979 resultados para VAR analysis


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In this study, we investigated the relationship of European Union carbon dioxide CO2 allowances EUAs prices and oil prices by employing a VAR analysis, Granger causality test and impulse response function. If oil price continues increasing, companies will decrease dependency on fossil fuels because of an increase in energy costs. Therefore, the price of EUAs may be affected by variations in oil prices if the greenhouse gases discharged by the consumption of alternative energy are less than that of fossil fuels. There are no previous studies that investigated these relationships. In this study, we analyzed eight types of EUAs EUA05 to EUA12 with a time series daily data set during 2005-2007 collected from a European Climate Exchange time series data set. Differentiations in these eight types were redemption period. We used the New York Mercantile Exchange light sweet crude price as an oil price. From our examination, we found that only the EUA06 and EUA07 types of EUAs Granger-cause oil prices and vice versa and other six types of EUAs do not Granger-cause oil price. These results imply that the earlier redemption period types of EUAs are more sensitive to oil price. In employing the impulse response function, the results showed that a shock to oil price has a slightly positive effect on all types of EUAs for a very short period. On the other hand, we found that a shock to price of EUA has a slightly negative effect on oil price following a positive effect in only EUA06 and EUA07 types. Therefore, these results imply that fluctuations in EUAs prices and oil prices have little effect on each other. Lastly, we did not consider the substitute energy prices in this study, so we plan to include the prices of coal and natural gas in future analyses.

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In this paper, we depart from the literature on electricity consumption–real GDP in that for the first time we examine the reaction of real GDP to shocks in electricity consumption. To achieve this goal, we use the structural vector autoregressive (SVAR) model and examine the impact of electricity consumption shocks on real GDP for the G7 countries. We find that except for the USA, electricity consumption has a statistically significant positive impact on real GDP over short horizons. This finding implies that except for the USA, electricity conservation policies will hurt real GDP in the G7 countries.

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Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

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Despite the belief, supported byrecentapplied research, thataggregate datadisplay short-run comovement, there has been little discussion about the econometric consequences ofthese data “features.” W e use exhaustive M onte-Carlo simulations toinvestigate theimportance ofrestrictions implied by common-cyclicalfeatures for estimates and forecasts based on vectorautoregressive and errorcorrection models. First, weshowthatthe“best” empiricalmodeldevelopedwithoutcommoncycles restrictions neednotnestthe“best” modeldevelopedwiththoserestrictions, duetothe use ofinformation criteria forchoosingthe lagorderofthe twoalternative models. Second, weshowthatthecosts ofignoringcommon-cyclicalfeatures inV A R analysis may be high in terms offorecastingaccuracy and e¢ciency ofestimates ofvariance decomposition coe¢cients. A lthough these costs are more pronounced when the lag orderofV A R modelsareknown, theyarealsonon-trivialwhenitis selectedusingthe conventionaltoolsavailabletoappliedresearchers. T hird, we…ndthatifthedatahave common-cyclicalfeatures andtheresearcherwants touseaninformationcriterium to selectthelaglength, theH annan-Q uinn criterium is themostappropriate, sincethe A kaike and theSchwarz criteriahave atendency toover- and under-predictthe lag lengthrespectivelyinoursimulations.

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Four-dimensional variational data assimilation (4D-Var) combines the information from a time sequence of observations with the model dynamics and a background state to produce an analysis. In this paper, a new mathematical insight into the behaviour of 4D-Var is gained from an extension of concepts that are used to assess the qualitative information content of observations in satellite retrievals. It is shown that the 4D-Var analysis increments can be written as a linear combination of the singular vectors of a matrix which is a function of both the observational and the forecast model systems. This formulation is used to consider the filtering and interpolating aspects of 4D-Var using idealized case-studies based on a simple model of baroclinic instability. The results of the 4D-Var case-studies exhibit the reconstruction of the state in unobserved regions as a consequence of the interpolation of observations through time. The results also exhibit the filtering of components with small spatial scales that correspond to noise, and the filtering of structures in unobserved regions. The singular vector perspective gives a very clear view of this filtering and interpolating by the 4D-Var algorithm and shows that the appropriate specification of the a priori statistics is vital to extract the largest possible amount of useful information from the observations. Copyright © 2005 Royal Meteorological Society

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The present study examines empirically the inflation dynamics of the euro area. The focus of the analysis is on the role of expectations in the inflation process. In six articles we relax rationality assumption and proxy expectations directly using OECD forecasts or Consensus Economics survey data. In the first four articles we estimate alternative Phillips curve specifications and find evidence that inflation cannot instantaneously adjust to changes in expectations. A possible departure of expectations from rationality seems not to be powerful enough to totally explain the persistence of euro area inflation in the New Keynesian framework. When expectations are measured directly, the purely forward-looking New Keynesian Phillips curve is outperformed by the hybrid Phillips curve with an additional lagged inflation term and the New Classical Phillips curve with a lagged expectations term. The results suggest that the euro area inflation process has become more forward-looking in the recent years of low and stable inflation. Moreover, in low inflation countries, the inflation dynamics have been more forward-looking already since the late 1970s. We find evidence of substantial heterogeneity of inflation dynamics across the euro area countries. Real time data analysis suggests that in the euro area real time information matters most in the expectations term in the Phillips curve and that the balance of expectations formation is more forward- than backward-looking. Vector autoregressive (VAR) models of actual inflation, inflation expectations and the output gap are estimated in the last two articles.The VAR analysis indicates that inflation expectations, which are relatively persistent, have a significant effect on output. However,expectations seem to react to changes in both output and actual inflation, especially in the medium term. Overall, this study suggests that expectations play a central role in inflation dynamics, which should be taken into account in conducting monetary policy.

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This thesis analyzes how matching takes place at the Finnish labor market from three different angles. The Finnish labor market has undergone severe structural changes following the economic crisis in the early 1990s. The labor market has had problems adjusting from these changes and hence a high and persistent unemployment has followed. In this thesis I analyze if matching problems, and in particular if changes in matching, can explain some of this persistence. The thesis consists of three essays. In the first essay Finnish Evidence of Changes in the Labor Market Matching Process the matching process at the Finnish labor market is analyzed. The key finding is that the matching process has changed thoroughly between the booming 1980s and the post-crisis period. The importance of the number of unemployed, and in particular long-term unemployed, for the matching process has vanished. More unemployed do not increase matching as theory predicts but rather the opposite. In the second essay, The Aggregate Matching Function and Directed Search -Finnish Evidence, stock-flow matching as a potential micro foundation of the aggregate matching function is studied. In the essay I show that newly unemployed match mainly with the stock of vacancies while longer term unemployed match with the inflow of vacancies. When aggregating I still find evidence of the traditional aggregate matching function. This could explain the huge support the aggregate matching function has received despite its odd randomness assumption. The third essay, How do Registered Job Seekers really match? -Finnish occupational level Evidence, studies matching for nine occupational groups and finds that very different matching problems exist for different occupations. In this essay also misspecification stemming from non-corresponding variables is dealt with through the introduction of a completely new set of variables. The new outflow measure used is vacancies filled with registered job seekers and it is matched by the supply side measure registered job seekers.

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It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models.

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The present work seeks to investigate the dynamics of capital account liberalization and its impact on short run capital flows to Brazil in the period of 1995-2002, considering different segments such as the monetary, derivative and equity markets. This task is pursued by developing a comparative study of financial flows and examining how it is affected by the uncovered interest parity, country risk and the legislation on portfolio capital flows. The empirical framework is based on a vector autoregressive (VAR) analysis using impulse-response functions, variance decomposition and Granger causality tests. In general terms the results indicate a crucial role played by the uncovered interest parity and the country risk to explain portfolio flows, and a less restrictive (more liberalized) legislation is not significant to attract such flows.

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The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in the borrower's decision to default or prepay on his mortgage by estimating a multinomial logit model with borrower-specific random coefficients.

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Since the abolition of the official peg and the introduction of a managed float in April 2012, the Central Bank of Myanmar has operated the daily two–way auctions of foreign exchange aimed at smoothing exchange rate fluctuations. Despite the reforms to the foreign exchange regime, however, informal trading of foreign exchange remains pervasive. Using the daily informal exchange rate and Central Bank auction data, this study examines the impacts of auctions on the informal market rate. First, a VAR analysis indicates that the official rate did not Granger cause the informal rate. Second, GARCH models indicate that the auctions did not reduce the conditional variance of the informal rate returns. Overall, the auctions have only a quite modest impact on the informal exchange rate.

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This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

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Este trabajo estima el coeficiente de pass through del tipo de cambio en los precios de bienes transables y no transables en Costa Rica, para el corto y el largo plazo. Se utiliza el análisis de mínimos cuadrados para estimar los coeficientes, y se explora la dinámica de ajuste de los modelos utilizando el análisis de vectores auto regresivo. Dentro de los principales resultados del modelo se encontró un coeficiente de pass through para los bienes transables de 13% en el corto plazo y de 68% en el largo plazo; para los bienes no transables, el pass through es de 10% y 52% en el corto y largo plazo respectivamente. En el largo plazo se incluye un 7% de pass through indirecto producto del efecto de los precios de los transables en los de no transables. El estudio de la dinámica de ajuste de los precios de transables y no transables ante un choque del tipo de cambio mostró una duración de 17 y 27 meses respectivamente. Además se realizaron pruebas de causalidad de Granger y estabilidad del modelo. La primera mostró una relación de precedencia entre las variaciones de tipo de cambio e inflación, y entre inflación de los transables y de los no transables. La segunda evidencia un cambio estructural en el modelo de los no transables entre fines de 1995 e inicio de 1996. AbstractThis paper estimates short run and long run coefficients of exchange rate pass through in to the prices of tradable and non tradable goods in Costa Rica. The coefficients are estimated by OLS. A VAR analysis is conducted in order to estimate the dynamic process between exchange rate and inflation. Granger causality test and a stability test are conducted too. The short run pass through coefficients are 13% and 10%, for tradable and non tradable goods respectively and the long run coefficients are 68% and 52% in the same order. There is a second stage pass through of 7% included in the long run coefficient for non tradable goods. The dynamic analysis shows that the adjustment process of prices as a result of an exchange rate shock takes 17 months for tradable goods and 27 months for non tradable goods. The Granger causality test shows precedence between variation in the exchange rate and inflation, and between the prices of tradable and non tradable goods. There is statistical evidence of a structural change in the non tradable model between the end of 1995 and the beginning of 1996.

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We study the macroeconomic effects of public and private investment in 17 OECD economies through a VAR analysis with annual data from 1960 to 2014. From impulse response functions we find that public investment had a positive growth effect in most countries, and a contractionary effect in Finland, UK, Sweden, Japan, and Canada. Public investment led to private investment crowding out in Belgium, Ireland, Finland, Canada, Sweden, the UK and crowding-in effects in the rest of the countries. Private investment has a positive growth effect in all countries; crowds-out (crowds-in) public investment in Belgium and Sweden (in the rest of the countries). The partial rates of return of public and private investment are mostly positive.