macroblog

About


The Atlanta Fed's macroblog provides commentary on economic topics including monetary policy, macroeconomic developments, financial issues and Southeast regional trends.

Authors for macroblog are Dave Altig and other Atlanta Fed economists.


May 27, 2015


myCPI: Getting More Personal with Inflation

Last Friday's inflation report was interesting. The consumer price index (CPI) rose only 1.2 percent in April, as falling energy and flat food prices helped to keep the overall index in check.

Does a 1.2 percent (annualized) rise in the cost of living sound about right to you? No? Well, the performance of the CPI reflects the buying habits of the average urban consumer, which is a way to say it sort of reflects the buying habits of everyone, but isn't likely to reflect the buying habits of anyone in particular.

Are you a dapper guy? Good news for you—the cost of men's suits, sport coats, and outerwear fell 4.5 percent (monthly) in April. Fitness buff? Not such good news for you—sporting goods prices jumped 0.9 percent last month. Did you spent a lot of time in the emergency room in April? Even worse news for you: the cost of hospital services rose 1.9 percent last month, their biggest jump in about 25 years! Are you a big blue monster that lives on Sesame Street? Then you had a really good month in April—cookie prices fell 2.4 percent.

OK, you get the idea: different people, different experiences with costs. And of course the folks over at the Bureau of Labor Statistics (BLS) recognize that "it is unlikely that your experience will correspond precisely with either the national indexes or the indexes for specific cities or regions." (Here are some helpful facts about the CPI.)

But that got us wondering if we could take some of the same building blocks that the BLS uses to construct the CPI and create somewhat more individualized price indexes that reflect a wider variety of price change experiences.

So we created 144 individualized market baskets that attempt to capture some of the variation that occurs across different demographic characteristics including age, income, gender, size of household, education, and whether or not you are a homeowner. (You can find greater detail on the construction of these indexes here.) The resulting indexes—we're calling this myCPI—may yield a closer approximation to your cost of living experience than one based on the apocryphal average consumer.

For example, suppose you are a single female who is over 55 years old, rents her place, has an income of more than $70,000, and didn't attend college. In April, your myCPI rose at an annualized rate of 1.4 percent, pretty close to the official CPI growth rate of 1.2 percent for the month. However, your myCPI has risen 1.1 percent over the past year, whereas the official CPI has fallen 0.2 percent.

Are you a male, under 35 years old, married, and without a college degree, but you own your home and make more than $70,000 annually? Your myCPI was virtually flat in April, and people matching your description have seen their cost of living decline by 1.0 percent over the past year.

 

April 2015

 

1-month percent change (annualized rate)

Year-over-year percent change

Official CPI

1.2

-0.2

Female, over 55, without college degree, renter, high income

1.4

1.1

Couple, less than 35 years, without college degree, homeowner, high income

0.1

-1.0

Family (3+ persons); head of household 35–55 years old, homeowner, college degree, middle income

0.6

-0.1

We don't know exactly what you are buying, where you shop, and what prices you are paying, so we can't know how closely your particular circumstance matches any of the 144 indexes we came up with. But within some (perhaps large) margin of error, we can construct a market basket based on the spending habits of people who fit your description in rather broadly defined terms, and we can apply the major price components of the CPI to that particular basket of things. So if you want an idea of the rise (or fall) in the cost of living for someone like yourself (and you know you do), head on over to our website, answer a few questions, and sign up. Every month we'll send you an e-mail update on your myCPI shortly after every CPI release.


May 27, 2015 in Inflation | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01b8d11acf65970c

Listed below are links to blogs that reference myCPI: Getting More Personal with Inflation:

Comments

Would really love to download the mycpi data series that results! Thanks.

Posted by: Steve Roth | May 27, 2015 at 06:32 PM

Extremely cool!

Posted by: Squeeky Wheel | May 28, 2015 at 09:29 AM

I like the down to earth fundamental comparisons. I seem to remember that one FR CEO commented that he could determine the state of the economy by observing activity at Pawn Shops. That is a pretty good barometer for the average person.

Posted by: Hilton T. Meadows | June 02, 2015 at 11:24 AM

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

February 23, 2015


Are Oil Prices "Passing Through"?

In a July 2013 macroblog post, we discussed a couple of questions we had posed to our panel of Southeast businesses to try and gauge how they respond to changes in commodity prices. At the time, we were struck by how differently firms tend to react to commodity price decreases versus increases. When materials costs jumped, respondents said they were likely to pass them on to their customers in the form of price increases. However, when raw materials prices fell, the modal response was to increase profit margins.

Now, what firms say they would do and what the market will allow aren't necessarily the same thing. But since mid-November, oil prices have plummeted by roughly 30 percent. And, as the charts below reveal, our panelists have reported sharply lower unit cost observations and much more favorable margin positions over the past three months...coincidence?



photo of Mike Bryan
By Mike Bryan, vice president and senior economist,
photo of Brent Meyer
Brent Meyer, economist, and
photo of Nicholas Parker
Nicholas Parker, economic policy specialist, all in the Atlanta Fed's research department

February 23, 2015 in Energy, Inflation, Pricing | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01b8d0dc3293970c

Listed below are links to blogs that reference Are Oil Prices "Passing Through"?:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

January 09, 2015


Gauging Inflation Expectations with Surveys, Part 3: Do Firms Know What They Don’t Know?

In the previous two macroblog posts, we introduced you to the inflation expectations of firms and argued that the question you ask matters a lot. In this week's final post, we examine another important dimension of our data: inflation uncertainty, a topic of some deliberation at the last Federal Open Market Committee meeting (according to the recently released minutes).

Survey data typically measure only the inflation expectation of a respondent, not the certainty surrounding that prediction. As a result, survey-based measures often use the disagreement among respondents as a proxy for uncertainty, but as Rob Rich, Joe Tracy, and Matt Ploenzke at the New York Fed caution in this recent blog post, you probably shouldn't do this.

Because we derive business inflation expectations from the probabilities that each firm assigns to various unit cost outcomes, we can measure the inflation uncertainty of a respondent directly. And that allows us to investigate whether uncertainty plays a role in the accuracy of firm inflation predictions. We wanted to know: Do firms know what they don't know?

The following table, adapted from our recent working paper, reports the accuracy of a business inflation forecast relative to the firm's inflation uncertainty at the time the forecast was made. We first compare the prediction accuracy of firms who have a larger-than-average degree of prediction uncertainty against those with less-than-average uncertainty. We also compare the most uncertain firms with the least uncertain firms.

On average, firms provide relatively accurate, unbiased assessments of their future unit cost changes. But the results also clearly support the conclusion that more uncertain respondents tend to be significantly less accurate inflation forecasters.

Maybe this result doesn't strike you as mind-blowing. Wouldn't you expect firms with the greatest inflation uncertainty to make the least accurate inflation predictions? We would, too. But isn't it refreshing to know that business decision-makers know when they are making decisions under uncertainty? And we also think that monitoring how certain respondents are about their inflation expectation, in addition to whether the average expectation for the group has changed, should prove useful when evaluating how well inflation expectations are anchored. If you think so too, you can monitor both on our website's Inflation Project page.

January 9, 2015 in Business Inflation Expectations, Forecasts, Inflation, Inflation Expectations | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01b7c732566f970b

Listed below are links to blogs that reference Gauging Inflation Expectations with Surveys, Part 3: Do Firms Know What They Don’t Know?:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

January 07, 2015


Gauging Inflation Expectations with Surveys, Part 2: The Question You Ask Matters—A Lot

In our previous macroblog post, we discussed the inflation expectations of firms and observed that—while on average these expectations look similar to that of professional forecasters—they reveal considerably more variation of opinion. Further, the inflation expectations of firms look very different from what we see in the household survey of inflation expectations.

The usual focal point when trying to explain measurement differences among surveys of inflation expectations is the respondent, or who is taking the survey. In the previous macroblog post, we noted that some researchers have indicated that not all households are equally informed about inflation trends and that their expectations are somehow biased by this ignorance. For example, Christopher Carroll over at Johns Hopkins suggests that households update their inflation expectations through the news, and some may only infrequently read the press. Another example comes from a group of researchers at the New York Fed and Carnegie Mellon They've suggested that less financially literate households tend to persistently have the highest inflation expectations.

But what these and related research assume is that whom you ask the question of is of primary significance. Could it be that it's the question being asked that accounts for such disagreement among the surveys?

We know, for example, that professional forecasters are asked to predict a particular inflation statistic, while households are simply asked about the behavior of "prices in general" and prices "on the average." To an economist, these amount to pretty much the same thing. But are they the same thing in the minds of non-economists?

You may be surprised, but the answer is no (as a recent Atlanta Fed working paper discussed). When we asked our panel of firms to predict by how much "prices will change overall in the economy"—essentially the same question the University of Michigan asks households—business leaders make the same prediction we see in the survey of households: Their predictions seem high relative to the trend in the inflation data, and the range of opinion among businesses on where prices "overall in the economy" are headed is really, really wide (see the table).

150107a

But what if we ask businesses to predict a particular inflation statistic, as the Philly Fed asks professional forecasters to do? We did that, too. And you know what? Not only did a majority of our panelists (about two-thirds) say they were "familiar" with the inflation statistic, but their predictions looked remarkably similar to that of professional forecasters (see the table).

150107b

So when we ask firms to answer the same question asked of professional forecasters, we got back something that was very comparable to responses given by professional forecasters. But when you ask firms the same question typically asked of households, we got back responses that looked very much like what households report.

Moreover, we dug through the office file cabinets, remembering a related table adapted from a joint project between the Cleveland Fed and the Ohio State University that was highlighted in a 2001 Cleveland Fed Economic Commentary. In August 2001, a group of Ohio households were asked to provide their perception of how much the Consumer Price Index (CPI) had increased over the last 12 months, and we compared it with how much they thought "prices" had risen over the past 12 months.

The households reported that the CPI had risen 3 percent—nearly identical to what the CPI actually rose over the period (2.7 percent). However, in responding to the vaguely worded notion of "prices," the average response was nearly 7 percent (see the table). So again, it seems that the loosely defined concept of "prices" is eliciting a response that looks nothing like what economists would call inflation.

150107c

So it turns out that the question you ask matters—a lot—more so, evidently, than to whom you ask the question. What's the right question to ask? We think it's the question most relevant to the decisions facing the person you are asking. In the case of firms (and others, we suspect), what's most relevant are the costs they think they are likely to face in the coming year. What is unlikely to be top-of-mind for business decision makers is the future behavior of an official inflation statistic or their thoughts on some ambiguous concept of general prices.

In the next macroblog post, we'll dig even deeper into the data.

photo of Mike Bryan
By Mike Bryan, vice president and senior economist,
photo of Brent Meyer
Brent Meyer, economist, and
photo of Nicholas Parker
Nicholas Parker, economic policy specialist, all in the Atlanta Fed's research department

January 7, 2015 in Business Inflation Expectations, Forecasts, Inflation, Inflation Expectations | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01b8d0b9f07a970c

Listed below are links to blogs that reference Gauging Inflation Expectations with Surveys, Part 2: The Question You Ask Matters—A Lot:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

January 05, 2015


Gauging Inflation Expectations with Surveys, Part 1: The Perspective of Firms

Inflation expectations matter. Just ask any central banker (such as the Federal Reserve, the European Central Bank, the Bank of England, or the Bank of Japan).

Central bankers measure inflation expectations in more than a few ways, which is another way of saying no measure of inflation expectations is entirely persuasive.

Survey data on inflation expectations are especially hard to interpret. Surveys of professional economists, such as the Federal Reserve Bank of Philadelphia's Survey of Professional Forecasters, reveal inflation expectations that, over time, track fairly close to the trend in the officially reported inflation data. But the inflation predictions by professional forecasters are extraordinarily similar and call into question whether they represent the broader population.

The inflation surveys of households, however, reveal a remarkably wide range of opinion on future inflation compared to those of professional forecasters. Really, really wide. For example, in any particular month, 13 percent of the University of Michigan's survey of households predicts year-ahead inflation to be more than 10 percent, an annual inflation rate not seen since October 1981. Even in the aggregate, the inflation predictions of households persistently track much higher than the officially reported inflation data (see the chart). These and other curious patterns in the household survey data call into question whether these data really represent the inflation predictions on which households act.

Household Expectations Overshoot Inflation Measures

Even if you're unfamiliar with the literature on this subject, the above observations may not strike you as particularly hard to believe. Economists are, presumably, expert on inflation, while households experience inflation from their own unique—some would suggest even uninformed—perspectives.

We have yet another survey of inflation expectations, one from the perspective of businesses leaders. We think this may be an especially useful perspective on future inflation since business leaders, after all, are the price setters. Our survey has been in the field for a little more than three years now—just long enough, we think, to step back and take stock of what business inflation expectations look like, especially in comparison to the other survey data.

Our initial impressions are reported in a recent Atlanta Fed working paper, and the next few macroblog posts will share some of our favorite observations from this research.

We have been asking firms to assign probabilities to possible changes in their unit costs over the year ahead. From these probabilities, we compute how much firms think their costs are going to change in the coming year and how certain they are of that change (see the table). What we find is that the inflation expectations of firms, on average, look something like the inflation predictions of professional forecasters, but not so much like the predictions of households.

Summary Descriptive Statistics: Inflation Expectations (Oct. 2011 - Dec. 2014)

But we also find that there is a significant range of opinion among firms, more so than the range of opinions that forecasting professionals express. Some of the variation among firms appears to be related to their particular industries and are broadly correlated with the uneven cost pressures shown in similar industrial breakdowns of the Producer Price Index from the U.S. Bureau of Labor Statistics (see the table).

Own Unit Cost Expectations by Industry and Firm Size (Oct. 2011 - Dec. 2014)
(enlarge)

So what we have now are three surveys of inflation expectations, each yielding very different inflation predictions. What accounts for the variation we see across the surveys? Our survey allows us to experiment a bit, which was one of the motivations for conducting it. We didn't just want to measure the inflation expectations of firms; we wanted to learn about those expectations. In the next few macroblog posts, we'll tell you a few of the things we've learned. And we think some of our initial findings will surprise you.


January 5, 2015 in Business Inflation Expectations, Forecasts, Inflation, Inflation Expectations | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01bb07d284c6970d

Listed below are links to blogs that reference Gauging Inflation Expectations with Surveys, Part 1: The Perspective of Firms:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

November 04, 2014


Data Dependence and Liftoff in the Federal Funds Rate

When asked "at which upcoming meeting do you think the FOMC [Federal Open Market Committee] will FIRST HIKE its target for the federal funds rate," 46 percent of the October Blue Chip Financial Forecasts panelists predicted that "liftoff" would occur at the June 2015 meeting, and 83 percent chose liftoff at one of the four scheduled meetings in the second and third quarters of next year.

Of course, this result does not imply that there is an 83 percent chance of liftoff occurring in the middle two quarters of next year. Respondents to the New York Fed's most recent Primary Dealer Survey put this liftoff probability for the middle two quarters of 2015 at only 51 percent. This more relatively certain forecast horizon for mid-2015 is consistent with the "data-dependence principle" that Chair Yellen mentioned at her September 17 press conference. The idea of data dependence is captured in this excerpt from the statement following the October 28–29 FOMC meeting:

[I]f incoming information indicates faster progress toward the Committee's employment and inflation objectives than the Committee now expects, then increases in the target range for the federal funds rate are likely to occur sooner than currently anticipated. Conversely, if progress proves slower than expected, then increases in the target range are likely to occur later than currently anticipated.

If the timing of liftoff is indeed data dependent, a natural extension is to gauge the likely "liftoff reaction function." In the current zero-lower bound (ZLB) environment, researchers at the University of North Carolina and the St. Louis Fed have analyzed monetary policy using shadow fed funds rates, shown in figure 1 below, estimated by Wu and Xia (2014) and Leo Krippner.

Unlike the standard fed funds rate, a shadow rate can be negative at the ZLB. The researchers found that the shadow rates, particularly Krippner's, act as fairly good proxies for monetary policy in the post-2008 ZLB period. Krippner also produces an expected time to liftoff, estimated from his model, shown in figure 1 above. His model's liftoff of December 2015 is six months after the most likely liftoff month identified by the aforementioned Blue Chip survey.

I included Krippner's shadow rate (spliced with the standard fed funds rate prior to December 2008) in a monthly Bayesian vector autoregression alongside the six other variables shown in figure 2 below.

The model assumes that the Fed cannot see contemporaneous values of the variables when setting the spliced policy—that is, the fed funds/shadow rate. This assumption is plausible given the approximately one-month lag in economic release dates. The baseline path assumes (and mechanically generates) liftoff in June 2015 with outcomes for the other variables, shown by the black lines, that roughly coincide with professional forecasts.

The alternative scenarios span the range of eight possible outcomes for low inflation/baseline inflation/high inflation and low growth/baseline growth/high growth in the figures above. For example, in figure 2 above, the high growth/low inflation scenario coincides with the green lines in the top three charts and the red lines in the bottom three charts. Forecasts for the spliced policy rate are conditional on the various growth/inflation scenarios, and "liftoff" in each scenario occurs when the spliced policy rate rises above the midpoint of the current target range for the funds rate (12.5 basis points).

The outcomes are shown in figure 3 below. At one extreme—high growth/high inflation—liftoff occurs in March 2015. At the other—low growth/low inflation—liftoff occurs beyond December 2015.

One should not interpret these projections too literally; the model uses a much narrower set of variables than the FOMC considers. Nonetheless, these scenarios illustrate that the model's forecasted liftoffs in the spliced policy rate are indeed consistent with the data-dependence principle.

Photo of Pat HigginsBy Pat Higgins, senior economist in the Atlanta Fed's research department

November 4, 2014 in Economics, Employment, Federal Reserve and Monetary Policy, Forecasts, Inflation, Monetary Policy | Permalink

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01b7c7003c6e970b

Listed below are links to blogs that reference Data Dependence and Liftoff in the Federal Funds Rate:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

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

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01a3fd455f7a970b

Listed below are links to blogs that reference Are We There Yet?:

Comments

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

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

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

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01a511f29aa7970c

Listed below are links to blogs that reference Getting There?:

Comments

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

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

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01a511d587bd970c

Listed below are links to blogs that reference Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 3):

Comments

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

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

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

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00d8341c834f53ef01a511d43d18970c

Listed below are links to blogs that reference Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 2):

Comments

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

Post a comment

Comments are moderated and will not appear until the moderator has approved them.

If you have a TypeKey or TypePad account, please Sign in

Google Search



Recent Posts


July 2015


Sun Mon Tue Wed Thu Fri Sat
      1 2 3 4
5 6 7 8 9 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30 31  

Archives


Categories


Powered by TypePad