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June 26, 2014

Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 3)

On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.

This is the last of three posts on that talk. The first post reviewed alternative inflation measures; the second looked at ways to work with the Consumer Price Index to get a clear view of inflation. The full text of the speech is available on the Atlanta Fed's events web page.

The challenge of communicating price stability

Let me close this blog series with a few observations on the criticism that measures of core inflation, and specifically the CPI excluding food and energy, disconnect the Federal Reserve from households and businesses "who know price changes when they see them." After all, don't the members of the Federal Open Market Committee (FOMC) eat food and use gas in their cars? Of course they do, and if it is the cost of living the central bank intends to control, the prices of these goods should necessarily be part of the conversation, notwithstanding their observed volatility.

In fact, in the popularly reported all-items CPI, the Bureau of Labor Statistics has already removed about 40 percent of the monthly volatility in the cost-of-living measure through its seasonal adjustment procedures. I think communicating in terms of a seasonally adjusted price index makes a lot of sense, even if nobody actually buys things at seasonally adjusted prices.

Referencing alternative measures of inflation presents some communications challenges for the central bank to be sure. It certainly would be easier if progress toward either of the Federal Reserve's mandates could be described in terms of a single, easily understood statistic. But I don't think this is feasible for price stability, or for full employment.

And with regard to our price stability mandate, I suspect the problem of public communication runs deeper than the particular statistics we cite. In 1996, Robert Shiller polled people—real people, not economists—about their perceptions of inflation. What he found was a stark difference between how economists think about the word "inflation" and how folks outside a relatively small band of academics and policymakers define inflation. Consider this question:

140626_tbl1

And here is how people responded:

140626_tbl2

Seventy-seven percent of the households in Shiller's poll picked number 2—"Inflation hurts my real buying power"—as their biggest gripe about inflation. This is a cost-of-living description. It isn't the same concept that most economists are thinking about when they consider inflation. Only 12 percent of the economists Shiller polled indicated that inflation hurt real buying power.

I wonder if, in the minds of most people, the Federal Reserve's price-stability mandate is heard as a promise to prevent things from becoming more expensive, and especially the staples of life like, well, food and gasoline. This is not what the central bank is promising to do.

What is the Federal Reserve promising to do? To the best of my knowledge, the first "workable" definition of price stability by the Federal Reserve was Paul Volcker's 1983 description that it was a condition where "decision-making should be able to proceed on the basis that 'real' and 'nominal' values are substantially the same over the planning horizon—and that planning horizons should be suitably long."

Thirty years later, the Fed gave price stability a more explicit definition when it laid down a numerical target. The FOMC describes that target thusly:

The inflation rate over the longer run is primarily determined by monetary policy, and hence the Committee has the ability to specify a longer-run goal for inflation. The Committee reaffirms its judgment that inflation at the rate of 2 percent, as measured by the annual change in the price index for personal consumption expenditures, is most consistent over the longer run with the Federal Reserve's statutory mandate.

Whether one goes back to the qualitative description of Volcker or the quantitative description in the FOMC's recent statement of principles, the thrust of the price-stability objective is broadly the same. The central bank is intent on managing the persistent, nominal trend in the price level that is determined by monetary policy. It is not intent on managing the short-run, real fluctuations that reflect changes in the cost of living.

Effectively achieving price stability in the sense of the FOMC's declaration requires that the central bank hears what it needs to from the public, and that the public in turn hears what they need to know from the central bank. And this isn't likely unless the central bank and the public engage in a dialog in a language that both can understand.

Prices are volatile, and the cost of living the public experiences ought to reflect that. But what the central bank can control over time—inflation—is obscured within these fluctuations. What my colleagues and I have attempted to do is to rearrange the price data at our disposal, and so reveal a richer perspective on the inflation experience.

We are trying to take the torture out of the inflation discussion by accurately measuring the things that the Fed needs to worry about and by seeking greater clarity in our communications about what those things mean and where we are headed. Hard conversations indeed, but necessary ones.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department

 


June 26, 2014 in Business Cycles, Data Releases, Inflation | Permalink

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It would seem the non-economists may also be saying that the economists low inflation is their own stagnant wage.

Sure, they may see prices rising, but they stated what they suffer is the reduction of purchasing power.

Perhaps they would be happy to see prices rising rapidly as long as their own wages outpace.

The 70s may not have been so bad for them.

Posted by: cfaman | June 27, 2014 at 10:01 AM

In addition to the issues discussed in the article, Fed policy makers typically ignore one-time prices changes, particularly those originating on the supply side of the economy -- e.g., those caused by bad weather or a foreign conflict. 

The public can't ignore those price changes, which comprise their daily reality.

Posted by: Thomas Wyrick | July 06, 2014 at 05:57 PM

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June 24, 2014

Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 2)

On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.

This is the second of three posts based on that talk. Yesterday's post considered the median CPI and other trimmed-mean measures.

Is it more expensive, or does it just cost more money? Inflation versus the cost of living

Let me make two claims that I believe are, separately, uncontroversial among economists. Jointly, however, I think they create an incongruity for how we think about and measure inflation.

The first claim is that over time, inflation is a monetary phenomenon. It is caused by too much money chasing a limited number of things to buy with that money. As such, the control of inflation is rightfully the responsibility of the institution that has monopoly control over the supply of money—the central bank.

My second claim is that the cost of living is a real concept, and changes in the cost of living will occur even in a world without money. It is a description of how difficult it is to buy a particular level of well-being. Indeed, to a first approximation, changes in the cost of living are beyond the ability of a central bank to control.

For this reason, I think it is entirely appropriate to think about whether the cost of living in New York City is rising faster or slower than in Cleveland, just as it is appropriate to ask whether the cost of living of retirees is rising faster or slower than it is for working-aged people. The folks at the Bureau of Labor Statistics produce statistics that can help us answer these and many other questions related to how expensive it is to buy the happiness embodied in any particular bundle of goods.

But I think it is inappropriate for us to think about inflation, the object of central bank control, as being different in New York than it is in Cleveland, or to think that inflation is somehow different for older citizens than it is for younger citizens. Inflation is common to all things valued by money. Yet changes in the cost of living and inflation are commonly talked about as if they are the same thing. And this creates both a communication and a measurement problem for the Federal Reserve and other central banks around the world.

Here is the essence of the problem as I see it: money is not only our medium of exchange but also our numeraire—our yardstick for measuring value. Embedded in every price change, then, are two forces. The first is real in the sense that the good is changing its price in relation to all the other prices in the market basket. It is the cost adjustment that motivates you to buy more or less of that good. The second force is purely nominal. It is a change in the numeraire caused by an imbalance in the supply and demand of the money being provided by the central bank. I think the concept of "core inflation" is all about trying to measure changes in this numeraire. But to get there, we need to first let go of any "real" notion of our price statistics. Let me explain.

As a cost-of-living approximation, the weights the Bureau of Labor Statistics (BLS) uses to construct the Consumer Price Index (CPI) are based on some broadly representative consumer expenditures. It is easy to understand that since medical care costs are more important to the typical household budget than, say, haircuts, these costs should get a greater weight in the computation of an individual's cost of living. But does inflation somehow affect medical care prices differently than haircuts? I'm open to the possibility that the answer to this question is yes. It seems to me that if monetary policy has predictable, real effects on the economy, then there will be a policy-induced disturbance in relative prices that temporarily alters the cost of living in some way.

But if inflation is a nominal experience that is independent of the cost of living, then the inflation component of medical care is the same as that in haircuts. No good or service, geographic region, or individual experiences inflation any differently than any other. Inflation is a common signal that ultimately runs through all wages and prices.

And when we open up to the idea that inflation is a nominal, not-real concept, we begin to think about the BLS's market basket in a fundamentally different way than what the BLS intends to measure.

This, I think, is the common theme that runs through all measures of "core" inflation. Can the prices the BLS collects be reorganized or reweighted in a way that makes the aggregate price statistic more informative about the inflation that the central bank hopes to control? I think the answer is yes. The CPI excluding food and energy is one very crude way. Food and energy prices are extremely volatile and certainly point to nonmonetary forces as their primary drivers.

In the early 1980s, Otto Eckstein defined core inflation as the trend growth rate of the cost of the factors of production—the cost of capital and wages. I would compare Eckstein's measure to the "inflation expectations" component that most economists (and presumably the FOMC) think "anchor" the inflation trend.

The sticky-price CPI

Brent Meyer and I have taken this idea to the CPI data. One way that prices appear to be different is in their observed "stickiness." That is, some prices tend to change frequently, while others do not. Prices that change only infrequently are likely to be more forward-looking than are those that change all the time. So we can take the CPI market basket and separate it into two groups of prices—prices that tend to be flexible and those that are "sticky" (a separation made possible by the work of Mark Bils and Peter J. Klenow).

Indeed, we find that the items in the CPI market basket that change prices frequently (about 30 percent of the CPI) are very responsive to changes in economic conditions, but do not seem to have a very forward-looking character. But the 70 percent of the market basket items that do not change prices very often—these are accounted for in the sticky-price CPI—appear to be largely immune to fluctuations in the business conditions and are better predictors of future price behavior. In other words, we think that some "inflation-expectation" component exists to varying degrees within each price. By reweighting the CPI market basket in a way that amplifies the behavior of the most forward-looking prices, the sticky-price CPI gives policymakers a perspective on the inflation experience that the headline CPI can't.

Here is what monthly changes in the sticky-price CPI look like compared to the all-items CPI and the traditional "core" CPI.


Let me describe another, more radical example of how we might think about reweighting the CPI market basket to measure inflation—a way of thinking that is very different from the expenditure-basket approach the BLS uses to measure the cost of living.

If we assume that inflation is ultimately a monetary event and, moreover, that the signal of this monetary inflation can be found in all prices, then we might use statistical techniques to help us identify that signal from a large number of price data. The famous early-20th-century economist Irving Fisher described the problem as trying to track a swarm of bees by abstracting from the individual, seemingly chaotic behavior of any particular bee.

Cecchetti and I experimented along these lines to measure a common signal running through the CPI data. The basic idea of our approach was to take the component data that the BLS supplied, make a few simple identifying assumptions, and let the data itself determine the appropriate weighting structure of the inflation estimate. The signal-extraction method we chose was a dynamic-factor index approach, and while we didn't pursue that work much further, others did, using more sophisticated and less restrictive signal-extraction methods. Perhaps most notable is the work of Ricardo Reis and Mark Watson.

To give you a flavor of the approach, consider the "first principal component" of the CPI price-change data. The first principal component of a data series is a statistical combination of the data that accounts for the largest share of their joint movement (or variance). It's a simple, statistically shared component that runs through all the price data.

This next chart shows the first principal component of the CPI price data, in relation to the headline CPI and the core CPI.


Again, this is a very different animal than what the folks at the BLS are trying to measure. In fact, the weights used to produce this particular common signal in the price data bear little similarity to the expenditure weights that make up the market baskets that most people buy. And why should they? The idea here doesn't depend on how important something is to the well-being of any individual, but rather on whether the movement in its price seems to be similar or dissimilar to the movements of all the other prices.

In the table below, I report the weights (or relative importance) of a select group of CPI components and the weights they would get on the basis of their contribution to the first principal component.

140624b

While some criticize the CPI because it over weights housing from a cost-of-living perspective, it may be these housing components that ought to be given the greatest consideration when we think about the inflation that the central bank controls. Likewise, according to this approach, restaurant costs, motor vehicle repairs, and even a few food components should be taken pretty seriously in the measurement of a common inflation signal running through the price data.

And what price movements does this approach say we ought to ignore? Well, gasoline prices for one. But movements in the prices of medical care commodities, communications equipment, and tobacco products also appear to move in ways that are largely disconnected from the common thread in prices that runs through the CPI market basket.

But this and other measures of "core" inflation are very much removed from the cost changes that people experience on a monthly basis. Does that cause a communications problem for the Federal Reserve? This will be the subject of my final post.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department

 

June 24, 2014 in Business Cycles, Data Releases, Inflation | Permalink

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Great thoughts, thanks for sharing. taking the the idea of core inflation as the movements in prices that contain information about future inflation, have you ever thought about applying partial least squares (PLS) rather than PCA for dimension reduction, and making a future value of headline inflation the Y variable in the PLS decomposition of the Y'X? then you would get weightings that reflected the information content of each price series x on future Y, rather than PCA which simply decomposes the variance within X'X

Posted by: Michael Hugman | June 25, 2014 at 11:10 AM

This is very interesting. But I wonder, is it really possible to distinguish monetary inflation from cost-of-living inflation? As you say, monetary inflation reflects an imbalance between the supply and demand for money. Where does the demand for money come from? Presumably from the level of real activity. And how do we measure real activity independent of money, if not as a level of well-being?

In fact, the measurement of quantity in terms of well-being is the explicit basis of the hedonic price adjustments that go into a significant fraction of the CPI. So at the least, if you want a pure monetary measure of inflation, shouldn't you strip those adjustments back out?

Along the same lines, you say the inflation controlled by the central should be identical in New York and Cleveland. But what if monetary policy produces identical rates of money supply growth in both cities, while different real growth rates mean that money demand is rowing faster in one place than the other?

Posted by: JW Mason | June 27, 2014 at 09:42 AM

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June 23, 2014

Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 1)

On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.

In this, and the following two blogs, I'll be posting a modestly edited version of that talk. A full version of my prepared remarks will be posted along with the third installment of these posts.

The ideas expressed in these blogs and the related speech are my own, and do not necessarily reflect the views of the Federal Reserve Banks of Atlanta or Cleveland.

Part 1: The median CPI and other trimmed-mean estimators

A useful place to begin this conversation, I think, is with the following chart, which shows the monthly change in the Consumer Price Index (CPI) (through April).


The monthly CPI often swings between a negative reading and a reading in excess of 5 percent. In fact, in only about one-third of the readings over the past 16 years was the monthly, annualized seasonally adjusted CPI within a percentage point of 2 percent, which is the FOMC's longer-term inflation target. (Officially, the FOMC's target is based on the Personal Consumption Expenditures price index, but these and related observations hold for that price index equally well.)

How should the central bank think about its price-stability mandate within the context of these large monthly CPI fluctuations? For example, does April's 3.2 percent CPI increase argue that the FOMC ought to do something to beat back the inflationary threat? I don't speak for the FOMC, but I doubt it. More likely, there were some unusual price movements within the CPI's market basket that can explain why the April CPI increase isn't likely to persist. But the presumption that one can distinguish the price movements we should pay attention to from those that we should ignore is a risky business.

The Economist retells a conversation with Stephen Roach, who in the 1970s worked for the Federal Reserve under Chairman Arthur Burns. Roach remembers that when oil prices surged around 1973, Burns asked Federal Reserve Board economists to strip those prices out of the CPI "to get a less distorted measure. When food prices then rose sharply, they stripped those out too—followed by used cars, children's toys, jewellery, housing and so on, until around half of the CPI basket was excluded because it was supposedly 'distorted'" by forces outside the control of the central bank. The story goes on to say that, at least in part because of these actions, the Fed failed to spot the breadth of the inflationary threat of the 1970s.

I have a similar story. I remember a morning in 1991 at a meeting of the Federal Reserve Bank of Cleveland's board of directors. I was welcomed to the lectern with, "Now it's time to see what Mike is going to throw out of the CPI this month." It was an uncomfortable moment for me that had a lasting influence. It was my motivation for constructing the Cleveland Fed's median CPI.

I am a reasonably skilled reader of a monthly CPI release. And since I approached each monthly report with a pretty clear idea of what the actual rate of inflation was, it was always pretty easy for me to look across the items in the CPI market basket and identify any offending—or "distorted"—price change. Stripping these items from the price statistic revealed the truth—and confirmed that I was right all along about the actual rate of inflation.

Let me show you what I mean by way of the April CPI report. The next chart shows the annualized percentage change for each component in the CPI for that month. These are shown on the horizontal axis. The vertical axis shows the weight given to each of these price changes in the computation of the overall CPI. Taken as a whole, the CPI jumped 3.2 percent in April. But out there on the far right tail of this distribution are gasoline prices. They rose about 32 percent for the month. If you subtract out gasoline from the April CPI report, you get an increase of 2.1 percent. That's reasonably close to price stability, so we can stop there—mission accomplished.


But here's the thing: there is no such thing as a "nondistorted" price. All prices are being influenced by market forces and, once influenced, are also influencing the prices of all the other goods in the market basket.

What else is out there on the tails of the CPI price-change distribution? Lots of stuff. About 17 percent of things people buy actually declined in price in April while prices for about 13 percent of the market basket increased at rates above 5 percent.

But it's not just the tails of this distribution that are worth thinking about. Near the center of this price-change distribution is a very high proportion of things people buy. For example, price changes within the fairly narrow range of between 1.5 percent and 2.5 percent accounted for about 26 percent of the overall CPI market basket in the April report.

The April CPI report is hardly unusual. The CPI report is commonly one where we see a very wide range of price changes, commingled with an unusually large share of price increases that are very near the center of the price-change distribution. Statisticians call this a distribution with a high level of "excess kurtosis."

The following chart shows what an average monthly CPI price report looks like. The point of this chart is to convince you that the unusual distribution of price changes we saw in the April CPI report is standard fare. A very high proportion of price changes within the CPI market basket tends to remain close to the center of the distribution, and those that don't tend to be spread over a very wide range, resulting in what appear to be very elongated tails.


And this characterization of price changes is not at all special to the CPI. It characterizes every major price aggregate I have ever examined, including the retail price data for Brazil, Argentina, Mexico, Columbia, South Africa, Israel, the United Kingdom, Sweden, Canada, New Zealand, Germany, Japan, and Australia.

Why do price change distributions have peaked centers and very elongated tails? At one time, Steve Cecchetti and I speculated that the cost of unplanned price changes—called menu costs—discourage all but the most significant price adjustments. These menu costs could create a distribution of observed price changes where a large number of planned price adjustments occupy the center of the distribution, commingled with extreme, unplanned price adjustments that stretch out along its tails.

But absent a clear economic rationale for this unusual distribution, it presents a measurement problem and an immediate remedy. The problem is that these long tails tend to cause the CPI (and other weighted averages of prices) to fluctuate pretty widely from month to month, but they are, in a statistical sense, tethered to that large proportion of price changes that lie in the center of the distribution.

So my belated response to the Cleveland board of directors was the computation of the weighted median CPI (which I first produced with Chris Pike). This statistic considers only the middle-most monthly price change in the CPI market basket, which becomes the representative aggregate price change. The median CPI is immune to the obvious analyst bias that I had been guilty of, while greatly reducing the volatility in the monthly CPI report in a way that I thought gave the Federal Reserve Bank of Cleveland a clearer reading of the central tendency of price changes.

Cecchetti and I pushed the idea to a range of trimmed-mean estimators, for which the median is simply an extreme case. Trimmed-mean estimators trim some proportion of the tails from this price-change distribution and reaggregate the interior remainder. Others extended this idea to asymmetric trims for skewed price-change distributions, as Scott Roger did for New Zealand, and to other price statistics, like the Federal Reserve Bank of Dallas's trimmed-mean PCE inflation rate.

How much one should trim from the tails isn't entirely obvious. We settled on the 16 percent trimmed mean for the CPI (that is, trimming the highest and lowest 8 percent from the tails of the CPI's price-change distribution) because this is the proportion that produced the smallest monthly volatility in the statistic while preserving the same trend as the all-items CPI.

The following chart shows the monthly pattern of the median CPI and the 16 percent trimmed-mean CPI relative to the all-items CPI. Both measures reduce the monthly volatility of the aggregate price measure by a lot—and even more so than by simply subtracting from the index the often-offending food and energy items.


But while the median CPI and the trimmed-mean estimators are often referred to as "core" inflation measures (and I am guilty of this myself), these measures are very different from the CPI excluding food and energy.

In fact, I would not characterize these trimmed-mean measures as "exclusionary" statistics at all. Unlike the CPI excluding food and energy, the median CPI and the assortment of trimmed-mean estimators do not fundamentally alter the underlying weighting structure of the CPI from month to month. As long as the CPI price change distribution is symmetrical, these estimators are designed to track along the same path as that laid out by the headline CPI. It's just that these measures are constructed so that they follow that path with much less volatility (the monthly variance in the median CPI is about 95 percent smaller than the all-items CPI and about 25 percent smaller than the CPI less food and energy).

I think of the trimmed-mean estimators and the median CPI as being more akin to seasonal adjustment than they are to the concept of core inflation. (Indeed, early on, Cecchetti and I showed that the median CPI and associated trimmed-mean estimates also did a good job of purging the data of its seasonal nature.) The median CPI and the trimmed-mean estimators are noise-reduced statistics where the underlying signal being identified is the CPI itself, not some alternative aggregation of the price data.

This is not true of the CPI excluding food and energy, nor necessarily of other so-called measures of "core" inflation. Core inflation measures alter the weights of the price statistic so that they can no longer pretend to be approximations of the cost of living. They are different constructs altogether.

The idea of "core" inflation is one of the topics of tomorrow's post.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist in the Atlanta Fed's research department

June 23, 2014 in Data Releases, Economic conditions, Inflation | Permalink

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Or you aware that if you look at the NSA core CPI that over half of the annual increase normally occurs in the first quarter.

Normally, if the first quarter change in the NSA core CPI is smaller than in the prior year the annual increase will be smaller than in the prior year. The same thing holds if it is larger.

I would be happy to send you an excell file
with the data arranged to demonstrate this.

Posted by: Spencer | June 24, 2014 at 11:11 AM

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July 16, 2013

Commodity Prices and Inflation: The Perspective of Firms

We’ve been thinking a lot about commodity prices lately. In case you haven’t noticed, they’ve been falling. And with inflation already tracking well under the Federal Open Market Committee’s (FOMC) longer-term objective of 2 percent, it’s reasonable to wonder whether the modest downward tilt in commodity prices is likely to put even more, presumably unwanted, disinflation into the pipeline.

We take some comfort from research by Chicago Fed President Charles Evans and coauthor Jonas Fisher, vice president and macroeconomist, also of the Chicago Fed. They conducted a statistical analysis of commodity prices and core inflation and found no meaningful relationship between the two in the post-Volcker era of the Fed. According to the authors,

[I]f commodity and energy prices were to lead to a general expectation of a broader increase in inflation, more substantial policy rate increases would be justified. But assuming there is a generally high degree of central-bank credibility, there is no reason for such expectations to develop—in fact, in the post-Volcker period, there have been no signs that they typically do.

We took this bit of good news to our boss here at the Atlanta Fed, Dennis Lockhart, who hit us with a question we wish we had thought to ask. To paraphrase: Is the response of inflation different for commodity price increases compared to commodity price decreases? The idea here is that, for a time at least, firms will pass commodity price increases on to their customers but simply enjoy higher margins when commodity prices decline.

So we reached out to our business inflation expectations (BIE) survey panel and put the question to them. Of the 209 firms who responded to the survey in July, half were asked how they would likely respond to an unexpected 10 percent increase in the costs of raw materials, and the other half were asked how they would likely respond to an unexpected 10 percent decrease. What we learned was that the boss was on to something.

For the half of the panel given the raw materials cost increase, about 52 percent indicated they would mostly push the materials costs on to their customers in the form of higher prices, compared to only 18 percent who indicated they would decrease their margins. But of the half of our sample that was given a decline in raw materials costs, 43 percent indicated they would mostly take their good fortune in the form of better margins and only 25 percent indicated that the drop in raw materials costs would induce them to drop their prices.

Of course, what a firm thinks it will do and what the marketplace will allow are not necessarily the same. But this got us thinking back to the earlier work at the Chicago Fed. Does this sort of “asymmetric” response to commodity prices appear in the data?

Following (roughly) the procedure that Evans and Fisher used, we computed the influence of a positive “shock” of one standard deviation (about 5 percent) to commodity prices on core inflation. (Our sample runs from 1954 to 2013.) As did Evans and Fisher, we confirmed that commodity price increases had a significant positive influence on core inflation, spread out over a period of several years. But we were surprised to see that when businesses were hit with a similar-sized decrease in commodities prices, the opposite didn’t occur. Commodity price declines did not produce any downward pressure on core inflation.

As in Evans and Fisher, focusing in on just the post-Volcker era (from 1982 forward), we found that the influence of positive commodity price increases on core inflation was significantly diminished (although it appears to be just a little stronger than what they had reported). However, the influence of commodity price decreases on core inflation remained the same—nada.

For many of you, this result probably doesn’t strike you as pathbreaking. There are many macroeconomic models where prices are “sticky” going down but pretty flexible on the way up. But if the question is whether we think the recent slide in commodity prices is likely to put added downward pressure on core inflation, we’re likely to echo Evans and Fisher with a bit more emphasis: the decline in commodity prices isn’t likely to have an influence on core inflation unless it leads to a general expectation of a broader disinflation. And there is no evidence in the data that suggests this is likely—post-Volcker era or not.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist,

Photo of Brent MeyerBrent Meyer, economist, and

Photo of Nicholas ParkerNicholas Parker, senior economic research analyst, all in the Atlanta Fed's research department


July 16, 2013 in Business Inflation Expectations, Inflation, Pricing | Permalink

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Good analysis.

Does this same dynamic apply to wages? Recent trends in real wages and corporate profits support the idea that when wages fall, firms use it to expand margins. So if we ever get wages to rise again in line with productivity, maybe we'll see firms pass on the costs to their customers. In a consumer-driven economy, wouldn't this create a self-reinforcing cycle of economic growth?

Posted by: Tom in Wisconsin | July 17, 2013 at 10:47 PM

Ha Ha! Tom! Good one!

Dude, increasing wages is the very definition of inflation!

lol!

As for Mr. Bryan's analysis: really, who did not already know this, but for him & a few others at the Atlanta Fed?

Posted by: Edward Ericson Jr. | July 28, 2013 at 08:40 AM

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June 25, 2013

Getting Back to Normal?

Central to any discussion about monetary policy is the degree to which the economy is underperforming relative to its potential, or in more ordinary language, how much slack exists. OK, so how much slack is there, and how long will it take to be absorbed? Well, if you ask the Congressional Budget Office (and a lot of people do), they would have told you last February (their latest estimate) that the economy was underperforming just a shade more than 4 percent relative to its potential last summer, and that slack was likely to increase a little by this summer (to around 4.7 percent). Go to the International Monetary Fund (IMF), and they tell a very similar story in their April World Economic Outlook. The IMF estimates that the amount of slack in the U.S. economy was about 4.2 percent last year, and they expected it would rise a little to about 4.4 percent this year.

As devotees of our Business Inflation Expectations survey know (and you know who you are), the Atlanta Fed has a quarterly, subjective measure of economic slack in the economy as seen by business leaders. This month, businesses told us something pretty interesting—the amount of slack they think they have narrowed pretty sharply between March and June.

Last March, the panel told us that their unit sales were 7.7 percent below "normal"—similar to their assessments in December and September. This month, however, the group cut their estimate of slack to 4.3 percent below normal, on average (see the table).

130625a

What we find most encouraging about this assessment (well, besides the speed at which the slack was being taken up) is that the improvement was most prominent among small and medium-sized firms. These are firms that, according to our survey and other reports (like this one from the National Federation of Independent Business), have been lagging behind in the recovery. Indeed, in June, mid-sized firms indicated that unit sales were only 1.5 percent below normal, a shade better than the big firms in our panel (see the table).

130625b

A look at the industry composition of our survey reveals that the pickup of slack was relatively broadly based too. Only the firms in the mining and utilities, and the professional and business services areas reported more slack relative to March (and the amounts were pretty small at that). Elsewhere, the amount of slack appears to have narrowed quite a bit.

OK, so slack is shrinking, and according to these estimates, it shrank quite a bit between March and June. Does that mean we should be anticipating growing price pressure? Well, we can turn to our panelists again for an answer, and they say no. Projecting over the year ahead, our panelists report little change in either their inflationary sentiment or their inflation uncertainty (see the table).

130625c

Last Wednesday, at the conclusion of its June meeting, the Federal Open Market Committee said that the recovery is proceeding and the labor market is improving, but inflation expectations remain stable. Our June poll of business leaders appears to have also endorsed this view of the economy.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist,

Photo of Brent MeyerBrent Meyer, economist, and

Photo of Nicholas ParkerNicholas Parker, senior economic research analyst, all in the Atlanta Fed's research department

 

June 25, 2013 in Business Inflation Expectations, Federal Reserve and Monetary Policy, GDP, Inflation, Inflation Expectations | Permalink

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May 09, 2013

Weighing In on the Recent Discrepancy in the Inflation Statistics

Recently, there has been a divergence between inflation as measured by the Consumer Price Index (CPI) and the preferred inflation measure of the Federal Open Market Committee (FOMC), which is the price index for personal consumption expenditures (PCE). That divergence is fairly evident in the “core” measures of these two price statistics shown in the chart below.

This strikes us (and others, like Reuters’ Pedro da Costa) as a pretty significant development. The core CPI is telling us that the underlying inflation trend is still holding reasonably close to the FOMC’s longer-term target of 2 percent. But the behavior of the core PCE is rather reminiscent of 2010, when the inflation statistics slid to uncomfortably low levels—a contributing factor to the FOMC’s adoption of QE2. Which of these inflation statistics are we to believe?

Part of the divergence between the two inflation measures is due to rents. Rents are rising at a good pace right now, and since it’s pretty clear that the CPI over-weights their influence, we might be inclined to dismiss some part of the CPI’s more elevated signal. But then there are all those “non-market” components that have been pulling the PCE inflation measure lower—and these aren’t in the CPI. These are components of the PCE price index for which there are no clearly observable transaction prices. They include the “cost” of services provided to households by nonprofit organizations, or the benefits households receive that can only be imputed (i.e., that “free” checking account your bank provides if you maintain a high balance.) Since we can’t really observe the price of these things, we’d probably be inclined to dismiss their influence on PCE the inflation measure. But we’ve done the math, and the impact of these two influences accounts for only about a third of the recent gap between the core PCE and the core CPI inflation measures. Most of the disagreement between the two inflation estimates is coming from elsewhere.

We could continue to parse, item by item, all the various components and weights of the two statistics to get to the bottom of this discrepancy. But in the end, such an accounting exercise would merely tell us why the gap between the two measures has emerged, not which measure is giving the best signal of emerging inflation trends.

As an alternative approach, we thought we’d let the data speak for themselves and search for a common trend that runs through the detailed price data. What we have in mind is to compute the “first principal component” of the disaggregated data used to calculate the CPI and the PCE price indexes. The first principal component is a weighting of the data that explains as much of the data variation as possible. So, in effect, the detailed price data in each price index are being reweighted in a way that reveals their most commonly shared trend, and not by their share of consumer expenditure.

The chart below shows the 12-month trend of the first principal component derived from the 45 CPI components used in the computation of the Federal Reserve Bank of Cleveland’s median CPI, and the first principal component derived from the 177 components used in the computation of the Federal Reserve Bank of Dallas’s trimmed-mean PCE. (These are the most detailed component price data we could easily get our hands on.)

So what do we make of this picture? Well, three things:

First, inflation as measured by the PCE price index has tended to track about 0.25 percentage point under inflation as measured by the CPI over time. So part of the gap between the two inflation measures appears to be a long-term feature of the two inflation statistics.

Second, the first principal components of both the CPI and the PCE data have been persistently under their precrisis averages. In the case of the PCE measure, the first principal component is under the FOMC’s 2 percent target (a point that has not gone unnoticed by Paul Krugman).

A third takeaway from the chart is that the “disinflation” pattern traced out by these principal components has been gradual and modest—much more so than what the core PCE has recently indicated and what the data were telling us back in 2010.

Does that mean we should ignore the recent disinflation being exhibited in the core PCE inflation measure? Well, let’s put it this way: If you’re a glass-half-full sort, we’d say that the recent disinflation trend exhibited by the PCE price index doesn’t seem to be “woven” into the detailed price data, and it certainly doesn’t look like what we saw in 2010. But to you glass-half-empty types, we’d also point out that getting the inflation trend up to 2 percent is proving to be a curiously difficult task.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist,

Photo of Pat HigginsPat Higgins, economist,

Photo of Brent MeyerBrent Meyer, economist, and

Photo of Nicholas ParkerNicholas Parker, senior economic research analyst, all in the Atlanta Fed’s research department


May 9, 2013 in Business Inflation Expectations, Economics, Inflation, Pricing | Permalink

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No, the correct takeaway is the the focus should be on nominal gdp, which is the number that we know with significantly more certainty. There is no single explanation for why CPI, the GDP deflator, and PCE diverge (the principal components are not likely to be stable through time). Sometimes the answer is rents, sometimes its import prices, sometimes the answer is the various weights. all of the above.

Posted by: dwb | May 10, 2013 at 09:48 AM

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April 16, 2013

Improvement in the Outlook? The BIE Panel Thinks So

Earlier this month, Dennis Lockhart, the Atlanta Fed’s top guy, gave his assessment of the economy and monetary policy to the Kiwanis Club of Birmingham, Alabama. Here’s the essential takeaway:

There are encouraging developments in the economy, to be sure, but the evidence of sustainable momentum that will deliver “substantial improvement in the outlook for the labor market” is not yet conclusive. ... How will I, as one policymaker, determine that the balance has shifted and the time for a policy change has come? Well, one key consideration is the array of risks to the economic outlook and my degree of confidence in the outlook.

To help the boss assess the risks to the outlook, we reached out to our Business Inflation Expectations (BIE) panel to get a sense of how they view the outlook for their businesses and, notably, how they assess the risks to that outlook. Specifically, we asked:

Projecting ahead, to the best of your ability, please assign a percent likelihood to the following changes to UNIT SALES LEVELS over the next 12 months.

The table below summarizes the answers and compares them to the responses we got to this statement last November.

First, the business outlook of our panel has improved decidedly since last November. On average, our panel sees unit sales growth averaging 1.8 percent. OK, not a spectacular number, but, to our eyes at least, much improved from the 1.2 percent the group was expecting when we queried five months ago.

And how about the assessment of the risks President Lockhart indicated was also a key consideration? Here again, the sentiment in our panel appears to have shifted favorably. Last November, our panel put the likelihood that their year-ahead unit sales growth would be 1 percent or less at 50 percent. The group now puts the chances of a downshift in business activity at 37 percent. Meanwhile, the upside potential for their sales has grown. Last November, the panel put the chances of a “significant” improvement in unit sales at about 20 percent; this month, the group thinks the likelihood is 30 percent.

And this improved sentiment isn’t centered in just a few industries—it’s spread across a wide swath of the economy. Firms in construction and real estate, which were, on average, projecting 12-month unit sales growth of 1.1 percent last November, now put that growth number at 1.8 percent. The average sales outlook of general-services firms has risen from 1 percent to 2.2 percent; finance and insurance companies went from 0.5 percent to 1.3 percent; and retailers/wholesalers’ unit sales projections rose from 1.5 percent to 2 percent. And manufacturers, who posted relatively strong expectations last November, reported about the same sales outlook this month as they did five months ago.

To be clear, President Lockhart’s recent comments—and the Federal Open Market Committee statement on which they are based—indicate he is looking for a substantial improvement in the outlook for the labor market, not sales. But we’re going to assume that it’s unlikely to have one without the having the other. And is our panel’s unit sales forecast “substantially” improved? Well, what constitutes “substantial” is in the eye of the beholder, but if this isn’t a substantial improvement in the outlook, it’s certainly a move in that direction.

Photo of Mike BryanBy Mike Bryan, vice president and senior economist, and

Photo of Nick ParkerNick Parker, economic research analyst, both in the Atlanta Fed’s research department

April 16, 2013 in Business Inflation Expectations, Economics, Inflation, Inflation Expectations | Permalink

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March 01, 2013

What the Dual Mandate Looks Like

Sometimes simple, direct points are the most powerful. For me, the simplest and most direct points in Chairman Bernanke’s Senate testimony this week were contained in the following one minute and 49 seconds of video (courtesy of Bloomberg):

At about the 1:26 mark, the Chairman says:

So, our accommodative monetary policy has not really traded off one of [the FOMC’s mandated goals] against the other, and it has supported both real growth and employment and kept inflation close to our target.

To that point, here is a straightforward picture:

Inflation and Unemployment

I concede that past results are no guarantee of future performance. And in his testimony, the Chairman was very clear that prudence dictates vigilance with respect to potential unintended consequences:

Highly accommodative monetary policy also has several potential costs and risks, which the committee is monitoring closely. For example, if further expansion of the Federal Reserve's balance sheet were to undermine public confidence in our ability to exit smoothly from our accommodative policies at the appropriate time, inflation expectations could rise, putting the FOMC's price stability objective at risk...

Another potential cost that the committee takes very seriously is the possibility that very low interest rates, if maintained for a considerable time, could impair financial stability. For example, portfolio managers dissatisfied with low returns may reach for yield by taking on more credit risk, duration risk, or leverage.

Concerns about such developments are fair and, as Mr. Bernanke makes clear, shared by the FOMC. Furthermore, the language around the Fed’s ultimate decision to end or alter the pace of its current open-ended asset-purchase program is explicitly cast in terms of an ongoing cost-benefit analysis. But anyone who wants to convince me that monetary policy actions have been contrary to our dual mandate is going to have to explain to me why that conclusion isn’t contradicted by the chart above.

Photo of Dave AltigBy Dave Altig, executive vice president and research director of the Atlanta Fed

March 1, 2013 in Employment, Federal Reserve and Monetary Policy, Inflation, Monetary Policy | Permalink

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November 20, 2012

Rose-Colored Glasses Make the Future Look Blurry: Sales Uncertainty as Seen by the November BIE

Uncertainty is widely cited as being a significant contributor to the economy's subpar growth. Reddy and Thurm report in yesterday's Wall Street Journal that "half of the nation's 40 biggest publicly traded corporate spenders have announced plans to curtail capital expenditures this year or next," in large measure because of rising economic uncertainty. But how uncertain is the current economic outlook? A few economists have attempted to measure business uncertainty, often by using the degree of disagreement between various forecasts, the volatility of certain economic indicators, or some combination of the two. (Two such approaches can be found here and here.)

We thought we'd use our Business Inflation Expectations (BIE) survey to see if we could gauge the degree of business uncertainty directly. Last week, we asked our panel to assign probabilities to various sales outcomes for their businesses for the coming year. (This methodology is the same one we have been using to measure inflation uncertainty, except in this case our business panel was asked to reveal their expectations for unit sales growth over the year ahead.)

Specifically, we put to our panel the following statement:

Projecting ahead, to the best of your ability, please assign a percent likelihood to the following changes to unit sales over the next 12 months.

Panelists were given the following five unit sales outcomes:

  1. down (less than –1 percent)
  2. about unchanged (–1 percent to 1 percent)
  3. up somewhat (1.1 percent to 3 percent)
  4. up significantly (3.1 percent to 5 percent)
  5. up very significantly (greater than 5 percent)

One hundred and ninety-four businesses responded, and here's what they told us: On average, firms expect unit sales growth of about 1.2 percent in the coming year. That's more pessimistic than the real gross domestic product (GDP) forecast of the consensus of economists for the year (about 2 percent). But the range of possible outcomes seemed, to our eyes a least, to be large and unbalanced.

Consider the chart below, which shows the probabilities the panel, on average, assigned to the various sales outcomes. They assigned a 48 percent chance that their unit sales will grow 1 percent or less in the coming year, balanced against only 23 percent likelihood that unit sales will grow more than 3 percent over the next 12 months. In other words, in the minds of our BIE panel, the range of likely sales outcomes over the year ahead is pretty wide, with a fairly weighty chance that unit sales growth may not move in a positive range at all.

121120b

Perhaps we are making a bit too much of the size of the uncertainty businesses are attaching to the outlook. After all, we don't know what uncertainties firms face even in the best of times (since this is the first time we've asked this question). But when we dug into the data a little deeper, we found something else of interest. The degree of economic uncertainty varies widely by firm. Moreover, the greatest uncertainty about the future was held by the panelists who have the most optimistic sales outlook.

Check out the table below. It shows the degree of sales forecast uncertainty on the basis of whether a firm's sales projection is high or low.

121120_tbl

Panelists with the most optimistic sales expectations (the 39 firms with the highest sales forecasts) predicted unit sales growth of a little more than 3.5 percent this year, compared with about a 0.5 percent decline in unit sales for the 39 most pessimistic panelists. But also note that those who are relatively optimistic about the coming year have much greater uncertainty about their future than those who are relatively pessimistic—in fact, they're almost twice as uncertain.

What the November BIE survey seems to be saying is that it isn't just that an uncertain business outlook is reining in our growth prospects, but that the outlook is especially uncertain for the firms that think they have the best opportunity for expansion. Apparently, those wearing rose-colored glasses are having trouble seeing through them.

Note: The regular November Business Inflation Expectations report will be released Wednesday morning.

Mike BryanBy Mike Bryan, vice president and senior economist,

Laurel GraefeLaurel Graefe, economic policy analysis specialist, and

Nicholas ParkerNicholas Parker, economic research analyst, all with the Atlanta Fed

 


November 20, 2012 in Business Inflation Expectations, Inflation, Inflation Expectations | Permalink

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But the coefficient of variation is far higher in the bottom quintile, right?

Posted by: Sebastien Turban (@PtitSeb) | November 21, 2012 at 02:21 PM

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November 09, 2012

Getting the Questions Right

Among the plethora of post-election exit-poll results, the CNBC website highlights a particularly interesting response, linked from the mega-blog Instapundit with the title "Voters Worry More About Inflation Than You Think." The CNBC article itself, written by Allison Linn, describes the poll results in more detail:

It's no surprise that voters in Tuesday's presidential election identified the economy as the No. 1 issue in the campaign, far ahead of health care and the federal budget deficit.
But it was a surprise that so many voters identified rising prices as the biggest economic problem they face.

Linn notes something of a disconnect between this view and the facts on the ground:

...inflation has generally been running well under 2 percent, and Federal Reserve bankers repeatedly have said they feel comfortable that low inflation allows them to keep interest rates at rock-bottom levels.

Yet in an exit poll of more than 25,000 voters conducted by NBC News, 37 percent identified rising prices as the biggest problem facing people like them.

Unemployment was cited by 38 percent, only slightly more than the number who said inflation was their top economic concern. Taxes were named by 14 percent and the housing market was the top concern of 8 percent.

The policy stakes on understanding these responses are pretty high. In the end, the cost of inflation comes in the form of how it may distort behavior and the allocation of resources. So the expectation or perception of significant inflation is at least as pernicious as the measurement itself.

But what, exactly, does this concern about "inflation" actually reflect? Probably not what we think. Some time ago, my colleagues Mike Bryan and Guhan Venkatu (from the Cleveland Fed) made note of "The Curiously Different Inflation Perspectives of Men and Women." Their findings are pretty informative:

Over the past few years, the Federal Reserve Bank of Cleveland, with assistance from the Ohio State University, has studied household inflation perceptions and expectations using a monthly survey of approximately 500 Ohioans (the FRBC/OSU Inflation Psychology Survey). This survey, which records respondents' perceptions of price changes over the past 12 months as well as their expectations for price changes over the next 12 months, has uncovered a surprising result. The data indicate that the public's estimates and predictions of inflation are significantly and systematically related to the demographic characteristics of the respondents. People with high incomes perceive and anticipate much less inflation than people with low incomes, married people less than singles, whites less than nonwhites, and middle-aged people less than young people. This Commentary describes what is perhaps the most curious observation of all: Even after we hold constant income, age, education, race, and marital status, men and women hold very different views on the rate at which prices are changing.

...[S]tatistical tests reveal that even after we adjust for the respondents' age, race, education, and income, women in our survey tended to think inflation was 1.9 percentage points higher than men. A similar examination of respondents' predictions of future inflation yields the same basic result: After we account for other major demographic factors, on average, women expected prices to rise 2.1 percentage points more than men.

It is important to note that this result was not unique to the Cleveland Fed study:

An examination of survey data collected by the University of Michigan (which has recorded the inflation forecasts of U.S. households on a monthly basis since 1978) reveals that women consistently hold higher inflation expectations than men, even after we hold constant other important demographic characteristics of the respondent.

Most intriguing of all, the systematic overstatement of inflation by all consumers, relative to official statistics, and the difference in responses between men and women are not a result of ignorance about the facts, according to those official statistics:

In the August 2001 FRBC/OSU survey, we sought an answer to this question by asking, "Have you heard of the Consumer Price Index (CPI) before?" and "By about what percentage do you think the CPI went up (or down), on average, over the last 12 months?"

A significantly higher proportion of men had heard of the CPI compared to women (75 percent versus 61 percent, respectively). For those who had heard of the CPI, the average perception about how much it had risen over the past 12 months was surprisingly accurate—a perceived increase of 2.9 percent compared to an actual increase of 2.7 percent. It is also very interesting that men and women perceived the CPI's growth rate nearly identically (2.8 percent versus 3.1 percent, respectively.) However, of those who knew of the CPI, the average perception of price increases was 6.7 percent. And even within the subgroup of respondents who knew of the CPI, men had a significantly lower perception of price increases than did women (6.0 percent vs. 7.4 percent). In other words, the public believes that prices are rising more than the CPI reports, and women more so than men.

There are a couple of hypotheses that could be advanced to explain results like this. One is that the conspiracy crowd is correct and the official statistics are rigged and vastly understate true inflation. But that wouldn't get us anywhere near an understanding of why survey responses about inflation would be systematically different across men and women, higher- and low- income individuals, and just about any other demographic cuts we might make.

A second possibility it is that individuals' responses reflect price changes in their own personal market basket, which may differ from that of the average urban wage earner whose habits are reflected in the Consumer Price Index (CPI).That might explain why any demographic sub group could arrive at different inflation perceptions, but it doesn't explain why respondents as a whole systematically overstate inflation relative to the CPI.

I think the most likely explanation is that the survey respondents are expressing a much different concern than whether they believe food, gas, autos, banking services, or whatever are increasing or are likely to increase faster than the official statistics indicate. My guess is that they are telling us that they are concerned that their real—or inflation-adjusted—incomes are not rising fast enough to comfortably sustain their desired spending:


As I noted, the policy stakes are high. In the current environment, the policy prescription for fighting an incipient rise in inflation expectations would be much different than one deployed to address the reality of the chart above. All the more reason to make sure we understand the questions we are asking and the responses we get back.

Just to be sure, we monitor inflation trends and inflation expectations from a number of perspectives: Treasury Inflation Protected Securities (TIPS), forecasts, and the Business Inflation Expectations (BIE) survey, to name just three. And all are available on the Atlanta Fed's Inflation Project for the terminally curious to monitor with us.

Dave AltigBy Dave Altig, executive vice president and research director at the Atlanta Fed

 


November 9, 2012 in Inflation | Permalink

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The question of inflation perceptions is indeed the right question, and some recent work has been done on this. See "'Real-Feel' Inflation: Quantitative Estimation of Inflation Perceptions," Business Economics, Vol. 47, No. 1, National Association for Business Economics, pp. 14-26, which tries to quantify some of the known cognitive biases that operate on inflation perceptions (or at least, to provide the first pieces of a model to do so, were it calibrated properly).

You can find a copy of the paper, although not the BE version, here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1661941

Posted by: Michael Ashton | November 09, 2012 at 11:42 AM

You are looking at the personal income data that because of the massive inequality in the US significantly overstates the income of the bulk of the population.

If you look at the average hourly and weekly earnings published by the BLS you get a very different picture of real income growth.

Average hourly earnings growth is at the record low of 0.8% and with 2% that leaves real income growth much, much weaker than your chart implies. Moreover, the higher inflation stems from food and oil that is a necessity for
the 80% of the population this measure covers.

Posted by: Spencer | November 09, 2012 at 12:24 PM

I would think an analysis of gender perception differences should take into account the % of purchasing decisions by gender.

Women make (according to studies) 70% of the purchasing decisions and by that metric, it shouldn't be a surprise that women are more tuned into household budget.

Good points by Spencer - the 80% (and all, except the disposable income for the top 20% obviously doesn't receivce the same incemental impact as the bottom 80%)... face inflationary costs 3X the rate of headline CPI when faced with health care, higher ed and energy costs.

Posted by: Barclay | November 10, 2012 at 09:53 AM

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