848 resultados para Conditional sales
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We study the implications of the absence of arbitrage in an two period economy where default is allowed and assets are secured by collateral choosen by the borrowers. We show that non arbitrage sale prices of assets are submartingales, whereas non arbitrage purchase prices of the derivatives (secured by the pool of collaterals) are supermartingales. We use these non arbitrage conditions to establish existence of equilibrium, without imposing bounds on short sales. The nonconvexity of the budget set is overcome by considering a continuum of agents. Our results are particularly relevant for the collateralized mortgage obligations(CMO) markets.
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Esta dissertação trata inicialmente de questões relativas ao papel das políticas públicas voltadas à modernização da agricultura nos contextos internacional e brasileiro. Com efeito, procurou-se evidenciar como foram concebidos os processos de modernização agrícola assentados no produtivismo. A propósito, os problemas sócio-ambientais gerados por estas políticas propiciaram o início do debate sobre a multifuncionalidade da agricultura. No caso brasileiro, a contestação das políticas de modernização conservadora da agricultura chegando levou ao Programa Nacional de Fortalecimento da Agricultura Familiar (PRONAF), cujo público-alvo, os agricultores familiares, estiveram, em grande medida, alijados até então das políticas públicas modernizantes. Num segundo momento, chamou-se a atenção para a emergência da noção de multifuncionalidade da agricultura, particularmente no que ela pode vir a transformar os rumos do desenvolvimento rural brasileiro, além da questão da produção. Traçando paralelos com o debate da multifuncionalidade, dedicou-se um capítulo sobre a evolução das concepções em torno da propriedade fundiária: de um direito irrestrito à sua função sócio-ambiental. Na atualidade, a incorporação de demandas ambientais reorientaram essa discussão. Por outro lado, a dissertação permite também discutir o lugar do Conselho de Desenvolvimento Rural (CMDR) de Roca Sales, a partir de uma interpretação fundada nas lógicas de seu funcionamento. Destacou-se a dependência do conselho em relação a programas estaduais e federais cuja alocação de recursos exige a caução dos conselheiros do desenvolvimento rural. Enfim, procurou-se discutir as representações sociais dos atores locais, de alguma maneira implicados no conselho, sobre a agricultura e o mundo rural. Notadamente, tentou-se examinar em qual medida as preocupações com o desenvolvimento rural consideram funções não produtivas da agricultura, principalmente nas dimensões da: reprodução socioeconômica das famílias; promoção da segurança alimentar da sociedade e das próprias famílias rurais; manutenção do tecido social e cultural e preservação dos recursos naturais e da paisagem rural. Nesse sentido, puderam-se apreender nas visões dos atores locais percepções que se aproximam dos fundamentos da noção de multifuncionalidade da agricultura, principalmente quando relacionados à temas como: agroindustrialização familiar, diversificação, profissionalização do agricultor, segurança alimentar, autoconsumo e turismo rural. Com efeito, as preocupações com o desenvolvimento rural revelam propensões dos atores locais em considerar as funções não mercantis da agricultura.
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A Execução Condicional Dinâmica (DCE) é uma alternativa para redução dos custos relacionados a desvios previstos incorretamente. A idéia básica é buscar todos os fluxos produzidos por um desvio que obedecem algumas restrições relativas à complexidade e tamanho. Como conseqüência, um número menor de previsões é executado, e assim, um número mais baixo de desvios é incorretamente previsto. Contudo, tal como outras soluções multi-fluxo, o DCE requer uma estrutura de controle mais complexa. Na arquitetura DCE, é observado que várias réplicas da mesma instrução são despachadas para as unidades funcionais, bloqueando recursos que poderiam ser utilizados por outras instruções. Essas réplicas são geradas após o ponto de convergência dos diversos fluxos em execução e são necessárias para garantir a semântica correta entre instruções dependentes de dados. Além disso, o DCE continua produzindo réplicas até que o desvio que gerou os fluxos seja resolvido. Assim, uma seção completa do código pode ser replicado, reduzindo o desempenho. Uma alternativa natural para esse problema é reusar essas seções (ou traços) que são replicadas. O objetivo desse trabalho é analisar e avaliar a efetividade do reuso de valores na arquitetura DCE. Como será apresentado, o princípio do reuso, em diferentes granularidades, pode reduzir efetivamente o problema das réplicas e levar a aumentos de desempenho.
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Over the last decades, the analysis of the transmissions of international nancial events has become the subject of many academic studies focused on multivariate volatility models volatility. The goal of this study is to evaluate the nancial contagion between stock market returns. The econometric approach employed was originally presented by Pelletier (2006), named Regime Switching Dynamic Correlation (RSDC). This methodology involves the combination of Constant Conditional Correlation Model (CCC) proposed by Bollerslev (1990) with Markov Regime Switching Model suggested by Hamilton and Susmel (1994). A modi cation was made in the original RSDC model, the introduction of the GJR-GARCH model formulated in Glosten, Jagannathan e Runkle (1993), on the equation of the conditional univariate variances to allow asymmetric e ects in volatility be captured. The database was built with the series of daily closing stock market indices in the United States (SP500), United Kingdom (FTSE100), Brazil (IBOVESPA) and South Korea (KOSPI) for the period from 02/01/2003 to 09/20/2012. Throughout the work the methodology was compared with others most widespread in the literature, and the model RSDC with two regimes was de ned as the most appropriate for the selected sample. The set of results provide evidence for the existence of nancial contagion between markets of the four countries considering the de nition of nancial contagion from the World Bank called very restrictive. Such a conclusion should be evaluated carefully considering the wide diversity of de nitions of contagion in the literature.
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This paper proposes a two-step procedure to back out the conditional alpha of a given stock using high-frequency data. We rst estimate the realized factor loadings of the stocks, and then retrieve their conditional alphas by estimating the conditional expectation of their risk-adjusted returns. We start with the underlying continuous-time stochastic process that governs the dynamics of every stock price and then derive the conditions under which we may consistently estimate the daily factor loadings and the resulting conditional alphas. We also contribute empiri-cally to the conditional CAPM literature by examining the main drivers of the conditional alphas of the S&P 100 index constituents from January 2001 to December 2008. In addition, to con rm whether these conditional alphas indeed relate to pricing errors, we assess the performance of both cross-sectional and time-series momentum strategies based on the conditional alpha estimates. The ndings are very promising in that these strategies not only seem to perform pretty well both in absolute and relative terms, but also exhibit virtually no systematic exposure to the usual risk factors (namely, market, size, value and momentum portfolios).
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In this paper, we propose a class of ACD-type models that accommodates overdispersion, intermittent dynamics, multiple regimes, and sign and size asymmetries in financial durations. In particular, our functional coefficient autoregressive conditional duration (FC-ACD) model relies on a smooth-transition autoregressive specification. The motivation lies on the fact that the latter yields a universal approximation if one lets the number of regimes grows without bound. After establishing that the sufficient conditions for strict stationarity do not exclude explosive regimes, we address model identifiability as well as the existence, consistency, and asymptotic normality of the quasi-maximum likelihood (QML) estimator for the FC-ACD model with a fixed number of regimes. In addition, we also discuss how to consistently estimate using a sieve approach a semiparametric variant of the FC-ACD model that takes the number of regimes to infinity. An empirical illustration indicates that our functional coefficient model is flexible enough to model IBM price durations.
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This paper assesses whether eligibility for conditional cash transfer programs have been manipulated, as well as the impact of this phenomenon on time allocation within households. To perform this analysis, we use data from the 2006 PNAD (Brazilian national household survey) and investigate the eligibility manipulation for the Bolsa Família (Family Stipend) program during this time period. The program assists families with a monthly per capita income of around R$120.00 (US$60.00). By applying the tests developed by McCrary (2008), we find suggestive evidence that individuals manipulate their income by voluntarily reducing their labor supply in order to become eligible to the program. Moreover, the reduction in labor supply is greater among women, especially single or divorced mothers. This evidence raises some concern about the unintended consequences related to the eligibility criteria utilized by Bolsa Família, as well as the program’s impact on individuals living in extreme poverty.
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We study the effects of a conditional transfers program on school enrollment and performance in Mexico. We provide a theoretical framework for analyzing the dynamic educational decision and process inc1uding the endogeneity and uncertainty of performance (passing grades) and the effect of a conditional cash transfer program for children enrolled at school. Careful identification of the program impact on this model is studied. This framework is used to study the Mexican social program Progresa in which a randomized experiment has been implemented and allows us to identify the effect of the conditional cash transfer program on enrollment and performance at school. Using the mIes of the conditional program, we can explain the different incentive effects provided. We also derive the formal identifying assumptions needed to provide consistent estimates of the average treatment effects on enrollment and performance at school. We estimate empirically these effects and find that Progresa had always a positive impact on school continuation whereas for performance it had a positive impact at primary school but a negative one at secondary school, a possible consequence of disincentives due to the program termination after the third year of secondary school.
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This paper deals with the estimation and testing of conditional duration models by looking at the density and baseline hazard rate functions. More precisely, we foeus on the distance between the parametric density (or hazard rate) function implied by the duration process and its non-parametric estimate. Asymptotic justification is derived using the functional delta method for fixed and gamma kernels, whereas finite sample properties are investigated through Monte Carlo simulations. Finally, we show the practical usefulness of such testing procedures by carrying out an empirical assessment of whether autoregressive conditional duration models are appropriate to oIs for modelling price durations of stocks traded at the New York Stock Exchange.
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The estimation of labor supply elasticities has been an important issue m the economic literature. Yet all works have estimated conditional mean labor supply functions only. The objective of this paper is to obtain more information on labor supply, by estimating the conditional quantile labor supply function. vI/e use a sample of prime age urban males employees in Brazil. Two stage estimators are used as the net wage and virtual income are found to be endogenous to the model. Contrary to previous works using conditional mean estimators, it is found that labor supply elasticities vary significantly and asymmetrically across hours of work. vVhile the income and wage elasticities at the standard work week are zero, for those working longer hours the elasticities are negative.
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The objective of this paper is to evaluate the effect of the 1985 ”Employment Services for Ex-Offenders” (ESEO) program on recidivism. Initially, the sample has been split randomly in a control group and a treatment group. However, the actual treatment (mainly being job related counseling) only takes place conditional on finding a job, and not having been arrested, for those selected in the treatment group. We use a multiple proportional hazard model with unobserved heterogeneity for job seach and recidivism time which incorporates the conditional treatment effect. We find that the program helps to reduce criminal activity, contrary to the result of the previous analysis of this data set. This finding is important for crime prevention policy.
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Cash transfers targeted to poor people, but conditional on some behavior on their part, such as school attendance or regular visits to health care facilities, are being adopted in a growing number of developing countries. Even where ex-post impact evaluations have been conducted, a number of policy-relevant counterfactual questions have remained unanswered. These are questions about the potential impact of changes in program design, such as benefit levels or the choice of the means-test, on both the current welfare and the behavioral response of household members. This paper proposes a method to simulate the effects of those alternative program designs on welfare and behavior, based on microeconometrically estimated models of household behavior. In an application to Brazil’s recently introduced federal Bolsa Escola program, we find a surprisingly strong effect of the conditionality on school attendance, but a muted impact of the transfers on the reduction of current poverty and inequality levels.
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This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.