June 23, 2014
Torturing CPI Data until They Confess: Observations on Alternative Measures of Inflation (Part 1)
On May 30, the Federal Reserve Bank of Cleveland generously allowed me some time to speak at their conference on Inflation, Monetary Policy, and the Public. The purpose of my remarks was to describe the motivations and methods behind some of the alternative measures of the inflation experience that my coauthors and I have produced in support of monetary policy.
In this, and the following two blogs, I'll be posting a modestly edited version of that talk. A full version of my prepared remarks will be posted along with the third installment of these posts.
The ideas expressed in these blogs and the related speech are my own, and do not necessarily reflect the views of the Federal Reserve Banks of Atlanta or Cleveland.
Part 1: The median CPI and other trimmed-mean estimators
A useful place to begin this conversation, I think, is with the following chart, which shows the monthly change in the Consumer Price Index (CPI) (through April).
The monthly CPI often swings between a negative reading and a reading in excess of 5 percent. In fact, in only about one-third of the readings over the past 16 years was the monthly, annualized seasonally adjusted CPI within a percentage point of 2 percent, which is the FOMC's longer-term inflation target. (Officially, the FOMC's target is based on the Personal Consumption Expenditures price index, but these and related observations hold for that price index equally well.)
How should the central bank think about its price-stability mandate within the context of these large monthly CPI fluctuations? For example, does April's 3.2 percent CPI increase argue that the FOMC ought to do something to beat back the inflationary threat? I don't speak for the FOMC, but I doubt it. More likely, there were some unusual price movements within the CPI's market basket that can explain why the April CPI increase isn't likely to persist. But the presumption that one can distinguish the price movements we should pay attention to from those that we should ignore is a risky business.
The Economist retells a conversation with Stephen Roach, who in the 1970s worked for the Federal Reserve under Chairman Arthur Burns. Roach remembers that when oil prices surged around 1973, Burns asked Federal Reserve Board economists to strip those prices out of the CPI "to get a less distorted measure. When food prices then rose sharply, they stripped those out too—followed by used cars, children's toys, jewellery, housing and so on, until around half of the CPI basket was excluded because it was supposedly 'distorted'" by forces outside the control of the central bank. The story goes on to say that, at least in part because of these actions, the Fed failed to spot the breadth of the inflationary threat of the 1970s.
I have a similar story. I remember a morning in 1991 at a meeting of the Federal Reserve Bank of Cleveland's board of directors. I was welcomed to the lectern with, "Now it's time to see what Mike is going to throw out of the CPI this month." It was an uncomfortable moment for me that had a lasting influence. It was my motivation for constructing the Cleveland Fed's median CPI.
I am a reasonably skilled reader of a monthly CPI release. And since I approached each monthly report with a pretty clear idea of what the actual rate of inflation was, it was always pretty easy for me to look across the items in the CPI market basket and identify any offending—or "distorted"—price change. Stripping these items from the price statistic revealed the truth—and confirmed that I was right all along about the actual rate of inflation.
Let me show you what I mean by way of the April CPI report. The next chart shows the annualized percentage change for each component in the CPI for that month. These are shown on the horizontal axis. The vertical axis shows the weight given to each of these price changes in the computation of the overall CPI. Taken as a whole, the CPI jumped 3.2 percent in April. But out there on the far right tail of this distribution are gasoline prices. They rose about 32 percent for the month. If you subtract out gasoline from the April CPI report, you get an increase of 2.1 percent. That's reasonably close to price stability, so we can stop there—mission accomplished.
But here's the thing: there is no such thing as a "nondistorted" price. All prices are being influenced by market forces and, once influenced, are also influencing the prices of all the other goods in the market basket.
What else is out there on the tails of the CPI price-change distribution? Lots of stuff. About 17 percent of things people buy actually declined in price in April while prices for about 13 percent of the market basket increased at rates above 5 percent.
But it's not just the tails of this distribution that are worth thinking about. Near the center of this price-change distribution is a very high proportion of things people buy. For example, price changes within the fairly narrow range of between 1.5 percent and 2.5 percent accounted for about 26 percent of the overall CPI market basket in the April report.
The April CPI report is hardly unusual. The CPI report is commonly one where we see a very wide range of price changes, commingled with an unusually large share of price increases that are very near the center of the price-change distribution. Statisticians call this a distribution with a high level of "excess kurtosis."
The following chart shows what an average monthly CPI price report looks like. The point of this chart is to convince you that the unusual distribution of price changes we saw in the April CPI report is standard fare. A very high proportion of price changes within the CPI market basket tends to remain close to the center of the distribution, and those that don't tend to be spread over a very wide range, resulting in what appear to be very elongated tails.
And this characterization of price changes is not at all special to the CPI. It characterizes every major price aggregate I have ever examined, including the retail price data for Brazil, Argentina, Mexico, Columbia, South Africa, Israel, the United Kingdom, Sweden, Canada, New Zealand, Germany, Japan, and Australia.
Why do price change distributions have peaked centers and very elongated tails? At one time, Steve Cecchetti and I speculated that the cost of unplanned price changes—called menu costs—discourage all but the most significant price adjustments. These menu costs could create a distribution of observed price changes where a large number of planned price adjustments occupy the center of the distribution, commingled with extreme, unplanned price adjustments that stretch out along its tails.
But absent a clear economic rationale for this unusual distribution, it presents a measurement problem and an immediate remedy. The problem is that these long tails tend to cause the CPI (and other weighted averages of prices) to fluctuate pretty widely from month to month, but they are, in a statistical sense, tethered to that large proportion of price changes that lie in the center of the distribution.
So my belated response to the Cleveland board of directors was the computation of the weighted median CPI (which I first produced with Chris Pike). This statistic considers only the middle-most monthly price change in the CPI market basket, which becomes the representative aggregate price change. The median CPI is immune to the obvious analyst bias that I had been guilty of, while greatly reducing the volatility in the monthly CPI report in a way that I thought gave the Federal Reserve Bank of Cleveland a clearer reading of the central tendency of price changes.
Cecchetti and I pushed the idea to a range of trimmed-mean estimators, for which the median is simply an extreme case. Trimmed-mean estimators trim some proportion of the tails from this price-change distribution and reaggregate the interior remainder. Others extended this idea to asymmetric trims for skewed price-change distributions, as Scott Roger did for New Zealand, and to other price statistics, like the Federal Reserve Bank of Dallas's trimmed-mean PCE inflation rate.
How much one should trim from the tails isn't entirely obvious. We settled on the 16 percent trimmed mean for the CPI (that is, trimming the highest and lowest 8 percent from the tails of the CPI's price-change distribution) because this is the proportion that produced the smallest monthly volatility in the statistic while preserving the same trend as the all-items CPI.
The following chart shows the monthly pattern of the median CPI and the 16 percent trimmed-mean CPI relative to the all-items CPI. Both measures reduce the monthly volatility of the aggregate price measure by a lot—and even more so than by simply subtracting from the index the often-offending food and energy items.
But while the median CPI and the trimmed-mean estimators are often referred to as "core" inflation measures (and I am guilty of this myself), these measures are very different from the CPI excluding food and energy.
In fact, I would not characterize these trimmed-mean measures as "exclusionary" statistics at all. Unlike the CPI excluding food and energy, the median CPI and the assortment of trimmed-mean estimators do not fundamentally alter the underlying weighting structure of the CPI from month to month. As long as the CPI price change distribution is symmetrical, these estimators are designed to track along the same path as that laid out by the headline CPI. It's just that these measures are constructed so that they follow that path with much less volatility (the monthly variance in the median CPI is about 95 percent smaller than the all-items CPI and about 25 percent smaller than the CPI less food and energy).
I think of the trimmed-mean estimators and the median CPI as being more akin to seasonal adjustment than they are to the concept of core inflation. (Indeed, early on, Cecchetti and I showed that the median CPI and associated trimmed-mean estimates also did a good job of purging the data of its seasonal nature.) The median CPI and the trimmed-mean estimators are noise-reduced statistics where the underlying signal being identified is the CPI itself, not some alternative aggregation of the price data.
This is not true of the CPI excluding food and energy, nor necessarily of other so-called measures of "core" inflation. Core inflation measures alter the weights of the price statistic so that they can no longer pretend to be approximations of the cost of living. They are different constructs altogether.
The idea of "core" inflation is one of the topics of tomorrow's post.
By Mike Bryan, vice president and senior economist in the Atlanta Fed's research department
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May 20, 2014
Where Do Young Firms Get Financing? Evidence from the Atlanta Fed Small Business Survey
During last week's "National Small Business Week," Janet Yellen delivered a speech titled "Small Business and the Recovery," in which she outlined how the Fed's low-interest-rate policies have helped small businesses.
By putting downward pressure on interest rates, the Fed is trying to make financial conditions more accommodative—supporting asset values and lower borrowing costs for households and businesses and thus encouraging the spending that spurs job creation and a stronger recovery.
In general, I think most small businesses in search of financing would agree with the "rising tide lifts all boats" hypothesis. When times are good, strong demand for goods and services helps provide a solid cash flow, which makes small businesses more attractive to lenders. At the same time, rising equity and housing prices support collateral used to secure financing.
Reduced economic uncertainty and strong income growth can help those in search of equity financing, as investors become more willing and able to open their pocketbooks. But even when the economy is strong, there is a business segment that's had an especially difficult time getting financing. And as we've highlighted in the past, this is also the segment that has had the highest potential to contribute to job growth—namely, young businesses.
Why is it hard for young firms to find credit or financing more generally? At least two reasons come to mind: First, lenders tend to have a rearview-mirror approach for assessing commercial creditworthiness. But a young business has little track record to speak of. Moreover, lenders have good reason to be cautious about a very young firm: half of all young firms don't make it past the fifth year. The second reason is that young businesses typically ask for relatively small amounts of money. (See the survey results in the Credit Demand section under Financing Conditions.) But the fixed cost of the detailed credit analysis (underwriting) of a loan can make lenders decide that it is not worth their while to engage with these young firms.
While difficult, obtaining financing is not impossible. Over the past two years, half of small firms under six years old that participated in our survey (latest results available) were able to obtain at least some of the financing requested over all their applications. This 50-percent figure for young firms strongly contrasts with the 78 percent of more mature small firms that found at least some credit. Nonetheless, some young firms manage to find some credit.
This leads to two questions:
- What types of financing sources are young firms using?
- How are the available financing options changing?
To answer the first question, we pooled all of the financing applications submitted by small firms in our semiannual survey over the past two years and examined how likely they were to apply for financing and be approved across a variety of financing products.
Applications and approvals
While most mature firms (more than five years old) seek—and receive—financing from banks, young firms have about as many approved applications for credit cards, vendor or trade credit, or financing from friends or family as they do for bank credit.
The chart below shows that about two-thirds of applications on behalf of mature firms were for commercial loans and lines of credit at banks and about 60 percent of those applications were at least partially approved. In comparison, fewer than half of applications by young firms were for a commercial bank loan or line of credit, fewer than a third of which were approved. Further, about half of the applications by mature firms were met in full compared to less than one-fifth of applications by young firms.
In the survey, we also ask what type of bank the firm applied to (large national bank, regional bank, or community bank). It turns out this distinction matters little for the young firms in our sample—the vast majority are denied regardless of the size of the bank. However, after the five-year mark, approval is highest for firms applying at the smallest banks and lowest for large national banks. For example, firms that are 10 years or older that applied at a community bank, on average, received most of the amount requested, and those applying at large national banks received only some of the amount requested.
Half of young firms and about one-fifth of mature firms in the survey reported receiving none of the credit requested over all their applications. How are firms that don't receive credit affected? According to a 2013 New York Fed small business credit survey, 42 percent of firms that were unsuccessful at obtaining credit said it limited their business expansion, 16 percent said they were unable to complete an existing order, and 16 percent indicated that it prevented hiring.
This leads to the next couple of questions: How are the available options for young firms changing? Is the market evolving in ways that can better facilitate lending to young firms?
When thinking about the places where young firms seem to be the most successful in obtaining credit, equity investments or loans from friends and family ranked the highest according to the Atlanta Fed survey, but this source is not highly used (see the first chart). Is the low usage rate a function of having only so many "friends and family" to ask? If it is, then perhaps alternative approaches such as crowdfunding could be a viable way for young businesses seeking small amounts of funds to broaden their financing options. Interestingly, crowdfunding serves not just as a means to raise funds, but also as a way to reach more customers and potential business partners.
A variety of types of new lending sources, including crowdfunding, were featured at the New York Fed's Small Business Summit ("Filling the Gaps") last week. One major theme of the summit was that credit providers are increasingly using technology to decrease the credit search costs for the borrower and lower the underwriting costs of the lender. And when it comes to matching borrowers with lenders, there does appear to be room for improvement. The New York Fed's small business credit survey, for example, showed that small firms looking for credit spent an average of 26 hours searching during the first half of 2013. Some of the financial services presented at the summit used electronic financial records and relevant business data, including business characteristics and credit scores to better match lenders and borrowers. Another theme to come out of the summit was the importance of transparency and education about the lending process. This was considered to be especially important at a time when the small business lending landscape is changing rapidly.
The full results of the Atlanta Fed's Q1 2014 Small Business Survey are available on the website.
By Ellyn Terry, an economic policy analysis specialist in the Atlanta Fed's research department
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May 13, 2014
Today’s news brings another indication that low inflation rates in the euro area have the attention of the European Central Bank. From the Wall Street Journal (Update: via MarketWatch):
Germany's central bank is willing to back an array of stimulus measures from the European Central Bank next month, including a negative rate on bank deposits and purchases of packaged bank loans if needed to keep inflation from staying too low, a person familiar with the matter said...
This marks the clearest signal yet that the Bundesbank, which has for years been defined by its conservative opposition to the ECB's emergency measures to combat the euro zone's debt crisis, is fully engaged in the fight against super-low inflation in the euro zone using monetary policy tools...
Notably, these tools apparently do not include Fed-style quantitative easing:
But the Bundesbank's backing has limits. It remains resistant to large-scale purchases of public and private debt, known as quantitative easing, the person said. The Bundesbank has discussed this option internally but has concluded that with government and corporate bond yields already quite low in Europe, the purchases wouldn't do much good and could instead create financial stability risks.
Should we conclude that there is now a global conclusion about the value and wisdom of large-scale asset purchases, a.k.a. QE? We certainly have quite a bit of experience with large-scale purchases now. But I think it is also fair to say that that experience has yet to yield firm consensus.
You probably don’t need much convincing that QE consensus remains elusive. But just in case, I invite you to consider the panel discussion we titled “Greasing the Skids: Was Quantitative Easing Needed to Unstick Markets? Or Has it Merely Sped Us toward the Next Crisis?” The discussion was organized for last month’s 2014 edition of the annual Atlanta Fed Financial Markets Conference.
Opinions among the panelists were, shall we say, diverse. You can view the entire session via this link. But if you don’t have an hour and 40 minutes to spare, here is the (less than) ten-minute highlight reel, wherein Carnegie Mellon Professor Allan Meltzer opines that Fed QE has become “a foolish program,” Jeffries LLC Chief Market Strategist David Zervos declares himself an unabashed “lover of QE,” and Federal Reserve Governor Jeremy Stein weighs in on some of the financial stability questions associated with very accommodative policy:
You probably detected some differences of opinion there. If that, however, didn’t satisfy your craving for unfiltered debate, click on through to this link to hear Professor Meltzer and Mr. Zervos consider some of Governor Stein’s comments on monitoring debt markets, regulatory approaches to pursuing financial stability objectives, and the efficacy of capital requirements for banks.
By Dave Altig, executive vice president and research director of the Atlanta Fed.
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February 26, 2014
The Pattern of Job Creation and Destruction by Firm Age and Size
A recent Wall Street Journal blog post caught our attention. In particular, the following claim:
It’s not size that matters—at least when it comes to job creation. The age of the company is a bigger factor.
The following chart shows the average job-creation rate of expanding firms and the average job-destruction rates of shrinking firms from 1987 to 2011, broken out by various age and size categories:
In the chart, the colors represent age categories, and the sizes of the dot represent size categories. So, for example, the biggest blue dot in the far northeast quadrant shows the average rate of job creation and destruction for firms that are very young and very large. The tiny blue dot in the far east region of the chart represents the average rate of job creation and destruction for firms that are very young and very small. If an age-size dot is above the 45-degree line, then average net job creation of that firm size-age combination is positive—that is, more jobs are created than destroyed at those firms. (Note that the chart excludes firms less than one year old because, by definition in the data, they can have only job creation.)
The chart shows two things. First, the rate of job creation and destruction tends to decline with firm age. Younger firms of all sizes tend to have higher job-creation (and job-destruction) rates than their older counterparts. That is, the blue dots tend to lie above the green dots, and the green dots tend to be above the orange dots.
The second feature is that the rate of job creation at larger firms of all ages tends to exceed the rate of job destruction, whereas small firms tend to destroy more jobs than they create, on net. That is, the larger dots tend to lie above the 45-degree line, but the smaller dots are below the 45-degree line.
As pointed out in the WSJ blog post and by others (see, for example, work by the Kauffman Foundation here and here), once you control for firm size, firm age is the more important factor when measuring the rate of job creation. However, young firms are more dynamic in general, with rapid net growth balanced against a very high failure rate. (See this paper by John Haltiwanger for more on this up-or-out dynamic.) Apart from new firms, it seems that the combination of youth (between one and ten years old) and size (more than 250 employees) has tended to yield the highest rate of net job creation.
By John Robertson, a vice president and senior economist in the Atlanta Fed’s research department, and
Ellyn Terry, a senior economic analyst in the Atlanta Fed's research department
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November 15, 2013
Is Credit to Small Businesses Flowing Faster? Evidence from the Atlanta Fed Small Business Survey
The spigot of credit to small businesses appears to be turning faster. As of June 2013, outstanding amounts of small loans on the balance sheets of banks were 4 percent higher than their September 2012 levels, according to the Federal Deposit Insurance Corporation. While they are still 12 percent off 2007 levels, the recent increase is encouraging.
The turnaround in small loan portfolios is not the only sign of improved credit flows to small businesses. The Fed’s October 2013 senior loan officer survey indicates that credit terms to small firms have gradually eased since the second quarter of 2010. Approval ratings of banks and alternative lenders, as measured by Biz2Credit’s lending index, have also risen steadily over the past two years.
In addition to these positive signs, the Atlanta Fed’s third-quarter 2013 Small Business Survey has revealed signs of improvement among small business borrowers in the Southeast. The survey asked recent borrowers about their requests for credit and how successful they were at each place they applied. We also asked, “Over ALL your applications for credit, to what extent were you total financing needs met?” This measure of overall financing satisfaction showed some signs of improvement in the third quarter.
Chart 1 compares the overall financing satisfaction of small business borrowers in the first and third quarter of 2013. The portion of firms that received the full amount requested rose from 28 percent in the first quarter to 42 percent in the third quarter. Meanwhile, the portion that received none of the credit requested declined from 31 percent of the sample in the first quarter to 22 percent in the third quarter.
Further, financing satisfaction rose across a variety of dimensions. Chart 2 shows how average financing satisfaction changed for young firms and mature firms, across industries and by recent sales performance. In all cases, there were increases in the average amount of financing received from the first to the third quarter of 2013.
This broad-based increase in overall financing satisfaction is encouraging. Greater financial health of the applicant pool helped fuel the improvement in borrowing conditions. In the October survey, 52 percent of businesses reported that sales increased while 34 percent reported decreases. Sales have improved significantly from a year ago, when about as many firms reported sales increases as reported decreases. Measures of hiring and capital improvements over the year have also improved for the average firm in the survey (see chart 3).
Lending standards have been improving and small businesses have been slowly gaining momentum, but many obstacles remain. Open-ended questions in our survey revealed that small businesses are still concerned about a number of factors, including the general political and economic uncertainty, the impact of the Affordable Care Act, the higher collateral and personal guarantees required to obtain financing, and regulatory requirements that restrict lending. So while conditions on the ground seem to be improving for small businesses, there still appear to be headwinds that may be holding back a greater pace of improvement.
By Ellie Terry, an economic policy analysis specialist in the Atlanta Fed’s research department
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October 18, 2013
Why Was the Housing-Price Collapse So Painful? (And Why Is It Still?)
Foresight about the disaster to come was not the primary reason this year’s Nobel Prize in economics went to Robert Shiller (jointly with Eugene Fama and Lars Hansen). But Professor Shiller’s early claim that a housing-price bubble was full on, and his prediction that trouble was a-comin’, is arguably the primary source of his claim to fame in the public sphere.
Several years down the road, the causes and effects of the housing-price run-up, collapse, and ensuing financial crisis are still under the microscope. Consider, for example, this opinion by Dean Baker, co-director of the Center for Economic and Policy Research:
...the downturn is not primarily a “financial crisis.” The story of the downturn is a simple story of a collapsed housing bubble. The $8 trillion housing bubble was driving demand in the U.S. economy in the last decade until it collapsed in 2007. When the bubble burst we lost more than 4 percentage points of GDP worth of demand due to a plunge in residential construction. We lost roughly the same amount of demand due to a falloff in consumption associated with the disappearance of $8 trillion in housing wealth.
The collapse of the bubble created a hole in annual demand equal to 8 percent of GDP, which would be $1.3 trillion in today’s economy. The central problem facing the U.S., the euro zone, and the U.K. was finding ways to fill this hole.
In part, Baker’s post relates to an ongoing pundit catfight, which Baker himself concedes is fairly uninteresting. As he says, “What matters is the underlying issues of economic policy.” Agreed, and in that light I am skeptical about dismissing the centrality of the financial crisis to the story of the downturn and, perhaps more important, to the tepid recovery that has followed.
Interpreting what Baker has in mind is important, so let me start there. I have not scoured Baker’s writings for pithy hyperlinks, but I assume that his statement cited above does not deny that the immediate post-Lehman period is best characterized as a period of panic leading to severe stress in financial markets. What I read is his assertion that the basic problem—perhaps outside the crisis period in late 2008—is a rather plain-vanilla drop in wealth that has dramatically suppressed consumer demand, and with it economic growth. An assertion that the decline in wealth is what led us into the recession, is what accounts for the depth and duration of the recession, and is what’s responsible for the shallow recovery since.
With respect to the pace of recovery, evidence supports the proposition that financial crises without housing busts are not so unique—or if they are, the data tend to associate financial-related downturns with stronger-than-average recoveries. Mike Bordo and Joe Haubrich, respectively from Rutgers University and the Federal Reserve Bank of Cleveland, argue that the historical record of U.S. recessions leads us to view housing and the pace of residential investment as the key to whether tepid recoveries will follow sharp recessions:
Our analysis of the data shows that steep expansions tend to follow deep contractions, though this depends heavily on when the recovery is measured. In contrast to much conventional wisdom, the stylized fact that deep contractions breed strong recoveries is particularly true when there is a financial crisis. In fact, on average, it is cycles without a financial crisis that show the weakest relation between contraction depth and recovery strength. For many configurations, the evidence for a robust bounce-back is stronger for cycles with financial crises than those without...
Our results also suggest that a sizeable fraction of the shortfall of the present recovery from the average experience of recoveries after deep recessions is due to the collapse of residential investment.
From here, however, it gets trickier to reach conclusions about why changes in housing values are so important.
Simply put, why should there be a “wealth effect” at all? If the price of my house falls and I suffer a capital loss, I do in fact feel less wealthy. But all potential buyers of my house just gained the opportunity to obtain my house at a lower price. For them, the implied wealth gain is the same as my loss. If buyers and sellers essentially behave the same way, why should there be a large impact on consumption? *
I think this notion quickly leads you to the thought there is something fundamentally special about housing assets and that this special role relates to credit markets and finance. This angle is clearly articulated in these passages from a Bloomberg piece earlier in the year, one of a spate of articles in the spring about why rapidly recovering house prices were apparently not driving the recovery into a higher gear:
The wealth effect from rising house prices may not be as effective as it once was in spurring the U.S. economy...
The wealth effect “is much smaller,” said Amir Sufi, professor of finance at the University of Chicago Booth School of Business. Sufi, who participated in last year’s central-bank conference at Jackson Hole, Wyoming, reckons that each dollar increase in housing wealth may yield as little as an extra cent in spending. That compares with a 3-to-5-cent estimate by economists prior to the recession.
Many homeowners are finding they can’t refinance their mortgages because banks have tightened credit conditions so much they’re not eligible for new loans. Most who can refinance are opting not to withdraw equity after the first nationwide decline in house prices since the Great Depression reminded them home values can fall as well as rise...
Others are finding it difficult to refinance because credit has become a lot harder to come by. And that situation could worsen as banks respond to stepped-up government oversight.
“Credit is going to get tighter before it gets easier,” said David Stevens, president and chief executive officer of the Washington-based Mortgage Bankers Association...
“Households that have been through foreclosure or have underwater mortgages or are otherwise credit-constrained are less able than other households to take advantage” of low interest rates, Fed Governor Sarah Bloom Raskin said in an April 18 speech in New York.
(I should note that Sufi et al. previously delved into the relationship between household balance sheets and the economic downturn here.)
A more systematic take comes from the Federal Reserve Board’s Matteo Iacoviello:
Empirically, housing wealth and consumption tend to move together: this could happen because some third factor moves both variables, or because there is a more direct effect going from one variable to the other. Studies based on time-series data, on panel data and on more detailed, recent micro data point suggest that a considerable portion of the effect of housing wealth on consumption reflects the influence of changes in housing wealth on borrowing against such wealth.
That sounds like a financial problem to me and, in the spirit of Baker’s plea that it is the policy that matters, this distinction is more than semantic. The policy implications of an economic shock that alters the capacity to engage in borrowing and lending are not necessarily the same as those that result from a straightforward decline in wealth.
Having said that, it is not so clear how the policy implications are different. One possibility is that diminished access to credit markets also weakens policy-transmission mechanisms, calling for even more aggressive demand-oriented “pump-priming” policies of the sort Dean Baker advocates. But it is also possible that we have entered a period of deep structural repair that only time (and not merely government stimulus) can (or should) engineer: deleveraging and balance sheet repair, sectoral resource reallocation, new consumption habits, new business models driven by both market and regulatory imperatives, you name it.
In my view, it’s not yet clear which policy approach is closest to optimal. But I am fairly well convinced that good judgment will require us to think of the past decade as the financial event it was, and in many ways still is.
*Update: A colleague pointed out that my example describing housing price changes and wealth effects may be simplified to the point of being misleading. Implicitly, I am in fact assuming that the flow of housing services derived from housing assets is fixed, a condition that obviously would not hold in general. See section 3 of the Iacoviello paper cited above for a theoretical description of why, to a first approximation, we would not expect there to be a large consumption effect from changes in housing values.
By Dave Altig, executive vice president and research director at the Atlanta Fed
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October 04, 2013
Certain about Uncertainty
The Bloom-Davis index of Economic Policy Uncertainty hit 162 in September, up from 102 in August and the highest level seen since December 2012. With all this uncertainty, we can be certain that the events surrounding the government shutdown are having an impact.
This notion of increased uncertainty is captured nicely in our most recent poll of small businesses in the Southeast (past results available here), which went live on September 30, the day before the government shutdown. Although the survey is still out in the field, some early results show:
- Most firms are expressing more uncertainty (see the chart),
- For a significant portion of firms, uncertainty today is having a greater impact than six months ago, and
- The government is heavily featured as a source of the uncertainty.
Of course, what we really care about is whether higher uncertainty is affecting economic activity. When asked, 45 percent of our respondents indicate that uncertainty is in fact having a greater impact on their business than six months ago, up from 37 percent in the first-quarter 2013 survey (relative to fall 2012). Further, fewer firms so far have indicated that uncertainty is having less of an impact. In the current survey, 9 percent of firms have reported less of an effect, compared with 16 percent at the close of last April's survey.
And what are the sources of uncertainty, as seen by our panel of businesses? Eighty-percent of participants have responded to our open-ended question about the primary source(s) of uncertainty. The following "word cloud" summarizes their views:
We will get more responses to the survey over the next week or so, and these may show a different picture. But we're pretty certain of one thing—the duration of the current fiscal impasse in Washington will make a difference.
By John Robertson, vice president and senior economist, and
Ellyn Terry, economic policy analysis specialist, both in the research department of the Atlanta Fed
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