Como gerenciar a motivação e a liderança nas organizações militares da Marinha do Brasil para alavancar a eficácia do Programa Netuno

Este estudo busca identificar os fatores que contribuem para a motivação dos indivíduos nas organizações da Marinha do Brasil e quais fatores gerenciais podem contribuir para os métodos utilizados pelo Programa Netuno nas Organizações Militares da Marinha do Brasil. A pesquisa bibliográfica foi realizada com base na literatura existente sobre o assunto e seguiu, primeiramente, uma linha histórica da procura por um Estado mais eficiente até o momento da criação dos Programas GesPública do Governo Federal e Programa Netuno da Marinha do Brasil. Foi estudado como a Motivação e a Liderança são tratadas dentro destes programas de gestão, seguindo-se uma análise de algumas das principais teorias motivacionais de processo e conteúdo: Teoria Motivacional de Abraham H. Maslow; Teoria X e Y de Douglas McGregor; Teoria de Herzberg de Dois Fatores; Teoria das Necessidades Adquiridas de McClelland; Teoria ERG de Alderfer; Teoria da Equidade de Stacy Adams; Teoria da Modificação do Comportamento Organizacional (ModCO) de Luthans e Kreitner; e Teoria da Expectância de Vroom. Além destas, foram analisadas teorias da motivação no setor público, em especial a de James Perry. Também são descritos aspectos que contextualizam as Forças Armadas no cenário mundial e o seu desdobramento na motivação do pessoal, a fim de analisar os diversos fatores que influenciam a motivação no pessoal da Marinha do Brasil, desenvolvendo-se um quadro de correlação destes fatores com os reflexos do desempenho.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

The impact of social security reform on occupational and retirement behavior : a quantitative assessment for Brazil

Population ageing is a problem that countries will have to cope with within a few years. How would changes in the social security system affect individual behaviour? We develop a multi-sectoral life-cycle model with both retirement and occupational choices to evaluate what are the macroeconomic impacts of social security reforms. We calibrate the model to match 2011 Brazilian economy and perform a counterfactual exercise of the long-run impacts of a recently adopted reform. In 2013, the Brazilian government approximated the two segregated social security schemes, imposing a ceiling on public pensions. In the benchmark equilibrium, our modelling economy is able to reproduce the early retirement claiming, the agents' stationary distribution among sectors, as well as the social security deficit and the public job application decision. In the counterfactual exercise, we find a significant reduction of 55\% in the social security deficit, an increase of 1.94\% in capital-to-output ratio, with both output and capital growing, a delay in retirement claims of public workers and a modification in the structure of agents applying to the public sector job.