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Journal Article
Is It Time to Add Food-at-Home Inflation to Measures of Core Inflation?
Since the mid-1970s, the Federal Reserve has used core inflation to examine trends in underlying inflation. Core inflation is considered a more stable measure as it excludes energy and food, historically viewed as the most volatile components of inflation. However, core inflation can be a challenge for central bankers to communicate, as food inflation is highly salient to consumers. We argue that food-at-home inflation has become less volatile over time and could be added to measures of core inflation with few drawbacks.
Journal Article
Disruptions to Russian Energy Supply Likely to Weigh on European Output
The Russia-Ukraine war and subsequent oil sanctions from European countries have substantially disrupted the supply of Russian oil and gas. We estimate the effects of these disruptions on European output and find that a decline in the Russian oil and gas supply in 2022 could lead to a sizable drop in European output over 2023–24, though the effect differs across countries and sectors .
Journal Article
Will High Underlying Inflation Persist?
Underlying inflation—the rate of inflation that prevails after temporary imbalances in the economy are resolved—can help policymakers gauge whether current high rates of inflation are likely to persist. Using survey-based inflation expectations, we show that if current inflation forecasts are realized, underlying inflation should decline toward 2 percent in 2024. However, if inflation continues to surprise to the upside, underlying inflation may remain elevated for some time.
Journal Article
KC Fed LMCI Can Help Sift Out Noise in Payroll Data
Data on monthly payroll growth are noisy and subject to revisions, making real-time assessment of the health of the labor market challenging. We use the information encoded in the Kansas City Fed’s Labor Market Conditions Indicators (LMCI) to get a cleaner picture of payroll growth. According to the LMCI-implied estimates of payroll growth, the labor market may be stronger than official data suggest.
Journal Article
Estimating the Effects of Monetary Policy: An Ongoing Evolution
New monetary policy tools have lengthened the interval over which policy news is transmitted and processed.
Journal Article
Cutting-Edge Methods Did Not Improve Inflation Forecasting during the COVID-19 Pandemic
Amaze Lusompa and Sai A. Sattiraju investigate whether innovations in time-varying parameter models led to improved inflation forecasting during the pandemic. They find that despite their promise prior to the pandemic, forecasting innovations did not improve the accuracy of inflation forecasts relative to a baseline time-varying parameter model during the pandemic. Their results suggest that forecasters may need to develop a new class of forecasting models, introduce new forecasting variables, or rethink how they forecast to yield more effective inflation forecasts during extreme events.
Journal Article
Testing Hybrid Forecasts for Imports and Exports
The quality of economic forecasts tends to deteriorate during times of stress such as the COVID-19 pandemic, raising questions about how to improve forecasts during exceptional times. One method of forecasting that has received less attention is refining model-based forecasts with judgmental adjustment, or hybrid forecasting. Judgmental adjustment is the process of incorporating information from outside a model into a forecast or adjusting a forecast subjectively. Hybrid forecasts could be particularly useful during extraordinary times such as the COVID-19 pandemic, as models that do not ...
Working Paper
How High Does High Frequency Need to Be? A Comparison of Daily and Intradaily Monetary Policy Surprises
This paper investigates the utility of daily data in measuring high-frequency monetary policy surprises, comparing various announcement-day asset price changes with their intradaily (30-minute) counterparts. We find that both frequencies are similarly distributed and often highly correlated, particularly for longer-horizon measures. Testing daily surprises for systematic contamination from non-monetary policy news, we find no evidence to suggest that contemporaneous news releases bias their measurement. Empirical applications, including high-frequency passthrough to Treasury yields and proxy ...
Working Paper
Regression Model Selection Under General Conditions
This paper shows that various model selection criteria—an important but debated statistical tool—in fact make similar selections.
Working Paper
A Note on the Finite Sample Bias in Time Series Cross-Validation
It is well known that model selection via cross validation can be biased for time series models. However, many researchers have argued that this bias does not apply when using cross-validation with vector autoregressions (VAR) or with time series models whose errors follow a martingale-like structure. I show that even under these circumstances, performing cross-validation on time series data will still generate bias in general.