Macroeconomic stabilization, monetary-fiscal interactions, and Europe's monetary union

© 2018 Elsevier B.V. The euro area recently experienced a prolonged period of weak economic activity and very low inflation. This paper reviews models of business cycle stabilization with an eye to formulating lessons for policy in the euro area. According to standard models, after a large recessionary shock accommodative monetary and fiscal policy together may be necessary to stabilize economic activity and inflation. The paper describes practical ways for the euro area to be able to implement an effective monetary-fiscal policy mix

Priors about observables in vector autoregressions

Standard practice in Bayesian VARs is to formulate priors on the autoregressive parameters, but economists and policy makers actually have priors about the behavior of observable variables. We show how to translate the prior on observables into a prior on parameters using strict probability theory principles, a posterior can then be formed with standard procedures. We state the inverse problem to be solved and we propose a numerical algorithm that works well in practical situations. We prove equivalence to a fixed point formulation and a convergence theorem for the algorithm. We use this framework in two well known applications in the VAR literature, we show how priors on observables can address some weaknesses of standard priors, serving as a cross check and an alternative formulation

Construction of multi-step forecast regions of VAR processes using ordered block bootstrap

In this study, an ordered non-overlapping block bootstrap procedure has been proposed to obtain multi-step forecast regions for unrestricted vector autoregressive models. The proposed method is not based on either backward or forward representations, so it can be implemented to VARMA or VAR-GARCH models. Also, it is computationally more efficient than the existing techniques. Its finite sample performance is investigated by Monte Carlo experiments and two-real world examples. Our findings show that the proposed method is a good alternative to the available resampling methods and produces better results for long-term forecasting when the model is near non-stationary or near-cointegrated. © 2019, © 2019 Taylor & Francis Group, LLC