The Impact of the COVID-19 Pandemic on Business Expectations
We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms reports significant or severe disruption to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruption, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the ...
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 consumer price index (CPI). Unlike previous research, we evaluate the performance of symmetric and asymmetric trimmed means using a well known equality of prediction test. We find that there is a large swath of trimmed means that have statistically indistinguishable performance. Also, although the swath of statistically similar trims changes slightly over different sample periods, it always ...
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 ...
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.
American Firms Foresee a Huge Negative Impact of the Coronavirus
The rapid unfolding of the COVID-19 pandemic has created grave concerns for the health and welfare of the U.S. population and the economy. The economic worries are very apparent in financial markets. From the closing bell on February 21 through March 20, U.S. equities fell more than 30 percent, and stock market volatility skyrocketed.
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 ...
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 ...
Lessons for Forecasting Unemployment in the U.S.: Use Flow Rates, Mind the Trend
This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage 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 is useful in forecasting the unemployment rate. We find that any approach that leverages unemployment inflow and outflow rates performs well in the near term. Over longer forecast horizons, Tasci (2012) appears to be a ...
U.S. Firms Foresee Intensifying Coronavirus Impact
In late March—even before many states had issued shelter-in-place, stay-at-home, or shutdown orders—we noted that firms were bracing for a huge negative impact on sales revenues from developments surrounding the coronavirus. Results from our March Survey of Business Uncertainty (SBU)—a national survey of firms of varying sizes and industries—revealed that disruptions stemming from COVID-19 had led to sharp declines in expectations for year-ahead sales growth.
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 ...