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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.
Working Paper
The Passthrough of Agricultural Commodity Prices to Food Prices
Food inflation has been excluded from core measures of inflation under the reasoning that it is a phenomenon of the supply side of the economy, driven by stochastic supply shocks to agricultural production that can affect the availability of farm products and increase food price volatility. However, the share of food costs related to agricultural production has fallen over the years as food value chains have become more complex and food prices tied more closely to value added downstream in the supply chain. We calculate the magnitude and extent of agricultural price passthroughs to food ...
Working Paper
Local Projections, Autocorrelation, and Efficiency
It is well known that Local Projections (LP) residuals are autocorrelated. Conventional wisdom says that LP have to be estimated by OLS with Newey-West (or some type of Heteroskedastic and Autocorrelation Consistent (HAC)) standard errors and that GLS is not possible because the autocorrelation process is unknown and/or because the GLS estimator would be inconsistent. I derive the autocorrelation process of LP and show that it can be corrected for using a consistent GLS estimator. Estimating LP with GLS has three major implications: 1) LP GLS can be less biased, more efficient, and generally ...
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
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 ...
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
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
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.
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.
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 ...