New York Fed's New Inflation Gauge Is a Red Herring
(Bloomberg View) -- Many investors are worried that an inflation surge is just around the corner, and some have sought confirmation in a new measure from the Federal Reserve Bank of New York: the Underlying Inflation Gauge. This indicator has advanced steadily in recent months even as measured inflation has slowed. Yet, there is reason to be skeptical of this signal, which isn’t telling us anything we don’t already know.
The UIG captures sustained movements in inflation from information contained in a broad set of price, real activity and financial data. The measure is presented in two ways. The first data set includes 223 disaggregated price series in the consumer price index -- the “prices-only measure.” The second data set includes the disaggregated price data as well as a wide range of macroeconomic and financial data for a total of 346 series -- the “full data set measure.” The common trend is isolated among all these factors using a dynamic factor model. Think of this as an average across different variables that measure the same concept.
The chart below plots the two UIG indicators. The full data set measure, which incorporates more variables, is rising much faster than the prices-only measure. Many people have interpreted the rapid rise of the full data set measure as evidence that a sharp upturn in inflation is ahead. That is a comforting view in light of the weakness of core inflation over the last year. But it is misleading: The sharper increase of the full-data measure compared with the prices-only one tells us that real economic conditions have improved and financial conditions are easy.
Here’s why the UIG is not providing investors with new information.
First, the prices-only measure has a 0.92 correlation coefficient with headline CPI going back to 1995 and a 0.96 correlation coefficient with headline producer prices going back to 2011. That is, the prices-only measure is nearly perfectly positively correlated with more widely followed measures of inflation. Put simply, the prices-only data don’t tell us anything that isn’t reflected in the CPI and producer price index.
Second, the UIG full data set measure, which incorporates an additional 123 variables on real activity and from financial markets, is not much better. A cursory analysis shows minimal added value. The chart below plots the 12-month moving average of the ISM Composite Index against the UIG full data set measure; the correlation coefficient is a robust 0.88, though it has declined over the years. From 1997 to 2006, the correlation was 0.96. From 2007 until now, the correlation coefficient has shrunk to 0.82. The UIG lags the ISM Manufacturing PMI.
So we should be wary of analysts who use this indicator to forecast an inflation spike. Our analysis shows there is little reason to place much more emphasis on the UIG than on others. It a useful statistical exercise, but it’s hard to see why the Fed would want to boil down inflation analysis to one summary statistic, especially given how puzzling inflation has been lately.
Moreover, much of the recent upturn in the UIG full data set measure is driven by looser financial conditions and an improvement in real activity -- it lags the ISM, after all. Of course, much of the recent debate on inflation is about whether or how much these factors matter for inflation to begin with, especially in the context of subdued inflation expectations. So, if loose financial conditions and stronger growth do little to move price inflation, perhaps the premise of those who rely on UIG to claim inflation will turn up is flawed.
This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
Neil Dutta is the head of economics at Renaissance Macro Research, responsible for analyzing global trends and cross-market investment themes.
To contact the editor responsible for this story: Max Berley at mberley@bloomberg.net.
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