Hi, welcome to my website!

I am an applied macroeconomist and time-series econometrician and hold a position with the Research Centre of the Deutsche Bundesbank.

My research is concerned with forecast uncertainty, the dynamics of survey expectations, and informational frictions.
Most of the time, I end up solving signal extraction problems.

LATEST RESEARCH:

New WP: Constructing Fan Charts from the Ragged Edge of SPF Forecasts

with Todd E. Clark (FRB Cleveland), and Gergely Ganics (Banco de España)

Abstract: 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 partially unobserved, resulting in a multivariate unobserved components model. In our empirical analysis, we provide quarterly term structures of expectations and uncertainty bands. Our preferred specification features stochastic volatility in forecast updates, which improves forecast performance and yields model estimates of forecast uncertainty that vary over time. We conclude by constructing SPF-based fan charts for calendar-year forecasts like those published by the Federal Reserve.

Parts of this paper were earlier circulated under the title “Constructing the Term Structure of Uncertainty from the Ragged Edge of SPF Forecasts.”

New WP: What Is the Predictive Value of SPF Point and Density Forecasts?

with Todd E. Clark (FRB Cleveland), and Gergely Ganics (Banco de España)

Abstract: 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 entropic tilting, we let the resulting predictive densities exactly replicate the SPF’s probability bins. Our empirical analysis of SPF forecasts of GDP growth and inflation shows that tilting to the SPF’s probability bins can visibly affect our model-based predictive distributions. Yet in historical evaluations, tilting does not offer consistent benefits to forecast accuracy relative to the model-based densities that are centered on the SPF’s point forecasts and reflect the historical behavior of SPF forecast errors. That said, there can be periods in which tilting to the bin information helps forecast accuracy.

Parts of this paper were earlier circulated under the title “Constructing the Term Structure of Uncertainty from the Ragged Edge of SPF Forecasts.”

Discussion of Fabio Canova's FAQ paper on output gaps

"FAQ: How do I estimate the output gap?" (@CEPR, 2022)

Just accepted at RED:
Indeterminacy and Imperfect Information

with Thomas A. Lubik (FRB Richmond) and Christian Matthes (U Indiana)

Abstract: We study equilibrium determination in an environment where two types of agents have different information sets: Fully informed agents observe histories of all exogenous and endogenous variables. Less informed agents observe only a strict subset of the full information set and need to solve a dynamic signal extraction problem to gather information about the variables they do not directly observe. Both types of agents know the structure of the model and form expectations rationally. In this environment, we identify a new channel that generates equilibrium indeterminacy: Optimal information processing of the less informed agent introduces stable dynamics into the equation system that lead to self-fulling expectations. For parameter values that imply a unique equilibrium under full information, the limited information rational expectations equilibrium is indeterminate. We illustrate our framework with monetary policy models where an imperfectly informed central bank follows an interest rate rule.

NONE of the material posted on this personal website necessarily represents the views of

the Deutsche Bundesbank, the Eurosystem, the Bank for International Settlements,

the Board of Governors of the Federal Reserve System or the Federal Open Market Committee.