Evolução setorial e trajetórias tecnológicas em nível de empresas na indústria de celulose e papel no Brasil (1970 - 2004): contexto da política de substituição de importações à competição globalizada

Accordingly, a variety of firms's technological capabilities studies, the literature recently is still lacking about the dynamic of sector evolution and technological development in inter-firm and their implication for technical and economical financial performance. More lacking is the research catching up the evolution of industrial sectors after the institutional reforms in the 90. For that, the focus of the dissertation is to analyze the main of the evolution of the pulp and paper industry from 1970 to 2004, using as reference points the import-substitution policy and the economic deregulation of the 1990s. Futhermore, the work tries to evaluate how such changes at industry level have been perceived from a firm point of view in terms of accumulation of technological capabilities and improvement of economic financial performance. This linkage is tested and examined in the following firms: Aracruz (Barra do Riacho establishment ), Klabin (Monte Alegre establishment) e Votorantim Celulose e Papel ¿ VCP (Jacareí establishment), defining the same time period of sectoral level. As far as the industry level study is concerned, it is based on the average rate of annual growth of some selected variables, given that the technological capabilities test is performed according to the methodology already existing in the literature, but properly adapted to the pulp and paper case. Similarly, the analysis regarding the improvement of the economic financial performance is based on a set of industry specific indicators. Hence, the work is built upon multiple case studies, taking into account both the qualitative and quantitative evidence, i.e. interviews, direct observations, as well as firm reports. Finally, it is worth emphasizing as the analysis of the changes in the sector, in conjunction with the above mentioned methodology used to measure the technological capabilities in the context of an evolving industrial regime, is still lacking in emerging economies as well as in Brazil. According to the empirical evidence, the reforms of the 1990s had a positive impact on the industrial development, from both the national and international viewpoint. Such a transformation was evident at firm level in terms of accumulation of technological capabilities and improvement of economic financial indicators. Indeed, the results show that the speed of accumulation of technological capabilities within the firms influences positively the performance indicators. On the other hand, these are also related to external factors, such as the macroeconomic conditions, which as such have not been considered in details.

Analisando o risco de uma carteira de crédito via simulações de Monte Carlo

Neste trabalho, analisamos utilização da metodologia CreditRLsk+ do Credit Suisse sua adequação ao mercado brasileiro, com objetivo de calcular risco de uma carteira de crédito. Certas hipóteses assumidas na formulação do modelo CreditRisk+ não valem para o mercado brasileiro, caracterizado, por exemplo, por uma elevada probabilidade de defcnilt. Desenvolvemos, então, uma metodologia para cálculo da distribuição de perdas através do método de Simulação de Monte Cario, alterando algumas hipóteses originais do modelo com objetivo de adaptá-lo ao nosso mercado. utilização de simulações também oferece resultados mais precisos em situações onde as carteiras possuem uma pequena população de contratos, além de eliminar possíveis problemas de convergência do método analítico, mesmo considerando as hipóteses do modelo original. Verifica-se ainda que tempo computacional pode ser menor que da metodologia original, principalmente em carteiras com elevado número de devedores de perfis distintos com alocações em diversos setores da economia. Tendo em vista as restrições acima, acreditamos que metodologia proposta seja uma alternativa para forma analítica do modelo CreditRisk+. Apresentamos exemplos de utilização resultados providos por estas simulações. ponto central deste trabalho realçar importância da utilização de metodologias alternativas de medição de risco de crédito que incorporem as particularidades do mercado brasileiro.

Uma análise comparativa entre a metodologia analítica e a metodologia de simulação Monte Carlo para o cálculo do value at risk

O presente trabalho tem por objetivo descrever, avaliar comparar as metodologias analítica da simulação Monte Cario para cálculo do Value at Risk (Valor em Risco) de instituições financeiras de empresas. Para comparar as vantagens desvantagens de cada metodologia, efetuaremos comparações algébricas realizamos diversos testes empíricos com instituições hipotéticas que apresentassem diferentes níveis de alavancagem de composição em seus balanços, que operassem em diferentes mercados (consideramos os mercados de ações, de opções de compra de títulos de renda fixa prefixados).

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.