Marginal Distributions of Random Vectors Generated by Affine Transformations of Independent Two-Piece Normal Variables

Marginal probability density and cumulative distribution functions are presented for multidimensional variables defined by nonsingular affine transformations of vectors of independent two-piece normal variables, the most important subclass of Ferreira and Steel's general multivariate skewed distributions. The marginal functions are obtained by first expressing the joint density as a mixture of Arellano-Valle and Azzalini's unified skew-normal densities and then using the property of closure under marginalization of the latter class

Uncertainty And Risk Analysis Of Macroeconomic Forecasts: Fan Charts Revisited

Since 1996 the Bank of England (BoE) has been publishing estimates of probability distribution of the future outcomes of inflation and output growth. These density forecasts, known as "fan charts", became very popular with other central banks (e.g. Riskbank) as a tool to quantify uncertainties and risks of conditional point forecasts. The BoE's procedure is mainly a methodology to determine the distribution of a linear combination of independent random variables. In this article we propose an alternative methodology that addresses two issues with the BoE procedure that may affect the estimation of the densities. The first issue relates to a statistical shortcut taken by the BoE that implicitly considers that the mode of the linear combination of random variables is the (same) linear combination of the modes of those variables. The second issue deals with the assumption of independence, which may be restrictive. An illustration of the new methodology is presented and its results compared with the BoE approach.

Marginal Distributions of Random Vectors Generated by Affine Transformations of Independent Two-Piece Normal Variables

Marginal probability density and cumulative distribution functions are presented for multidimensional variables defined by non-singular affine transformations of vectors of independent two-piece normal variables, the most important subclass of Ferreira and Steel’s general multivariate skewed distributions. The marginal functions are obtained by first expressing the joint density as a mixture of Arellano-Valle and Azzalini’s unified skew-normal densities and then using the property of closure under marginalization of the latter class.

Determining the number of factors in approximate factor models with global and group-specific factors

For an approximate factor model, in a static representation, with a common component comprising global factors and factors specific to groups of variables, the consistency of the principal components estimator is discussed. An extension of the well known Bai and Ng criteria is proposed for determining the number of global and group-specific factors. The consistency of the suggested criteria is established and the small sample properties are assessed through Monte Carlo simulations. As an empirical illustration, the proposed criteria is applied to estimate the number of global and country-specific macroeconomic factors for the major euro area countries.

Forecasting Using Targeted Diffusion Indexes

The simplicity of the standard diffusion index model of Stock and Watson has certainly contributed to its success among practitioners resulting in a growing body of literature on factor-augmented forecasts. However, as pointed out by Bai and Ng, the ranked factors considered in the forecasting equation depend neither on the variable to be forecasted nor on the forecasting horizon. We propose a refinement of the standard approach that retains the computational simplicity while coping with this limitation. Our approach consists of generating a weighted average of all the principal components, the weights depending both on the eigenvalues of the sample correlation matrix and on the covariance between the estimated factor and the targeted variable at the relevant horizon. This "targeted diffusion index" approach is applied to US data and the results show that it outperforms considerably the standard approach in forecasting several major macroeconomic series. Moreover, the improvement is more significant in the final part of the forecasting evaluation period.

Dynamic factor models with jagged edge panel data: Taking on board the dynamics of the idiosyncratic components

The estimation of dynamic factor models for large cross-sections poses a challenge in a real time environment. As macroeconomic data become available with different delays, unbalanced panel data sets with missing values at the end of the sample period (the so-called "jagged edge") have to be handled when estimating the factor model. In this paper, we propose an EM algorithm which copes with such data sets, accounts for autoregressive common factors and allows for serial correlation in the idiosyncratic components. Based on Monte Carlo simulations, we find that taking on board the dynamics of the idiosyncratic components improves significantly the accuracy of the estimation of both the missing values and the common factors at the end of the sample period.

CONTRIBUIÇÃO DA OSTREICULTURA PARA FORMAÇÃO DA RENDA FAMILIAR: ESTUDO DE CASO DO PROJETO DE OSTREICULTURA COMUNITÁRIO DA FUNDAÇÃO ALPHAVILLE, EUSÉBIO – CEARÁ

As comunidades tradicionais da Zona Costeira do Ceará sofrem com o declínio da pesca, atividades extrativistas e pela falta de oportunidades de emprego. A ostreicultura comunitária se coloca como uma atividade produtiva sustentável e adaptada às condições ambientais locais, que pode ser explorada economicamente em regime comunitário. Neste sentido, este estudo propõe-se avaliar a rentabilidade econômica da ostreicultura comunitária e verificar em que proporção esta atividade contribui com a formação da renda familiar. Este estudo foi realizado na comunidade de Mangabeira, localizada no Município de Eusébio, Ceará, onde foi constituída uma associação produtiva voltada para o cultivo de ostras do mangue no estuário do Rio Pacoti. A metodologia consistiu primeiramente da realização de um diagnóstico socioeconômico dos membros da associação comunitária e, em seguida, das análises de custos, rentabilidade e sensibilidade da ostreicultura. Os resultados mostram que a ostreicultura comunitária exige baixos custos de investimento, proporciona elevada e robusta rentabilidade, e contribui significativamente para formação da renda familiar. -------------------------------------------------Traditional communities of Ceará Coastal Zone are suffering with the declining of fisheries and extractive production as well as lack of employment opportunities. The communitarian oyster farming is being considered as a sustainable activity and adapted to local environmental conditions which can be economically exploited through out common pool resource use. Given that, this study aims to assess the economic return of the communitarian oyster farming and verify in which proportion this activity contributes to the family income. This study was carried out in the Mangabeira community located in Eusébio, Ceará, where a productive association dedicated to mangrove oyster cultivation in the Pacoti River has been established. The methodology consisted first of carrying out a socio-economic assessment of the communitarian association and, after that, of analyzing the oyster farming costs, returns and sensitivity. The results showed that the communitarian oyster farming requires low investment costs, allows high and robust returns and contributes significantly to the familiar income formation.ostreicultura comunitária, associação, suplementação de renda, communitarian oyster farming, association, income supplementation, Community/Rural/Urban Development, Livestock Production/Industries,