We develop a new asymptotic theory for autocorrelation robust tests using a vector autoregressive (VAR) covariance matrix estimator. In contrast to the conventional asymptotics where the VAR order goes to in…nity but at a slower rate than the sample size, we have the VAR order grow at the same rate, as a …xed fraction of the sample size. Under this …xed-smoothing asymptotic speci…cation, the as...

Many forecasts are conditional in nature. For example, a number of central banks routinely report forecasts conditional on particular paths of policy instruments. Even though conditional forecasting is common, there has been little work on or with methods for evaluating conditional forecasts. This paper provides analytical, Monte Carlo, and empirical evidence on tests of predictive ability for ...

Recently, a significant share of the empirical analysis on the impact of public capital on regional growth has used multivariate time-series frameworks based on vector auto regressive (VAR) models. Nevertheless, not as much attention has been dedicated to the analysis of the long-run determinants of regional growth processes using multi-region panel data and applying panel integration and co-in...

We derive a framework for asymptotically valid inference in stable vector autoregressive (VAR) models with conditional heteroskedasticity of unknown form. We prove a joint central limit theorem for the VAR slope parameter and innovation covariance parameter estimators and address bootstrap inference as well. Our results are important for correct inference on VAR statistics that depend both on t...

This paper provides a unifying framework in which the coexistence of different form of common cyclical features can be tested and imposed to a cointegrated VAR model. This goal is reached by introducing a new notion of common cyclical features, namely the weak form of polynomial serial correlation common features, which encompasses most of the previous ones. Statistical inference is obtained by...

We specify a class of non-linear and non-Gaussian models for which we estimate and forecast the conditional distributions with daily frequency. We use these forecasts to calculate VaR measures for three different equity markets (US, GB and Japan). These forecasts are evaluated on the basis of different statistical performance measures as well as on the basis of their economic costs that go alon...

This paper presents empirical evidence on the behaviour of interbank lending in Germany after a monetary policy impulse. Our VAR analysis shows that following a monetary contraction, the banking system as a whole attracts additional funds from foreign banks. Whereas small cooperative and savings banks do not seem to directly access the interbank market themselves, they do so indirectly through ...

This paper investigates the effects of government spending on the real exchange rate and the trade balance in the US using a new VAR identification procedure based on spending forecast revisions. I find that the real exchange rate appreciates and the trade balance deteriorates after a government spending shock, although the effects are quantitatively small. The findings broadly match the theore...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

E 25 26 27 28 29 30 31 32 33 34 Article history: Received 15 November 2012 Received in revised form 25 January 2013 Accepted 29 January 2013 Available online xxxx JEL classification: C15 C32 G13 G15