992 resultados para VAR model


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The composition of the labour force is an important economic factor for a country. Often the changes in proportions of different groups are of interest. I this paper we study a monthly compositional time series from the Swedish Labour Force Survey from 1994 to 2005. Three models are studied: the ILR-transformed series, the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformation of the compositional differenced series of order 12. For each of the three models a VAR-model is fitted based on the data 1994-2003. We predict the time series 15 steps ahead and calculate 95 % prediction regions. The predictions of the three models are compared with actual values using MAD and MSE and the prediction regions are compared graphically in a ternary time series plot. We conclude that the first, and simplest, model possesses the best predictive power of the three models

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We explore the mutual dependencies and interactions among different groups of species of the plankton population, based on an analysis of the long-term field observations carried out by our group in the North–West coast of the Bay of Bengal. The plankton community is structured into three groups of species, namely, non-toxic phytoplankton (NTP), toxic phytoplankton (TPP) and zooplankton. To find the pair-wise dependencies among the three groups of plankton, Pearson and partial correlation coefficients are calculated. To explore the simultaneous interaction among all the three groups, a time series analysis is performed. Following an Expectation Maximization (E-M) algorithm, those data points which are missing due to irregularities in sampling are estimated, and with the completed data set a Vector Auto-Regressive (VAR) model is analyzed. The overall analysis demonstrates that toxin-producing phytoplankton play two distinct roles: the inhibition on consumption of toxic substances reduces the abundance of zooplankton, and the toxic materials released by TPP significantly compensate for the competitive disadvantages among phytoplankton species. Our study suggests that the presence of TPP might be a possible cause for the generation of a complex interaction among the large number of phytoplankton and zooplankton species that might be responsible for the prolonged coexistence of the plankton species in a fluctuating biomass.

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The aim of the study was to see if any relationship between government spending andunemployment could be empirically found. To test if government spending affectsunemployment, a statistical model was applied on data from Sweden. The data was quarterlydata from the year 1994 until 2012, unit-root test were conducted and the variables wheretransformed to its first-difference so ensure stationarity. This transformation changed thevariables to growth rates. This meant that the interpretation deviated a little from the originalgoal. Other studies reviewed indicate that when government spending increases and/or taxesdecreases output increases. Studies show that unemployment decreases when governmentspending/GDP ratio increases. Some studies also indicated that with an already largegovernment sector increasing the spending it could have negative effect on output. The modelwas a VAR-model with unemployment, output, interest rate, taxes and government spending.Also included in the model were a linear and three quarterly dummies. The model used 7lags. The result was not statistically significant for most lags but indicated that as governmentspending growth rate increases holding everything else constant unemployment growth rateincreases. The result for taxes was even less statistically significant and indicates norelationship with unemployment. Post-estimation test indicates that there were problems withnon-normality in the model. So the results should be interpreted with some scepticism.

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We show that incorporating the effects of exchange rate pass-through into a model can help in obtaining superior forecasts of domestic, industry-level inflation. Our analysis is based on a multivariate system of domestic inflation, import prices and exchange rates that incorporates restrictions from economic theory. These are restrictions on the transmission channels of the exchange rate pass-through to domestic prices, and are presented as testable hypotheses that lead to model reduction. We provide the results of various tests, including causality and prior restrictions, which support the underlying economic arguments and the model we use. The forecasting results for our model suggest that it has a superior performance overall, jointly producing more accurate forecasts of domestic inflation.

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Public capital has been considered to be the wheels of economic activity in a nation or region. The reverse effect, the contribution of economic growth to public capital, is also worth analysis. The non-structural vector auto-regression (VAR) approach is performed for the Australian economy using yearly data for the 1960-2008 period. The optimal lag is investigated to build the VAR model that is then tested for stability. The impulse response function is further employed to examine the response of one economic variable to the innovation of others and to determine the lagged terms for the maximum absolute value of the other variables’ responses. The results will provide historical evidence for the federal and regional governments of Australia to estimate the effects of these production variables, in particular, the effect of infrastructure spending on the gross domestic product.

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Many test results are found inconsistent with the expectations hypothesis of the term structure. The aim of this paper is to re-examine the expectations hypothesis of the term structure using the Australian interest rate data from 1969(7) to 1995(7). We start with the cointegration test on Rt, rt, and St followed by the Granger causality test from St to ∇ rt. Finally we carry out the VAR model of cross-equation restrictions test. Our findings show that there is no conclusive rejection of the expectations hypothesis of the term structure.

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Purpose – The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

Design/methodology/approach – The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short-term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

Findings –
The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre-shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

Practical implications –
The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

Originality/value – For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

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This research empirically investigates the impact of monetary policy on the housing market in Australia from 1996 to 2009. Three primary variables associated with the housing sector and monetary policy, including interest rates, money supply and house prices, are estimated by a structural vector autoregression (VAR) model. Depending upon the analysis using the impulse response function, it can be identified that monetary policy significantly affects the housing market in Australia by the adjustments in interest rates and money supply. The empirical results from this study may be useful for policy makers to enact appropriate policies in relation to the infrastructure planning.

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This thesis is composed of three essays referent to the subjects of macroeconometrics and Önance. In each essay, which corresponds to one chapter, the objective is to investigate and analyze advanced econometric techniques, applied to relevant macroeconomic questions, such as the capital mobility hypothesis and the sustainability of public debt. A Önance topic regarding portfolio risk management is also investigated, through an econometric technique used to evaluate Value-at-Risk models. The Örst chapter investigates an intertemporal optimization model to analyze the current account. Based on Campbell & Shillerís (1987) approach, a Wald test is conducted to analyze a set of restrictions imposed to a VAR used to forecast the current account. The estimation is based on three di§erent procedures: OLS, SUR and the two-way error decomposition of Fuller & Battese (1974), due to the presence of global shocks. A note on Granger causality is also provided, which is shown to be a necessary condition to perform the Wald test with serious implications to the validation of the model. An empirical exercise for the G-7 countries is presented, and the results substantially change with the di§erent estimation techniques. A small Monte Carlo simulation is also presented to investigate the size and power of the Wald test based on the considered estimators. The second chapter presents a study about Öscal sustainability based on a quantile autoregression (QAR) model. A novel methodology to separate periods of nonstationarity from stationary ones is proposed, which allows one to identify trajectories of public debt that are not compatible with Öscal sustainability. Moreover, such trajectories are used to construct a debt ceiling, that is, the largest value of public debt that does not jeopardize long-run Öscal sustainability. An out-of-sample forecast of such a ceiling is also constructed, and can be used by policy makers interested in keeping the public debt on a sustainable path. An empirical exercise by using Brazilian data is conducted to show the applicability of the methodology. In the third chapter, an alternative backtest to evaluate the performance of Value-at-Risk (VaR) models is proposed. The econometric methodology allows one to directly test the overall performance of a VaR model, as well as identify periods of an increased risk exposure, which seems to be a novelty in the literature. Quantile regressions provide an appropriate environment to investigate VaR models, since they can naturally be viewed as a conditional quantile function of a given return series. An empirical exercise is conducted for daily S&P500 series, and a Monte Carlo simulation is also presented, revealing that the proposed test might exhibit more power in comparison to other backtests.

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O presente estudo apresenta um modelo de previsão do preço e do volume comercializado no mercado transoceânico de minério de ferro. Para tanto, foi desenvolvido um modelo VAR, utilizando, além das variáveis endógenas com um lag de diferença, o preço do petróleo Brent e um índice de produção industrial. Após testar raiz unitária das variáveis e constatar que nenhuma era estacionária, o teste de cointegração atestou que existia relação de longo prazo entre as mesmas que era estacionária, afastando a possibilidade de uma regressão espúria. Como resultado, a modelagem VAR apresentou um modelo consistente, com elevada aderência para a previsão do preço e do volume negociado de minério de ferro no mercado transoceânico, não obstante ele tenha apresentado alguma imprecisão no curto prazo.

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O objetivo desse artigo é analisar o impacto da política fiscal sobre diversas variáveis macroeconômicas dos EUA. A metodologia do trabalho empírico baseia-se em um modelo VAR estrutural que incorpora fatores latentes (FAVAR) e para o qual desenvolve-se um esquema de identificação específico. Visto que os fatores são estimados por principal components, estes aproximam-se muito das séries observadas de produção industrial e taxa de juros. Como será visto, este resultado é de fundamental importância para a hipótese de identificação e a escolha dos instrumentos do modelo VAR. Por meio das funções de resposta ao impulso analisa-se os efeitos de um aumento do gasto do governo sobre variáveis de produto e consumo e, por sua vez, corroborando a hipótese de que tanto o PIB quanto as despesas de consumo das famílias aumentam depois desse choque exógeno. Em particular esse efeito sobre o consumo também é verificado quando separamos os indivíduos em várias classes de acordo com renda. Olhando cuidadosamente no entanto pode-se perceber que um aumento no gasto público possui mais impacto sobre os consumidores de renda mais baixa. Ou seja, é provável que por estarem sujeitas a restrições de crédito, as classes mais baixas tem mais dificuldade em suavizar o consumo após um choque agregado.

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Este estudo tem como objetivo determinar os principais fatores macroeconômicos que influenciam a formação do preço de imóveis, tomando como base o mercado imobiliário residencial da cidade de São Paulo entre os anos de 2001 e 2012. Para capturar o efeito endógeno do PIB, da taxa de juros e da bolsa de valores sobre o preço de imóveis, optou-se por um modelo VAR. Concluiu-se que, dentre as variáveis, o PIB foi o fator mais preponderante na formação do preço, chegando a ter um impacto quase três vezes superior à taxa de juros. Não foram encontradas evidências estatísticas significativas do efeito da bolsa sobre o preço dos imóveis. Constatou-se ainda que choques no PIB e na taxa de juros demoram, no mínimo, um ano para começarem a refletir sobre o preço. Essas conclusões foram mais robustas no período anterior à crise imobiliária americana de 2008.

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A persistência da inflação de serviços no Brasil entre 2005 e 2013, e forte alteração do preço relativo entre preços de serviços e preços de comercializáveis coincidiu temporalmente com forte aumento da renda nominal da população e queda do desemprego. Esta dissertação tem como objetivo identificar os fatores que foram mais importantes na formação dos preços dos serviços e se os salários contribuíram para a aceleração dos preços através do aumento de custos no setor ou através do aumento da demanda por estes itens. A partir de um modelo VAR com variáveis exógenas de controle para custos e para a demanda, o estudo conclui que as pressões de custo foram mais importantes para explicar o comportamento da inflação de serviços no Brasil no período considerado.

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O objetivo deste estudo é avaliar a propagação de choques econômicos de alguns países sobre o crescimento econômico brasileiro, com principal destaque para China, Estados Unidos da América (EUA) e Argentina, que são os principais parceiros comerciais do Brasil. O aumento do comércio com a China tornou o Brasil muito mais vulnerável a choques no PIB chinês e menos vulnerável, do que no passado recente, a choques no PIB americano, enquanto que a influência da Argentina manteve-se estável. Foi aplicada a metodologia Vetor Autorregressivo Global (Global Var – GVAR), introduzida por Pesaran, Schuermann e Weiner (2004), Garratt, Lee, Pesaran e Shin (2006) e Dées, Di Mauro, Pesaran e Smith (2007), para analisar os canais de comércio e a transmissão de choques entre o resto do mundo e o Brasil. Usando dados trimestrais a partir de 1990 até o final de 2013, foi possível constatar que o aumento da relevância da economia Chinesa na balança comercial Brasileira exerce pressão sobre o crescimento econômico do Brasil. Em suma, a China tornou-se mais relevante para o crescimento econômico do Brasil do que os EUA e a Argentina.