Forecasting inflation? Target the middle
The Median CPI is well-known as an accurate predictor of future infl ation. But it?s just one of many possible trimmed-mean inflation measures. Recent research compares these types of measures to see which tracks future inflation best. Not only does the Median CPI outperform other trims in predicting CPI inflation, it also does a better job of predicting PCE inflation, the FOMC?s preferred measure, than the core PCE.
Nowcasting U.S. Headline and Core Inflation
Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. price index for personal consumption expenditures (PCE) and the consumer price index (CPI). The model relies on relatively few variables and is tested using real-time data. The model?s nowcasting accuracy improves as information accumulates over the course of a month or quarter, and it easily outperforms a variety of statistical benchmarks. In head-to-head comparisons, the model?s nowcasts of CPI infl ation ...
Are banks forward-looking in their loan loss provisioning? Evidence from the Senior Loan Officer Opinion Survey (SLOOS)
The purpose of this study is to empirically analyze if loan loss provisioning is forward-looking. Using a confidential dataset that directly helps us identify loan demand and loan supply at the bank level, we test if the banks? provisioning behavior is different before and after the crisis. We find, for the entire sample of banks, loan loss provisioning is forward-looking and statistically significant in the post-crisis period. Our results show that the top quartiles of banks in our dataset exhibit a forward-looking approach to loan loss provisioning both in the pre- and post-crisis period. ...
The Effect of Component Disaggregation on Measures of the Median and Trimmed-Mean CPI
For decades, the Federal Reserve Bank of Cleveland (FRBC) has produced median and trimmed-mean consumer price index (CPI) measures. These have proven useful in various contexts, such as forecasting and understanding post-COVID inflation dynamics. Revisions to the FRBC methodology have historically involved increasing the level of disaggregation in the CPI components, which has improved accuracy. Thus, it may seem logical that further disaggregation would continue to enhance its accuracy. However, we theoretically demonstrate that this may not necessarily be the case. We then explore the ...
A Unified Framework to Estimate Macroeconomic Stars
We develop a flexible semi-structural time-series model to estimate jointly several macroeconomic "stars" -- i.e., unobserved long-run equilibrium levels of output (and growth rate of output), the unemployment rate, the real rate of interest, productivity growth, price inflation, and wage inflation. The ingredients of the model are in part motivated by economic theory and in part by the empirical features necessitated by the changing economic environment. Following the recent literature on inflation and interest rate modeling, we explicitly model the links between long-run survey expectations ...
Where would the federal funds rate be, if it could be negative?
In the wake of Great Recession, the Federal Reserve engaged in conventional monetary policy actions by reducing the federal funds rate. But soon the rate hit zero, and could go no lower. In such environments, policymakers still think in terms of where the federal funds rate should be, were it possible to go negative. To project the ?unconstrained path? of the funds rate?ignoring the zero lower bound?and to identify the key underlying shocks driving that path, we employ a statistical macroeconomic forecasting model. We find that the federal funds rate would have been extremely negative during ...
Unemployment after the recession: a new natural rate?
The past recession has hit the labor market especially hard, and economists are wondering whether some fundamentals of the market have changed because of that blow. Many are suggesting that the natural rate of long-term unemployment?the level of unemployment an economy can?t go below?has shifted permanently higher. We use a new measure that is based on the rates at which workers are finding and losing jobs and which provides a more accurate assessment of the natural rate. We find that the natural rate of unemployment has indeed shifted higher?but much less so than has been suggested. ...
Adjusting Median and Trimmed-Mean Inflation Rates for Bias Based on Skewness
Median and trimmed-mean inflation rates tend to be useful estimates of trend inflation over long periods, but they can exhibit persistent departures from the underlying trend over shorter horizons. In this Commentary, we document that the extent of this bias is related to the degree of skewness in the distribution of price changes. The shift in the skewness of the cross-sectional price-change distribution during the pandemic means that median PCE and trimmed-mean PCE inflation rates have recently been understating the trend in PCE inflation by about 15 and 35 basis points, respectively.
Forecasting Core Inflation and Its Goods, Housing, and Supercore Components
This paper examines the forecasting efficacy and implications of the recently popular breakdown of core inflation into three components: goods excluding food and energy, services excluding energy and housing, and housing. A comprehensive historical evaluation of the accuracy of point and density forecasts from a range of models and approaches shows that a BVAR with stochastic volatility in aggregate core inflation, its three components, and wage growth is an effective tool for forecasting inflation's components as well as aggregate core inflation. Looking ahead, the model's baseline ...
Improving inflation forecasts in the medium to long term
To accurately forecast the future rate of inflation, it is imperative to account for inflation?s underlying trend. This is especially important for medium- to long-run forecasts. In this Commentary I demonstrate a simple but powerful technique for incorporating this trend into standard statistical time series models and report the gains to accuracy. I find that incorporating the trend by modeling inflation as gap from an estimated underlying trend leads to substantial gains in forecast accuracy of about 20 percent to 30 percent, two to three years out.