Abstract: We take an off-the-shelf model with financial frictions and heterogeneity,
and study the mapping from a credit crunch, modeled as a
shock to collateral constraints, to simple aggregate wedges. We study
three variants of this model that only differ in the form of underlying
heterogeneity. We find that in all three model variants a credit
crunch shows up as a different wedge: efficiency, investment, and
labor wedges. Furthermore, all three model variants have an undistorted
Euler equation for the aggregate of firm owners. These results
highlight the limitations of using representative agent models to
identify sources of business cycle fluctuations.

Full article can be found here.

Abstract: We develop a rational expectations framework to study the consequences of alternative means to resolve the “unfunded liabilities” problem—unsustainable exponential growth in federal Social Security, Medicare, and Medicaid spending with no plan to finance it. Resolution requires specifying a probability distribution for how and when monetary and fiscal policies will change as the economy evolves through the 21st century. Beliefs based on that distribution determine the existence of and the nature of equilibrium. We consider policies that in expectation combine reaching a fiscal limit, some distorting taxation, modest inflation, and some reneging on the government’s promised transfers. In the equilibrium, inflation-targeting monetary policy cannot successfully anchor expected inflation. Expectational effects are always present, but need not have large impacts on inflation and interest rates in the short and medium runs.

Full article can be found here.

Abstract: I investigate the extent to which modern Dynamic Stochastic General Equilibrium
(DSGE) models can produce labor market dynamics in response to a financial crisis
that are consistent with the experience of the Great Recession. Using the methods of
Boivin and Giannoni (2006) and Kryshko (2011), I estimate two DSGE models in a
data-rich environment. This allows me to examine the dynamics of economic series not
obtainable in traditional DSGE model estimation. I find that negative financial shocks
are associated with longer recoveries in real investment, capital intensive sectors of the
labor market and average unemployment duration when compared to other negative
output shocks. These results hold when the recession magnitude is normalized across
the shocks. The two models estimated in this paper include close variations of the
Smets & Wouters (2003, 2007) New Keynesian model and the FRBNY (Del Negro et
al. 2013) model that augments the Smets & Wouters model with a financial accelera-
tor. I find the FRBNY model with a financial accelerator is equipped with better tools
to identify the dynamics associated with the Great Recession and its recovery in regard
to many labor and financial metrics including the unemployment rate, total number of
employees by sector and consumer loans.

Full article can be found here.

Abstract: Analytical or coding errors in posterior simulators can produce reasonable but incorrect approximations of posterior moments. This article develops simple tests of posterior simulators that detect both kinds of errors, and uses them to detect and correct errors in two previously published articles. The tests exploit the fact that a Bayesian model specifies the joint distribution of observables (data) and unobservables (parameters). There are two joint distribution simulators. The marginal-conditional simulator draws unobservables from the prior and then observables conditional on unobservables. The successive-conditional simulator alternates between the posterior simulator and an observables simulator. Formal comparison of moment approximations of the two simulators reveals existing analytical or coding errors in the posterior simulator.

Full article available here.

Abstract: This paper examines the macroeconomic dynamics of the
2007–09 recession in the United States and the subsequent slow recovery.
Using a dynamic factor model with 200 variables, we reach three main conclusions.
First, although many of the events of the 2007–09 collapse were unprecedented,
their net effect was to produce macro shocks that were larger versions
of shocks previously experienced, to which the economy responded in a historically
predictable way. Second, the shocks that produced the recession were
primarily associated with financial disruptions and heightened uncertainty,
although oil shocks played a role in the initial slowdown, and subsequent drag
was added by effectively tight conventional monetary policy arising from the
zero lower bound. Third, although the slow nature of the recovery is partly due
to the shocks of this recession, most of the slow recovery in employment, and
nearly all of the slow recovery in output, is due to a secular slowdown in trend
labor force growth.

Full paper can be found here.

Abstract: We examine global dynamics under learning in New Keynesian models
wheremonetary policy practices either price-level or nominal GDP targeting
and compare these regimes to inflation targeting. The interest-rate rules are
subject to the zero lower bound. The domain of attraction of the targeted
steady state is proposed as a new robustness criterion for a policy regime.
Robustness of price-level and nominal GDP targeting depends greatly on
whether forward guidance in these regimes is incorporated in private agents’
learning. We also analyze volatility of inflation, output and interest rate
during learning adjustment for the different policy regimes.

Full paper can be found here.

Abstract: The standard new Keynesian models predicts that temporary, negative supply shocks are expansionary at the zero lower bound (ZLB) because they raise inflation expectations and lower expected real interest rates, which stimulates consumption. This paper tests that prediction with oil supply shocks and the Great East Japan earthquake, demonstrating that negative supply shocks are contractionary at the ZLB despite also lowering expected real interest rates. A model with borrowing-constrained agents can match these findings for certain parameters, but simultaneously eliminates the channel by which the standard new Keynesian model generates fiscal multipliers above 1.

Full paper can be found here.

Sentiments and Aggregate Demand Fluctuations

Abstract: We formalize the Keynesian insight that aggregate demand driven by sentiments can generate output fluctuations under rational expectations. When production decisions must be made under imperfect information about demand, optimal decisions based on sentiments can generate stochastic self-fulfilling rational expectations equilibria in standard economies without persistent informational frictions, externalities, nonconvexities, or strategic complementarities in production. The models we consider are deliberately simple, but could serve as benchmarks for more complicated equilibrium models with additional features.

Full paper can be found here.

Synchronization and Bias in a Simple Macroeconomic Model

Abstract: In models with strategic uncertainty, such as macroeconomic models with multiple equilibria, agents must form beliefs about the actions of other players. In sunspot models agents coordinate by using an exogenous stochastic process, which is not inherently related to the fundamentals of the economy. I consider such a model with multiple equilibria, and assume that agents must learn to use the sunspot variables. I show that if different agents measure output with a slight bias (though the average bias in the economy vanishes), this leads to a complex nonlinear dynamic of synchronization of beliefs about the equilibrium being played. The economy fluctuates between long eras where the agents beliefs are almost homogenous and therefore they are coordinated on the use of the sunspots, and eras of dispersed beliefs where the coordination mechanism fails. I show that the equation describing the evolution of the economy is similar to the Kuramoto model, a prototypical model of synchronization phenomena, and make some first attempts at mapping the connections.

Full paper can be found here.

Presentation highlights:

-Specifying and estimating state space models in Python

-Specifying, solving, and estimating (log-linearized) DSGE models in Python

Full presentation can be found here.