In this paper, we briefly describe the automatic model selection which is provided by Autometrics in the PcGive program. The modeler only needs to specify the initial model and the significance level at which to reduce the model. Then, the algorithm does the rest. The properties of Autometrics are discussed. We also explain its background concepts and try to see whether the model selected by the Autometrics can perform well. For a given data set, we use Autometrics to find a “new” model, and then compare the “new” model with a previously selected one by another modeler. It is an interesting issue to see whether Autometrics can also find models which fit better to the given data. As an illustration, we choose three examples. It is true that Autometrics is labor saving and always gives us a parsimonious model. It is really an invaluable instrument for social science. But, we still need more examples to strongly support the idea that Autometrics can find a model which fits the data better, just a few examples in this paper is far from enough.

Made available in DSpace on 2016-03-15T19:32:58Z (GMT). No. of bitstreams: 1 Marisa Gomes da Costa.pdf: 2649705 bytes, checksum: 9dfdf2c39e3c4389540dc1f3a8f8d26f (MD5) Previous issue date: 2016-02-01 / This study aims to identify the determinants of Brazil country risk level, during the period from February 1995 to August 2015, based on the deviations from the covered interest rate parity condition. These deviations represent a measure of the risk assumed by an investor who choose to invest in a Brazilian security in Brazil, rather than do it abroad. Using Autometrics, an algorithm for automatic model selection, developed by Doornik (2009), thirty-nine explanatories variables were selected from previous studies. The Brazil country risk level is susceptible to changes in the balance of payments, import by GDP, the deviation covered interest rate parity of the previous period, the inflation rate, the change in exports, total debt per GDP, and external debt by exports. / Este estudo propõe-se a identificar os fatores determinantes do nível do risco Brasil, durante o período de fevereiro de 1995 a agosto de 2015, calculado pelos desvios da condição da paridade coberta de juros. Estes desvios representam a medida do risco assumido por um investidor ao optar investir em um título brasileiro no Brasil, ao invés de fazê-lo no exterior. Utilizando a técnica de seleção automática de modelos com a aplicação do algoritmo Autometrics, desenvolvido por Doornik (2009), trinta e nove variáveis explicativas foram selecionadas a partir de estudos anteriores. O nível do risco Brasil é altamente suscetível às variações do balanço de pagamento, da importação por PIB, do desvio da condição da paridade coberta do período anterior, à taxa de inflação, à variação das exportações (em $ e em volume), à dívida total por PIB e à dívida externa pela exportação.