A Time-Series Perspective on Safety, Liquidity, and Low Interest Rates
The previous post in this series discussed several possible explanations for the trend decline in U.S. real interest rates since the late 1990s. We noted that while interest rates have generally come down over the past two decades, this decline has been more pronounced for Treasury securities. The conclusion that we draw from this evidence is that the convenience associated with the safety and liquidity embedded in Treasuries is an important driver of the secular (long-term) decline in Treasury yields. In this post and the next, we provide an overview of the two complementary empirical ...
Multimodality in Macro-Financial Dynamics
We estimate the evolution of the conditional joint distribution of economic and financial conditions. While the joint distribution is approximately Gaussian during normal periods, sharp tightenings of financial conditions lead to the emergence of additional modes. The U.S. economy has historically resolved quickly to the “good” mode, but we conjecture that poor policy choices could lead to prolonged periods of multimodality. We argue that multimodality arises naturally in a macro-financial intermediary model with occasionally binding intermediary constraints.
Global Trends in Interest Rates
Long-term government bond yields are at their lowest levels of the past 150 years in advanced economies. In this blog post, we argue that this low-interest-rate environment reflects secular global forces that have lowered real interest rates by about two percentage points over the past forty years. The magnitude of this decline has been nearly the same in all advanced economies, since their real interest rates have converged over this period. The key factors behind this development are an increase in demand for safety and liquidity among investors and a slowdown in global economic growth.
Bank Capital and Real GDP Growth
We study the relationship between bank capital ratios and the distribution of future real GDP growth. Growth in the aggregate bank capital ratio corresponds to a smaller left tail of GDP—smaller crisis probability—but at the cost of a smaller right tail of growth outcomes—smaller probability of exuberant growth. This trade-off persists at horizons of up to eight quarters, highlighting the long-range consequences of changes in bank capital. We show that the predictive information in bank capital ratio growth is over and above that contained in real credit growth, suggesting importance ...
Opening the Toolbox: The Nowcasting Code on GitHub
In April 2016, we unveiled--and began publishing weekly--the New York Fed Staff Nowcast, an estimate of GDP growth using an automated platform for tracking economic conditions in real time. Today we go a step further by publishing the MATLAB code for the nowcasting model, available here on GitHub, a public repository hosting service. We hope that sharing our code will make it easier for people interested in monitoring the macroeconomy to understand the details underlying the nowcast and to replicate our results.
Traditional GDP forecasts potentially present an overly optimistic (or pessimistic) view of the state of the economy: by focusing on the point estimate for the conditional mean of growth, such forecasts ignore risks around the central forecast. Yet, policymakers around the world increasingly focus on risks to the central forecast in policy debates. For example, in the United States the Federal Open Market Committee (FOMC) commonly discusses the balance of risks in the economy, with the relative prominence of this discussion fluctuating with the state of the economy. In a recent paper, we ...
Priors for the long run
We propose a class of prior distributions that discipline the long-run predictions of vector autoregressions (VARs). These priors can be naturally elicited using economic theory, which provides guidance on the joint dynamics of macroeconomic time series in the long run. Our priors for the long run are conjugate, and can thus be easily implemented using dummy observations and combined with other popular priors. In VARs with standard macroeconomic variables, a prior based on the long-run predictions of a wide class of theoretical models yields substantial improvements in the forecasting ...
Monitoring Economic Conditions during a Government Shutdown
The recent partial shutdown of the federal government has disrupted publication schedules for many U.S. Census Bureau and Bureau of Economic Analysis (BEA) data releases. Most notably, the release of GDP for the fourth quarter of 2018—originally scheduled for January 30—has been postponed indefinitely. Even without the full slate of Census Bureau and BEA releases, forecasters have continued to make predictions for 2018:Q4 GDP growth; as of February 1, the New York Fed Staff Nowcast stands at 2.6 percent, the Atlanta Fed’s GDPNow stands at 2.5 percent, and the Blue Chip Financial ...
Changing Risk-Return Profiles
Are stock returns predictable? This question is a perennially popular subject of debate. In this post, we highlight some results from our recent working paper, where we investigate the matter. Rather than focusing on a single object like the forecasted mean or median, we look at the entire distribution of stock returns and find that the realized volatility of stock returns, especially financial sector stock returns, has strong predictive content for the future distribution of stock returns. This is a robust feature of the data since all of our results are obtained with real-time analyses ...
Economic predictions with big data: the illusion of sparsity
We compare sparse and dense representations of predictive models in macroeconomics, microeconomics, and finance. To deal with a large number of possible predictors, we specify a prior that allows for both variable selection and shrinkage. The posterior distribution does not typically concentrate on a single sparse or dense model, but on a wide set of models. A clearer pattern of sparsity can only emerge when models of very low dimension are strongly favored a priori.