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What makes an asset a “safe” asset? We study a model where two countries each issue sovereign bonds to satisfy investors’ safe asset demands. The countries differ in the float of their bonds and the fundamental resources available to rollover debts. A sovereign’s debt is safer if its fundamentals are strong relative to other possible safe assets, not merely strong on an absolute basis. If demand for safe assets is high, a large float enhances safety through a market depth benefit. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large.

This paper proposes a new method for measuring the impact of inflation on the real value of public debt. The distribution of debt debasement is based on two inputs: the distribution of privately held nominal debt by maturity, for which we provide new estimates, and the distribution of risk-adjusted inflation dynamics, for which we provide a novel copula estimator using options data. We find that inflation by itself is unlikely to lower the U.S. fiscal burden significantly because debt is concentrated at short maturities and perceived inflation shocks have little short-run persistence and are small.

Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures,Yield Curve Modeling and Forecastingcontains essential tools with enhanced utility for academics, central banks, governments, and industry.

A safe asset is a simple debt instrument that is expected to preserve its value during adverse systemic events. The supply of safe assets, private and public, has historically been concentrated in a small number of advanced economies, most prominently the United States. Over the last few decades, with minor cyclical interruptions, the supply of safe assets has not kept up with global demand. The reason is straightforward: the collective growth rate of the advanced economies that produce safe assets has been lower than the world's growth rate, which has been driven disproportionately by the high growth rate of high-saving emerging economies such as China. The signature of this growing shortage is a steady increase in the price of safe assets; equivalently, global safe interest rates must decline, as has been the case since the 1980s. The early literature, brought to light by Ben Bernanke's famous “savings glut” speech of 2005, focused on a general shortage of assets without isolating its safe asset component. The distinction, however, has become increasingly important over time, particularly in the aftermath of the subprime mortgage crisis and its sequels. We begin by describing the main facts and macroeconomic implications of safe asset shortages. Faced with such a structural conundrum, what are the likely short- to medium-term escape valves? We analyze four of them, each with its own macroeconomic and financial trade-offs.

We find that firms headquartered in U.S. counties with higher levels of social capital incur lower bank loan spreads. This finding is robust to using organ donation as an alternative social capital measure and incremental to the effects of religiosity, corporate social responsibility, and tax avoidance. We identify the causal relation using companies with a social-capital-changing headquarters relocation. We also find that high-social-capital firms face loosened nonprice loan terms, incur lower at-issue bond spreads, and prefer public bonds over bank loans. We conclude that debt holders perceive social capital as providing environmental pressure that constrains opportunistic firm behaviors in debt contracting.

We can only estimate the distribution of stock returns, but from option prices we observe the distribution of state prices. State prices are the product of risk aversion—the pricing kernel—and the natural probability distribution. The Recovery Theorem enables us to separate these to determine the market's forecast of returns and risk aversion from state prices alone. Among other things, this allows us to recover the pricing kernel, market risk premium, and probability of a catastrophe and to construct model-free tests of the efficient market hypothesis.

This article examines the link between the opportunity cost of money and time-varying liquidity premia of near-money assets. Higher interest rates imply higher opportunity costs of holding money and hence a higher premium for the liquidity service benefits of assets that are close substitutes for money. Consistent with this theory, short-term interest rates in the United States, United Kingdom, and Canada have a strong positive relationship with the liquidity premium of Treasury bills and other near-money assets over periods going back to the 1920s. Once the opportunity cost of money is taken into account, Treasury security supply variables lose their explanatory power for the liquidity premium, except for transitory short-run effects. These findings indicate a high elasticity of substitution between money and near-money assets. As a consequence, a central bank that follows an interest rate operating target not only elastically accommodates and neutralizes shocks to money demand, but effectively also shocks to near-money asset supply and demand.

We introduce a new measure of emerging market sovereign credit risk: the local currency credit spread, defined as the spread of local currency bonds over the synthetic local currency risk-free rate constructed using cross-currency swaps. We find that local currency credit spreads are positive and sizable. Compared with credit spreads on foreign-currency-denominated debt, local currency credit spreads have lower means, lower cross-country correlations, and lower sensitivity to global risk factors. We discuss several major sources of credit spread differentials, including positively correlated credit and currency risk, selective default, capital controls, and various financial market frictions.

Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such as volatility dynamics and unspanned macro factors. A three-factor model comprising a forward spread, a weighted combination of forward rates, and a macro factor generates notable gains in out-of-sample forecast accuracy compared with a model based on the expectations hypothesis. Such gains in predictive accuracy translate into higher risk-adjusted portfolio returns after accounting for estimation error and model uncertainty. Consistent with models featuring unspanned macro factors, our forecasts of future bond excess returns are strongly negatively correlated with survey forecasts of short rates. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2829 This paper was accepted by Gustavo Manso, finance.