We develop a two-country New Keynesian model with sticky local currency pricing,distribution costs and a demand elasticity increasing with the relative price. These features help to reduce the exchange rate pass-through to import price at the border and down the chain towards consumption price,...

How long does it take for exchange rate changes to pass through into inflation? Does it make a difference whether the exchange rate depreciates or appreciates? Do relatively large exchange rate changes entail more exchange rate pass-through? In this paper, we examine possible non-linearities in...

How long does it take for exchange rate changes to pass through into inflation? Does it make a difference whether the exchange rate depreciates or appreciates? Do relatively large exchange rate changes entail more exchange rate pass-through? In this paper, we examine possible non-linearities in...

How long does it take for exchange rate changes to pass through into in ation? Does it make a difference whether the exchange rate depreciates or appreciates? Do relatively large exchange rate changes entail more exchange rate pass-through? In this paper, we examine possible non-linearities in...

Implied volatility index of the S&P500 is considered as a dependent variable in a fractionally integrated ARMA model, whereas volatility measures based on interday and intraday datasets are considered as explanatory variables. The next trading day’s implied volatility forecasts provide...

This paper conducts a broad-based comparison of iterated and direct multi-period forecasting approaches applied to both univariate and multivariate models in the form of parsimonious factor-augmented vector autoregressions. To account for serial correlation in the residuals of the multi-period...

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

In this paper, we propose a Bayesian estimation and prediction procedure for noncausal autoregressive (AR) models. Specifically, we derive the joint posterior density of the past and future errors and the parameters, which gives posterior predictive densities as a byproduct. We show that the...

This paper addresses the issue of improving the forecasting performance of vector autoregressions (VARs) when the set of available predictors is inconveniently large to handle with methods and diagnostics used in traditional small-scale models. First, available information from a large dataset...

A path forecast refers to the sequence of forecasts 1 to H periods into the future. A summary of the range of possible paths the predicted variable may follow for a given confidence level requires construction of simultaneous confidence regions that adjust for any covariance between the elements...