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A state space representation of a linearized DSGE model implies a VAR in terms of observable variables. The model is said be non-invertible if there exists no linear rotation of the VAR innovations which can recover the economic shocks. Non-invertibility arises when the observed variables fail to perfectly reveal the state variables of the model. The imperfect observation of the state drives a wedge between the VAR innovations and the deep shocks, potentially invalidating conclusions drawn from structural impulse response analysis in the VAR. The principal contribution of this chapter is to show that non-invertibility should not be thought of as an “either/or” proposition – even when a model has a non-invertibility, the wedge between VAR innovations and economic shocks may be small, and structural VARs may nonetheless perform reliably. As an increasingly popular example, so-called “news shocks” generate foresight about changes in future fundamentals – such as productivity, taxes, or government spending – and lead to an unassailable missing state variable problem and hence non-invertible VAR representations. Simulation evidence from a medium scale DSGE model augmented with news shocks about future productivity reveals that structural VAR methods often perform well in practice, in spite of a known non-invertibility. Impulse responses obtained from VARs closely correspond to the theoretical responses from the model, and the estimated VAR responses are successful in discriminating between alternative, nested specifications of the underlying DSGE model. Since the non-invertibility problem is, at its core, one of missing information, conditioning on more information, for example through factor augmented VARs, is shown to either ameliorate or eliminate invertibility problems altogether.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

This article reviews the literature on the econometric relationship between DSGE and VAR models from the point of view of estimation and model validation. The mapping between DSGE and VAR models is broken down into three stages: (1) from DSGE to state-space model; (2) from state-space model to VAR( ∞ ); (3) from VAR( ∞ ) to finite-order VAR. The focus is on discussing what can go wrong at each step of this mapping and on critically highlighting the hidden assumptions. I also point out some open research questions and interesting new research directions in the literature on the econometrics of DSGE models. These include, in no particular order: understanding the effects of log-linearization on estimation and identification; dealing with multiplicity of equilibria; estimating nonlinear DSGE models; incorporating into DSGE models information from atheoretical models and from survey data; adopting flexible modeling approaches that combine the theoretical rigor of DSGE models and the econometric model’s ability to fit the data.

This paper aims to examine the interrelationships of monetary policy's structural shocks, the real exchange rate and stock prices.

According to quarterly data, variables such as gross domestic product, consumer price index, the real exchange rate, stock price and monetary policy indices in the structural vector autoregressions model are estimated. These variables' volatility is attributed to other variables’ structural shocks separately, and analysis of variance tables for all variables is presented.

The results show that structural shock on the exchange rate does not affect the stock price, but the monetary policy's structural shock positively impacts the real exchange rate. Moreover, the real exchange rate and monetary policy's structural shocks have a negative impact on the stock price index. However, no significant effect is found pertain to the real exchange rate structural shock, statistically.

To the best of the authors’ knowledge, the current study model is relatively novel in developing countries, and the study sought strength to develop knowledge on the subject of the study.

This paper aims to estimate the impact of the 2000s commodity boom in the major Latin American economies.

The author used a structural vector autorregresive analysis where the selection of variables is conditional on a New Keynesian Model for a small open economy.

The evidence indicates that the Argentinean nominal exchange rate appreciated less while its output and inflation grew more than those of the other nations when subjected to commodity shocks. These results are interpreted as a more aggressive leaning-against-the-wind intervention by Argentina, probably to avoid the Dutch disease. Although the effects with regard to output were indeed stronger in Argentina, this was only at the expense of higher inflation and volatility suffered during the boom.

At the time of the writing of this paper, no work had evaluated Argentinean underperformace to the manner in which its exchange rate policy was handled in comparison with the rest of the region during the boom. This paper intends to fill this gap.

The purpose of this paper is to compare responses of house prices in three important markets when faced with permanent and temporary shocks to income. It additionally decomposes each historical house price series into its permanent, temporary and deterministic components.

Using quarterly data over 1973‐2008, two‐variable systems of house prices and income are specified for three major house‐owning economies: New Zealand (NZ), the United Kingdom (UK) and the United States of America (USA).

NZ and UK housing markets are sensitive to both permanent and temporary shocks to income, while the US market reacts to temporary shocks with the permanent component having a largely insignificant role to play in house price composition. In NZ, the temporary component of house prices has tended to be positive over time, pushing prices higher than they would have been otherwise; while in the UK, both permanent and temporary components have tended to reinforce each other.

The paper uses state‐of‐the‐art methods to analyse the relationships between income and house prices in three economies.