New-Keynesian models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack of...

There is growing awareness that the distribution of IMF facilities may not be influenced only by the economic needs of the borrowers. This paper focuses on the fact that the IMF may favour geopolitically important countries in the distribution of IMF loans, differentiating between concessional...

In this paper, we study the dynamics and drivers of sovereign bond yields in euro area countries using a factor model with time-varying loading coeffi cients and stochastic volatility, which allows for capturing changes in the pricing mechanism of bond yields. Our key contribution is exploring...

The curse of dimensionality, a problem associated with analyzing the interaction of a relatively large number of endogenous macroeconomic variables, is a prevailing issue in the open economy macro literature. The most common practise to mitigate this problem is to apply the so-called Small Open...

This paper extends the analysis of infinite dimensional vector autoregressive models (IVAR) proposed in Chudik and Pesaran (2010) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. This extension is not straightforward and involves...

We develop a high-dimensional and partly nonlinear non-Gaussian dynamic factor model for the decomposition of systematic default risk conditions into a set of latent components that correspond with macroeconomic/financial, default-specific (frailty), and industry-specific effects. Discrete...

While the usefulness of factor models has been acknowledged over recent years, little attention has been devoted to the forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor models over different samples, including the...

This paper describes an algorithm to compute the distribution of conditional forecasts, i.e. projections of a set of variables of interest on future paths of some other variables, in dynamic systems. The algorithm is based on Kalman filtering methods and is computationally viable for large...

We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be observed at different time frequencies, may have missing observations, and may exhibit common...

This paper analyses the importance of common factors in shaping non-fuel commodity price movements for the period 1957-2008. For this purpose, a dynamic factor model is estimated using Kalman Filtering techniques. Based on this set-up we are able to separate common and idiosyncratic developments...