Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

Default mercado de crédito parcelado para bens duráveis : veículos automotores

The present work aims to study the macroeconomic factors influence in credit risk for installment autoloans operations. The study is based on 4.887 credit operations surveyed in the Credit Risk Information System (SCR) hold by the Brazilian Central Bank. Using Survival Analysis applied to interval censured data, we achieved a model to estimate the hazard function and we propose a method for calculating the probability of default in a twelve month period. Our results indicate a strong time dependence for the hazard function by a polynomial approximation in all estimated models. The model with the best Akaike Information Criteria estimate a positive effect of 0,07% for males over de basic hazard function, and 0,011% for the increasing of ten base points on the operation annual interest rate, toward, for each R$ 1.000,00 on the installment, the hazard function suffer a negative effect of 0,28% , and an estimated elevation of 0,0069% for the same amount added to operation contracted value. For de macroeconomics factors, we find statistically significant effects for the unemployment rate (-0,12%) , for the one lag of the unemployment rate (0,12%), for the first difference of the industrial product index(-0,008%), for one lag of inflation rate (-0,13%) and for the exchange rate (-0,23%). We do not find statistic significant results for all other tested variables.

European business schools and global leadership: an examination of the admission criteria of the european master in management programs ranked by the Financial Times 2010

O aumento de empresas que operam internacionalmente requer o desenvolvimento de líderes mundiais para colocar as estratégias em prática. Embora este processo de desenvolvimento é importante para o mundo corporativo, muitos futuros executivos são graduados de escolas de administração de empresas que estão intimamente ligados ao mundo de negócios e, portanto, desempenhão um papel importante no processo. Esta pesquisa examina se os programas europeus “Master in Management” classificado pelo Financial Times em 2010 selecionam aqueles candidatos que são mais adequados para o desenvolvimento de liderança global. Portanto, três anteriores meta-estudos são sintetizados para produzir um perfil de competências classificadas de um líder global. Então, informações sobre os critérios de admissão dos programas de mestrado são coletadas e comparadas com este perfil. Os resultados mostram que seis competências são medidas por mais da metade dos programas: proficiência em Inglês, capacidade analítica (racionamento lógico e quantitativo), capacidade de comunicação, conhecimento do negócio global, determinação para alcançar, motivação e capacidade interpessoal. Além disso, as habilidades operacionais requerentes pelos líderes globais não são significativas no processo de admissão e o foco é sobre as habilidades analíticas. Comparação dos resultados com o perfil anteriormente desenvolvido abrangente indica que uma quantidade significativa de programas pode subestimar o significado de habilidades pessoais e características para o desenvolvimento de líderes globais.