The identification of reduced-form VAR model had been the subject of numerous debates in the literature. Different sets of identifying assumptions can lead to very different conclusions in the policy debate. This paper proposes a theoretical consistent identification strategy using restrictions implied by a DSGE model. Monte Carlo simulations suggest the proposed identification strategy is succ...

Vector autoregressive model is a very popular tool in multiple time series analysis. Its parameters are usually estimated by the least squares procedure which is very sensitive to the presence of errors in data, e.g. outliers. If outliers were present, the estimation results would become unreliable. Therefore in the presented paper we will propose a new procedure for estimating multivariate reg...

This paper pursues an econometric investigation of the interactions between Japan’s housing investment and gross domestic product (GDP). A cointegrated vector autoregressive (VAR) analysis of Japan’s recent time series data reveals two cointegrating relationships, which characterize the underlying long-run interactions of the variables in question. The cointegrated VAR model is then reduced to ...

This paper proposes several parametric models to compute the portfolio VaR and CVaR in a given temporal horizon and for a given level of confidence. Firstly, we describe extension of the EWMA RiskMetrics model considering conditional elliptically distributed returns. Secondly, we examine several new models based on different stable Paretian distributional hypotheses of return portfolios. Finall...

Mainly due to new capital adequacy standards for banking and insurance, an increased interest exists in the aggregation properties of risk measures like Value-atRisk (VaR). We show how VaR can change from subto superadditivity depending on the properties of the underlying model. Mainly, the switch from a finite to an infinite mean model gives a completely different asymptotic behaviour. Our mai...

Direct measures of expectations, derived from survey data, are used in a Vector Autoregressive (VAR) model of actual and expected output series in eight industrial sectors comprising UK Manufacturing. Through the application of the Beveridge-Nelson decomposition, the VAR model is used to measure trend output in the Manufacturing Sector. This measure is compared with alternative trend measures o...

A positive technology shock may lead to a rise or a fall in per capita hours, depending on how hours enter the empirical VAR model. We provide evidence that, independent of how hours enter the VAR, a positive technology shock leads to a weak response in nominal wage inflation, a modest decline in price inflation, and a modest rise in the real wage in the short-run and a permanent rise in the lo...

This paper tests the ability of popular New Keynesian models, which are traditionally used to study monetary policy and business cycles, to match the data regarding a key channel for monetary transmission: the dynamic interactions between macroeconomic variables and their corresponding expectations. In the empirical analysis, we exploit direct data on expectations from surveys. To explain the j...

This paper describes alternative approaches to estimate the Value at Risk (VaR) of a position. Four methods are compared: the unconditional case, the model with time varying drift (modeled as an AR(l) process), the model with time varying drift and time varying volatility (modeled as a GARCH(I,l) process) with error terms that are normally distributed, and the model with time varying drift and ...

When dealing with market risk under the Basel II Accord, variation pays in the form of lower capital requirements and higher profits. Typically, GARCH type models are chosen to forecast Value-at-Risk (VaR) using a single risk model. In this paper we illustrate two useful variations to the standard mechanism for choosing forecasts, namely: (i) combining different forecast models for each period,...