The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.
- BLS Handbook of Methods
- Bureau of Economic Analysis
- Bureau of Labor Statistics
- Congressional Budget Office
- Economic Data - FRED® II, St. Louis Fed
- Office of Management and Budget
- Statistics: Releases and Historical Data, Board of Governors
- U.S. Census Bureau Economic Programs
- White House Economic Statistics Briefing Room
December 04, 2014
The Long and Short of Falling Energy Prices
Earlier this week, The Wall Street Journal asked the $1.36 trillion question: Lower Gas Prices: How Big A Boost for the Economy?
We will take that as a stand-in for the more general question of how much the U.S. economy stands to gain from a drop in energy prices more generally. (The "$1.36 trillion" refers to an estimate of energy spending by the U.S. population in 2012.)
It's nice to be contemplating a question that amounts to pondering just how good a good situation can get. But, as the Journal blog item suggests, the rising profile of the United States as an energy producer is making the answer to this question more complicated than usual.
The data shown in chart 1 got our attention:
As a fraction of total investment on nonresidential structures, spending on mining exploration, shafts, and wells has been running near its 50-year high over the course of the current recovery. As a fraction of total business investment in equipment and structures, the current contribution of the mining and oil sector is higher than any time since the early 1980s (and generally much higher than most periods during the last half century).
In a recent paper, economists Soren Andersen, Ryan Kellogg, and Stephen Salant explain why this matters:
We show that crude oil production from existing wells in Texas does not respond to current or expected future oil prices... In contrast, the drilling of new wells exhibits a strong price response...
In short, the investment piece really matters.
We've done our own statistical investigations, asking the following question: What is the estimated impact of energy price shocks in the second half of this year on investment, consumer spending, and gross domestic product (GDP)?
If you are interested, you can find the details of the statistical model here. But here is the bottom line: the estimated impact of energy price shocks is a very sizeable decline in investment in the mining and oil subsector relative to baseline and, more importantly, an extended period of flat to slightly negative growth in overall investment relative to baseline (see chart 2).
In our simulations, the "baseline" is the scenario without the ex-post energy price shocks occurring in the third and fourth quarters of 2014, while the "alternative" scenario incorporates the (estimated) actual energy price shocks that have occurred in the second half of this year. These shocks lead to a cumulative 8 percent drop in consumer energy prices and a 6 percent drop in producer energy prices by the fourth quarter of this year relative to baseline. By the fourth quarter of 2017, 2 percentage points of these respective energy price declines are reversed. In chart 2 above, each colored line represents the percentage point difference between the "alternative" scenario and the "baseline" scenario.
As for consumption and GDP? Like overall investment, there is a short-run drag before the longer-term boom, as chart 3 shows:
So is the recent decline in energy prices good news for the U.S. economy? Right now our answer is yes, probably—but we may have to be patient.
Note: We have updated this post since it was originally released, clarifying a sentence in the paragraph above chart 2 and providing the data for the charts. The original sentence stated: But here is the bottom line: the estimated impact of energy price shocks is a very sizeable decline in investment in the mining and oil subsector and, more importantly, an extended period of flat to slightly negative growth in overall investment (see chart 2).
TrackBack URL for this entry:
Listed below are links to blogs that reference The Long and Short of Falling Energy Prices:
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.
By Pat Higgins, senior economist in the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference Data Dependence and Liftoff in the Federal Funds Rate:
September 29, 2014
On Bogs and Dots
Consider this scenario. You travel out of town to meet up with an old friend. Your hotel is walking distance to the appointed meeting place, across a large grassy field with which you are unfamiliar.
With good conditions, the walk is about 30 minutes but, to you, the quality of the terrain is not so certain. Though nobody seems to be able to tell you for sure, you believe that there is a 50-50 chance that the field is a bog, intermittently dotted with somewhat treacherous swampy traps. Though you believe you can reach your destination in about 30 minutes, the better part of wisdom is to go it slow. You accordingly allot double the time for traversing the field to your destination.
During your travels, of course, you will learn something about the nature of the field, and this discovery may alter your calculation about your arrival time. If you discover that you are indeed crossing a bog, you will correspondingly slow your gait and increase the estimated time to the other side. Or you may find that you are in fact on quite solid ground and consequently move up your estimated arrival time. Knowing all of this, you tell your friend to keep his cellphone on, as your final meeting time is going to be data dependent.
Which brings us to the infamous “dots,” ably described by several of our colleagues writing on the New York Fed’s Liberty Street Economics blog:
In January 2012, the FOMC began reporting participants’ FFR [federal funds rate] projections in the Summary of Economic Projections (SEP). Market participants colloquially refer to these projections as “the dots” (see the second chart on page 3 of the September 2014 SEP for an example). In particular, the dispersion of the dots represents disagreement among FOMC [Federal Open Market Committee] members about the future path of the policy rate.
The Liberty Street discussion focuses on why the policy rate paths differ among FOMC participants and across a central tendency of the SEPs and market participants. Quite correctly, in my view, the blog post’s authors draw attention to differences of opinion about the likely course of future economic conditions:
The most apparent reason is that each participant can have a different assessment of economic conditions that might call for different prescriptions for current and future monetary policy.
The Liberty Street post is a good piece, and I endorse every word of it. But there is another type of dispersion in the dots that seems to be the source of some confusion. This question, for example, is from Howard Schneider of Reuters, posed at the press conference held by Chair Yellen following the last FOMC meeting:
So if you would help us, I mean, square the circle a little bit—because having kept the guidance the same, having referred to significant underutilization of labor, having actually pushed GDP projections down a little bit, yet the rate path gets steeper and seems to be consolidating higher—so if it’s data dependent, what accounts for the faster projections on rate increases if the data aren’t moving in that direction?
The Chair’s response emphasized the modest nature of the changes, and how they might reflect modest improvements in certain aspects of the data. That response is certainly correct, but there is another point worth emphasizing: It is completely possible, and completely coherent, for the same individual to submit a “dot” with an earlier (or later) liftoff date of the policy rate, or a steeper (or flatter) path of the rate after liftoff, even though their submitted forecasts for GDP growth, inflation, and the unemployment rate have not changed at all.
This claim goes beyond the mere possibility that GDP, inflation, and unemployment (as officially defined) may not be sufficiently complete summaries of the economic conditions a policymaker might be concerned with.
The explanation lies in the metaphor of the bog. The estimated time of arrival to a destination—policy liftoff, for example—depends critically on the certainty with which the policymaker can assess the economic landscape. An adjustment to policy can, and should, proceed more quickly if the ground underfoot feels relatively solid. But if the terrain remains unfamiliar, and the possibility of falling into the swamp can’t be ruled out with any degree of confidence...well, a wise person moves just a bit more slowly.
Of course, as noted, once you begin to travel across the field and gain confidence that you are actually on terra firma, you can pick up the pace and adjust the estimated time of arrival accordingly.
To put all of this a bit more formally, an individual FOMC participant’s “reaction function”—the implicit rule that connects policy decisions to economic conditions—may not depend on just the numbers that that individual writes down for inflation, unemployment, or whatever. It might well—and in the case of our thinking here at the Atlanta Fed, it does—depend on the confidence with which those numbers are held.
For us, anyway, that confidence is growing. Don’t take that from me. Take it from Atlanta Fed President Lockhart, who said in a recent speech:
I'll close with this thought: there are always risks around a projection of any path forward. There is always considerable uncertainty. Given what I see today, I'm pretty confident in a medium-term outlook of continued moderate growth around 3 percent per annum accompanied by a substantial closing of the employment and inflation gaps. In general, I'm more confident today than a year ago.
Viewed in this light, the puzzle of moving dots without moving point estimates for economic conditions really shouldn’t be much of a puzzle at all.
By Dave Altig, executive vice president and research director of the Atlanta Fed
TrackBack URL for this entry:
Listed below are links to blogs that reference On Bogs and Dots:
July 21, 2014
GDP Growth: Will We Find a Higher Gear?
We are still more than a week away from receiving the advance report for U.S. gross domestic product (GDP) from April through June. Based on what we know to date, second-quarter growth will be a large improvement over the dismal performance seen during the first three months of this year. As of today, our GDPNow model is reading an annualized second-quarter growth rate at 2.7 percent. Given that the economy declined by 2.9 percent in the first quarter, the prospects for the anticipated near-3 percent growth for 2014 as a whole look pretty dim.
The first-quarter performance was dominated, of course, by unusual circumstances that we don't expect to repeat: bad weather, a large inventory adjustment, a decline in real exports, and (especially) an unexpected decline in health services expenditures. Though those factors may mean a disappointing growth performance for the year as a whole, we will likely be willing to write the first quarter off as just one of those things if we can maintain the hoped-for 3 percent pace for the balance of the year.
Do the data support a case for optimism? We have been tracking the six-month trends in four key series that we believe to be especially important for assessing the underlying momentum in the economy: consumer spending (real personal consumption expenditures, or real PCE) excluding medical services, payroll employment, manufacturing production, and real nondefense capital goods shipments excluding aircraft.
The following charts give some sense of how things are stacking up. We will save the details for those who are interested, but the idea is to place the recent performance of each series, given its average growth rate and variability since 1990, in the context of GDP growth and its variability over that same period.
What do we learn from the foregoing charts? Three out of four of these series appear to be consistent with an underlying growth rate in the range of 3 percent. Payroll employment growth, in fact, is beginning to send signals of an even stronger pace.
Unfortunately, the series that looks the weakest relates to consumer spending. If we put any stock in some pretty basic economic theory, spending by households is likely the most forward-looking of the four measures charted above. That, to us, means a cautious attitude is the still the appropriate one. Or, to quote from a higher Atlanta Fed power:
... it will likely be hard to confirm a shift to a persistent above-trend pace of GDP growth even if the second-quarter numbers look relatively good.
This experience suggests to me that we can misread the vital signs of the economy in real time. Notwithstanding the mostly positive and encouraging character of recent data, we policymakers need to be circumspect when tempted to drop the gavel and declare the case closed. In the current situation, I feel it's advisable to accrue evidence and gain perspective. It will take some time to validate an outlook that assumes above-trend growth and associated solid gains in employment and price stability.
By Dave Altig, executive vice president and research director, and
Pat Higgins, a senior economist, both in the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference GDP Growth: Will We Find a Higher Gear?:
July 10, 2014
Introducing the Atlanta Fed's GDPNow Forecasting Model
The June 18 statement from the Federal Open Market Committee opened with this (emphasis mine):
Information received since the Federal Open Market Committee met in April indicates that growth in economic activity has rebounded in recent months.... Household spending appears to be rising moderately and business fixed investment resumed its advance, while the recovery in the housing sector remained slow. Fiscal policy is restraining economic growth, although the extent of restraint is diminishing.
I highlighted the business fixed investment (BFI) part of that passage because it contracted at an annual rate of 1.2 percent in the first quarter of 2014. Any substantial turnaround in growth in gross domestic product (GDP) from its dismal first-quarter pace would seem to require that BFI did in fact resume its advance through the second quarter.
We won't get an official read on BFI—or on real GDP growth and all of its other components—until July 30, when the U.S. Bureau of Economic Analysis (BEA) releases its advance (or first) GDP estimates for the second quarter of 2014. But that doesn't mean we are completely in the dark on what is happening in real time. We have enough data in hand to make an informed statistical guess on what that July 30 number might tell us.
The BEA's data-construction machinery for estimating GDP is laid out in considerable detail in its NIPA Handbook. Roughly 70 percent of the advance GDP release is based on source data from government agencies and other data providers that are available prior to the BEA official release. This information provides the basis for what have become known as "nowcasts" of GDP and its major subcomponents—essentially, real-time forecasts of the official numbers the BEA is likely to deliver.
Many nowcast variants are available to the public: the Wall Street Journal Economic Forecasting Survey, the Philadelphia Fed Survey of Professional Forecasters, and the CNBC Rapid Update, for example. In addition, a variety of proprietary nowcasts are available to subscribers, including Aspen Publishers' Blue Chip Publications, Macroeconomic Advisers GDP Tracking, and Moody's Analytics high-frequency model.
With this macroblog post, we introduce the Federal Reserve Bank of Atlanta's own nowcasting model, which we call GDPNow.
GDPNow will provide nowcasts of GDP and its subcomponents on a regularly updated basis. These nowcasts will be available on the pages of the Atlanta Fed's Center for Quantitative Economic Research (CQER).
A few important notes about GDPNow:
- The GDPNow model forecasts are nonjudgmental, meaning that the forecasts are taken directly from the underlying statistical model. (These are not official forecasts of either the Atlanta Fed or its president, Dennis Lockhart.)
- Because nowcasts are often based on both modeling and judgment, there is no reason to expect that GDPNow will agree with alternative forecasts. And we do not intend to present GDPNow as superior to those alternatives. Different approaches have their pluses and minuses. An advantage of our approach is that, because it is nonjudgmental, our methodology is easily replicable. But it is always wise to avoid reliance on a single model or source of information.
- GDPNow forecasts are subject to error, sometimes substantial. Internally, we've regularly produced nowcasts from the GDPNow model since introducing an earlier version of it in an October 2011 macroblog post. A real-time track record for the model nowcasts just before the BEA's advance GDP release is available on the CQER GDPNow webpage, and will be updated on a regular basis to help users make informed decisions about the use of this tool.
So, with that in hand, does it appear that BFI in fact "resumed its advance" last quarter? The table below shows the current GDPNow forecasts:
We will update the nowcast five to six times each month following the releases of certain key economic indicators listed in the frequently asked questions. Look for the next GDPNow update on July 15, with the release of the retail trade and business inventory reports.
If you want to dig deeper, the GDPNow page includes downloadable charts and tables as well as numerical details including the model's nowcasts for GDP, its subcomponents, and how the subcomponent nowcasts are built up from both the underlying source data and the model parameters. This working paper supplies the model's technical documentation. We hope economy watchers find GDPNow to be a useful addition to their information sets.
By Pat Higgins, a senior economist in the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference Introducing the Atlanta Fed's GDPNow Forecasting Model:
April 28, 2014
New Data Sources: A Conversation with Google's Hal Varian
New Data Sources: A Conversation with Google's Hal Varian
In recent years, there has been an explosion of new data coming from places like Google, Facebook, and Twitter. Economists and central bankers have begun to realize that these data may provide valuable insights into the economy that inform and improve the decisions made by policy makers.
As chief economist at Google and emeritus professor at UC Berkeley, Hal Varian is uniquely qualified to discuss the issues surrounding these new data sources. Last week he was kind enough to take some time out of his schedule to answer a few questions about these data, the benefits of using them, and their limitations.
Mark Curtis: You've argued that new data sources from Google can improve our ability to "nowcast." Can you describe what this means and how the exorbitant amount of data that Google collects can be used to better understand the present?
Hal Varian: The simplest definition of "nowcasting" is "contemporaneous forecasting," though I do agree with David Hendry that this definition is probably too simple. Over the past decade or so, firms have spent billions of dollars to set up real-time data warehouses that track business metrics on a daily level. These metrics could include retail sales (like Wal-Mart and Target), package delivery (UPS and FedEx), credit card expenditure (MasterCard's SpendingPulse), employment (Intuit's small business employment index), and many other economically relevant measures. We have worked primarily with Google data, because it's what we have available, but there are lots of other sources.
Curtis: The ability to "nowcast" is also crucially important to the Fed. In his December press conference, former Fed Chairman Ben Bernanke stated that the Fed may have been slow to acknowledge the crisis in part due to deficient real-time information. Do you believe that new data sources such as Google search data might be able to improve the Fed's understanding of where the economy is and where it is going?
Varian: Yes, I think that this is definitely a possibility. The real-time data sources mentioned above are a good starting point. Google data seems to be helpful in getting real-time estimates of initial claims for unemployment benefits, housing sales, and loan modification, among other things.
Curtis: Janet Yellen stated in her first press conference as Fed Chair that the Fed should use other labor market indicators beyond the unemployment rate when measuring the health of labor markets. (The Atlanta Fed publishes a labor market spider chart incorporating a variety of indicators.) Are there particular indicators that Google produces that could be useful in this regard?
Varian: Absolutely. Queries related to job search seem to be indicative of labor market activity. Interestingly, queries having to do with killing time also seem to be correlated with unemployment measures!
Curtis: What are the downsides or potential pitfalls of using these types of new data sources?
Varian: First, the real measures—like credit card spending—are probably more indicative of actual outcomes than search data. Search is about intention, and spending is about transactions. Second, there can be feedback from news media and the like that may distort the intention measures. A headline story about a jump in unemployment can stimulate a lot of "unemployment rate" searches, so you have to be careful about how you interpret the data. Third, we've only had one recession since Google has been available, and it was pretty clearly a financially driven recession. But there are other kinds of recessions having to do with supply shocks, like energy prices, or monetary policy, as in the early 1980s. So we need to be careful about generalizing too broadly from this one example.
Curtis: Given the predominance of new data coming from Google, Twitter, and Facebook, do you think that this will limit, or even make obsolete, the role of traditional government statistical agencies such as Census Bureau and the Bureau of Labor Statistics in the future? If not, do you believe there is the potential for collaboration between these agencies and companies such as Google?
Varian: The government statistical agencies are the gold standard for data collection. It is likely that real-time data can be helpful in providing leading indicators for the standard metrics, and supplementing them in various ways, but I think it is highly unlikely that they will replace them. I hope that the private and public sector can work together in fruitful ways to exploit new sources of real-time data in ways that are mutually beneficial.
Curtis: A few years ago, former Fed Chairman Bernanke challenged researchers when he said, "Do we need new measures of expectations or new surveys? Information on the price expectations of businesses—who are, after all, the price setters in the first instance—as well as information on nominal wage expectations is particularly scarce." Do data from Google have the potential to fill this need?
Varian: We have a new product called Google Consumer Surveys that can be used to survey a broad audience of consumers. We don't have ways to go after specific audiences such as business managers or workers looking for jobs. But I wouldn't rule that out in the future.
Curtis: MIT recently introduced a big-data measure of inflation called the Billion Prices Project. Can you see a big future in big data as a measure of inflation?
Varian: Yes, I think so. I know there are also projects looking at supermarket scanner data and the like. One difficulty with online data is that it leaves out gasoline, electricity, housing, large consumer durables, and other categories of consumption. On the other hand, it is quite good for discretionary consumer spending. So I think that online price surveys will enable inexpensive ways to gather certain sorts of price data, but it certainly won't replace existing methods.
By Mark Curtis, a visiting scholar in the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference New Data Sources: A Conversation with Google's Hal Varian:
November 20, 2013
The Shadow Knows (the Fed Funds Rate)
The fed funds rate has been at the zero lower bound (ZLB) since the end of 2008. To provide a further boost to the economy, the Federal Open Market Committee (FOMC) has embarked on unconventional forms of monetary policy (a mix of forward guidance and large-scale asset purchases). This situation has created a bit of an issue for economic forecasters, who use models that attempt to summarize historical patterns and relationships.
The fed funds rate, which usually varies with economic conditions, has now been stuck at near zero for 20 quarters, damping its historical correlation with economic variables like real gross domestic product (GDP), the unemployment rate, and inflation. As a result, forecasts that stem from these models may not be useful or meaningful even after policy has normalized.
A related issue for forecasters of the ZLB period is how to characterize unconventional monetary policy in a meaningful way inside their models. Attempts to summarize current policy have led some forecasters to create a "virtual" fed funds rate, as originally proposed by Chung et al. and incorporated by us in this macroblog post. This approach uses a conversion factor to translate changes in the Fed's balance sheet into fed funds rate equivalents. However, it admits no role for forward guidance, which is one of the primary tools the FOMC is currently using.
So what's a forecaster to do? Thankfully, Jim Hamilton over at Econbrowser has pointed to a potential patch. However, this solution carries with it a nefarious-sounding moniker—the shadow rate—which calls to mind a treacherous journey deep within the hinterlands of financial economics, fraught with pitfalls and danger.
The shadow rate can be negative at the ZLB; it is estimated using Treasury forward rates out to a 10-year horizon. Fortunately we don't need to take a jaunt into the hinterlands, because the paper's authors, Cynthia Wu and Dora Xia, have made their shadow rate publicly available. In fact, they write that all researchers have to do is "...update their favorite [statistical model] using the shadow rate for the ZLB period."
That's just what we did. We took five of our favorite models (Bayesian vector autoregressions, or BVARs) and spliced in the shadow rate starting in 1Q 2009. The shadow rate is currently hovering around minus 2 percent, suggesting a more accommodative environment than what the effective fed funds rate (stuck around 15 basis points) can deliver. Given the extra policy accommodation, we'd expect to see a bit more growth and a lower unemployment rate when using the shadow rate.
Before showing the average forecasts that come out of our models, we want to point out a few things. First, these are merely statistical forecasts and not the forecast that our boss brings with him to FOMC meetings. Second, there are alternative shadow rates out there. In fact, St. Louis Fed President James Bullard mentioned another one about a year ago based on work by Leo Krippner. At the time, that shadow rate was around minus 5 percent, much further below Wu and Xia's shadow rate (which was around minus 1.2 percent at the end of last year). Considering the disagreement between the two rates, we might want to take these forecasts with a grain of salt.
Caveats aside, we get a somewhat stronger path for real GDP growth and a lower unemployment rate path, consistent with what we'd expect additional stimulus to do. However, our core personal consumption expenditures inflation forecast seems to still be suffering from the dreaded price-puzzle. (We Googled it for you.)
Perhaps more important, the fed funds projections that emerge from this model appear to be much more believable. Rather than calling for an immediate liftoff, as the standard approach does, the average forecast of the shadow rate doesn't turn positive until the second half of 2015. This is similar to the most recent Wall Street Journal poll of economic forecasters, and the September New York Fed survey of primary dealers. The median respondent to that survey expects the first fed funds increase to occur in the third quarter of 2015. The shadow rate forecast has the added benefit of not being at odds with the current threshold-based guidance discussed in today's release of the minutes from the FOMC's October meeting.
Moreover, today's FOMC minutes stated, "modifications to the forward guidance for the federal funds rate could be implemented in the future, either to improve clarity or to add to policy accommodation, perhaps in conjunction with a reduction in the pace of asset purchases as part of a rebalancing of the Committee's tools." In this event, the shadow rate might be a useful scorecard for measuring the total effect of these policy actions.
It seems that if you want to summarize the stance of policy right now, just maybe...the shadow knows.
By Pat Higgins, senior economist, and
Brent Meyer, research economist, both of the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference The Shadow Knows (the Fed Funds Rate):
August 30, 2013
Still Waiting for Takeoff...
On Thursday, we got a revised look at the economy’s growth rate in the second quarter. While the 2.5 percent annualized rate was a significant upward revision from the preliminary estimate, it comes off a mere 1.1 percent growth rate in the first quarter. That combines for a subpar first-half growth rate of 1.8 percent. OK, it’s growth, but not as strong as one would expect for a U.S. expansion and clearly a disappointment to the many forecasters who had once (again) expected this to be the year the U.S. economy shakes itself out of the doldrums.
Now, we’re not blind optimists when it comes to the record of economic forecasts. We know well that the evidence says you shouldn’t get overly confident in your favorite economists’ prediction. Most visions of the economy’s future have proven to be blurry at best.
Still, we at the Atlanta Fed want to know how to best interpret this upward revision to the second-quarter growth estimate and how it affects our president’s baseline forecast “for a pickup in real GDP growth over the balance of 2013, with a further step-up in economic activity as we move into 2014.”
What we can say about the report is that the revised second-quarter growth estimate is a decided improvement from the first quarter and a modest bump up from the recent four-quarter growth trend (1.6 percent). And there are some positive indicators within the GDP components. For example, real exports posted a strong turnaround last quarter, presumably benefiting from Europe’s emerging from its recession. And the negative influence of government spending cuts, while still evident in the data, was much smaller than during the previous two quarters. Oh, and business investment spending improved between the first and second quarters.
All good, but these data simply give us a better fix on where we were in the second quarter, not necessarily a good signal of where we are headed. To that we turn to our “nowcast” estimate for the third quarter based on the incoming monthly data (the evolution of which is shown in the table below).
A "nowcasting" exercise generates quarterly GDP estimates in real time. The technical details of this exercise are described here, but the idea is fairly simple. We use incoming data on 100-plus economic series to forecast 12 components of GDP for the current quarter. We then aggregate those forecasts of GDP components to get a current-quarter estimate of overall GDP growth.
We caution that unlike others, our nowcast involves no interpretation whatsoever of these data. In what is purely a statistical exercise, we let the data do all the speaking for themselves.
Given the first data point of July—the July jobs report—the nowcast for the third quarter was pretty bleak (1.1 percent). Things improved a few days later with the release of strong international trade data for June, and stepped up further with the June wholesale trade report. But the remainder of the recent data point to a third-quarter growth rate that is very close to the lackluster performance of the first half.
In his speech a few weeks ago, President Dennis Lockhart indicated what he was looking for as drivers for stronger growth in the second half of this year.
“I expect consumer activity to strengthen.”
Today’s read on real personal consumption expenditures (PCE) probably isn’t bolstering confidence in that view. Real PCE was virtually flat in July, undermining private forecasters’ expectation of a moderate gain. Our nowcast for real GDP slipped down 0.5 percentage points to 1.4 percent on the basis of this data, and pegged consumer spending at 1.7 percent for Q3—in line with Q2’s 1.8 percent gain.
“I expect business investment to accelerate somewhat.”
The July data were pretty disappointing on this score. The durable-goods numbers released a few days ago were quite weak, causing our nowcast, and those of the others we follow, to revise down the third-quarter growth estimate.
“I expect the rebound we have seen in the housing sector to continue.”
Check. Our nowcast wasn’t affected much by the housing starts data, but the existing sales numbers produced a positive boost to the estimate. Our nowcast’s estimate of residential investment growth in the third quarter is well under what we saw in the second quarter. But at 5.3 percent, the rebound looks to be continuing.
“I expect the recent improvement in exports to last.”
Unfortunately, the July trade numbers don’t get reported until next week. So we’re going to mark this one as missing in action. But as we said earlier, that June trade number was strong enough to cause our third-quarter nowcast to be revised up a bit.
“And I expect to see an easing of the public-sector spending drag at the federal, state, and local levels.”
Again, check. The July Treasury data indicated growth in government spending overall.
So the July data are a mixed bag: some positives, some disappointments, and some missing-in-actions. But if President Lockhart were to ask us (and something tells us he just might), we’re likely to say that on the basis of the July indicators, the “pickup in real GDP growth over the balance of 2013” isn’t yet very evident in the data.
This news isn’t likely to come as a big surprise to him. Again, here’s what he said publicly two weeks ago:
When I weigh the balance of risks around the medium-term outlook I laid out, I have some concerns about the potential for ambiguous or disappointing data. I also think that it is important to be realistic about the degree to which we are likely to have clarity in the near term about the direction of the economy. Both the quantity of information and the strength of the signal conveyed by the data will likely be limited. As of September, the FOMC will have in hand one more employment report, two reports on inflation, a revision to the second-quarter GDP data, and preliminary incoming signals about growth in the third quarter. I don't expect to have enough data to be sure of my outlook.
It’s still a little early to say with any confidence we won’t eventually see a pickup this quarter, and we can hope that the incoming August numbers show a more marked improvement. All we can say at this point is that after seeing most of the July data, it still feels like we’re stuck on the tarmac.
By Mike Bryan, vice president and senior economist,
Patrick Higgins, senior economist, and
Brent Meyer, economist, all in the Atlanta Fed's research department
TrackBack URL for this entry:
Listed below are links to blogs that reference Still Waiting for Takeoff...:
July 05, 2013
A Quick Independence Day Weekend, Post-Employment Report Update
From what I gather, a lot of people took notice of this statement, from Chairman Bernanke’s June 19 press conference:
If the incoming data are broadly consistent with this forecast, the Committee currently anticipates that it would be appropriate to moderate the monthly pace of purchases later this year. And if the subsequent data remain broadly aligned with our current expectations for the economy, we would continue to reduce the pace of purchases in measured steps through the first half of next year, ending purchases around midyear. In this scenario, when asset purchases ultimately come to an end, the unemployment rate would likely be in the vicinity of 7 percent, with solid economic growth supporting further job gains, a substantial improvement from the 8.1 percent unemployment rate that prevailed when the Committee announced this program.
That 7 percent assessment to which the Chairman was referring comes, of course, from the outlook summarized in the Summary of Economic Projections, published following the June 18–19 meeting of the Federal Open Market Committee.
Here are the unemployment forecasts specifically:
The highlighted numbers represent the “central tendency” projections for the average fourth quarter unemployment rate in 2013, 2014, and 2015 (in blue) and the “longer run” (in green). Naturally enough, getting to a 6.5 percent to 6.8 percent unemployment rate in the fourth quarter of 2014 is pretty likely to imply the unemployment rate crossing 7 percent sometime around roughly the middle of next year.
So, how do things look after the June employment report? As is our wont, we turn to our Jobs Calculator to answer such questions, and come up with the following. If the U.S. economy creates 191,000 jobs per month (the average for the past 12 months), and the labor force participation rate stays at 63.5 percent (its June level), and all the other important assumptions (such as the ratio of establishment survey to household survey employment) remain the same, then the economy’s schedule looks like this:
Note also the implication of this statement...
[T]he Committee decided to keep the target range for the federal funds rate at 0 to 1/4 percent and currently anticipates that this exceptionally low range for the federal funds rate will be appropriate at least as long as the unemployment rate remains above 6-1/2 percent , inflation between one and two years ahead is projected to be no more than a half percentage point above the Committee's 2 percent longer-run goal, and longer-term inflation expectations continue to be well anchored.
...which certainly aids in understanding this information, from the last Summary of Economic Projections:
I will leave it to the principals to articulate whether today’s report materially changes anything contained in last month’s projections. In the meantime, enjoy your weekend.
By Dave Altig, executive vice president and research director of the Atlanta Fed
TrackBack URL for this entry:
Listed below are links to blogs that reference A Quick Independence Day Weekend, Post-Employment Report Update:
February 22, 2013
Nature Abhors an Output Gap
In The Washington Post, Neil Irwin highlights a shortcoming that I know all too well:
Throughout the halting economic recovery that began in 2009, the formal economic projections released by the Congressional Budget Office, White House Council of Economic Advisers, and Federal Reserve have displayed quite a consistent pattern: This year may be one of sluggish growth, they acknowledge. But stronger growth, of perhaps 3.5 percent, is just around the corner, and will arrive next year.
Consider, for example, the Fed's projections in November of 2009. Sure, growth would be slow in 2010, they held. But 2011 growth, they expected, would be 3.4 to 4.5 percent, and 2012 would 3.5 to 4.8 percent growth. The actual levels of growth were 2 percent in 2011 and 1.5 percent in 2012.
What's amazing is that the Fed's newest projections, released in December of 2012, look like they could have been copy and pasted from 2009, just with the years changed: They forecast sluggish growth in 2013, 2.3 to 3 percent, followed by a pickup to 3 to 3.5 percent in 2014 and 3 to 3.7 percent in 2015.
I, for one, am guilty as charged, and feel pretty fortunate that the offense is not a hanging one. In fact I don't think Irwin's indictment is overly harsh, and he is on the right track when he offers up this explanation for the last several years' persistently overly rosy projections:
Economic forecasters tend to look at past experience and extrapolate; in the past, when there has been a recession, the very forces that caused the recession become unwound, sowing the seeds for expansion...
Here is a basic fact about macroeconomic forecasting. The truly powerful driver of forecasts is mean reversion, which is the tendency of models to predict that gross domestic product (GDP) will move toward an average trend over time. This fact holds true whether we are talking about formal statistical analysis or the intuitive judgmental adjustments that all forecasters apply to their formal statistical models.
Forecasters are not completely robotic, of course. Irwin is correct when he says "forecasters tend to look at past experience and extrapolate, but forecasters do leaven past experience with incoming details that alter judgments about what is the mean—the "normal state," if you will—to which the economy will converge. But whatever is that normal state, our models insist that we will converge to it.
Nothing illustrates this property of forecasting reality better than this chart, which supplements the latest economic projections from the Congressional Budget Office:
The potential GDP line in that chart is the level of production that represents the structural path of the economy. Forecasters, no matter where they think that potential GDP line might be, all believe actual GDP will eventually move back to it. "Output gaps"—the shaded area representing the cumulative miss of actual GDP relative to its potential—simply won't last forever. And if that means GDP growth has to accelerate in the future (as it does when GDP today is below its potential)—well, that's just the way it is.
Unfortunately, potential GDP is not so simple to divine. We have to guess (or, more generously, estimate) what it is. That guessing game has been harder than usual over the past several years. Here is the record of the CBO's potential GDP since 2009:
I think this picture is a fairly representative record of how views about the potential level of U.S. GDP has evolved over the past several years. What has not been resolved is the debate over what conclusions should be drawn from persistent overestimates of potential and serial misses to the high side on GDP projections.
Irwin seems to be of two minds. On the one hand he offers very structural-sounding reasons for poor forecasting experience:
... the financial-crisis-induced recession of 2008–2009 was so deep that it had deep-seated effects that go beyond those explained by those traditional relationships. It messed up the workings of the financial system, and banks are still trying to figure out what the new one looks like.
On the other hand, he makes appeals to very traditional explanations tied to deficient spending and insufficient policy stimulus (though even here structural change may be one reason that stimulus has been insufficient):
Breakdowns in the financial system mean that low-interest rate policies from the Fed don't have their usual punch. An overhang of household debt means that consumers hold their wallets more than usual. Federal fiscal stimulus to offset those effects is now long-over...
This much, in any event, is clear: Given any starting point where the level of GDP is below its potential level—that is, given an output gap—forecasts will include a bounce back in GDP growth above its long-run average, at least for a while. That's just the way it works.
If, contrary to conventional wisdom, you believe that the true output gaps are much smaller than suggested in the CBO picture above, you might want to take the under on a bet to whether GDP forecasts will prove too optimistic once again.
By Dave Altig, executive vice president and research director of the Atlanta Fed
TrackBack URL for this entry:
Listed below are links to blogs that reference Nature Abhors an Output Gap:
- Is Wage Growth Accelerating?
- Unemployment Risk and Unions
- Cumulative U.S. Trade Deficits Resulting in Net Profits for the U.S. (and Net Losses for China)
- The Slump in Undocumented Immigration to the United States
- A Quick Pay Check: Wage Growth of Full-Time and Part-Time Workers
- Back to the '80s, Courtesy of the Wage Growth Tracker
- Introducing the Atlanta Fed's Taylor Rule Utility
- Payroll Employment Growth: Strong Enough?
- Forecasting Loan Losses for Stress Tests
- Men at Work: Are We Seeing a Turnaround in Male Labor Force Participation?
- October 2016
- September 2016
- August 2016
- July 2016
- June 2016
- May 2016
- April 2016
- March 2016
- February 2016
- January 2016
- Business Cycles
- Business Inflation Expectations
- Capital and Investment
- Capital Markets
- Data Releases
- Economic conditions
- Economic Growth and Development
- Exchange Rates and the Dollar
- Fed Funds Futures
- Federal Debt and Deficits
- Federal Reserve and Monetary Policy
- Financial System
- Fiscal Policy
- Health Care
- Inflation Expectations
- Interest Rates
- Labor Markets
- Latin America/South America
- Monetary Policy
- Money Markets
- Real Estate
- Saving, Capital, and Investment
- Small Business
- Social Security
- This, That, and the Other
- Trade Deficit
- Wage Growth