Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that...

The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to deal with this problem. Graphical models, which provide a rigorous language to analyze the statistical and logical properties of causal relations, associate a particular set of...

In this study, we explore the pass-through of exchange rate fluctuations to domestic CPI and its components for Azerbaijan, Kazakhstan and Russia. Using the data of 2003:Q1- 2016:Q2, we estimate a VAR model and find significant but incomplete pass-through in all sample countries. The accumulated...

The main goal of this research is to construct and assess forecast intervals for monthly US/EURO foreign exchange rate. The point forecasts used to build the intervals are based on a vector autoregression (VAR model) and on a Bayesian VAR model for data starting with the first month of 1999. The...

We propose a method for estimating a subset of the parameters of a structural rational expectations model by exploiting changes in policy. We define a class of models, midway between a vector autoregression and a structural model, that we call the recoverable structure. As an application of our...

In this paper we propose Granger (non-)causality tests based on a VAR model allowing for time-varying coefficients. The functional form of the time-varying coefficients is a Logistic Smooth Transition Autoregressive (LSTAR) model using time as the transition variable. The model allows for...

This paper shows how to identify the structural shocks of a Vector Autore-gression (VAR) while at the same time estimating a dynamic stochastic general equilibrium (DSGE) model that is not assumed to replicate the data generating process. It proposes a framework to estimate the parameters of the...

This paper considers the problem of forecasting real and financial macroeconomic variables across a large number of countries in the global economy. To this end, a global vector autoregressive (GVAR) model previously estimated over the 1979:Q1–2003:Q4 period by Dees, de Mauro, Pesaran, and...

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...