DSGE Models and Central Banks

Abstract

Over the past 15 years there has been remarkable progress in the specification and estimation of dynamic stochastic general equilibrium (DSGE) models. Central banks in developed and emerging market economies have become increasingly interested in their usefulness for policy analysis and forecasting. This paper reviews some issues and challenges surrounding the use of these models at central banks. It recognises that they offer coherent frameworks for structuring policy discussions. Nonetheless, they are not ready to accomplish all that is being asked of them. First, they still need to incorporate relevant transmission mechanisms or sectors of the economy; second, issues remain on how to empirically validate them; and finally, challenges remain on how to effectively communicate their features and implications to policy makers and to the public. Overall, at their current stage DSGE models have important limitations. How much of a problem this is will depend on their specific use at central banks. --DSGE models,central banks,communication m,estimation,modelling

Macroprudential Policy – A Literature Review

“…Instead, they generally assume complete markets. Moreover, they analyse deviations from steady state -where the steady state is independent of financial regulation -and do not model financial booms and busts (see Buiter, 2009 andTovar, 2008).…”

Financial Frictions and Credit Spreads

“…The financial crisis, which began in earnest in the summer of 2007, has exposed the need for macroeconomic analysis to more explicitly embed imperfections, notably financial frictions, into the canonical macro model that many academics and policy makers routinely employ in policy analysis. While the weaknesses of the canonical model (Woodford (2003)) are well-known (e.g., Goodhart (2008), Tovar (2008), Chari et al (2009)), the profession has not yet given up on this approach to the analysis of monetary policy. 1 For example, Goodfriend and McCallum (2007) show that an otherwise standard optimizing model, variants of which are now the staple of models used by central banks in policy analysis, is capable of explaining credit spreads.…”

Perspectival representation in DSGE models

“…The problem with empirical grounding or even the lack of clear meaning of the shocks notwithstanding, Romer, however, does not provide an argument to the effect that the proposed elimination will improve macroeconomic theorizing. Hence his proposed strategy may seem dubious insofar as stochastic disturbances, analyzed and computed based on the shocks to mimic actual aggregate fluctuations, form constitutive part of DSGE models, whose structural parameters yield an understanding of the mechanisms, which are fruitful for policy making (Tovar, 2009;Braun, 2017). Prima facie then we have good reasons to consider the suggested removal as a step diminishing the theoretical coherence of macroeconomic theory as embedded in the DSGEs and thus violating the criteria of empirical grounding.…”

“…Admittedly it was the advancements from RBC to DSGE, and in particular the SW models elaborated for the European Central Bank, that have significantly contributed a more widespread adoption of DSGE models in analysis and forecasting (Tovar, 2009;Kocherlakota, 2010, p. 17). Of course DSGE models may be outperformed in different aspects, such as short-term forecasting.…”