Working Papers

The Asset Market Channel of Market Power
(with Dalton Rongxuan Zhang)
Preliminary draft
Last updated: July 2026

Abstract
Over the past forty years, U.S. market power has risen, long-run real rates have fallen, and wealth has concentrated at the top. We propose a model in which rising market power endogenously lowers long-run rates, raises top wealth shares, and yet has only a muted effect on the long-run level of output. The asset market channel linking these aggregate trends rests on two departures from benchmark general equilibrium models of market power: 1) households hold differentiated ownership claims to market-power profits and 2) households face idiosyncratic income risk, which makes long-run asset demand imperfectly elastic. To quantify how the endogenous response of rates shapes the real effects of market power in the long run, we derive a sufficient-statistic representation of asset market clearing in terms of factor shares, relative saving propensities, asset-demand elasticity, and the tradable share of profits. The sufficient-statistic exercise and the full nonlinear transition point to the same conclusion: the asset market channel lowers the long-run return by up to 238 basis points and raises the top-1% wealth share by up to 55.5%. At the same time, long-run output falls by only 2.6%, an 86% smaller decline than in the representative-household benchmark. The asset market channel therefore dampens output losses from market power while magnifying its effects on wealth concentration.

Explaining the Macroeconomic Inertia Puzzle
Last updated: July 2025

Abstract
Benchmark macroeconomic models require additional frictions to explain the sluggish response of aggregate variables to sudden shocks or changes in policy. I show that standard heterogeneous-agent (HA) models—the Blanchard (1985) perpetual youth and Bewley (1986) incomplete markets models—are consistent with aggregate consumption inertia without the use of habit preferences or any specific model of expectation underreaction to dampen the responsiveness of consumption-savings decisions. I instead replicate observed consumption inertia in standard HA models by directly substituting survey expectations of income and interest rates for agents’ expectations. I propose a new theory of macroeconomic inertia that rationalizes the observed extrapolation bias in survey expectations by embedding an unobserved components model of expectations into a tractable HA general equilibrium environment. Inertia results when expectations imperfectly account for the equilibrium amplification of shocks, which is large in HA economies. This imperfect inference causes expectations to gradually unanchor as agents repeatedly misattribute large responses of equilibrium outcomes simply to larger shocks. This theory also illustrates a novel drawback to inertial monetary policy rules and the delayed financing of fiscal deficits: Policy regimes that act more gradually experience longer transmission lags due to their decreased effectiveness at anchoring expectations.

Optimal Long-Run Fiscal Policy with Heterogeneous Agents
(with Adrien Auclert, Matt Rognlie, and Ludwig Straub)
Last updated: September 2024

Abstract
We introduce a new method for characterizing the steady state of dynamic Ramsey problems, building on the dual approach to optimal taxation. Applying this method to standard calibrations of heterogeneous-agent models a la Aiyagari (1995), we find that in many cases Ramsey steady states do not exist, with our results suggesting that long-run immiseration is optimal instead. When Ramsey steady states do exist, they are associated with optimal long-run labor income taxes close to 100%. We show that these conclusions are related to strong anticipatory effects of future tax changes.

Work in Progress

When Predetermined Variables Can (and Should) Be Used as Instruments
(with Andrea Ferrara)

Abstract
We propose a method for using predetermined variables as instruments to estimate structural equations and provide a new justification for their exogeneity and relevance. Assuming the structural disturbance follows an ARMA process, the equation can be transformed so that sufficiently deep lags of observable variables are exogenous. To analyze instrument relevance, we consider the New Keynesian Phillips curve and contrast predetermined variables with monetary policy shocks under two equilibrium models as the slope κ → 0, a setting prone to weak identification. Under representative-agent rational expectations, both instrument sets become weak as the curve flattens: policy shocks cease to move inflation expectations, while controls absorb the predictive content of past observables. Under heterogeneous learning, firms form and update beliefs differently, creating persistent disagreement that shapes the evolution of average expectations over time. Predetermined variables predict these dynamics, which the controls do not fully span, while monetary policy shocks do not. Predetermined variables may be stronger instruments because they capture the dynamic effects of many past shocks and propagation channels, while external instruments isolate only a few. Applying our method to estimate the NKPC, monetary, and fiscal policy rules using U.S. data, we find that using predetermined variables as instruments yields stable, economically sensible coefficient estimates across a wide range of specifications.

Publications

Online Estimation of DSGE Models
(with Marco Del Negro, Edward Herbst, Ethan Matlin, Reca Sarfati, and Frank Schorfheide)
The Econometrics Journal, January 2021

Abstract
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating dynamic stochastic general equilibrium (DSGE) model posterior distributions. We show how the tempering schedule can be chosen adaptively, document the accuracy and runtime benefits of generalized data tempering for ‘online’ estimation (that is, re-estimating a model as new data become available), and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts and study the sensitivity of the predictive performance to changes in the prior distribution. We find that making priors less informative (compared with the benchmark priors used in the literature) by increasing the prior variance does not lead to a deterioration of forecast accuracy.

DSGE Forecasts of the Lost Recovery
(with Marco Del Negro, Marc P. Giannoni, Abhi Gupta, Pearl Li, & Erica Moszkowski)
International Journal of Forecasting, October-December 2019
Available ungated as a Federal Reserve Bank of New York Staff Report.

Abstract
The years following the Great Recession were challenging for forecasters. Unlike other deep downturns, this recession was not followed by a swift recovery, but instead generated a sizable and persistent output gap that was not accompanied by deflation as a traditional Phillips curve relationship would have predicted. Moreover, the zero lower bound and unconventional monetary policy generated an unprecedented policy environment. We document the actual real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model during this period and explain the results using the pseudo real-time forecasting performance results from a battery of DSGE models. We find the New York Fed DSGE model’s forecasting accuracy to be comparable to that of private forecasters, and notably better for output growth than the median forecasts from the FOMC’s Summary of Economic Projections. The model’s financial frictions were key in obtaining these results, as they implied a slow recovery following the financial crisis.