951 resultados para vector auto-regressive model


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O objetivo central desse artigo é o de propor e avaliar modelos econométricos de previsão para o PIB industrial brasileiro. Para tanto, foram utilizados diversos modelos de previsão como também combinações de modelos. Foi realizada uma analise criteriosa das séries a serem utilizadas na previsão. Nós concluímos que a utilização de vetores de cointegração melhora substancialmente a performance da previsão. Além disso, os modelos de combinação de previsão, na maioria dos casos, tiveram uma performance superior aos demais modelos, que já apresentavam boa capacidade preditiva.

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The thesis at hand adds to the existing literature by investigating the relationship between economic growth and outward foreign direct investments (OFDI) on a set of 16 emerging countries. Two different econometric techniques are employed: a panel data regression analysis and a time-series causality analysis. Results from the regression analysis indicate a positive and significant correlation between OFDI and economic growth. Additionally, the coefficient for the OFDI variable is robust in the sense specified by the Extreme Bound Analysis (EBA). On the other hand, the findings of the causality analysis are particularly heterogeneous. The vector autoregression (VAR) and the vector error correction model (VECM) approaches identify unidirectional Granger causality running either from OFDI to GDP or from GDP to OFDI in six countries. In four economies causality among the two variables is bidirectional, whereas in five countries no causality relationship between OFDI and GDP seems to be present.

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This paper contributes to the literature on aid and economic growth. We posit that it is not the levei of aid flows per se but the stability of such flows that determines the impact of aid on economic growth. Three measures of aid instability are employed. One is a simple deviation from trend, and measures overall instability. The other measures are based on auto-regressive estimates to capture deviations from an expected trend. These measures are intended to proxy for uncertainty in aid receipts. We posit that such uncertainty will influence the relationship between aid and investment and how recipient governments respond to aid, and will therefore affect how aid impacts on growth. We estimate a standard cross-country growth regression including the leveI of aid, and find aid to be insignificant (in line with other results in the literature). We then introduce measures of instability. Aid remains insignificant when we account for overall instability. However, when we account for uncertainty (which is negative and significant), we find that aid has a significant positive effect on growth. We conduct stability tests that show that the significance of aid is largely due to its effect on the volume of investment. The finding that uncertainty of aid receipts reduces the effectiveness of aid is robust. When we control for this, aid appears to have a significant positive influence on growth. When the regression is estimated for the sub-sample of African countries these findings hold, although the effectiveness of aid appears weaker than for the full sample.

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A taxa de desemprego no Brasil sofreu redução significativa do começo do século XXI até o fim do ano de 2014. No entanto, esta redução significativa não foi acompanhada do esperado crescimento econômico disposto na teoria. Desta forma, constata-se que embora a taxa de desemprego tenha se reduzido, não necessariamente as pessoas estavam trabalhando e produzindo. Procurará se entender os fatores que influenciaram esta trajetória de redução da taxa de desemprego por meio de influência na PEA e no número de admissões de empregados, que aproximaremos à oferta e à demanda por mão de obra. Ou seja, pretende-se verificar as variáveis que influenciaram uma possível redução da oferta de trabalho, assim como uma maior demanda por trabalho, resultantes em uma redução da taxa de desemprego. Serão consideradas variáveis de renda, de transferência de renda, de educação e de crescimento econômico na análise das influências da baixa taxa de desemprego. Com base em um modelo vetor de correção de erros (VEC) pretende-se identificar quais variáveis efetivamente afetaram o panorama do desemprego.

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Increasing competition caused by globalization, high growth of some emerging markets and stagnation of developed economies motivate Consumer Packaged Goods (CPGs) manufacturers to drive their attention to emerging markets. These companies are expected to adapt their marketing activities to the particularities of these markets in order to succeed. In a country classified as emerging market, regions are not alike and some contrasts can be identified. In addition, divergences of marketing variables effect can also be observed in the different retail formats. The retail formats in emerging markets can be segregated in chain self-service and traditional full-service. Thus, understanding the effectiveness of marketing mix not only in country aggregated level data can be an important contribution. Inasmuch as companies aim to generate profits from emerging markets, price is an important marketing variable in the process of creating competitive advantage. Along with price, promotional variables such as in-store displays and price cut are often viewed as temporary incentives to increase short-term sales. Managers defend the usage of promotions as being the most reliable and fastest manner to increase sales and then short-term profits. However, some authors alert about sales promotions disadvantages; mainly in the long-term. This study investigates the effect of price and in-store promotions on sales volume in different regions within an emerging market. The database used is at SKU level for juice, being segregated in the Brazilian northeast and southeast regions and corresponding to the period from January 2011 to January 2013. The methodological approach is descriptive quantitative involving validation tests, application of multivariate and temporal series analysis method. The Vector-Autoregressive (VAR) model was used to perform the analysis. Results suggest similar price sensitivity in the northeast and southeast region and greater in-store promotion sensitivity in the northeast. Price reductions show negative results in the long-term (persistent sales in six months) and in-store promotion, positive results. In-store promotion shows no significant influence on sales in chain self-service stores while price demonstrates no relevant impact on sales in traditional full-service stores. Hence, this study contributes to the business environment for companies wishing to manage price and sales promotions for consumer brands in regions with different features within an emerging market. As a theoretical contribution, this study fills an academic gap providing a dedicated price and sales promotion study to contrast regions in an emerging market.

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In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The dengue virus is transmitted in regions previously infested with the mosquito Aedes aegypti. To assess the spreading and establishment of the dengue disease vector, a mathematical model is developed that takes into account the diffusion and advection phenomena. A discrete model based on the cellular automata approach, which is a good framework to deal with small populations, is also developed to be compared with the continuous modeling.

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The study of charmonium dissociation in heavy ion collisions is generally performed in the framework of effective Lagrangians with meson exchange. Some studies are also developed with the intention of calculate form factors and coupling constants related with charmed and light mesons. These quantifies are important in the evaluation of charmonium cross sections. In this Letter we present a calculation of the omega DD vertex that is a possible interaction vertex in some meson-exchange models spread in the literature. We used the standard method of QCD sum rules in order to obtain the vertex form factor as a function of the transferred momentum. Our results are compatible with the value of this vertex form factor (at zero momentum transfer) obtained in the vector-meson dominance model. (c) 2006 Elsevier B.V. All rights reserved.

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The simultaneous investigation of the pion electromagnetic form factor in the space- and timelike regions within a light-front model allows one to address the issue of nonvalence components of the pion and photon wave functions. Our relativistic approach is based on a microscopic vector-meson-dominance model for the dressed vertex where a photon decays in a quark-antiquark pair, and on a simple parametrization for the emission or absorption of a pion by a quark. The results show an excellent agreement in the space like region up to -10 (GeV/c)(2), while in timelike region the model produces reasonable results up to 10 (GeV/c)(2).

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.

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This paper presents a new approach for damage detection in Structural Health Monitoring (SHM) systems, which is based on the Electromechanical Impedance (EMI) principle and Autoregressive (AR) models. Typical applications of EMI in SHM are based on computing the Frequency Response Function (FRF). In this work the procedure is based on the EMI principle but the results are determined through the coefficients of AR models, which are computed from the time response of PZT transducers bonded to the monitored structure, and acting as actuator and sensors at the same time. The procedure is based on exciting the PZT transducers using a wide band chirp signal and getting its time response. The AR models are obtained in both healthy and damaged conditions and used to compute statistics indexes. Practical tests were carried out in an aluminum plate and the results have demonstrated the effectiveness of the proposed method. © 2012 IEEE.

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This paper examines the interdependence between expectations and growth by analysing Uruguayan manufacturing industry, divided for the purpose into four industry groupings differentiated by trade participation and production specialization. The study shows that there is a long-run relationship between industrialists' expectations and output growth in each grouping. In the most trade-oriented groupings the relationship is one of predetermination, showing how useful expectations are as a guide to sectoral growth. Expectations in the four industrial groupings are shown to follow a common long-run trend, identified with the one guiding the export grouping. Impulse-response simulations derived from a multisectoral vector autoregression (VAR) model confirm the important role of the industries most exposed to international competition in spreading shorter-term shocks.