Working Papers
The Fragility of Government Funding Advantage
(previously circulated as “Convenience Yields and Financial Repression”)
(with Jonathan Payne)
[PDF, March 2025]
US federal debt plays a special role in the US economy and so gives the US government a funding advantage, often summarized by the spread between the yield on high-grade US corporate bonds and comparable US treasuries. Why? One reason is that government regulation (and/or repression) of the financial sector influences asset pricing and helps make long term US federal debt an endogenously “safe-asset”. We study the mechanics, limitations, and macroeconomic trade-offs involved with generating a government funding advantage through restrictions on the financial sector. We show the government cannot choose all three of: (i) high funding advantage, (ii) a well-functioning financial sector, and (iii) fiscal policy that leads to systematic debt devaluation. We relate our theories to new US historical corporate and treasury yield curve data from 1860-2024.
Historical US Funding Cost Advantage: 1860-2024
(with Clemens Lehner, Jonathan Payne and Jack Shurtleff)
[PDF, April 2025]
We estimate a historical funding cost advantage of the US government, as measured by the spread between yields on high-grade corporate bonds and treasuries. We construct a new dataset with monthly price, cash-flow, and rating information for US corporate bonds over the period 1860-2024. We deploy a Kernel Ridge regression to estimate US high-grade corporate and treasury yield curves making adjustments for tax treatment and time-varying embedded option values. A high-grade corporate to treasury spread emerged well before Bretton Woods with the introduction of the 1862-65 National Banking Acts. Previous estimates have mismeasured and exaggerated US funding advantage in the post-WWII period. In particular, funding advantage is negatively correlated with inflation and goes to zero during the Great Inflation in the 1970s-80s. We find little evidence that the US strategically exploits its monopoly power.
US Monetary, Financial, and Fiscal Priorities
(with Jonathan Payne, George Hall, and Thomas J. Sargent)
[PDF, January 2024]
US federal governments have confronted trade-offs among lowering borrowing costs, maintaining price stability, and maintaining financial stability. During the gold standard era, successive administrations prioritized decreasing government borrowing costs and keeping trend inflation low. Starting with FDR, the government prioritized financial and business cycle stability and was willing to use inflation taxes to lower its debt obligations and redistribute wealth between nominal creditors and debtors. Towards the end of the twentieth century, the government embraced financial deregulation and aggressive inflation targeting. We use our estimates for historical yields and inflation processes to indicate how those changing policy priorities affected or coincided with key macroeconomic correlations. The slope of both the US federal debt yield curve and the “Phillips curve” has changed signs as government priorities have changed.
Estimating Historical Yield Curves With Sparse Data
(with Jonathan Payne, George Hall, and Thomas J. Sargent)
[PDF, July 2023]
Estimating 19th century US federal bond yield curves involves challenges because few bonds were traded, bonds had peculiar features, government policies changed often, and there were wars. This paper compares statistical approaches for confronting these difficulties and shows that a dynamic Nelson-Siegel model with stochastic volatility and bond-specific pricing errors does a good job for historical US bond prices. This model is flexible enough to interpolate data across periods in a time-varying way without over-fitting. We exploit new computational techniques to deploy our model and estimate yield curves for US federal debt from 1790-1933.
Sticky Leverage: Comment
(with Andrea Ajello, and Ander Perez-Orive)
[PDF, June 2023]
We revisit the role of long-term nominal corporate debt for the transmission of inflation shocks in the general equilibrium model of Gomes, Jermann, and Schmid (2016). We show that inaccuracies in the model solution and calibration strategy lead GJS to a model equilibrium in which nominal long-term debt is systematically mispriced. As a result, the quantitative importance of corporate leverage in the transmission of inflation shocks to real activity in their framework is six times larger than what arises under the rational expectations equilibrium.
Learning with Misspecified Models
(with Dániel Csaba)
[PDF, July 2023]
We consider learning with a set of likelihoods when the learner’s set is misspecified. We study welfare implications of entertaining a misspecified set by focusing on the limit point of learning and the associated best-responding policy. Building on such policies, we define consistency requirements for sets of likelihoods that a utility-maximizing agent would find desirable. We characterize a class of decision problems for which exponential families of likelihoods—with payoff-relevant moments as sufficient statistics—exist that satisfy our consistency requirements therefore guaranteeing the asymptotic implementation of optimal policies irrespective of the data generating process.
Published or Forthcoming Papers
Inflation and Regulation of Government Debt: US Historical Evidence
(with Jonathan Payne)
Forthcoming in the Annual Review of Financial Economics (Volume 17)
[PDF, January 2025]
Governments have often used two policy instruments to lower financing costs: the money supply to generate seigniorage and regulation of the financial system to increase demand for their interest bearing bonds. Both involve trade-offs. This article marshals historical evidence and economic theories about how the US federal government has arranged monetary, financial, and fiscal systems since 1800 to lower its financing costs. In doing so, we infer evolving priorities of different US administrations.
Costs of Financing US Federal Debt Under a Gold Standard: 1791-1933
(with Jonathan Payne, George Hall, and Thomas J. Sargent)
The Quarterly Journal of Economics (2025), 140 (1): 793–833, doi: 10.1093/qje/qjae028
[PDF, September 2024]
Estimating Robustness
Journal of Economic Theory (2022) 199: 105225, doi: 10.1016/j.jet.2021.105225
[PDF, February 2021] [online_appendix] [code]
featured in the inaugural David K. Backus Memorial Lecture by Tom Sargent [video]
Optimal Positive Capital Taxes at Interior Steady States
(with Jess Benhabib)
AEJ:Macroeconomics (2021) 13 (1): 114-50, doi: 10.1257/mac.20180191
[PDF, January 2020] [NBER working paper 25895]
Twisted Probabilities, Uncertainty, and Prices
(with Lars Peter Hansen, Thomas J. Sargent, and Lloyd Han)
Journal of Econometrics (2020) 216 (1) : 151-174, doi: 10.1016/j.jeconom.2020.01.011
[PDF, January 2020] [online appendix] [code, binder]
Dormant Projects
Uncertainty Shocks in a Monetary Economy
[PDF, November 2019]
This paper studies a stochastic economy with flexible prices in which money has real effects. A representative household faces a portfolio choice between a nominally safe asset that provides transaction services and a risky productive capital with time-varying return volatility. Stochastic volatility and the behavior of the central bank determine an equilibrium asset allocation. When the objective of monetary policy is to stabilize inflation around a fixed target, the nominally safe asset becomes a relatively safe store of value in real terms as well. As a result, in response to higher uncertainty, the private sector shifts resources away from risky capital, causing output and investment to fall. To investigate the resulting non-linear dynamics, I solve the model globally and compute generalized impulse response functions across the support of the stationary distribution. Impulse response functions with respect to volatility shocks exhibit strong state dependence: large falls in investment are more likely in a high-risk (low interest rate) environment than in a low-risk (high interest rate) environment. I use the calibrated model to interpret recent events and find that the model predicts comovements observed among a set of key macro variables during and after the Great Recession.