The literature on localised knowledge spillovers and growth focuses on the relative importance of intra vs. inter-industry externalities, but the nature and the characteristics of the dynamic linkages across manufacturing sectors are not investigated. In this Paper we perform a very...

In a situation where agents can only observe a noisy signal of the shock to future economic fundamentals, SVAR models can still be successfully employed to estimate the shock and the associated impulse response functions. Identification is reached by means of dynamic rotations of the reduced...

We introduce noisy information into a standard present value stock price model. Agents receive a noisy signal about the structural shock driving future dividend variations. The resulting equilibrium stock price includes a transitory component — the "noise bubble" — which can be responsible...

We identify government spending news and surprise shocks using a novel identification based on the Survey of Professional Forecasters. News shocks lead to an increase of the interest rate, a real appreciation of US dollar and a worsening of the trade balance. The opposite is found for the...

We derive necessary and sufficient conditions under which a set of variables is informationally sufficient, i.e. it contains enough information to estimate the structural shocks with a VAR model. Based on such conditions, we suggest a procedure to test for informational sufficiency. Moreover, we...

This paper uses a structural, large dimensional factor model to evaluate the role of 'news' shocks (shocks with a delayed effect on productivity) in generating the business cycle. We find that (i) existing small-scale VECM models are affected by 'non-fundamentalness' and therefore fail to...

We study the effects of government spending by using a structural, large dimensional, dynamic factor model. We find that the government spending shock is non-fundamental for the variables commonly used in the structural VAR literature, so that its impulse response functions cannot be...