Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting
We introduce a new dataset of real gross domestic product (GDP) growth and core personal consumption expenditures (PCE) inflation forecasts produced by the staff of the Board of Governors of the Federal Reserve System. In contrast to the eight Greenbook forecasts a year the staff produces for Federal Open Market Committee (FOMC) meetings, our dataset has roughly weekly forecasts. We use these new data to study whether the staff forecasts efficiently and whether efficiency, or lack thereof, is time-varying. Prespecified regressions of forecast errors on forecast revisions show that the staff's ...
Forecasts of the Lost Recovery
The years following the Great Recession were challenging for forecasters for a variety of reasons, including an unprecedented policy environment. This post, based on our recently released working paper, documents the real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model in the wake of the Great Recession. We show that the model’s predictive accuracy was on par with that of private forecasters and proved to be quite a bit better, at least in terms of GDP growth, than that of the median forecasts from the Federal Open Market Committee’s ...
Tracking and stress-testing U.S. household leverage
Borrowers? housing equity is an important component of their wealth and a critical determinant of their vulnerability to shocks. In this paper, we create a unique data set that enables us to provide a comprehensive look at the ratio of housing debt to housing values?what we refer to as household leverage?at the micro level. An advantage of our data is that we are able to study the evolution of household leverage over time and locations in the United States. We find that leverage was at a very low point just prior to the large declines in house prices that began in 2006, and rose very quickly ...
The Effects of the saving and banking glut on the U.S. economy
We use a quantitative equilibrium model with houses, collateralized debt, and foreign borrowing to study the impact of global imbalances on the U.S. economy in the 2000s. Our results suggest that the dynamics of foreign capital flows account for between one-fourth and one-third of the increase in U.S. house prices and household debt that preceded the financial crisis. The key to these findings is that the model generates the sustained low level of interest rates observed over that period.
The 2008 U.S. Auto Market Collapse
New vehicle sales in the U.S. fell nearly 40 percent during the past recession, causing significant job losses and unprecedented government interventions in the auto industry. This paper explores three potential explanations for this decline: increasing oil prices, falling home values, and falling household income expectations. First, we use the historical macroeconomic relationship between oil prices and vehicle sales to show that the oil price spike explains roughly 15 percent of the auto sales decline between 2007 and 2009. Second, we establish that declining home values explain only a ...
Selecting Primal Innovations in DSGE models
DSGE models are typically estimated assuming the existence of certain primal shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are "non-existent" and propose a method to select the primal shocks driving macroeconomic uncertainty. Forcing these non-existing shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select primal shocks and estimate model ...
Computing Equilibria of Stochastic Heterogeneous Agent Models Using Decision Rule Histories
This paper introduces a general method for computing equilibria with heterogeneous agents and aggregate shocks that is particularly suitable for economies with private information. Instead of the cross-sectional distribution of agents across individual states, the method uses as a state variable a vector of spline coefficients describing a long history of past individual decision rules. Applying the computational method to a Mirrlees RBC economy with known analytical solution recovers the solution perfectly well. This test provides considerable confidence on the accuracy of the method.
Assessing Macroeconomic Tail Risks in a Data-Rich Environment
We use a large set of economic and financial indicators to assess tail risks of the three macroeconomic variables: real GDP, unemployment, and inflation. When applied to U.S. data, we find evidence that a dense model using principal components (PC) as predictors might be misspecified by imposing the “common slope” assumption on the set of predictors across multiple quantiles. The common slope assumption ignores the heterogeneous informativeness of individual predictors on different quantiles. However, the parsimony of the PC-based approach improves the accuracy of out-of-sample forecasts ...
A Theory of Housing Demand Shocks
Aggregate housing demand shocks are an important source of house price fluctuations in the standard macroeconomic models, and through the collateral channel, they drive macroeconomic fluctuations. These reduced-form shocks, however, fail to generate a highly volatile price-to-rent ratio that comoves with the house price observed in the data (the ?price-rent puzzle?). We build a tractable heterogeneous-agent model that provides a microeconomic foundation for housing demand shocks. The model predicts that a credit supply shock can generate large comovements between the house price and the ...
Heterogeneity in the Dynamics of Disaggregate Unemployment
This paper explores the role that unobserved heterogeneity within an observed category plays in the dynamics of disaggregate unemployment and in the cross-sectional differences across individuals of the duration of unemployment spells. The distribution of unobserved heterogeneity is characterized as a mixture of two distributions with each mean and weight determined by the inflows and outflows of workers with unobserved types H and L, which are identified based on the nonlinear state-space model of Ahn and Hamilton (2016). I found that the contribution of each factor to the dynamics of ...