Federal Reserve Bank of Cleveland
Economic Trends (Current)

(Covering March 13, 2008, to April 10, 2008. Contains the most recent articles in all the topic areas. As new articles are written during the month, they replace the existing ones in a topic area.)

1.25.08
The Economy in Perspective

by Mark S. Sniderman

 

There once were some bankers from Gaff
Whose products were layered with math.
With assets worth billions
Now stated in millions,
Those chaps were too clever by half!

This old house…With the U.S. mortgage finance industry in a serious state of disrepair, now is the time to draw up the blueprints, acquire some new tools, roll up our sleeves, and get to work building a sounder structure.

Houses have foundations and support elements, plumbing and electrical, heating and cooling systems, insulation, and, of course, décor. So too, the mortgage finance industry is made up of a set of components such as property appraisers, and loan brokers, originators, servicers; and holders. And just as houses cannot be built without the consent of local officials who determine zoning and building codes, the mortgage finance industry operates under the jurisdiction of various federal and state regulators.

Back in the day, mortgage holders were most likely the originating banks and thrift institutions (as they were fondly called), but the residents of that staid “buy and hold” bungalow have been displaced by occupants of glamorous “originate and sell” mansions. These occupants include independent brokers selling loans on behalf of mortgage banks, which themselves raise funds in capital markets instead of relying on insured deposits. And now the family of mortgage holders include not only the familiar secondary market entities Fannie Mae, Freddie Mac, Ginnie Mae, and FHA/VA, but also and importantly, global investors who hold claims to portions of mortgage pools that have been aggregated by investment banks, layered with private insurance, and graded by private rating agencies.

Explanations of the mortgage debacle range from lenders’ greed and borrowers’ naiveté on the one hand, to all actors in the drama merely responding to the incentives in front of them. The greed-cum-naiveté story leads us in the direction of sturdier consumer protection, such as the Federal Reserve’s proposed revisions to its Truth in Lending regulation (adopted under the Home Ownership and Equity Protection Act), higher standards for state banking supervisors, who license mortgage brokers, and stronger financial literacy programs.

The incentives story reminds us that human nature is susceptible to the lure of the fast buck, such as the chance to earn excessive returns from mortgage-backed securities or buying a house with no money down. In recent years, mortgage lures became so powerful that investors happily filled the entire structure—from wholesale investment bankers to retail mortgage brokers—with cash, all fees and commissions paid up front. And many borrowers, it is said, tried to live beyond their means either by borrowing heavily to acquire a home or maintaining their living standards by cashing out equity built up in better times. Not having to put much equity into the deal, and having low monthly payments, created strong incentives for home buyers hoping to live the American Dream.

So how can we build a stronger structure for financing mortgages? Several ideas are being advanced, including more borrower equity in the deals; more disclosure to borrowers about the terms and conditions of the loan; better education for borrowers before they shop for loans; greater investor liability for any illegal, unfair, or abusive practices committed earlier in the ownership chain.

Lawmakers and regulators are finding some holes in the mortgage finance industry that merit repair, but they should realize that the industry participants—brokers, originators, investment bankers, rating agencies, and consumers—are also likely to change their behavior in response to the market forces unleashed by the current fiasco. There is every reason to believe that the rehabbed industry will be sturdier than the one it replaces and able to protect everyone it serves from losing the roofs over their heads.


03.25.08

Inflation and Prices

February Price Statistics

by Michael F. Bryan and Brent Meyer

The Consumer Price Index (CPI) was virtually unchanged from January, rising only 0.3 percent at an annualized rate in February. This moderation—from increases of 4.8 percent in January and 4.4 percent in December—resulted from a modest increase in food prices, which was offset by a decrease in energy prices, and a slowdown in price appreciation among all items less food and energy. The CPI excluding food and energy (core CPI) was flat, rising only 0.5 percent (at an annualized rate) during the month, compared to a 3.8 percent jump in January. The Median and 16 Percent Trimmed-Mean CPI measures rose 1.4 percent and 1.0 percent, respectively, in February. This stands in stark contrast to last month, when both measures of underlying inflation rose in excess of 4 percent. Producer prices remained elevated in February, as the Producer Price Index (PPI) for finished goods rose 4.2 percent and the PPI excluding food and energy surged 6.8 percent, outpacing all of its longer-term trends.

January Price Statistics

    Percent change, last
    1mo.a 3mo.a 6mo.a 12mo. 5yr.a 2007 avg.
Consumer Price Index
  All items
0.3
3.1
4.7
4.0
2.9
4.2
  Less food and energy
0.5
2.3
2.5
2.3
2.1
2.4
  Medianb
1.4
3.0
3.2
3.0
2.6
3.1
  16% trimmed meanb
1.0
2.7
3.0
2.8
2.4
2.8
Producer Price Index
  Finished goods
4.2
4.0
9.6
6.4
3.9
7.0
  Less food and energy
6.8
4.8
3.2
2.4
1.9
2.1

a. Annualized.
b. Calculated by the Federal Reserve Bank of Cleveland.
Sources: U.S. Department of Labor, Bureau of Labor Statistics; and Federal Reserve Bank of Cleveland.

The 12-month growth rate in the CPI was 4.0 percent in February, down 0.3 percentage point from a month ago. The core CPI and trimmed-mean measures ticked down as well and are now ranging between 2.3 percent and 2.8 percent.

Over the past three months, nearly 55 percent of the components of the CPI rose in excess of 3.0 percent, compared to only 32 percent in February. Some relatively large components, such as lodging away from home and motor fuel prices, decreased during the month, after posting strong increases over the last quarter. However, components with strong responsiveness to commodity prices—like jewelry and watches—continued to show large price increases.

Core services prices rose just 1.0 percent in February, their smallest increase since May 2005. As a consequence, the 12-month growth rate in core services prices ticked down to 3.2 percent from 3.4 percent in January. Core goods prices fell 0.9 percent during the month and have remained unchanged over the past 12 months.

According to the March preliminary Survey of Consumers (University of Michigan) near-term (one-year ahead) household inflation expectations jumped up from 3.9 percent in February to 4.6 percent. Expectations over the longer-term (5 to 10 years), however, actually ticked down to 3.3 percent.


03.25.08

Money, Financial Markets, and Monetary Policy

Down Another Seventy-Five

by Charles T. Carlstrom and Sarah Wakefield

On March 18, 2008, the Federal Open Market Committee (FOMC) voted to lower its target for the federal funds rate by 75 basis points to 2.25 percent. In supporting the move, the committee noted that “Growth in consumer spending has slowed and labor markets have softened.  Financial markets remain under considerable stress, and the tightening of credit conditions and the deepening of the housing contraction are likely to weigh on economic growth over the next few quarters.” Despite these concerns, the committee noted that “Inflation has been elevated, and some indicators of inflation expectations have risen.” Concerns about inflation were behind the two dissents recorded at the meeting. Those dissenting, Richard W. Fisher of Dallas and Charles I. Plosser  of Philadelphia, “preferred less aggressive action at this meeting.”

Since September 2007, the FOMC has cut its funds rate target 300 basis points. While the speed of the cuts has certainly been dramatic, it is useful to recognize that the overall quantity cut is not unprecedented. Just before the beginning of the 2001 recession, the FOMC began to cut rates and by the end of six months, it had cut them 275 basis points. From January 2001 to December 2001, rates were cut a whopping 475 basis points.

One indicator of the financial pressure mentioned in the committee’s statement is the spread between the three-month LIBOR, the rate at which banks lend to each other in the wholesale London money market, and the rate on the on the comparable 90-day Treasury security, the rate at which the U.S. government borrows. A look at this spread shows that stress in financial markets has been quite elevated since July 2007. More alarming is that the spread is higher now than it was during the Russian default crisis or the Asian crisis. To address this stress, the Federal Reserve has not only cut the funds rate, but it has also created two new lending programs, the Term Auction Facility (TAF) and the Term Security Lending Facility (TSLF).

The TAF was introduced in December to address “elevated pressures in short-term funding markets.” The TAF provides another means by which the Federal Reserve can inject liquidity into the banking system. Historically, the Fed did this with loans to financial institutions, but concern had arisen that such loans did not always adequately accommodate periods of financial stress. One reason for this shortcoming was thought to be financial institutions’ possible reluctance to borrow through the discount window for fear it would signal financial weakness. The TAF was instituted to overcome this stigma effect. In addition, it provides a 28-day loan rather than the overnight loans that were typically offered at the discount window.

In its March 11 announcement, the Fed affirmed that the TSLF facility was instituted “to promote liquidity in the financing markets for Treasury and other collateral and thus to foster the functioning of financial markets more generally.”  It provides increased liquidity by dealing directly with a group of primary dealers (including some major nondepository investment banks, which do not have direct access through the TAF). It also accepts a wider range of assets as collateral than the TAF. In particular, the program allows these institutions to borrow Treasury securities backed by the pledge of Aaa-rated mortgaged-backed securities. These securities, however, were already allowed as collateral through the discount window. Like the TAF, the TSLF also provides loans with  28-day terms.

Besides short-term financial stresses, officials are concerned that longer-term credit is becoming harder to secure. The fear is that shorter-term liquidity issues can become longer-term credit problems. Should credit issues gain a hold, they cannot be attacked through the short-term funding arrangements offered by the Fed. Instead, broad cuts in the funds rate, as well as clear communication about the rate’s future path, will be needed to attack longer-term credit issues.

One measure of these longer-term credit problems is the spread between yields on Aaa-rated securities, the highest-quality corporate bond, and the comparable 10-year Treasury note. This measure of credit risks is clearly elevated but does remain below its levels during the 2001 recession. More alarming to some is that since July, it has increased more than 125 basis points—a six-month movement beyond anything witnessed in recent history.

While acknowledging the risks to inflation, the committee indicated that these risks were outweighed by risks to the real economy by stating, “However, downside risks to growth remain.” The markets interpreted this statement as evidence that more rate cuts are almost certain to occur. Over 90 percent of participants in the fed funds futures market expect at least a 25 basis point cut at or before the next scheduled meeting, April 29–30. Nearly 60 percent of participants are betting on a cut of at least 50 basis points.

April Meeting Probabilities

Date
1.50%
1.75%
2.00%
2.25%
2.50%
3/3/2008
19.15%
10.40%
38.01%
22.18%
10.26%
3/4/2008
21.38%
9.58%
41.22%
17.28%
10.53%
3/5/2008
16.35%
6.00%
36.43%
27.72%
13.49%
3/6/2008
18.22%
19.54%
32.22%
20.04%
9.97%
3/7/2008
25.99%
23.17%
27.28%
13.98%
9.59%
3/10/2008
37.07%
0.00%
40.60%
12.52%
9.81%
3/11/2008
12.71%
8.11%
31.80%
35.23%
12.15%
3/12/2008
12.24%
10.65%
34.75%
29.61%
11.76%
3/13/2008
27.36%
0.00%
37.42%
25.74%
9.48%
3/14/2008
50.52%
0.00%
32.15%
13.64%
3.69%
3/17/2008
87.36%
0.00%
3.11%
8.33%
1.20%
3/18/2007
39.64%
19.72%
31.56%
7.16%
1.92%

Note: Probabilities are calculated using trading-day closing prices from options on federal funds futures that trade on the Chicago Board of Trade.
Source: Chicago Borad of trade and Bloomberg Financial Services.

While fed funds futures provide a sense of where the funds rate is expected to head in the immediate future, the one-year Overnight Index Swap rate (OIS) provides a measure of what the funds rate is expected to average over the next year. A look at this rate suggests that the funds rate will average 50 basis points lower than the current funds rate, and thus that by next year, more than another 50 basis points will be cut.


03.20.08

Money, Financial Markets, and Monetary Policy

What Is the Yield Curve Telling Us?

by Joseph G. Haubrich and Katie Corcoran

Since last month, the yield curve has gotten steeper, with long-term interest rates rising and short-term interest rates falling.  One reason for noting this is that the slope of the yield curve has achieved some notoriety as a simple forecaster of economic growth. The rule of thumb is that an inverted yield curve (short rates above long rates) indicates a recession in about a year, and yield curve inversions have preceded each of the last six recessions (as defined by the NBER). Very flat yield curves preceded the previous two, and there have been two notable false positives: an inversion in late 1966 and a very flat curve in late 1998. More generally, though, a flat curve indicates weak growth, and conversely, a steep curve indicates strong growth. One measure of slope, the spread between 10-year bonds and 3-month Treasury bills, bears out this relation, particularly when real GDP growth is lagged a year to line up growth with the spread that predicts it.

The yield curve has continued to get steeper, with a slight drop in long rates overshadowed by the plunge in short rates.  The spread remains positive, with the 10-year rate moving down to 3.51 percent while the 3-month rate dropped all the way to 1.37 percent (both for the week ending March 14).  Standing at 214 basis points, the spread is well above February’s 144 basis points, and January’s 127 basis points.  Projecting forward using past values of the spread and GDP growth suggests that real GDP will grow at about a 2.7 percent rate over the next year. This is on the high side of other forecasts.

While such an approach predicts when growth is above or below average, it does not do so well in predicting the actual number, especially in the case of recessions. Thus, it is sometimes preferable to focus on using the yield curve to predict a discrete event: whether or not the economy is in recession. Looking at that relationship, the expected chance of the economy being in a recession next March stands at 2.7 percent, down from February’s 3.7 percent, and from January’s already low 4.8 percent.  

This probability of recession is below several recent estimates, and perhaps seems strange the in the midst of the recent financial concerns, but one aspect of those concerns has been a flight to quality, which lowers Treasury yields. Also related to those concerns is the reduction of the federal funds target rate and the discount rate by the Federal Reserve, which tends to steepen the yield curve.  Furthermore, the forecast is for where the economy will be next March, not earlier in the year.

On the other hand, a year ago, the yield curve was predicting a 46 percent chance that the US economy would be in a recession in March 2008, a number that seemed unreasonably high at the time.

To compare the 2.7 percent probability of recession to some other probabilities and learn more about different techniques of predicting recessions, head on over to the Econbrowser blog.

Of course, it might not be advisable to take this number quite so literally, for two reasons. First, this probability is itself subject to error, as is the case with all statistical estimates. Second, other researchers have postulated that the underlying determinants of the yield spread today are materially different from the determinants that generated yield spreads during prior decades. Differences could arise from changes in international capital flows and inflation expectations, for example. The bottom line is that yield curves contain important information for business cycle analysis, but, like other indicators, they should be interpreted with caution.

For more detail on these and other issues related to using the yield curve to predict recessions, see the Commentary “Does the Yield Curve Signal Recession?


03.07.08

International Markets

Are We Importing Inflation?

By Owen F. Humpage and Michael Shenk

Headline and core price indexes recently have been rising at a disconcertingly fast pace, respectively reflecting in large measure the direct and secondary pass-through effects of record oil prices, rapidly rising agricultural prices, and the dollar’s depreciation.  Some observers, noting the international lineage of these price patterns, wonder if world economic development and the integration of global markets have doomed the United States to a permanently higher rate of inflation. This question reflects a very common misunderstanding of what price indexes tell us and of the true nature of inflation. To be sure, greater global claims on scarce world resources will raise our cost of living, but inflation has everywhere and always been a home-grown, central-bank problem.

January CPI Statistics

    Annualized percent change, last:
    1mo. 3mo. 6mo. 12mo. 2007 avg.
Consumer Price Index
  All items
4.8
6.8
4.7
4.4
2.9
  Less food and energy
3.8
3.1
2.7
2.5
2.3
  Median
4.2
3.7
3.4
3.2
3.1
  Trimmed mean
4.3
3.5
3.1
3.0
2.7

Source: The Bureau of Labor Statistics

Inflation refers to the deterioration in the purchasing power of money that results when a central bank creates more money than the public wants to hold. Inflation manifests itself as a rise in all prices and wages—in fact, anything denominated in dollars. If the public’s demand for money grows at 3 percent per year and if the central bank creates money at 5 percent per year, then prices will eventually rise at 2 percent per year, and they will keep climbing as long as the disparity between the supply and demand for money continues. While the rate of inflation is ultimately under the control of central banks, the speed with which an inflationary monetary impulse filters through to wages and prices seems to depend on many things, including the amount of slack in an economy, whether the public anticipated the inflation, and the degree of price competitiveness throughout the economy. When the economy is operating at full tilt, when people generally anticipate inflation, and when firms and workers operate in a highly competitive environment, monetary excesses are likely to translate quickly into higher prices and wages.

Inflation is not the only type of price pressures that an economy experiences.  Individual prices adjust continually to the ebb and flow of supply and demand pressures. Economists often refer to these as relative (or sometimes real) price adjustments. Although they hit our price indexes much like inflation, relative prices adjustments are fundamentally different. For one thing, relative price changes convey important information about the relative scarcities of goods and services. A rising relative price indicates that demand has outstripped supply (or that supply has fallen short of demand), while a falling price denotes just the opposite. Relative price changes also help stabilize the economy.  A rising relative price induces consumers to conserve on a specific good and to look for substitutes.  A rising relative price also entices producers to bring more of the good to market. Relative price changes are vital for the smooth functioning of any market economy; inflation, however, contributes no information useful to our consumption, production, and labor choices.

Import Prices

  Average annual percentage change:
2/02-1/08
CPI
3.0
Imports
  All
5.8
  Foods
6.5
  Industrial materials
17.0
  Capital goods
−0.6
  Automotive
1.0
  Consumer
0.7
  Petroleum
26.8
  Nonpetroleum
2.2

Source: The Bureau of Labor Statistics.

Export Prices

  Average annual percentage change:
2/02-1/08
CPI
3.0
Imports
  All
3.6
  Foods
10.1
  Industrial materials
9.1
  Capital goods
0.2
  Automotive
1.0
  Consumer
1.3
  Agriculture
9.9
  Nonagriculture
3.0

Source: The Bureau of Labor Statistics.

Currently, petroleum and agricultural goods are experiencing very strong upward relative price pressures. Two factors seem to account for this. First, the world has experienced what seems to be unprecedented economic performance in recent years according to IMF data.  Between 2004 and 2007, the world economy grew at an exceptionally strong 5.1 percent average annual rate, and nearly all nations have shared in this expansion.  Emerging market countries in Southeast Asia, notably China and India, have led the way. As these nations develop, they place greater demands on world food stuffs, petroleum supplies, and other resources. Also putting upward pressure on many prices has been the dollar’s depreciation. Since early 2002, the dollar has depreciated more than 25 percent on a broad, trade-weighted basis. A dollar depreciation reduces the foreign-currency prices of dollar-denominated goods and thereby shifts world demand toward those goods. Because of the dollar’s role as the key international currency, most of the world’s commodities, like oil and agricultural goods, are denominated in dollars. The prices of U.S. foods and industrial-materials exports, for example, are rising at or near double-digit levels.

Although relative price pressures can be broad based, their impact on the overall price level in an economy is by nature transitory. Petroleum and agricultural products enter the production process of a very wide range of other goods. Consequently, higher prices of these basic commodities tend to pass through into the prices of other producer and consumer goods. Nevertheless, as long as the central bank is not creating an excessive amount of money, this pass-through effect is limited. As consumers spend more money on higher-priced petroleum and agricultural goods—the quantity demand of these items seems fairly unresponsive to price changes—then they eventually must have less money to spend on other goods and services. Other relative prices must then fall, so that over the intermediate to long term, the average rate of the price rise tends to equal the underlying inflation rate as determined by monetary policy. People’s cost of living certainly will rise, their incomes will buy less, and their economic well-being will be diminished. Nevertheless, these relative price pressures do not generate inflation.

One wrinkle in this story has to do with the dollar’s depreciation. Since early 2006, the depreciation seems to reflect international portfolio diversification, rather than excessive U.S. money growth. Over the past 25 years, the U.S. has financed its current account deficits by issuing financial claims to the rest of the world. Economists have long expected that, at some point, foreign investors—both private and official—would become reluctant to hold additional dollar-denominated assets and at this point the dollar would depreciate. Of course, concerns about future inflation could motivate portfolio diversification and dollar depreciation, but to date, direct measures provide little evidence of rising inflation expectations. We are not importing inflation through the dollar’s depreciation.


03.24.08

Economic Activity

Does the Recent Trend in Labor Demand Presage Recession?

By Murat Tasci and Beth Mowry

The number of job openings or vacancies posted by employers constitutes a good measure of unmet labor demand. Assuming employers spend some time and resources to recruit workers, this measure could give us a nice clue about their expectations of future labor market conditions.

The longest time series of vacancies that we have is the Help-Wanted Advertising Index (HWAI) provided by the Conference Board. This index is monthly and tracks help-wanted ads in more than 50 major metro area newspapers. HWAI is normalized to 100 for 1987. A higher index value indicates higher numbers of help-wanted ads are appearing in newspapers.

The HWAI experienced sharp declines in every postwar recession. More interestingly, every decline in the index has been accompanied by a recession, with the exception of the mid-1960s. After hovering in the 40s for most of the 2003–2005 period, the index started to fall gradually at the beginning of 2006. In January 2008, the index hit 21, its all-time low.

Ironically, the index by itself may not be very informative about the difficulty employers have in filling positions, because that difficulty depends not just on how many vacancies there are, but also on the number of workers who are looking for jobs. For instance, the index could be low (indicating few vacancies), but employers could expect to fill vacant positions relatively easily if many unemployed people are searching for work.

In order to assess employers’ difficulty in finding workers, we need measure of market tightness, which we have in the ratio of help-wanted newspapers ads to the number of unemployed workers. Movements in this ratio closely follow those of the HWAI. During expansions, both market tightness and the HWAI rise, and during recessions, they both decline. Recent labor market conditions, according to this measure, have been exceptionally slack. Currently, the ratio stands at 0.205, the lowest it has ever been.

However, the declining trend in these measures might be related to factors independent of labor market conditions. In particular, a shift toward posting vacancies online rather than in newspapers could be responsible for it. The Conference Board started to gather and report data on online help-wanted ads in May 2005. Although this series is not long enough to cover a full business cycle, we still see that vacancies, as measured by online ads, have grown from about 3.1 million to more than 4.3 million in two years (May 2005–May 2007). These numbers suggest that the HWAI might be understating the true availability of jobs in the labor market. In addition to tracking the number of help-wanted ads posted online, the Conference Board also tracks how many of those postings are new. It would be fair to assume that movements in total help-wanted ads are driven by the new postings every month. However, the raw data captures a lot of seasonal movements. When we look at year-over-year changes in online ads to remove this seasonality, we see an increasing trend in job postings until mid-2007, after which postings decline. In February 2008, total new ads increased by only 103,000 relative to February 2007, the smallest year-over-year increase since May 2006.

One other major source of data on job availability, and one that is more comprehensive than the HWAI, is the Job Openings and Labor Turnover Survey (JOLTS) published by Bureau of Labor Statistics. It samples from the same universe as the Current Employment Survey, and each establishment in the Survey provides data on job openings in a given month.

The picture painted by JOLTS data confirms the view that the HWAI might be understating the actual availability of jobs. According to JOLTS, employers were creating more and more vacancies every month up until mid-2007. Since then, the trend seems to have reversed. According to the most recent data, there were about 3,925,000 job openings in January 2008.

Four industries accounted for almost two-thirds of the total monthly job openings on average—education and health services; professional and business services; trade, transportation, and utilities; and leisure and hospitality. All sectors roughly follow a similar pattern over time, although three sectors experienced larger declines in response to the last economic downturn: professional and business services; manufacturing; and trade, transportation, and utilities. Even though job openings have leveled off recently in these sectors, we have not observed a decline similar enough the one observed at the onset of the last recession to indicate a significant slowdown in the labor market.

Overall, different measures of job availability all suggest that the number of new job vacancies advertised might be falling. Total job openings are still far from their pre-recession peak of 4,580,000 (in December 2000), which is consistent with the last recovery’s designation as a “jobless” one.


 

03.18.08

Economic Activity

Home Price Indexes

By Michael Shenk

According to most major measures, home prices are declining—and if market commentators are right, prices may continue to fall in the near future.  This decline may be hard to stomach for recent home buyers, home sellers, or those in need of refinancing, but should it really have been so unexpected? 

Over the past 30 years, and presumably even before that (we don’t have much data prior to the mid-1970s) nominal home prices have risen steadily. According to the data we do have, prices have risen approximately 2–2.5 percent annually on average after adjusting for inflation. Of course, price growth isn’t within this range every year, but prices do seem to dance around it. Growth of this sort is often referred to as mean reverting since the series fluctuates in the short term but always seems to return to the average rate of growth in the long term. If home price growth is in fact mean reverting, one would expect periods of above-average growth to be followed by periods of slow growth—barring any fundamental shift in the market. For instance, one of the many factors that influences the price of homes is population growth; if population growth were to fall permanently from its long-term average of 1.3 percent to, say, 0.8 percent (the long-range growth forecast of the Census Bureau), we would expect the average growth rate of home prices to permanently shift down as well.

In reality, it is difficult to tell whether changes in price appreciation are the result of fundamental changes in the market or just short-term changes due to speculation or varying economic conditions. If we assume for the sake of argument that there hasn’t been a fundamental shift in the market, we should be able to get a good idea of how much farther home prices might fall by looking at the price levels warranted by their average long-term growth rate.
           
To calculate this estimate of where home prices “should” be, we need to make a few additional assumptions. The first assumption is that home prices grow at a constant rate over time. The second assumption is that all of the available data are valid and consistent with the first assumption. This means we won’t exclude periods where the growth might seem atypical. Using a basic loglinear regression, we get the following two pictures of our estimates. 

According to these rough estimates, homes prices are still above the levels warranted by their average growth rates and therefore seem likely to fall somewhat in the future. Just how much they are likely to fall depends on the index one looks at and how much one expects the market to compensate for the above-average growth of the past few years. As the charts show, housing prices seem to be mean-reverting: Periods in which prices are above their “expected” levels are generally followed by periods in which prices are below these levels. Keep in mind that these are real figures and that any future inflation reduces the amount by which home prices are likely to fall.


03.18.08

Economic Activity

Preliminary Employment Data Might Miss a Recession Onset

By Yoonsoo Lee and Beth Mowry

As we move further into 2008, concerns are growing about the U.S. economy heading toward recession. The Employment Situation reports released by the Bureau of Labor Statistics have received a lot of attention in recent months, as economists try to determine the extent to which housing troubles may have spilled over to the broader economy. This month’s Employment Situation reported a decline of 63,000 two nonfarm payrolls in February and a revised loss in January, which increased the initial tally of 17,000 job losses to one of 22,000. The last time two consecutive months of decline occurred was in June 2003.
 
While the timely information provided by preliminary numbers can help us to assess labor market conditions, those numbers are subject to two monthly revisions after they are first released, as well as annual revisions every February. These revisions can be substantial and are sometimes even larger than the payroll changes themselves. The graph below, showing initial releases and revised numbers, demonstrates how significant revisions for any given month can be. January’s report this year, for example, initially reported a gain in December of just 18,000 nonfarm jobs but was revised up in the following report to a gain of 82,000. In August last year a payroll loss was initially reported, but with the revision the net change moved into positive territory.

Historically, payroll numbers usually dip sharply during or prior to recessions. But it important to note that this observation is based on revised numbers. The data initially reported might have shown a different picture at the time. To get an idea of how much this picture might change from initial release to revision, we prepared graphs of both sets of employment numbers around the two most recent recessions.

Around the 2000–2001 recession, both initial and revised data indicate a slowing labor market approaching  July, although the initial data show a somewhat steeper descent.  Despite the slowing trend in nonfarm employment growth in early 1990, growth continued to average about 200,000 jobs per month over the year. Payroll growth sharply turned negative in July, the official starting point of the recession. However, July’s loss of 219,000 jobs ended up being revised to a loss of just 89,000 later.

Revisions appear to have been more dramatic leading up to the 2001 recession than the 1990–1991 recession.  The initial data show slowing, but employment gains looked solid right up to the onset of the recession in March. However, the revised data paint a much less optimistic picture, twice crossing negative territory in the two quarters preceeding the recession. Employment gains of 268,000 in January and 135,000 in Feburary were revised down to –16,000 and 61,000. 

As of January 2001, labor indicators such as payroll employment, the unemployment rate, and the employment-to-population ratio all looked to be holding strong. Reports based on the initial releases of early 2001 thus painted a relatively positive picture of the labor market. Even the Cleveland Fed’s January Economic Trends assessed labor markets as “holding steady, albeit with slower job growth than earlier in 2000, despite signs of weakening in the overall economy.” However, with April’s employment report (of March activity), negative change was posted, the unemployment rate edged up 0.1 percent, the employment-to-population ratio decreased 0.1 percent, and the percentage of the civilian labor force unemployed for 15 weeks or longer increased slightly. The author of the Trends article's commented that, “While variations in these labor market series are common, even during periods of robust economic growth, their recent simultaneous movements seem atypically strong and suggest that first-quarter economic activity slowed considerably.”
  
In both recessions, payrolls declined in the first month of the recession. While it seems as though payroll numbers might be insightful turning-point indicators, there are some notable exceptions as well. For example, initial releases for July and August 2000 showed respective declines of 108,000 and 105,000. However, these numbers were later revised upward, revealing increases of 163,000 and 3,000 jobs.

Three-Month Moving Average of Employment Changes

Three-month moving averages can remove some of the volatility of preliminary data and provide a more tempered trend of payroll employment. A moving average is useful because it takes into account both the latest preliminary data and past months’ revisions. However, the diluted nature of moving averages also delays their response to turning points in economic activity. In the 2001 graph, for instance, a three-month moving average smoothes out the peaks and troughs of the monthly change data, but it also shifts the start of the decline to after the start of the recession.



The current three-month moving average of payroll change declined 55,000 to 42,000 between December and January.


03.12.08

Economic Activity

Housing Doldrums

By O. Emre Ergungor

The deterioration in the housing market shows no sign of abating. The S&P/Case-Shiller house price index registered a 9 percent year-over-year drop in the final quarter of 2007, the sharpest decline in its 21-year history.  The Office of Federal Housing Enterprise Oversight (OFHEO) price index also moved into negative territory for the first time in its 17-year history.  While both indexes show downward pressure on home prices, the magnitude of the decline differs significantly between the two indexes.  The reason is that OFHEO tracks only homes with mortgages below Fannie Mae and Freddie Mac’s conforming loan limit ($417,000 in 2006 and 2007), while the S&P/Case-Shiller index tracks home sales in all price ranges and is therefore more affected by the pricey housing of the coastal areas. (OFHEO’s limit has been temporarily raised to $729,000 or 125 percent of an area’s median home price, whichever is lower.)

The decline in prices has not translated into higher volumes just yet.  The number of new single-family homes sold has dropped 58 percent since 2005, reaching 588,000 units in January.  The median sales price, now at $216,000, has declined almost 18 percent since March 2007.

In parallel with the weakening of demand and the decline in prices, residential investment has slowed sharply in recent quarters.  Construction permits, which signal building activity going forward, have declined sharply, from 1.8 million units per year in the fall of 2005 to 673,000 units in January 2008.

The sharp decline in new home sales and the high levels of inventory suggest that the weakness in this market is likely to stay with us for some time.  At the current sales pace, it would take about 10 months to move the existing inventory.  This pace represents a significant deterioration from its level early in the decade and is worse than when it bottomed out at the end of the previous housing downturn in 1991.

A concern for economic observers is that a home is the most important asset in the household portfolio, comprising more than 30 percent of total assets.  When the stock market dropped sharply in the 2000–2003 period, the strength in home values cushioned the blow from falling stock prices and allowed households to keep spending.  The slowdown in appreciation over recent months suggests that housing may not be there to pick up the slack in the next downturn.

The deterioration in the housing industry and its impact on the nation’s economic output are visible in construction spending. While nonresidential construction spending (commercial buildings and shopping malls) has increased rapidly in the last two years, its contribution to the economy could not make up for the sharp decline in residential construction activity. As residential construction continues to deteriorate, whether the demand for commercial buildings will remain strong remains to be seen.

As the housing situation continues to deteriorate, mortgage-related losses are taking a big bite out of the profits of mortgage lenders. The earnings of thrifts—FDIC-insured depository institutions that specialize in mortgage lending—dropped sharply in the fourth quarter of 2007, a loss of almost $5 billion from a profit of around $4 billion earlier in the year.

The deterioration in earnings does not appear to be widespread, but the institutions at which the deterioration is concentrated are among the largest in the industry. The chart below shows the total assets of unprofitable thrifts as a fraction of total industry assets in a particular size category. (Year-end data up until the end of 2006 are separated into different categories of asset size and represented by different lines.  Data for 2007 appear in the bars and are divided into four quarters. For example, the green line expresses the assets of unprofitable thrifts with total assets of more than $1 billion as a fraction of the total assets of all large thrifts.) In 1990, almost 50 percent of large-thrift assets were owned by unprofitable large thrifts.  When 2007 began, this ratio was 3.5 percent and it declined to 1.8 percent in the second quarter.  Fast forward two quarters to December 2007, and 60 percent of large-thrift assets are owned by unprofitable large institutions, which exceeds the level during the thrift crisis of the late 1980s.  Note that asset sizes have not been adjusted for inflation.  Therefore, a $1 billion thrift in 1990 was an economically bigger institution than a $1 billion thrift today.

The charts below show the number of unprofitable institutions in each size category.  In the first quarter of 2007 (bars), about 20 percent of thrifts with assets less than $300 million and 10 percent of thrifts with assets greater than $1 billion were unprofitable.  Those numbers jumped to 29 and 27 percent, respectively, at the end of 2007.  These numbers are well below the levels they reached in late 1980s.  What these numbers suggest is that compared to 20 years ago, we have fewer troubled institutions, but those that are troubled are the largest ones.

Bank holding companies and financial holding companies (BHCs and FHCs) seem to have fared better in these difficult times.  BHCs and FHCs are holding companies that own a diverse set of financial institutions, ranging from depository institutions to insurance companies and investment banks.  While the number of unprofitable institutions has increased, the industry as a whole has created enough profit to absorb the losses from the unprofitable institutions.  Overall industry profits were still positive and strong in the last quarter of 2007.


03.10.07

Economic Activity

The Employment Situation

By Yoonsoo Lee and Beth Mowry

Nonfarm payroll employment declined by 63,000 in February, coming in below expectations of a 25,000 gain. January’s loss (initially 17,000) was revised downward to a loss of 22,000. Payroll declines were last seen in August 2003, and this report brings the second consecutive monthly decline. December’s gains were also cut in half to just 41,000 jobs. Somewhat surprisingly, the unemployment rate dipped slightly, from 4.9 percent to 4.8 percent, but this was because of a decline of 450,000 jobs in the labor force, not a rise in employment. Subtracting out the government’s contribution of 38,000 jobs, private sector payrolls fell by a significant 101,000.

Goods-producing industries lost 89,000 workers in February. The manufacturing sector led the way with a 52,000 loss, its largest since July 2003 and the twentieth straight month of decline. Within manufacturing, durable goods lost 40,000 jobs and nondurable goods lost 12,000. In production manufacturing, 59,000 jobs were cut, the largest loss this category has experienced since July 2003.  Construction continued its shedding trend for the eighth consecutive month, losing 39,000 jobs. Within construction, residential construction faced the largest losses (14,000), but nonresidential construction also lost 3,700 jobs.

Service sector employment rose by just 26,000 workers last month, its weakest gain since October 2005. Even with the government’s 38,000 payroll boost to the total services figure, private services lost 12,000. Within services, leisure and hospitality continued a positive streak, adding 21,000 to their payrolls, and health services added 36,800. Food services continued to go strong, adding 19,900 employees. Professional business services, which lost 9,000 jobs in January, experienced its second straight month of decline with a loss of 20,000 jobs. Temporary help fell the most within professional business services, with a loss of 27,600. Financial service activities also fell by 12,000, in line with a year of fairly consistent and comparable decline.

Labor Market Conditions

       
Average monthly change 
(thousands of employees, NAICS)
       
2004
2005
2006
2007
YTD
February
2008

Payroll employment

173
211
175
91
−63
 

Goods-producing

26
32
3
−38
−89
   

Construction

25
35
13
−19
−39
   

Heavy and civil engineering

1
4
3
−1
−5
   

Residentiala

10
11
−2
−10
−26
   

Nonresidential b

2
4
7
1
−9
   

Manufacturing

−1
−7
−14
−22
−52
   

Durable goods

8
2
−4
−16
−40
   

Nondurable goods

−9
−8
−10
−6
−12
 

Service-providing

148
179
172
130
26
   

Retail trade

16
19
5
6
−34
   

Financial activitiesc

8
14
9
−9
−12
   

PBSd

39
56
46
26
−20
   

Temporary help svcs.

11
17
1
−7
−28
   

Education and health svcs.

33
36
39
44
30
 

Leisure and hospitality

26
23
32
29
21
 

Government

14
14
16
21
38
 

Local educational svcs.

9
6
6
5
11
       
Average for period (percent)

Civilian unemployment rate

5.5
5.1
4.6
4.6
4.8

a. Includes construction of residential buildings and residential specialty trade contractors.
b. Includes construction of nonresidential buildings and nonresidential specialty trade contractors.
c. Financial activities include the finance, insurance, and real estate sector and the rental and leasing sector.
d. PBS is professional business services (professional, scientific, and technical services, management of companies and enterprises, administrative and support, and waste management and remediation services.
Source: Bureau of Labor Statistics.

The three-month moving average of private sector employment growth dipped into negative territory for the first time since August 2003. This measure can provide a cleaner read of labor market conditions because it removes some of the monthly volatility and the consistent boost provided by the government.

Labor Market Conditions and Revisions

       
Average monthly change 
(thousands of employees, NAICS)
       
December
current
Revision to
December
January
current
Revision to
January
February
2008

Payroll employment

41
−41
−22
−5
−63
 

Goods-producing

−73
−12
−54
−3
−89
   

Construction

−55
−10
−25
2
−39
   

Heavy and civil engineering

−5.2
0
−5.3
2
−5
   

Residentiala

−36.9
−5
−29.7
−2
−26
   

Nonresidentialb

−13.5
−5
10.1
1
−9
   

Manufacturing

−22
−2
−31
−3
−52
   

Durable goods

−24
−5
−19
−7
−40
   

Nondurable goods

2
3
−12
4
−12
 

Service-providing

114
−29
32
−2
26
   

Retail trade

−25
−13
0
−11
−34
   

Financial activitiesc

−8
−7
−8
−6
−12
   

PBSd

52
−18
−9
2
−20
   

Temporary help svcs.

−5
2
−11
−2
−28
   

Education and health svcs.

46
−10
49
2
30
 

Leisure and hospitality

7
−15
11
−8
21
 

Government

55
27
4
22
38
 

Local educational svcs.

17
3
0
5
11

a. Includes construction of residential buildings and residential specialty trade contractors.
b. Includes construction of nonresidential buildings and nonresidential specialty trade contractors.
c. Financial activities include the finance, insurance, and real estate sector and the rental and leasing sector.
d. PBS is professional business services (professional, scientific, and technical services, management of companies and enterprises, administrative and support, and waste management and remediation services.
Source: Bureau of Labor Statistics.

Overall, this month’s employment report points to further weakening in labor markets. However, it is worth noting that monthly numbers are volatile and subject to revision. The Bureau of Labor Statistics (BLS) revised January’s initial loss of 17,000 jobs to a slightly larger loss of 22,000 in this month’s report. December’s gain of 82,000 was also trimmed back to a gain of 41,000. Payroll gains (or losses in this case) for January and February are subject to revision in the next report.


03.14.08

Regional Activity

Patent Trends in the Fourth District

By Robert J. Sadowski

Education and innovation contributed more to income growth at the state level than other potential factors, according to research conducted at the Federal Reserve Bank of Cleveland. Educational attainment, for example, increased a state’s average per capita personal incomes relative to other states by 8 percent, but innovation—measured by patents per capita—boosts personal income nearly 20 percent. Given the importance of innovation to economic performance, we investigate patenting activity in the Fourth District and compare District trends with those across the nation. 

Until the mid-1990s, patenting in the Fourth District exceeded that in the U.S. on a per capita basis.  However, in the late 1990s, patenting rates began to accelerate across the nation and within the District, but the acceleration at the national level was greater.  One industry—electronics—is primarily responsible for the surge. Because electronics is so highly concentrated in a few geographic areas—primarily California, Texas, and the Boston to New York corridor—the gap in patents per capita between the nation and the Fourth District has widened over time.  If patents in the electronics industry are excluded from the comparison, the Fourth District actually has more patents per capita than the United States as a whole from 1975 through 2003. (The curiously steep decline in patents during the late 1970s was brought about by budget constraints at the United States Patent and Trade Office (USPTO). These constraints had caused a three-month patent printing backlog by the end of 1979.) 

Electronic patents began trending upward in 1984.  Nationally, the number of electronic patents issued from 1975 through 1983 was relatively flat, averaging 9,900 per year.  This average increased to 18,400 between 1984 and 1997 and climbed even further to 48,000 from 1998 through 2003.  Growth was nonuniform across different subgroups of the industry. The share of patents in computer hardware and peripheral equipment increased from 15 percent between 1975 and 1983 to 30 percent between 1998 and 2003, while at the same time patents for instrumentation declined from 43 percent to 28 percent.  The share of patents in communications equipment and electronic components held steady at about 38 percent between 1975 and 2003.  

From 1984 to 2003, the nation’s average annual per capita growth in electronic patents exceeded that of the Fourth District by two percentage points.  Further, 36 percent of all patents issued nationally were in electronics compared to 20 percent in the District.  California led the nation in electronic patents, having garnered 25 percent of those issued between 1975 and 2003.  Other leading states include New York, Texas, Massachusetts, and New Jersey.  Among companies, IBM was assigned the highest number of electronic patents with almost six percent of the total.  Other high-patenting companies include Motorola, Eastman Kodak, Xerox, and AT&T.  Within the Fourth District, inventors living in the southwestern area—from Dayton south through Lexington—were awarded the highest number of electronic patents.  The Cleveland-Akron area received the second-highest number, followed by the Pittsburgh metro area.  Leading District organizations for electronic patents include Westinghouse, General Electric, Lexmark, Proctor & Gamble, and the U.S. Air Force.

Electronic patents are highly concentrated in 18 counties across the United States.  These counties—call them the high-tech counties—are found primarily in the five states cited earlier.  Inventors living in the high-tech counties were awarded 39 percent of all electronic patents issued between 1975 and 2003, while inventors residing in the 168 counties of the Fourth District received 3.6 percent.  On a per capita basis, electronic patenting in the high-tech counties stood at 81 per 10,000 residents compared to 14 in the District and 17 in the remainder of the United States. 

Fourth District patenting activity remains vigorous.  As mentioned earlier, the District has a higher per capita patent rate than the nation across the entire 1975–2003 period when electronics industry patents are excluded from the comparison.  Although the District lags the U.S. average in electronics patents, it nonetheless remains highly competitive in innovation across most broad-based industry groups, especially chemicals and machinery.


03.12.08

Regional Activity

Labor Force Participation in the United States and Ohio

By Tim Dunne and Kyle Fee

A key determinant of the size of the labor force is the labor force participation rate. The labor force participation rate is the fraction of the working age population (16-year olds and up) that is currently employed or actively looking for employment. Changes in the labor force participation rate along with the growth in the population determine the growth in the labor force. For the nation as a whole, the labor force participation rate has risen markedly since World War II. This rise is well documented and is due primarily to the increased participation of women in the labor force and the U.S. baby boom after WWII. 

Ohio has also experienced a substantial rise in its labor force. Closing out the last century, the gains in Ohio’s rate of labor force participation were similar to those of the nation as a whole. From 1980 through 2000, the U.S. rate rose 3.4 percentage points, and Ohio’s rose 3.7 percentage points. However, from 2000 to 2006, the national labor force participation rate dropped 1 percent to 66.2 percent, while Ohio’s edged up 0.1 percent to 67.2.

What is behind these recent patterns in labor force participation rates? Several studies have noted that important shifts in the labor force participation rates of specific age groups have affected overall labor force participation rates. The table below illustrates this observation by disaggregating labor force participation rates into different age groups for the years 2000 and 2006. For workers under the age of 55, labor force participation rates fell or held steady in the United States as well as in Ohio. For workers over the age of 55, participation rates rose. Somewhat surprisingly, labor force participation for individuals in the 16 to 19 age group drops quite a bit. Nationally, the labor force participation rate of these younger workers fell 8.5 percentage points, roughly 16 percent—a very large downward shift for this group. Ohio has also experienced a relatively large drop in labor force participation for this age group, though not as large as the U.S. decline. Alternatively, older workers have markedly increased their participation rates. Workers aged 55 to 64 increased their labor force participation by 4.5 percentage points across the United States and by 6.8 percentage points in Ohio. This rise in the labor force participation of older workers is a more recent phenomenon, having begun in the mid-1990s.

Labor Force Participation Rates

  U.S. Ohio
Age
2000 2006 2000 2006
16 to 19
52.2
43.7
58.9
53.0
20 to 24
77.9
74.6
81.3
77.1
25 to 34
84.6
83.0
85.3
84.5
35 to 44
84.8
83.8
85.1
85.1
45 to 54
82.6
81.9
83.2
82.1
55 to 64
59.2
63.7
57.3
64.1
65+
12.8
15.4
12.4
14
Total
67.2
66.2
67.1
67.2

 

Source: Current Population Survey.

In order to see which age groups of workers have had the largest impact on changes in labor force participation rates over the 2000–2006 period, we do a decomposition analysis. The analysis separates the changes in overall labor force participation rates into two sources: one is that the participation rates of different age groups could be changing, and two is that the share of workers in each group could be growing or shrinking. For example, the labor force participation rates for age groups could hold steady but if the share of workers in high labor-force-participation groups fell (age groups 25 through 54), then overall labor force participation rates could fall. For each age group, the charts below decompose the contribution to the overall change into the part that is due to changes in labor force participation rates for the group and the part that is due to changes in the age group’s share of workers. Bars that extend out from the center to the left indicate a negative impact on the labor force participation rate and bars that extend out to the right show a positive effect. Green bars show the impact of a change in the share of workers in an age group, blue bars show the effect of change in the labor force participation rate for the group, and red bars show the effect of the aggregate effect.

The U.S. decomposition shows that the largest negative impact on the labor force participation rate comes from the 35 to 44 age group. Driving the negative effect is the share of workers (the long green bar).While the participation rates of workers aged 35 to 44 are very high, their falling share of the overall labor force has acted to lower the overall labor force participation rate. The youngest age group also has a substantial negative effect on overall labor force participation. However, its effect is driven by the fact that the labor force participation rate has fallen sharply for this group, while the change in the share of workers makes less of a contribution. On the positive side, the rise in the share of workers aged 45 through 64 has acted to increase the nation’s labor force participation. On balance, though, the overall effect (the last set of bars on the chart) is negative, with both changes in shares and labor force participation rates acting to lower the overall U.S. labor force participation rate.

In the case of Ohio, the patterns are roughly similar with a few key differences. The share of workers in the 45–54 age group grew strongly in Ohio, and this accounted for a substantial fraction of the rise in the labor force in Ohio. While this group behaved in the same way in the nation as a whole, its impact was much weaker. A difference between Ohio and the U.S. emerges in the 20–24 age group, which had a slight positive impact on labor force participation in Ohio but a net negative effect for the nation. Finally, similar to the national story, changes in labor force participation patterns for the youngest group of workers exerted an overall drag on Ohio’s labor force participation rate. 

 


02.22.08

Regional Activity

Fourth District Employment Conditions

By Tim Dunne and Kyle Fee

The district’s unemployment rate jumped 0.5 percent to 5.7 percent for the month of December.  The increase in the unemployment rate can be attributed to an increase in the number of people unemployed (10.4 percent), as well as a decrease in the number of people employed (−0.6 percent) with no change to the labor force.  December’s sharp rise in the district’s unemployment rate cancels out the large drop in the rate seen in November.  We discussed the recent fluctuations in regional unemployment statistics last month in The Ups and Downs in Regional Employment Statistics

Compared to the national unemployment rate, the district’s rate stood 0.7 percent higher in December and has been consistently higher since early 2004. From the same time last year, the Fourth District’s unemployment rate increased 0.3 percentage point, whereas the national unemployment rate increased 0.5 percentage point.

County-level unemployment rates differ significantly across the district. Of the 169 counties in the Fourth District, 25 had an unemployment rate below the national average in November and 144 had a higher rate. Rural Appalachian counties continue to experience high levels of unemployment. Conversely, Fourth District Pennsylvania has 8 counties with unemployment rates below the national rate.  Unemployment rates for the District’s major metropolitan areas ranged from a low of 4.2 percent in Lexington to a high of 6.6 percent in Toledo.

Lexington and Akron are the only large metropolitan statistical areas (MSAs) to have comparable nonfarm employment growth with the nation over the past 12 months (0.7 percent, 0.7 percent, and 0.9 percent, respectively). By contrast, Dayton and Toledo were the only large MSAs to see declines in nonfarm employment. Employment in goods-producing industries increased in Akron (0.6 percent), while all other Fourth District metropolitan areas all lost goods-producing jobs. Nationally, goods-producing employment declined by 2.0 percent.

Table image  Table text

Employment in service-providing industries saw its largest gains in Lexington (1.2 percent) and Columbus (0.9 percent). On the national level, employment in service-providing industries increased 1.4 percent. Nationally, employment in trade, transportation and utilities services increased 0.9 percent since last December; however, no large metro area in the Fourth District experienced change in employment in these industries.  Professional and business services employment grew faster than the nation’s 2.0 percent in Columbus (2.8 percent) and Akron (2.2 percent).  Compared to the nation’s 2.8 percent increase in education and health services employment over the past 12 months, Lexington’s 5.8 percent growth in these industries is noteworthy.


02.22.08

Banking and Financial Institutions

Banking Structure

by Joe Haubrich and Saeed Zaman

Passage of the 1994 Reigle–Neal Act, which regulates interstate banking, has spurred the consolidation of depository institutions. The number of FDIC-insured commercial banks fell from 10,166 in the middle of 1995 to 7,350 in the middle of 2007, a decline of more than 27 percent. The total number of banking offices, however, increased nearly 28 percent over that period, from 65,321 to 83,358.

The number of FDIC-insured savings associations fell by about 40 percent over the period, from 2,082 in 1995 to 1,244 in 2007. The number of savings association offices also declined, but less sharply than the number of institutions (less than 12 percent, from 15,637 in 1995 to 13,903 in 2007). In contrast, the total number of offices of FDIC-insured depository institutions increased almost 20 percent, from 80,958 in 1995 to 97,261 in 2007. This count does not include other channels for delivering banking services, such as automated teller machines, telephone banking, and online banking. Hence, the reduction in the number of insured depository institutions has not decreased the availability of bank services for most consumers.

The effects of the banking industry’s interstate consolidation are evident: All but five states now report that more than 15 percent of depository institution branches are part of an out-of-state bank or savings association. And in over half the states, 30 percent or more of all branches are offices of out-of-state depository institutions.


02.22.08

Banking and Financial Institutions

Business Loan Markets

by Joe Haubrich and Saeed Zaman

The Federal Reserve Board’s January 2008 survey of senior loan officers (covering the months of October 2007 through December 2007) found considerable tightening of credit standards for commercial and industrial loans since the last survey. About one-third of all domestic banks and two-thirds of all foreign banks surveyed reported having tightened standards for these types of loans for small as well as large and medium-sized firms. The remaining fraction of banks reported little change. The reasons cited for tightening included a less favorable economic outlook, a reduced tolerance for risk, and worsening of industry-specific problems. A large fraction of domestic and foreign banks increased the cost of credit lines and the premiums charged on loans to riskier borrowers. About two-fifths of the domestic banks and nearly eight-tenths of the foreign banks surveyed raised lending spreads (loan rates over the cost of funds).

Demand for commercial and industrial loans continued to weaken over the period surveyed, though the fraction of large domestic banks reporting weaker demand is relatively unchanged from the previous survey. About 35 percent of small domestic banks and 40 percent of foreign banks reported weaker demand. Those who reported weaker demand cited decreased investment in inventories, plants and equipment, and a decrease in customers’ need to finance mergers and acquisitions as reasons.

Bank balance sheets have yet to reflect the decline in businesses’ appetite for bank loans in the face of tightening credit standards. The $90 billion increase in bank and thrift holdings of business loans in the third quarter of 2007 is one of the biggest quarterly increases ever, and it marks the fourteenth consecutive quarterly increase in the bank and thrift holdings of commercial and industrial loans. The sharp reversal in the trend of quarterly declines in commercial and industrial loan balances on the books of FDIC-insured institutions prior to the second quarter of 2004 is still going strong.

The utilization rate of business loan commitments (draw downs on prearranged credit lines extended by banks to commercial and industrial borrowers) held at 36.53 percent of total commitments. It held steady despite the fact that recent financial turmoil has made access to capital markets more difficult, which suggests the possibility of lower demand by borrowers.

 


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