macroblog

August 12, 2014

Are We There Yet?

Editor’s note: This macroblog post was published yesterday with some content inadvertently omitted. Below is the complete post. We apologize for the error.

Anyone who has undertaken a long road trip with children will be familiar with the frequent “are we there yet?” chorus from the back seat. So, too, it might seem on the long post-2007 monetary policy road trip. When will the economy finally look like it is satisfying the Federal Open Market Committee’s (FOMC) dual mandate of price stability and full employment? The answer varies somewhat across the FOMC participants. The difference in perspectives on the distance still to travel is implicit in the range of implied liftoff dates for the FOMC’s short-term interest-rate tool in the Summary of Economic Projections (SEP).

So how might we go about assessing how close the economy truly is to meeting the FOMC’s objectives of price stability and full employment? In a speech on July 17, President James Bullard of the St. Louis Fed laid out a straightforward approach, as outlined in a press release accompanying the speech:

To measure the distance of the economy from the FOMC’s goals, Bullard used a simple function that depends on the distance of inflation from the FOMC’s long-run target and on the distance of the unemployment rate from its long-run average. This version puts equal weight on inflation and unemployment and is sometimes used to evaluate various policy options, Bullard explained.

We think that President Bullard’s quadratic-loss-function approach is a reasonable one. Chart 1 shows what you get using this approach, assuming a goal of year-over-year personal consumption expenditure inflation at 2 percent, and the headline U-3 measure of the unemployment rate at 5.4 percent. (As the U.S. Bureau of Labor Statistics defines unemployment, U-3 measures the total unemployed as a percent of the labor force.) This rate is about the midpoint of the central tendency of the FOMC’s longer-run estimate for unemployment from the June SEP.

Chart 1: Progress toward Objectives: U-3 Gap

Notice that the policy objective gap increased dramatically during the recession, but is currently at a low value that’s close to precrisis levels. On this basis, the economy has been on a long, uncomfortable trip but is getting pretty close to home. But other drivers of the monetary policy minivan may be assessing how far there is still to travel using an alternate road map to chart 1. For example, Atlanta Fed President Dennis Lockhart has highlighted the role of involuntary part-time work as a signal of slack that is not captured in the U-3 unemployment rate measure. Indeed, the last FOMC statement noted that

Labor market conditions improved, with the unemployment rate declining further. However, a range of labor market indicators suggests that there remains significant underutilization of labor resources.

So, although acknowledging the decline in U-3, the Committee is also suggesting that other labor market indicators may suggest somewhat greater residual slack in the labor market. For example, suppose we used the broader U-6 measure to compute the distance left to travel based on President Bullard’s formula. The U-6 unemployment measure counts individuals who are marginally attached to the labor force as unemployed and, importantly, also counts involuntarily part-time workers as unemployed. One simple way to incorporate the U-6 gap is to compute the average difference between U-6 and U-3 prior to 2007 (excluding the 2001 recession), which was 3.9 percent, and add that to the U-3 longer-run estimate of 5.4 percent, to give an estimate of the longer-run U-6 rate of 9.3 percent. Chart 2 shows what you get if you run the numbers through President Bullard’s formula using this U-6 adjustment (scaling the U-6 gap by the ratio of the U-3 and U-6 steady-state estimates to put it on a U-3 basis).

Chart 2: Progress toward Objectives: U-3 Gap versus U-6 Gap

What the chart says is that, up until about four years ago, it didn’t really matter at all what your preferred measure of labor market slack was; they told a similar story because they tracked each other pretty closely. But currently, your view of how close monetary policy is to its goals depends quite a bit on whether you are a fan of U-3 or of U-6—or of something in between. I think you can put the Atlanta Fed’s current position as being in that “in-between” camp, or at least not yet willing to tell the kids that home is just around the corner.

In an interview last week with the Wall Street Journal, President Lockhart effectively put some distance between his own view and those who see the economy as being close to full employment. The Journal’s Real Time Economics blog quoted Lockhart:

“I’m not ruling out” the idea the Fed may need to raise short-term interest rates earlier than many now expect, Mr. Lockhart said in an interview with The Wall Street Journal. But, at the same time, “I’m a little bit cautious” about the policy outlook, and still expect that when the first interest rate hike comes, it will likely happen somewhere in the second half of next year.

“I remain one who is looking for further validation that we are on a track that is going to make the path to our mandate objectives pretty irreversible,” Mr. Lockhart said. “It’s premature, even with the good numbers that have come in ... to draw the conclusion that we are clearly on that positive path,” he said.

Mr. Lockhart said the current unemployment rate of 6.2% will likely continue to decline and tick under 6% by the end of the year. But, he said, there remains evidence of underlying softness in the job sector, and, he also said, while inflation shows signs of firming, it remains under the Fed’s official 2% target.

Our view is that the current monetary policy journey has made considerable progress toward its objectives. But the trip is not yet complete, and the road ahead remains potentially bumpy. In the meantime, I recommend these road-trip sing-along selections.

Photo of John RobertsonBy John Robertson, a vice president and senior economist in the Atlanta Fed’s research department


August 12, 2014 in Economics, Employment, Federal Reserve and Monetary Policy, Inflation, Labor Markets, Monetary Policy, Pricing, Unemployment | Permalink

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Major problems with U6 include the fact that someone working 34 hours but wants to work 35 or more is considered unemployed (not partially unemployed) -- a very loose definition of an unemployed person. Also, some policymakers conflate marginally attached with discouraged workers. Only one-third of the marginally attached are discouraged about job prospects (the other two-thirds didn't look for work because of illness, school, etc. -- i.e., for reasons monetary policy cannot address). So there are very good reasons for President Bullard's objective function to be based on U3 rather than U6. Additionally, what policymakers should consider, to follow through with your analogy, is when you arrive at your destination should you still have the accelerator pressed to the floor? Or does it not make sense to let off of the gas a bit as you approach your destination (to avoid driving the minivan right through your home).

Posted by: Conrad DeQuadros | August 14, 2014 at 12:57 PM

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August 08, 2014

Getting There?

To say that last week was somewhat eventful on the macroeconomic data front is probably an exercise in understatement. Relevant numbers on GDP growth (past and present), employment and unemployment, and consumer price inflation came in quick succession.

These data provide some of the context for our local Federal Open Market Committee participant’s comments this week (for example, in the Wall Street Journal’s Real Time Economics blog, with similar remarks made in an interview on CNBC’s Closing Bell). From that Real Time Economics blog post:

Although the economy is clearly growing at a respectable rate, Federal Reserve Bank of Atlanta President Dennis Lockhart said Wednesday it is premature to start planning an early exit from the central bank’s ultra-easy policy stance.

“I’m not ruling out” the idea the Fed may need to raise short-term interest rates earlier than many now expect, Mr. Lockhart said in an interview with The Wall Street Journal. But, at the same time, “I’m a little bit cautious” about the policy outlook, and still expect that when the first interest rate hike comes, it will likely happen somewhere in the second half of next year.

“I remain one who is looking for further validation that we are on a track that is going to make the path to our mandate objectives pretty irreversible,” Mr. Lockhart said. “It’s premature, even with the good numbers that have come in...to draw the conclusion that we are clearly on that positive path,” he said.

Why so “cautious”? Here’s the Atlanta Fed staff’s take on the state of things, starting with GDP:

With the annual benchmark revision in hand, 2013 looks like the real deal, the year that the early bet on an acceleration of growth to the 3 percent range finally panned out. Notably, fiscal drag (following the late-2012 budget deal), which had been our go-to explanation of why GDP appeared to have fallen short of expectations once again, looks much less consequential on revision.

Is 2014 on track for a repeat (or, more specifically, comparable performance looking through the collection of special factors that weighed on the first quarter)? The second-quarter bounce of real GDP growth to near 4 percent seems encouraging, but we are not yet overly impressed. Final sales—a number that looks through the temporary contribution of changes in inventories—clocked in at a less-than-eye-popping 2.3 percent annual rate.

Furthermore, given the significant surprise in the first-quarter final GDP report when the medical-expenditure-soaked Quarterly Services Survey was finally folded in, we’re inclined to be pretty careful about over-interpreting the second quarter this early. It’s way too early for a victory dance.

Regarding labor markets, here is our favorite type of snapshot, courtesy of the Atlanta Fed’s Labor Market Spider Chart:

Atlanta Fed Labor Market Spider Chart

There is a lot to like in that picture. Leading indicators, payroll employment, vacancies posted by employers, and small business confidence are fully recovered relative to their levels at the end of the Great Recession.

On the less positive side, the numbers of people who are marginally attached or who are working part-time while desiring full-time hours remain elevated, and the overall job-finding rate is still well below prerecession levels. Even so, these indicators are noticeably better than they were at this time last year.

That year-over-year improvement is an important observation: the period from mid-2012 to mid-2013 showed little progress in the broader measures of labor-market performance that we place in the resource “utilization” category. During the past year, these broad measures have improved at the same relative pace as the standard unemployment statistic.

We have been contending for some time that part-time for economic reasons (PTER) is an important factor in understanding ongoing sluggishness in wage growth, and we are not yet seeing anything much in the way of meaningful wage pressures:

Total Private Earnings, year/year % change, sa

There was, to be sure, a second-quarter spike in the employment cost index (ECI) measure of labor compensation growth, but that increase followed a sharp dip in the first quarter. Maybe the most recent ECI reading is telling us something that hourly earnings are not, but that still seems like a big maybe. Outside of some specific sectors and occupations (in manufacturing, for example), there is not much evidence of accelerating wage pressure in either the data or in anecdotes we get from our District contacts. We continue to believe that wage growth is most consistent with the view that that labor market slack persists, and underlying inflationary pressures (from wage costs, at least) are at bay.

Clearly, it’s dubious to claim that wages help much in the way of making forward predictions on inflation (as shown, for example, in work from the Chicago Fed, confirming earlier research from our colleagues at the Cleveland Fed). And in any event, we are inclined to agree that the inflation outlook has, in fact, firmed up. At this time last year, it was hard to argue that the inflation trend was moving in the direction of the Committee’s objective (let alone that it was not actually declining).

But here again, a declaration that the risks have clearly shifted in the direction of overshooting the FOMC’s inflation goals seems wildly premature. Transitory factors have clearly elevated recent statistics. The year-over-year inflation rate is still only 1.5 percent, and by most cuts of the data, the trend still looks as close to that level as to 2 percent.

'Trends' in the June Core PCE

We do expect measured inflation trends to continue to move in the direction of 2 percent, but sustained performance toward that objective is still more conjecture than fact. (By the way, if you are bothered by the appeal to a measure of core personal consumption expenditures in that chart above, I direct you to this piece.)

All of this is by way of explaining why we here in Atlanta are “a little bit cautious” about joining any chorus singing from the we’re-moving-on-up songbook. Paraphrasing from President Lockhart’s comments this week, the first steps to policy normalization don’t have to wait until the year-over-year inflation rate is consistently at 2 percent, or until all of the slack in the labor market is eliminated. But it is probably prudent to be fairly convinced that progress to those ends is unlikely to be reversed.

We may be getting there. We’re just not quite there yet.

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


August 8, 2014 in Economic conditions, Economics, Employment, Federal Reserve and Monetary Policy, GDP, Inflation, Labor Markets | Permalink

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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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