A Unified Framework to Estimate Macroeconomic Stars
The Review of Economics and Statistics (2024) forthcoming, [working paper] [download stars' estimates]
Forecasting Core Inflation and Its Goods, Housing, and Supercore Components (with Todd Clark and Matthew Gordon)
International Journal of Central Banking (2024) forthcoming, [working paper] [latest version] [online appendix]
Nowcasting Inflation (with Edward Knotek II)
in: Ascari, G., and Trezzi, R. (eds.), Research Handbook of Inflation, Cheltenham, UK: Edward Elgar, 2024, forthcoming [working paper]
Post-COVID Inflation Dynamics: Higher for Longer (with Randal Verbrugge)
Journal of Forecasting (2024) 43(4): 871-893 [journal version] [working paper] [latest version: paper and online appendix]
Improving Inflation Forecasts Using Robust Measures (with Randal Verbrugge)
International Journal of Forecasting (2024) 40(2): 735-745 [journal version] [working paper]
The Hard Road to a Soft Landing: Evidence from a (Modestly) Nonlinear Structural Model (with Randal Verbrugge)
Energy Economics (2023) 123:106733 [journal version] [working paper]
Real-Time Density Nowcasts of US Inflation: A Model-Combination Approach (with Edward Knotek II)
International Journal of Forecasting (2023) 39(4): 1736-1760 [journal version] [working paper]
Asymmetric Responses of Consumer Spending to Energy Prices: A Threshold VAR Approach (with Edward Knotek II)
Energy Economics (2021) 95:105127 (lead article) [journal version] [working paper]
Combining Survey Long-Run Forecasts and Nowcasts with BVAR Forecasts Using Relative Entropy (with Ellis W. Tallman)
International Journal of Forecasting (2020) 36(2): 373–398 [journal version] [working paper]
Financial Nowcasts and Their Usefulness in Macroeconomic Forecasting (with Edward Knotek II)
International Journal of Forecasting (2019) 35(4): 1708-1724 [journal version] [working paper]
The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy (with Brent Meyer)
Empirical Economics (2019) 57(2): 603–630 [journal version] [working paper]
Nowcasting US Headline and Core Inflation (with Edward Knotek II)
Journal of Money, Credit, and Banking (2017) 49(5): 931–968 [journal version] [working paper]
Forecasting Inflation: Phillips Curve Effects on Services Price Measures (with Ellis W. Tallman)
International Journal of Forecasting (2017) 33(2): 442–457 [journal version] [working paper]
Evidence of Forward-Looking Loan–Loss Provisioning with Credit Market Information (with L. Balasubramanyan & James B. Thomson)
Journal of Financial Services Research (2017) 52(3): 191–223 [journal version] [working paper]
Credit Market Information Feedback (with Lakshmi Balasubramanyan, Ben Craig, and James B. Thomson)
Atlantic Economic Journal (2016) 44(3): 405–407 [journal version] [working paper]
Oil Price Fluctuations and US Banks (2024) (with Paolo Gelain and Marco Lorusso) [Under review]
Federal Reserve Bank of Cleveland, Working Paper No. 24-11 [working paper]
Abstract
We document a sizable effect of oil price fluctuations on US banking variables by estimating an SVAR with sign restrictions as in Baumeister and Hamilton (2019). We find that oil market shocks that lead to a contraction in world economic activity unambiguously lower the amount of bank credit to the US economy, tend to decrease US banks' net worth, and tend to increase the US credit spread. The effects can be strong and long-lasting, or more modest and short-lived, depending on the source of the oil price fluctuations. The effects are stronger for smaller and lower leveraged banks.
Improving the Median CPI: Maximal Disaggregation Isn't Necessarily Optimal (2024) (with Christian Garciga and Randal Verbrugge) [Under review]
Federal Reserve Bank of Cleveland, Working Paper No. 24-02 [working paper]
-- previously titled: The Effect of Component Disaggregation on Measures of the Median and Trimmed-Mean CPI
-- ASSA (American Economic Association) 2025 video link
Abstract
For decades, the Federal Reserve Bank of Cleveland (FRBC) has produced the Median Consumer Price Index (CPI). It has proven useful in various contexts, such as forecasting and understanding post-COVID inflation dynamics. Historically, revisions/improvements to the FRBC methodology have involved increasing the level of disaggregation in the CPI components. Thus, it may be reasonable to assume that further disaggregation improves the properties of the median CPI. We theoretically demonstrate: not necessarily. We then empirically explore the impact of further disaggregation by examining fifteen candidate baskets of CPI items that vary by the level of disaggregation. In line with prior literature, we find that greater disaggregation in the shelter indexes improves the ability of the Median CPI to track the medium-term trend in CPI inflation and its predictive power over future CPI movements. In contrast, increasing disaggregation in the remaining components leads to a deterioration in performance. Our preferred Median CPI measure suggests lower trend inflation pre-pandemic, a faster acceleration in trend inflation in 2021, and a faster deceleration in trend inflation after 2022.
The Distributional Predictive Content of Measures of Inflation Expectations (2023) (with James Mitchell)
Federal Reserve Bank of Cleveland, Working Paper No. 23-31 [working paper] [Under revision]
Abstract
This paper examines the predictive relationship between the distribution of realized inflation in the US and measures of inflation expectations from households, firms, financial markets, and professional forecasters. To allow for nonlinearities in the predictive relationship we use quantile regression methods. We find that the ability of households to predict future inflation, relative to that of professionals, firms, and the market, increases with inflation. While professional forecasters are more accurate in the middle of the inflation density, households’ expectations are more useful in the upper tail. The predictive ability of measures of inflation expectations is greatest when combined. We show that it is helpful to let the combination weights on different agents’ expectations of inflation vary by quantile when assessing inflationary pressures probabilistically.
A Medium Scale Forecasting Model for Monetary Policy (2011) (with Kenneth Beauchemin)
Federal Reserve Bank of Cleveland, Working Paper No. 11-28 [working paper] [Permanent Working Paper]
Abstract
This paper presents a 16-variable Bayesian VAR forecasting model of the U.S. economy for use in a monetary policy setting. The variables that comprise the model are selected not only for their effectiveness in forecasting the primary variables of interest, but also for their relevance to the monetary policy process. In particular, the variables largely coincide with those of an augmented New-Keynesian DSGE model. We provide out-of sample forecast evaluations and illustrate the computation and use of predictive densities and fan charts. Although the reduced form model is the focus of the paper, we also provide an example of structural analysis to illustrate the macroeconomic response of a monetary policy shock.
PhD Thesis submitted to the Department of Economics, University of Strathclyde, UK. (2021)
Essays in Forecasting and Empirical Macroeconomics [link]