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Working Paper
A Time Series Model of Interest Rates With the Effective Lower Bound
Modeling interest rates over samples that include the Great Recession requires taking stock of the effective lower bound (ELB) on nominal interest rates. We propose a flexible time? series approach which includes a ?shadow rate??a notional rate that is less than the ELB during the period in which the bound is binding?without imposing no?arbitrage assumptions.{{p}}The approach allows us to estimate the behavior of trend real rates as well as expected future interest rates in recent years.
Working Paper
Are spectral estimators useful for implementing long-run restrictions in SVARs?
No, not really, since spectral estimators suffer from small sample and misspecification biases just as VARs do. Spectral estimators are no panacea for implementing long-run restrictions. ; In addition, when combining VAR coefficients with non-parametric estimates of the spectral density, care needs to be taken to consistently account for information embedded in the non-parametric estimates about serial correlation in VAR residuals. This paper uses a spectral factorization to ensure a correct representation of the data's variance. But this cannot overcome the fundamental problems of estimating ...
Working Paper
Trend inflation in advanced economies
We derive estimates of trend inflation for fourteen advanced economies from a framework in which trend shocks exhibit stochastic volatility. The estimated specification allows for time-variation in the degree to which longer-term inflation expectations are well anchored in each economy. Our results bring out the effect of changes in monetary regime (such as the adoption of inflation targeting in several countries) on the behavior of trend inflation. Our estimates expand on the previous literature in several dimensions: For each country, we employ a multivariate approach that pools different ...
Working Paper
Measuring the level and uncertainty of trend inflation
Firmly-anchored inflation expectations are widely viewed as playing a central role in the successful conduct of monetary policy. This paper presents estimates of trend inflation, based on information contained in survey expectations, the term structure of interest rates, and realized inflation rates. My application combines a variety of data sources at the monthly frequency and it can flexibly handle missing data arising from infrequent observations and limited data availability. In order to assess whether inflation expectations are anchored, uncertainty surrounding future changes in trend ...
Working Paper
Addressing COVID-19 Outliers in BVARs with Stochastic Volatility
Incoming data in 2020 posed sizable challenges for the use of VARs in economic analysis: Enormous movements in a number of series have had strong effects on parameters and forecasts constructed with standard VAR methods. We propose the use of VAR models with time-varying volatility that include a treatment of the COVID extremes as outlier observations. Typical VARs with time-varying volatility assume changes in uncertainty to be highly persistent. Instead, we adopt an outlier-adjusted stochastic volatility (SV) model for VAR residuals that combines transitory and persistent changes in ...
Working Paper
What is the Predictive Value of SPF Point and Density Forecasts?
This paper presents a new approach to combining the information in point and density forecasts from the Survey of Professional Forecasters (SPF) and assesses the incremental value of the density forecasts. Our starting point is a model, developed in companion work, that constructs quarterly term structures of expectations and uncertainty from SPF point forecasts for quarterly fixed horizons and annual fixed events. We then employ entropic tilting to bring the density forecast information contained in the SPF’s probability bins to bear on the model estimates. In a novel application of ...
Working Paper
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee's Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. Compared to constant-variance approaches, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts.
Working Paper
Constructing Fan Charts from the Ragged Edge of SPF Forecasts
We develop a model that permits the estimation of a term structure of both expectations and forecast uncertainty for application to professional forecasts such as the Survey of Professional Forecasters (SPF). Our approach exactly replicates a given data set of predictions from the SPF (or a similar forecast source) without measurement error. Our model captures fixed horizon and fixed-event forecasts, and can accommodate changes in the maximal forecast horizon available from the SPF. The model casts a decomposition of multi-period forecast errors into a sequence of forecast updates that may be ...
Working Paper
Measuring Uncertainty and Its Effects in the COVID-19 Era
We measure the effects of the COVID-19 outbreak on uncertainty, and we assess the consequences of the uncertainty for key economic variables. We use a large, heteroskedastic vector autoregression (VAR) in which the error volatilities share two common factors, interpreted as macro and financial uncertainty. Macro and financial uncertainty are allowed to contemporaneously affect the macroeconomy and financial conditions, with changes in the common component of the volatilities providing contemporaneous identifying information on uncertainty. The model includes additional latent volatility ...
Working Paper
Indeterminacy and Imperfect Information
We study equilibrium determination in an environment where two kinds of agents have different information sets: The fully informed agents know the structure of the model and observe histories of all exogenous and endogenous variables. The less informed agents observe only a strict subset of the full information set. All types of agents form expectations rationally, but agents with limited information need to solve a dynamic signal extraction problem to gather information about the variables they do not observe. We show that for parameter values that imply a unique equilibrium under full ...