The Usefulness of the Median CPI in Bayesian VARs Used for Macroeconomic Forecasting and Policy
In this paper we investigate the forecasting performance of the median Consumer Price Index (CPI) in a variety of Bayesian vector autoregressions (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or Phillips curve approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro variables. We find that inclusion of an extreme trimmed-mean measure?the median CPI?improves the forecasts of both core and headline inflation (CPI and ...
Trimmed-mean inflation statistics: just hit the one in the middle
This paper reinvestigates the performance of trimmed-mean inflation measures some 20 years since their inception, asking whether there is a particular trimmed mean measure that dominates the median CPI. Unlike previous research, we evaluate the performance of symmetric and asymmetric trimmed-means using a well-known equality of prediction test. We fi nd that there is a large swath of trimmed-means that have statistically indistinguishable performance. Also, while the swath of statistically similar trims changes slightly over different sample periods, it always includes the median CPI?an ...
Simple ways to forecast inflation: what works best?
There are many ways to forecast the future rate of inflation, ranging from sophisticated statistical models involving hundreds of variables to hunches based on past experience. We generate a number of forecasts using a simple statistical model and an even simpler estimating rule, adding in various measures thought to be helpful in predicting the course of inflation. Then we compare their forecast accuracy. We find that no single specification outperforms all others over all time periods. For example, the median and 16 percent trimmed-mean measures outperform all other specifications during ...
Demographic differences in inflation expectations: what do they really mean?
It has often been reported that different demographic groups show persistent differences in their inflation expectations. Some reasonable explanations have been suggested, but most have failed to fully explain these apparent differences. We argue that the demographic differences have been overstated by using the mean to describe differences across demographic groups. When we use the median to describe inflation expectations, we find little meaningful difference across demographic groups.
When will the world?s production of oil peak, and what will the economic consequences be? Calculating when turns out not to be so straightforward as it seems, but predicting the likely economic consequences is?and they?re not as bleak as many fear.
COVID-19 Is a Persistent Reallocation Shock
Drawing on data from the firm-level Survey of Business Uncertainty, we present three pieces of evidence that COVID-19 is a persistent reallocation shock. First, rates of excess job and sales reallocation over 24-month periods have risen sharply since the pandemic struck, especially for sales. We compute these rates by aggregating over monthly firm-level observations that look back 12 months and ahead 12 months. Second, as of December 2020, firm-level forecasts of sales revenue growth over the next year imply a continuation of recent changes, not a reversal. Third, COVID-19 shifted relative ...
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.
Surveying Business Uncertainty
We elicit subjective probability distributions from business executives about their own-firm outcomes at a one-year look-ahead horizon. In terms of question design, our key innovation is to let survey respondents freely select support points and probabilities in five-point distributions over future sales growth, employment, and investment. In terms of data collection, we develop and field a new monthly panel Survey of Business Uncertainty (SBU). The SBU began in 2014 and now covers about 1,750 firms drawn from all 50 states, every major nonfarm industry, and a range of firm sizes. We find ...
Businesses Are in Uncharted Waters
Inflation expectations in our April Business Inflation Expectations (BIE) survey fell to an all-time low (going back to October 2011) of 1.4 percent, plunging far below its next lowest level of 1.7 percent (most recently observed in February 2020). Perhaps unsurprisingly, firms have bigger worries on their minds. And our boss, President Raphael Bostic, agreed, noting on Wednesday that "inflation at this point is not something I'm particularly worried about."
Lessons for forecasting unemployment in the United States: use flow rates, mind the trend
This paper evaluates the ability of autoregressive models, professional forecasters, and models that incorporate unemployment flows to forecast the unemployment rate. We pay particular attention to flows-based approaches?the more reduced-form approach of Barnichon and Nekarda (2012) and the more structural method in Tasci (2012)?to generalize whether data on unemployment flows are useful in forecasting the unemployment rate. We find that any approach that considers unemployment inflow and outflow rates performs well in the near term. Over longer forecast horizons, Tasci (2012) appears to be a ...