Regional or educational disparities? a counterfactual exercise

This work investigates the impact of schooling Oil income distribution in statesjregions of Brazil. Using a semi-parametric model, discussed in DiNardo, Fortin & Lemieux (1996), we measure how much income diíferences between the Northeast and Southeast regions- the country's poorest and richest - and between the states of Ceará and São Paulo in those regions - can be explained by differences in schooling leveIs of the resident population. Using data from the National Household Survey (PNAD), we construct counterfactual densities by reweighting the distribution of the poorest region/state by the schooling profile of the richest. We conclude that: (i) more than 50% of the income di:fference is explained by the difference in schooling; (ii) the highest deciles of the income distribution gain more from an increase in schooling, closely approaching the wage distribution of the richest region/state; and (iii) an increase in schooling, holding the wage structure constant, aggravates the wage disparity in the poorest regions/ states.

Modelagem paramétrica de curvas de crédito no mercado brasileiro

Após a crise financeira de 2008, é perceptível a intensificação de esforços globais para aperfeiçoar métodos de avaliação de risco e ajuste de exposição de capital para tornar o sistema financeiro mundial mais sólido e consistente. O objetivo deste trabalho é propor um modelo de estimação de curvas de crédito privado no Brasil, aplicando a modelagem paramétrica de Nelson & Siegel (1987) a uma amostra de preços de debêntures. Os resultados obtidos poderão ser utilizados para auxiliar reguladores e profissionais de mercado com análises de risco, apreçamento de ativos ilíquidos e percepção de expectativas.

Tree-structured smooth transition models

The goal of this paper is to introduce a class of tree-structured models that combines aspects of regression trees and smooth transition regression models. The model is called the Smooth Transition Regression Tree (STR-Tree). The main idea relies on specifying a multiple-regime parametric model through a tree-growing procedure with smooth transitions among different regimes. Decisions about splits are entirely based on a sequence of Lagrange Multiplier (LM) tests of hypotheses.

All-pay auctions with endogenous asymmetries

We study N-bidders, asymmetric all-pay auctions under incomplete information. First, we solve for the equilibrium of a parametric model. Each bidder’s valuation is independently drawn from an uniform [0, αi] where the parameter αi may vary across bidders. In this game, asymmetries are exogenously given. Next, a two-stage game where asymmetries are endogenously generated is studied. At the first stage, each bidder chooses the level of an observable, costly, value-enhancing action. The second stage is the bidding sub-game, whose equilibrium is simply the equilibrium of the, previously analyzed, game with exogenous asymmetries. Finally, natural applications of the all pay-auction in the context of political lobbying are considered: the effects of excluding bidders, as well as, the impact of caps on bids.

Análise de performance de fundos de investimento multimercado no Brasil

O objetivo deste trabalho é verificar se os fundos de investimento Multimercado no Brasil geram alphas significativamente positivos, ou seja, se os gestores possuem habilidade e contribuem positivamente para o retorno de seus fundos. Para calcular o alpha dos fundos, foi utilizado um modelo com sete fatores, baseado, principalmente, em Edwards e Caglayan (2001), com a inclusão do fator de iliquidez de uma ação. O período analisado vai de 2003 a 2013. Encontramos que, em média, os fundos multimercado geram alpha negativo. Porém, apesar de o percentual dos que geram interceptos positivos ser baixo, a magnitude dos mesmos é expressiva. Os resultados diferem bastante por classificação Anbima e por base de dados utilizada. Verifica-se também se a performance desses fundos é persistente através de um modelo não-paramétrico baseado em tabelas de contingência. Não encontramos evidências de persistência, nem quando separamos os fundos por classificação.

The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

A (semi-)parametric functional coefficient autoregressive conditional duration model

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.