DSGE Models Used by Policymakers: A Survey

October 28, 2020

By Takeshi Yagihashi


The paper conducts a comprehensive survey on the current state of the dynamic stochastic general equilibrium (DSGE) models developed by policy institutions, including central banks, government agencies, and international organizations around the world. Our main sample consists of 84 models developed by 58 institutions, and many of them were developed or updated after the 2008 financial crisis. We first document the evolution of macroeconomic models used for policy purpose, and then provide summary statistics on the models by type of institution, region, and number of authors of the publication. We find that there is a steady increase in the development of DSGE models by policy institutions. While central banks have been the main users of DSGE models, more government agencies in Europe have been actively developing their own DSGE models in the years following the 2008 Global Financial Crisis. We also find that some institutions have multiple DSGE models serving different purposes. Next, we narrow our focus to a subset of 42 models that are owned and actively used by policy institutions, and conduct a model comparison based on five key model features. Although the models share common basic structures, there are large variations in parameter values and modelling strategies, some of which do not necessarily reflect the findings of the empirical literature. Finally, we create a score card for each model depending on whether the model incorporated recent empirical findings on the five model features. Two models have a score of 4 out of 5, and the overall average is 2.21. In conclusion, there is a greater need for future DSGE policy models to adopt more recent findings in the empirical literature.

There is widely held belief that DSGE models are not used in policymaking. This is far from the truth, and this papers gives a nice compilation of some of the uses in ministries, central banks, and international organizations. As I have shown several times on this blog, they are incredibly powerful for understanding scenarios, especially when one faces a historically new situation, when there is a lack of data, or when one needs to disentangle several shocks.


The limits to robust monetary policy in a small open economy with learning agents

October 26, 2020

By André Marine Charlotte and Dai Meixing


We study the impact of adaptive learning for the design of a robust monetary policy using a small open-economy New Keynesian model. We find that slightly departing from rational expectations substantially changes the way the central bank deals with model misspecification. Learning induces an intertemporal trade-off for the central bank, i.e., stabilizing inflation (output gap) today or stabilizing it tomorrow. The central bank should optimally anchoring private agents expectations in the short term in exchange of easier future intratemporal trade-offs. Compared to the rational expectations equilibrium, the possibility to conduct robust monetary policy is limited in a small open economy under learning for any exchange rate pass-through level and any degree of trade openness. The misspecification that can be introduced into all equations of the model is lower in a small open economy, and approaches zero at high speed as the learning gain rises.

Central banking is hard: so much is endogenous and based on expectations and incomplete information. This paper shows that if there is learning in play, this is doubly difficult. And still, in this model there is complete certainty about interest rates. Imagine when that is not the case.

Uncertainty and Monetary Policy during Extreme Events

October 23, 2020

By Giovanni Pellegrino, Efrem Castelnuovo and Giovanni Caggiano


How damaging are uncertainty shocks during extreme events such as the great recession and the Covid-19 outbreak? Can monetary policy limit output losses in such situations? We use a nonlinear VAR framework to document the large response of real activity to a financial uncertainty shock during the great recession. We replicate this evidence with an estimated DSGE framework featuring a concept of uncertainty comparable to that in our VAR. We employ the DSGE model to quantify the impact on real activity of an uncertainty shock under different Taylor rules estimated with normal times vs. great recession data (the latter associated with a stronger response to output). We find that the uncertainty shock-induced output loss experienced during the 2007-09 recession could have been twice as large if policymakers had not responded aggressively to the abrupt drop in output in 2008Q3. Finally, we use our estimated DSGE framework to simulate different paths of uncertainty associated to different hypothesis on the evolution of the coronavirus pandemic. We find that: i) Covid-19-induced uncertainty could lead to an output loss twice as large as that of the great recession; ii) aggressive monetary policy moves could reduce such loss by about 50%.

Thus, public policy can be effective at alleviating (partially) large shocks that hit an economy, in particular by being flexible to react to uncertain events. That seems a good description of what fiscal and monetary policy can do. And the main thing monetary policy should do. Fiscal policy can have other goals, too.

A Structural Model of the Labor Market to Understand Gender Gaps among Marginalized Roma Communities

October 19, 2020

By Mauricio Salazar-Saenz and Monica Robayo


This paper constructs and estimates a household-level search model to analyze Roma spouses’ utility maximization for leisure, home production, and work. The paper aims to explain labor market gender gaps in a marginalized Roma population with low labor market participation rates (males 53 percent and females 17 percent). The analysis uses data from the 2017 Regional Roma Survey for six Western Balkan countries. The simulation results show that the main source for gender differentials in the labor market is the unequal opportunities in favor of males — not gender preferences or differences in home production productivity. Therefore, most of the gender differences in the labor market can be closed by providing wives the same labor market conditions as husbands. Counterfactual policy experiments show that policies that increase the frequency of receiving a job offer, decrease the frequency of laying off workers, and reduce search increase Roma husbands’ labor participation. Policies that equalize wages induces more wives to join the labor market and husbands to withdraw from it. This outcome signals that the wage gap is the dimension that deters the greatest number of Roma wives from joining the labor market.

There are two reasons I highlight this particular paper this week. The first is the rather unusual topic that actually fits very well for the modelling strategy. DSGE models are actually great tools in unusual setups where data or information may be lacking. Theory does wonders in such situations! The second reason is that I love how the paper is written. Each paragraph is introduced by one sentence in bold that summarizes it. Great for quick reading and getting additional details when you want them.