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.

September 21, 2015

What Do U.S. Businesses Know that New Zealand Businesses Don't? A Lot (Apparently).

A recent paper presented at the Brookings Institute, picked up by the Financial Times and the Washington Post, suggests that when it comes to communicating their inflation objective, central banks have a lot of work to do. This conclusion is based primarily on two pieces of evidence.

The first piece is that when businesses in New Zealand are asked about their expectations for changes in "overall prices"—which presumably corresponds with their inflation expectation—the responses, on average, appear to be much too high relative to observed inflation trends. And the responses vary widely from business to business. According to this survey, the average firm in New Zealand expects 4 to 5 percent inflation on a year-ahead basis, and 3.5 percent inflation over the next five to 10 years. Those expectations are for the average firm. Apparently, about one in four firms in New Zealand think inflation in the year ahead will be more than 5 percent, and about one in six firms believe inflation will top 5 percent during the next five to 10 years. Certainly, these aren't the responses one would expect from businesses operating in an economy (like New Zealand) where the central bank has been targeting 2 percent inflation for the past 13 years, over which time inflation has averaged only 2.2 percent (and a mere 0.9 percent during the past four years).

But count us skeptical of this evidence. In this paper from last year, we challenge the assumption that asking firms (or households, for that matter) about expected changes in "overall prices" corresponds to an inflation prediction.

The second piece of evidence regarding the ineffectiveness of inflation targeting is more direct—the authors of this paper actually asked New Zealand businesses a few questions about the central bank and its policies, including this one:

What annual percentage rate of change in overall prices do you think the Reserve Bank of New Zealand is trying to achieve? (Answer: ______%)

The distribution of answers by New Zealand firms is shown in the chart below. According to the survey, the median New Zealand firm appears to think the central bank's inflation target is 5 percent. Indeed, more than a third of firms in New Zealand reported that they think the central bank is targeting an inflation rate greater than 5 percent. Only about 12 percent of the firms were able to correctly identify their central bank's actual inflation target of 2 percent (actually, the New Zealand inflation target is a range of between 1 and 3 percent, centered on 2 percent).

If this weren't embarrassing enough for central bankers, the study also reports that New Zealand households (like U.S. households) don't seem to know who the head of the central bank is. In fact, the authors show that there are more online searches for "puppies" than for information about macroeconomic variables.

OK, to be honest, we don't find that last result very surprising. Puppies are adorable. Central bankers? Not so much. But we were very surprised to see just how high and wide-ranging businesses in New Zealand perceived their central bank's inflation target to be. We're surprised because that bit of information doesn't fit with our understanding of U.S. firms.

In December 2011, the month before the Fed officially announced an explicit numerical target for inflation, we wanted to know whether firms had already formed an opinion about the Fed's inflation objective. So we asked a panel of Southeast businesses the following question:


What we learned was that 16 percent of the 151 firms who responded to our survey had no opinion regarding what rate of inflation the Federal Reserve was aiming for. But of the firms that had an opinion, 58 percent identified a 2 percent inflation target.

But perhaps this isn't a fair comparison to the recent survey of New Zealand businesses. In our 2011 survey, firms had only six options to choose from (including "no opinion"). It could be that our choice of options biased the responses away from high inflation values. So last week, we convened another panel of firms and asked the question in the same open-ended format given to New Zealanders:

What annual rate of inflation do you think the Federal Reserve is aiming for over the long run? (Answer: ______%)

The only material distinction between their question and ours is that we substituted the word "inflation" for the phrase "changes in overall prices." (For this special survey, we polled a national sample of firms that had never before answered one of our survey questions.) The chart below shows what we found relative to the results recently reported for New Zealand firms.

Our survey results look very similar to our results of four years ago. About one in five of the 102 firms that answered our survey was unsure about the Fed's inflation target. But almost 53 percent of the firms that responded answered 2 percent. (On average, U.S. firms judged the central bank's inflation target to be 2.2 percent, just a shade higher than our actual target.)

Furthermore, the distribution of responses to our survey was very tightly centered on 2 percent. The highest estimate of the Fed's inflation target (from only one firm) was 5 percent. So again, our results don't at all resemble what has been reported for the firms down under.

Why is there a glaring difference between what the survey of New Zealand firms found and what we're finding? Well, as noted earlier, we've got our suspicions, but we'll keep studying the issue. And in the meantime, have you seen this?

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

Editor's note: Learn more about inflation and the consumer price index in an ECONversations webcast featuring Atlanta Fed economist Brent Meyer.

September 21, 2015 in Federal Reserve and Monetary Policy, Inflation | Permalink


One possibility is that U.S. executives are better at parroting stated Fed goals, while holding diverse interpretations of the phrase. For example, how many executives know the difference between PCE and CPI indices? And is 2% an aspirational upper limit, or a target with symmetrical Fed responses?

It would be interesting to ask U.S. business members what they view as the Fed's acceptable inflationary range.

Posted by: A | September 21, 2015 at 05:35 PM

So you compare a small open economy with a massive, relatively closed one - and are "surprised" that the massive, closed one has more stable expectations. Try something - take a seat on the outside of big roundabout - then one towards the inside. Notice anything?

Posted by: reason | September 28, 2015 at 03:50 AM

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September 04, 2015

5-Year Deflation Probability Moves Off Zero

Since 2010, our Bank has regularly posted 5-year deflation probabilities derived from prices of Treasury Inflation-Protected Securities (TIPS) on our Deflation Probabilities web page. Each deflation probability, which measures the likelihood of a decline in the Consumer Price Index over a fixed five-year window, is estimated by comparing the price of a recently issued 5-year TIPS with a 10-year TIPS issued about five years earlier. Because the 5-year TIPS has more "deflation protection" than the 10-year TIPS, the implied deflation probability rises when the 5-year TIPS becomes more valuable relative to the 10-year TIPS. (See this macroblog post for a more detailed explanation, or this appendix with the mathematical details.)

From early September 2013 to the first week of August 2015, the five-year deflation probability estimated with the most recently issued 5-year TIPS was identically 0 as the chart shows.

Of course, we should not interpret this long period of zero probability of deflation too literally. It could easily be the case that the "true" deflation probability was slightly above zero but that confounding factors—such as differences in the coupon rates, maturity dates, or liquidity of the TIPS issues—prevented the model from detecting it.

Since August 11, however, the deflation probability has had its own "liftoff" of sorts, fluctuating between 0.0 and 1.3 percent over the 16-day period ending August 26 before rising steadily to 4.1 percent on September 2. Of course, this rise off zero could be temporary, as it proved to be in the summer of 2013.

How seriously should we take this recent liftoff? We can look at options prices on Consumer Price Index inflation (inflation caps and floors) to get a full probability distribution for future inflation; see this published article by economists Yuriy Kitsul and Jonathan Wright or a nontechnical summary in this New York Times article. An alternative is simply to ask professional forecasters for their subjective probabilities of inflation falling within various ranges like "1.0 to 1.4 percent," "1.5 to 1.9 percent," and so forth. The Philly Fed's Survey of Professional Forecasters does just this, with the chart below showing probabilities of low inflation for the Consumer Price Index excluding food and energy (core CPI) from each of the August surveys since 2007.

Although the price index, and the horizon for the inflation outcome, differs from the TIPS-based deflation probability, we see that the shape of the curves is broadly similar to the one shown in the first chart. In the most recent survey, the probability that next year's core CPI inflation rate will be low was small and not particularly elevated relative to recent history. However, the deadline date for this survey was August 11, before liftoff in either the TIPS-based deflation probability or the recent volatility in global financial markets. So stay tuned.

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

September 4, 2015 in Deflation, Federal Reserve and Monetary Policy, Inflation | Permalink


I just wrote a note to investors citing 'deflation' as 'public enemy number one' , in contradistinction to the market's seemingly relentless concern about a hike in rates by the Fed, and a reaction in which equity markets and long-term bonds sell off. With deflation being more of a risk, as clear from your article, the expectation that long rates will rise seems unfounded.
I wish I had seen your article before launching my note as i would have cited it w/proper attribution.
I look forward to seeing more of your work on this topic.

Posted by: Ed L. | September 08, 2015 at 11:48 AM

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July 17, 2015

Getting to the Core of Goods and Services Prices

In yesterday's macroblog post, I highlighted an aspect of a recent Wall Street Journal article that concerns how households perceive inflation. Today, I'm going back to the same well to comment on another aspect of that story, which correctly notes that service-sector prices are rising at a faster clip than the price of goods.

Of course, this isn't just a recent event. Core services prices have outpaced core goods prices over the past 50 years, save a few short-lived deviations. What's unusual about the current recovery, as the chart below shows, is how low services inflation has been.

Core Goods and Services Prices

In the nearly six years since the end of the 2007–09 recession, core services prices have risen at an annualized pace of 2.1 percent, a full percentage point below their average during the last expansion. Conversely, the annualized growth rate in core goods prices during the recovery has been 0.5 percent, compared to a decline of 0.6 percent during the last expansion (see the chart below).

Core Goods and Services Prices

To see how broad-based the slowdown across core services prices has been relative to that of core goods prices, let's take a deeper dive into the components. The chart below compares the difference between a particular component's annualized growth rate during the current expansion and its growth rate during the previous expansion. A negative number here means that a component's price is growing more slowly now than it did prior to the recession.

It's evident that the slowdown in core services prices is fairly broad-based (17 of 22 components are exhibiting disinflation relative to their growth rate over the previous expansion). For core goods components, that number is just five of 15 components. So, if we accept the premise of the WSJ article—that trends in services prices more closely reflect "unused domestic capacity"—then it's possible we could be farther away than we think.

July 17, 2015 in Inflation | Permalink


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July 16, 2015

Different Strokes for Different Folks

A recent Wall Street Journal article offered an interesting conjecture. The author stated,"[b]ecause consumers pay service bills more often than they buy most goods other than food and gasoline, perceptions of inflation skew on the high side."

Research supports the idea that inflation perceptions are unusually influenced by particular prices. For example, some authors have noted that inflation expectations appear to be unusually influenced by movements in gasoline prices.

This research by Georganas, Healy, and Li shows that inflation perceptions are affected by how frequently people buy a particular good—so that nondurable goods prices like gasoline affect inflation perceptions more than durable goods.

And recent work by Johannsen at the Federal Reserve Board shows that demographic groups who have a more disperse set of inflation experiences also tend to hold more disperse inflation expectations. One thing I think we can say is that different demographic groups appear to have different inflation experiences, as this research by Hobjin, Mayer, Stennis, and Topa indicates.

For example, let's take a look at the difference between the inflation experiences of two households. The first is a single older female (over 55 years of age) who rents her home and has a relatively low income (less than $30,000 a year). The second is a young couple (younger than 35 years old) who own their home and have a high income (over $70,000 annually). Both households have high school educations. Recently, the difference between the inflation experiences of these two demographic groups has opened up to a sizable 2.0 percentage points (see the chart). Why?

Different Inflation Experiences

Well, the spending habits of these two groups contain a few striking differences. For example, the older female spends a lot more of her household income on food at home, rent, and medical care than the young couple does (see the table). Also, the young couple appears to spend a larger fraction of their income on transportation (a large portion of which is gasoline).

Comparison of myCPI Weights

Average of the previous five years (through December 2014)


A young couple, homeowner, high income, high school education

Older female, renter, low income, high school education

Food at home



Food away from home









Household operations



Household furnishings and equipment









Medical care












Note: "Other" includes personal care, alcohol, tobacco, reading, and miscellaneous goods and services
Source: Author's calculations based on the BLS's Consumer Expenditure Survey

What's the inflation experience for someone in your particular demographic group? Let's find out. We've developed a tool called myCPI. It allows users to track a measure of the cost of living that captures some of the variation that occurs between demographic groups. In less than a minute, you can answer a few questions about your demographic category, and we'll show you the cost-of-living trends for "your" group. And if you want, we'll send you updates of your demographic group's inflation with every consumer price index (CPI) report.

Why not get your myCPI report? And when tomorrow's CPI report is released, we'll send you a note telling your how your group's cost-of-living adjustment compares to the average urban consumer in the headline CPI.

July 16, 2015 in Inflation | Permalink


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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



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



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



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



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


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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

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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


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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


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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).


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).


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.


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


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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)

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


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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


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