves que são percebidas como sendo a base para start-ups bem sucedidas são pesquisa & desenvolvimento e comercialização. Funções de liderança não são tão importantes. Somente a startup focada na tecnologia tem uma "função de chefe executivo" com maior importância do que as startups médias. Além disso, empreendedores em série, bem sucedidos ou não, focam predominantemente aspectos relacionados ao marketing e à captação de recursos em detrimento de aspectos ligados à gestão do negócio. No final, os empresários, muitas vezes tem um preconceito ao respeito da sua formação acadêmica porque ele sobrestimam funções que eles pensam poder fazer em comparação das funções que eles são capazes de fazer. Nessa tese, intent-se demonstrar a relação entre as funções ocupadas por um sócio e as ações que ele possui na startup. Essa relação depende do número de sócios (conhecido como acionistas), o tipo de sócios (acionistas principais ou acionistas segundarias) e o impacto na administração corporativa a respeito da distribuição do capital próprio.
Resumo:
We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.