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1 • • • • • • • The Economy in Perspective OK. So Money Can’t Buy You Love. But It Can Produce Price Stability. L et’s face it. A decade of strong economic growth, capital investment, budget surpluses, and improved job opportunities doesn’t just happen. It results from an environment where people know that the dollars they have today will deliver value they can depend on now and for years to come. Performance like that takes a special kind of monetary policy. One that can leverage its portfolio of networked research talent to create customized monetary policy solutions in a rapidly changing global context. Using our acclaimed zero-inflation analytical platform, we aspire to maintain the dollar’s purchasing integrity 24/7. FRB Cleveland • November 2000 So, you don’t have to care too much for money. Only what it buys. THE FEDERAL RESERVE BANK OF CLEVELAND. Dollars that Power the World. www.clev.frb.org 2 • • • • • • • Monetary Policy Trillions of dollars 7.2 THE M3 AGGREGATE Trillions of dollars 4.9 THE M2 AGGREGATE 4.7 M2 growth, 1995–2000 a 9 M3 growth, 1995–2000 a 12 5% 9 1% 6 6.4 3 3 6% 0 1% 0 2% 6 5% 4.5 6% 6.8 2% 6.0 4.3 5% 6% 5.6 4.1 1% 2% 5% 6% 5.2 3.9 1% 2% 4.8 3.7 1998 1997 1999 Trillions of dollars 19 DOMESTIC NONFINANCIAL DEBT 2000 7% 600 6 Sweep-adjusted base growth, 1995–2000 a 15 10 7% 4 17 1999 Billions of dollars 640 THE MONETARY BASE Debt growth, 1995–2000 a 8 18 1998 1997 2000 1% 3% 5 2 560 0 3% 10% 0 Sweep-adjusted base b 7% 16 520 3% 7% 5% 15 480 3% 5% 14 440 1997 1998 1999 2000 1997 1998 1999 2000 FRB Cleveland • November 2000 a. Growth rates are percentage rates calculated on a fourth-quarter over fourth-quarter basis. The 2000 growth rates for M2 and M3 are calculated on an estimated October over 1999:IVQ basis. The 2000 growth rates for debt and the sweep-adjusted base are calculated on an August over 1999:IVQ basis. b. The sweep-adjusted base contains an estimate of required reserves saved when balances are shifted from reservable to nonreservable accounts. NOTE: Data are seasonally adjusted. Last plots for M2, M3, and the monetary base are estimated for October 2000. Last plots for debt and the sweepadjusted base are August 2000. Dotted lines for M2, M3, and debt are FOMC-determined provisional ranges. All other dotted lines represent growth rates and are for reference only. SOURCE: Board of Governors of the Federal Reserve System. Until recently, the Federal Open Market Committee (FOMC) established growth ranges for the broad monetary aggregates (M2 and M3) and domestic nonfinancial debt. For some time, these ranges have not been meaningful indicators in terms of defining specific rates consistent with the goal of price stability. Federal Reserve Chairman Alan Greenspan noted in his October 19 remarks at the Cato Institute, “We have difficulty defining those (money growth) limits with precision, and within any such limits, there remains significant scope for discretion in setting policy.” A casual inspection of the aggregates illustrates the difficulty: For almost four years, the growth rates of M2 and M3 have consistently met or exceeded the upper limit of the FOMC-determined ranges—yet economic expansion has continued with relatively modest inflation. This is not to say that money growth is irrelevant: Inflation is still believed to result from excessive money growth. However, “excessive” is difficult to define over the short term. M2 growth of roughly 6% is not generally associated with price stability, but with real output growth averaging a remarkable 5%, the resulting inflation has been modest. Through October, year-to-date growth rates of M2, M3, and debt are estimated to be 6.0%, 9.0%, and 5.8%, respectively. In keeping with the pattern established early this year, (continued on next page) 3 • • • • • • • Monetary Policy (cont.) Percent, weekly average 9 LONG-TERM INTEREST RATES Percent, weekly average 6.5 SHORT-TERM INTEREST RATES 6.0 8 Conventional mortgage 1-year T-bill a 5.5 7 5.0 30-year Treasury a 3-month T-bill a 6 4.5 10-year Treasury a 5 4.0 4 3.5 1996 1997 1998 1999 2000 1996 2001 Percent, weekly average 7.25 RESERVE MARKET RATES 1998 1997 1999 2000 2001 Percent 7.25 IMPLIED YIELDS ON FEDERAL FUNDS FUTURES b May 7.00 June April 6.75 6.75 Intended federal funds rate July 6.25 6.50 August September March Effective federal funds rate October 25, 2000 6.25 5.75 6.00 5.25 February 5.75 Discount rate January 4.75 5.50 4.25 5.25 1996 1997 1998 1999 2000 2001 Jan. March FRB Cleveland • November 2000 a. Constant maturity. b. Last active trading day of the month unless otherwise noted. SOURCES: Board of Governors of the Federal Reserve System; and Chicago Board of Trade. growth in the narrower measures of money is much less robust. Year-todate growth in the sweep-adjusted base was only 1.8% through August (the most recent sweeps data available), partly reflecting an offset to rapid Y2K-related growth in 1999. Looking at interest rates, the rapid and sustained increases in short-term Treasury yields of 1999 have not characterized the 1-year T-bill so far this year. Trading in a relatively narrow range, the 1-year yield was down 9 basis points (bp) since the beginning of the year to 5.94% as of October 20. In contrast, the 3-month T-bill yield has continued to climb, reaching 6.3% (up 87 bp this year). As a result, the inversion at the short end of the yield curve, which first appeared in July, continues to deepen. Long-term Treasury yields peaked simultaneously early in the year and have largely moved together. Both the 10-year and 30-year Treasury bond yields are down (88 bp to 5.68% and 81 bp to 5.77%, respectively) through October 20. The spread between 30-year conventional mortgage rates and long-term Treasury yields has widened by around 50 bp over this period. While market May July 2000 Sept. Nov. Jan. March 2001 rates moved up sharply when the FOMC tightened by 75 bp in 1999, rates have not responded in similar fashion this year despite an additional percentage point increase. Expectations of policy action, embodied in implied yields on federal funds futures, have changed significantly since May. The steeply sloped implied yield curves of the first two quarters have gradually flattened, culminating in the current inversion of 15 bp between the October 2000 and March 2001 contracts. 4 • • • • • • • Expectations, Markets, and the “Political”Economy Percent, end of day 2.6 TREASURY INFLATION-INDEXED SECURITIES (TIIS) SPREAD Percent 16 ALTERNATIVE INFLATION MEASURES CPI, all items a 2.1 12 Year-ahead household inflation expectations b 1.6 8 10-year Treasury bond minus 10-year TIIS 4 1.1 0 0.6 1998 1999 2000 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2001 Price (cents) 55 PRESIDENTIAL VOTE-SHARE FUTURES d Percent 65 PRESIDENTIAL GALLUP POLL c Percent, October 53 60 Democratic 48 55 50 43 Bush 38 50 45 45 Republican 40 Gore 40 35 May June July Aug. Sept. Oct. Jan. Feb. March April May June July Aug. Sept. Oct. FRB Cleveland • November 2000 a. Year-over-year percent change. b. Median expected change in consumer prices as measured by the University of Michigan’s Survey of Consumers, lagged 12 months. c. Beginning September 5, 2000, three-day rolling poll results among likely voters are displayed. Previous polls were conducted at irregular intervals. Values may not sum to 100% because results for all candidates are not shown. Last plot is October 25. d. Reform Party contracts (not shown) also trade on the IEM’s 2000 Presidential Vote-Share Market. Last plot is October 25. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; University of Michigan; University of Iowa, Henry B. Tippie College of Business; Bloomberg Financial Information Services; and the Gallup Organization. When it comes to measuring people’s expectations, economists are often skeptical of the direct approach— asking them. Instead, economists prefer information derived from markets, where people have money on the line and thus have incentives to use information carefully and to reveal their true beliefs. The federal funds futures market provides a market-based gauge of future monetary policy. Likewise, the Treasury inflation-indexed securities (TIIS) market provides one measure of information about inflation expectations. Coupon and principal payments of TIIS are linked to the Consumer Price Index (CPI), thereby ensuring investors a return that is not influenced by inflation—that is, a real return. The spread between the 10-year TIIS and the 10-year Treasury bond provides a measure of market participants’ expectations for average CPI inflation during the remaining time to maturity. Market information can also be used to gauge expectations about other events, such as political elections. While most people are familiar with national polling organizations such as the Gallup Poll, fewer know about the Iowa Electronic Markets (IEM), a small-scale futures exchange where contracts’ values are determined by political perceptions. The IEM operates a Presidential Vote-Share futures market which pays $1 times the vote share of the contract party’s (Democratic, Republican, or Reform) nominee. In other words, the futures contract trades at (continued on next page) 5 • • • • • • • Expectations, Markets, and the “Political”Economy (cont.) Price (cents) 75 PRESIDENTIAL WINNER-TAKES-ALL FUTURES a Democratic National Convention 65 Republican National Convention Republican 55 45 Democratic 35 Presidential debates 25 May June July August September November October Price (cents) 80 NEW YORK SENATE WINNER-TAKES-ALL FUTURES c Price (cents) 60 CONGRESSIONAL WINNER-TAKES-ALL FUTURES b Non-Republican House, Republican Senate 50 Clinton 60 Giuliani 40 Republican House, Republican Senate 40 30 Lazio 20 20 Non-Republican House, Non-Republican Senate 10 Other Republican Republican House, Non-Republican Senate 0 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. 0 Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. FRB Cleveland • November 2000 a. Reform Party contracts (not shown) also trade in the IEM’s Presidential Winner-Takes-All Market. b. Contract liquidation values are determined by the number of seats won by the Republican party in the U.S. House of Representatives and Senate. c. Contract liquidation values are determined by the outcome of the U.S. Senate election in New York. NOTE: Last plot for all charts is October 25. SOURCE: University of Iowa, Henry B. Tippie College of Business. the percentage of the popular vote that market participants believe each nominee will garner. In the IEM, one can also purchase a contract that pays $1 if the candidate of the contract party becomes president, and pays nothing otherwise. This is known as a winnertakes-all market. The share price for each party can be interpreted as the expected probability of that party’s candidate winning. On September 17, for example, the contract for the Republican candidate was trading at 34 cents. If market participants on that day had felt that George W. Bush’s chance of winning the election was greater than 34 percent, they would have bought more Republican shares, driving up the price of the Republican contract. Markets can be straightforward, like the Presidential Winner-TakesAll Market, where payoffs are determined by which candidate wins, or more complex, as in the Congressional Control Winner-Takes-All Market, which offers four contracts defined by whether the Republican party retains control of the House and Senate. If carefully designed, markets can even accommodate surprise events: In the New York Senate Winner-Takes-All Market, for instance, the withdrawal of early favorite Rudolph Giuliani and Congressman Rick Lazio’s acceptance of the GOP nomination were accommodated by spinning off another contact. 6 • • • • • • • Operating Balances Billions of dollars 40 OPERATING BALANCES a Billions of dollars 900 GDP PER DOLLAR OF OPERATING BALANCES 800 30 700 600 20 500 400 Reserve balances 10 300 200 Service-related balances 0 100 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Billions of dollars REQUIRED RESERVES b 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Standard deviation FEDERAL FUNDS RATE FRB Cleveland • November 2000 a. Monthly average of depository institutions’ daily balances on deposit with Federal Reserve Banks. b. Monthly average of daily reserve balances and vault cash applied to reserve requirements. c. Actual reserves adjusted for changes in reserve requirements, plus estimated required reserves saved through sweep accounts. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis; and Board of Governors of the Federal Reserve System. Banks’ operating balances on deposit at Federal Reserve Banks have been declining over most of the past decade. Banks hold these balances for two reasons: as reserve balances that, along with vault cash, satisfy legal reserve requirements and as service-related balances that banks voluntarily contract to hold for handling interbank payments. (Balances other than these are relatively stable and low.) The decline in operating balances can be gauged roughly by the rapid increase in the ratio of nominal GDP to balances. In effect, more and more economic and financial interbank business is being transacted with a progressively smaller amount of central bank deposit money. The decline in the actual volume of operating balances is masked by related, more familiar measures of base money. Operating balances are the quantity that the Federal Reserve controls in implementing monetary policy through open market operations to regulate the federal funds rate. Monitoring the supply of base money, however, requires careful attention to shifts in demand such as those instigated by changes in reserve requirements and by new banking technologies such as sweep accounts that economize on required reserves. Making those two adjustments turns the 1990s’ decline in actual bank reserves into an increase in the reserves component of the monetary base. Policy analysts also have been concerned that volatility in the fed funds rate might increase as uncontrollable changes in the daily supply of central bank money loom larger in determining its quantity. This, however, does not seem to have been a problem. 7 • • • • • • • Gold Dollars per troy ounce 550 GOLD SPOT AND FUTURES CONTRACT PRICES a Millions of troy ounces 300 CENTRAL BANKS’ GOLD RESERVES 500 250 Futures price 450 200 400 150 350 100 300 Spot price 50 250 0 200 1988 1992 1996 2000 U.S. Germany France Japan U.K. 4/27/2000 10/26/2000 Dollars 80 GOLD FUTURES CALL OPTIONS c Dollars per troy ounce 5 GOLD SPOT AND FUTURES PRICE BASIS b 0 70 –5 60 –10 50 –15 40 –20 30 –25 20 –30 10 0 –35 1988 1992 1996 2000 11/16/1998 5/12/1999 11/1/1999 FRB Cleveland • November 2000 a. Gold futures are based on the Bloomberg generic series. The current security is June 2001. b. The basis is the spot price of gold less the futures contract price. c. Call price on December 2000 futures at a strike price of $270 per troy ounce. SOURCES: World Gold Council, Gold Demand Trends; and Bloomberg Financial Information Services. For those who think it is the “only real money” as well as those who, with Lord Keynes, consider it a “barbarous relic,” gold retains its fascination. Over the past decade, however, it has been a poor investment because its dollar price has generally declined. Much of this decline can be traced to concerns over gold’s future role in the world monetary system. Central banks hold over one-fourth of the total gold supply, so their actions—and rumors about their actions—have a significant effect on gold prices. One way to gauge expectations about price movements is to look at the futures market, but this is less true for gold than for most other commodities. Gold, with a large supply and low storage costs, is often a “fullcarry market,” with the futures price tied to the spot price by the cost of borrowing money and carrying the gold forward. Thus, with a few exceptions, the basis (the difference between the spot and futures price) responds more to interest rates than to gold conditions. The options market, which is particularly sensitive to changes in risk, may provide more information. The option to buy a December 2000 gold futures contract became more valuable in late September 1999 when European central banks announced they would limit gold sales. This not only increased the price of gold but also resolved uncertainty, pushing the call price higher. 8 • • • • • • • Exchange Rates Cents/yen 1.05 YEN SPOT AND FUTURES EXCHANGE RATES a Dollars/euro 1.2 EURO SPOT AND FUTURES EXCHANGE RATES a Yen futures 1.00 1.1 0.95 Euro futures Euro spot 1.0 0.90 Yen spot 0.85 0.9 0.80 0.8 0.75 1/4/1999 6/24/1999 12/15/1999 6/7/2000 10/25/2000 Dollars/euro 16 EURO SIX-MONTH CALL OPTION, IMPLIED VOLATILITY b 1/4/1999 6/23/1999 12/10/1999 6/2/2000 10/25/2000 Yen/dollar 25 YEN SIX-MONTH CALL OPTION, IMPLIED VOLATILITY b 20 12 15 8 10 5 4 1/4/1999 6/24/1999 12/15/1999 6/7/2000 10/25/2000 1/4/1999 6/24/1999 12/15/1999 6/7/2000 10/25/2000 FRB Cleveland • November 2000 a. Euro and yen futures are based on the Bloomberg generic series. The current securities are March 2001 futures contracts. b. Volatilities implied by the call options on exchange rates are based on the Bloomberg generic series. SOURCE: Bloomberg Financial Information Services. Since June, the euro has continued its slide against the dollar, but many of the reasons cited for its decline fail a simple test. If the cause of the euro’s weakness is merely the relative strength of the U.S. economy or a high degree of confidence in Alan Greenspan, the dollar should show comparable strength against the Japanese yen, but that does not seem to be the case. Rather, the yen has held steady against the dollar in both spot and futures markets. We can gain another perspective by looking at the option markets for these currencies. Because options are very sensitive to the volatility of the underlying asset, it is possible to use modern option pricing techniques to back out an implied volatility from an option price. This gives a market measure of uncertainty based on expected volatility, that is, how much exchange rate variability market participants expect. The charts tell two quite different stories about the euro and the yen. Uncertainty about the euro has been growing since June. While the euro has fallen against the dollar, the markets have seemed increasingly uncertain about the direction of the exchange rate. This means that recovery is a possibility, but the downside is that people lack the confidence for investment. Implied volatility for the dollar-to-yen exchange rate has been declining since June of this year. 9 • • • • • • • Inflation and Prices 12-month percent change 4.00 CPI AND MEDIAN CPI September Price Statistics 3.75 Percent change, last: 1 mo.a 3 mo.a 12 mo. 5 yr.a 1999 avg. 3.50 3.25 Consumer prices Median CPI b All items 6.4 2.8 3.5 2.5 2.7 3.3 2.7 2.5 2.4 1.9 3.1 3.2 2.9 2.8 2.3 Finished goods 11.0 2.6 3.3 1.6 2.9 Less food 3.00 2.75 and energy Median b Producer prices 2.50 CPI 2.25 2.00 FOMC central tendency projections as of July 1999 c 1.75 Less food and energy 4.1 2.2 1.2 1.2 0.8 1.50 1.25 1995 1996 1998 1997 1999 2000 12-month percent change 4.00 PCE CHAIN-TYPE PRICE INDEX AND CPI 3.75 Four-quarter percent change 6 EMPLOYMENT COST INDEX AND PRODUCTIVITY 3.50 5 2001 3.25 CPI 3.00 4 2.75 ECI 2.50 3 2.25 FOMC central tendency projections as of July 2000 c 2.00 1.75 1.50 2 Output per hour, nonfarm business sector 1 1.25 PCE Chain-Type Price Index 1.00 0.75 0 1995 1996 1997 1998 1999 2000 2001 1995 1996 1997 1998 1999 2000 2001 FRB Cleveland • November 2000 a. Annualized. b. Calculated by the Federal Reserve Bank of Cleveland. c. Upper and lower bounds for inflation path as implied by the central tendency growth ranges issued by the FOMC and nonvoting Reserve Bank presidents. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; U.S. Department of Commerce, Bureau of Economic Analysis; and Federal Reserve Bank of Cleveland. The CPI rose 0.5% (6.4% annual rate) during September, after falling for the first time in more than 14 years the month before. September’s retail price numbers were driven principally by the CPI’s energy component, which rose by a substantial amount in September (56.8% annual rate) after falling in August. In fact, the correlation between monthly percent changes in the CPI’s energy component and the CPI has been nearly 97% in 2000, suggesting how strongly energy price movements have affected the overall CPI. Accordingly, it might be instructive to consider the CPI without energy prices to see whether other goods prices show a similar pattern. If they do, we might suppose that broader price pressures are at work in the economy. But in September, the CPI excluding energy rose at an annual rate of 2.7%, almost exactly the same as in August. Moreover, while energy prices have been very volatile throughout 2000, the CPI excluding energy has been quite stable, posting quarterly increases at annual rates of 2.4%, 2.7%, and 2.7% to date this year. One closely watched indicator of future price increases at the retail level is the quarterly Employment Cost Index (ECI). Part of its popularity results from two theories that emphasize the importance of labor market dynamics in determining the inflation rate. According to one of these views, if firms are forced to pay workers more for the same output, the cost increase will ultimately be passed on to consumers in the form of higher goods prices. The other view holds that causation runs in the opposite direction: The expectation (continued on next page) 10 • • • • • • • Inflation and Prices (cont.) Percent of market basket 60 SELECTED MARKET-BASKET ITEMS 12-month percent change 4.0 CPI AND EURO-AREA HICP 3.5 50 CPI Euro-area HICP a 3.0 40 CPI 2.5 30 2.0 Euro-area HICP a 20 1.5 10 1.0 0 0.5 1995 1996 1997 1998 1999 2000 Goods b 2001 Services b Energy Food 12-month percent change 5 GOODS AND SERVICES PRICES 12-month percent change 4.5 ADJUSTED CPI AND EURO-AREA HICP 4.0 4 Euro-area HICP, services a 3.5 CPI, services 3 3.0 CPI using HICP market basket c 2 2.5 2.0 1 Euro-area HICP, goods a Euro-area HICP a 1.5 0 1.0 CPI, goods –1 0.5 1995 1996 1997 1998 1999 2000 2001 1995 1996 1997 1998 1999 2000 2001 FRB Cleveland • November 2000 a. Harmonized Index of Consumer Prices. b. Excludes food and energy items. c. This adjustment applies the euro area’s HICP market-basket shares for 2000 to the entire time series of CPI data. The limited extent of the CPI’s disaggregation makes this adjustment only an approximation. NOTE: Price data are not seasonally adjusted. SOURCES: U.S. Department of Labor, Bureau of Labor Statistics; and Eurostat. of higher goods prices in the future induces workers to seek greater compensation gains. In either case, third-quarter ECI data give little cause for concern. Year-over-year ECI increases were larger in 2000 than in the recent past. But unlike those earlier increases, they have not exceeded productivity growth. European countries seeking entrance to the continent’s Economic and Monetary Union must demonstrate (among other things) a measure of price stability. The Harmonized Index of Consumer Prices (HICP) provides a consistent basis for comparing inflation performance across nations. It also permits evaluation of inflation in the entire 11-nation euro area, whose monetary policy is controlled by the European Central Bank. A look at the two prominent retail price measures for the euro area and the U.S. suggests that Europe’s inflation performance is superior. However, this sort of comparison may be misleading because the two areas’ market baskets differ so significantly, most noticeably in the very different proportions of goods and services in each index. A more valid comparison involves applying the market basket of the euro area’s HICP to price data from the CPI. The result suggests that the two regions’ inflation performances are more similar than the unadjusted indexes show, but inflation in Europe since 1998 is still shown to be lower than in the U.S. Disaggregating each retail price measure into price indexes for goods and services reveals the reason: Although the inflation rate for goods has recently been somewhat lower in Europe than in the U.S., Europe’s inflation rate for services has been well below that of the U.S. since 1996. 11 • • • • • • • Economic Activity Index, log scale a 10 NOMINAL AND REAL GDP b,c Real GDP and Components, 2000:IIIQ (Advance estimate) 8 Change, billions of 1996 $ 5.52 6 Real GDP 63.3 Consumer spending 69.8 Durables 16.2 Nondurables 22.2 Services 32.6 Business fixed investment 23.8 Equipment 23.6 Structures 1.2 Residential investment –8.9 Government spending –14.3 National defense –9.4 Net exports –7.4 Exports 42.8 Imports 50.3 Change in private inventories 1.3 Nominal 4 7.19 2 3.29 Real 10.22 3.19 2.98 1 1969 1974 1979 1984 1989 1994 2.7 4.5 7.5 4.9 3.7 5.3 5.3 9.3 5.4 4.3 6.9 8.5 1.7 –9.2 –3.6 –10.2 — 16.2 13.9 12.9 14.0 9.3 –1.2 2.1 –1.3 — 11.7 13.7 — — 1999 Annualized percent change from previous quarter 9 GDP AND BLUE CHIP FORECAST b 8 Percent change, last: Four Quarter quarters 4.2 MARGIN OF ERROR FOR 2000:IIIQ ADVANCE GDP GROWTH d Final estimate Advance estimate 7 3.7 Blue Chip forecast, October 10, 2000 6 3.2 5 30-year average 4 2.7 3 2 2.2 1 0 1.7 IIIQ IVQ 1999 IQ IIQ IIIQ 2000 IVQ IIQ IQ 2001 Two-thirds of revisions Nine-tenths of revisions FRB Cleveland • November 2000 a. The indexes’ initial values of 1 represent the level of real and nominal GDP in 1969:IIIQ, when nominal GDP passed $1 trillion. The numbers along the plot lines are average annual growth rates of nominal and real GDP, measured at business-cycle peaks (dotted vertical lines) approximately a decade apart. Most recent growth rates are for the period ending 2000:IIIQ. b. Chain-weighted data in billions of 1996 dollars. c. Components of real GDP need not add to totals because current dollar values are deflated at the most detailed level for which all required data are available. d. The margin of error, which is based on the 1978–99 period, represents the range of positive and negative revision between the advance and final estimates. NOTE: All data are seasonally adjusted and annualized. SOURCES: U.S. Department of Commerce, Bureau of Economic Analysis and Bureau of the Census; National Bureau of Economic Research; and Blue Chip Economic Indicators, October 10, 2000. Nominal GDP crossed the $10 trillion threshold in 2000:IIIQ, according to the advance estimate released late in October. Since 1969, when nominal GDP was at $1 trillion, increases in real GDP have contributed less to reaching the $10 trillion mark than have price level increases. Of course, some of this may be an illusion created by the oft-noted upward bias in measures of inflation. More certain is the decade-by-decade slowing in nominal GDP’s rate of increase. Slowing inflation more than offset increases in real GDP’s growth rate. Real GDP’s annual rate of increase was only 2.7% in the advance estimate for 2000:IIIQ, considerably slower than in the recent past. The final estimate, when released near year’s end, could be higher or lower than this, though advance estimates tend to be conservative and the final estimate is more often higher than lower. Taken at face value, the substantial reduction of GDP growth in the past quarter may have resulted more from special factors than from any underlying weakness in the economy. In fact, consumption expenditures contributed 3 percentage points to growth in the third quarter, up from only 2.1 percentage points in the second quarter. Nonresidential business investment, while dampened from its second-quarter pace, still added another 0.9 percentage point to GDP growth, representing a small increase in spending on structures and a moderate increase in spending on equipment and software. The combined 3.9 percentage points that consumption and business fixed investment contributed to (continued on next page) 12 • • • • • • • Economic Activity (cont.) Percentage points 3 CONTRIBUTION OF CHANGE IN INVENTORY Percentage points 4 CONTRIBUTIONS TO 2000:IIIQ REAL GDP GROWTH TO GDP GROWTH 3 2 2 Exports 1 Nonresidential fixed investment 1 Change in inventory 0 Personal consumption Residential investment –1 0 –1 Government expenditures –2 –2 Imports –3 –3 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Ratio Hundreds of current dollars per acre 120 AGRICULTURAL LAND VALUE AND PRICES 10 23 Land value a 110 Percent 20 Percent 26 FARM INCOME AND SUBSIDY 18 Subsidies/farm national income b 9 100 8 90 20 16 17 14 14 12 7 Output prices/input prices 10 11 Corporate farm profits/farm national income c 80 6 1985 1987 1989 1991 1993 1995 1997 1999 8 8 1985 1987 1989 1991 1993 1995 1997 1999 FRB Cleveland • November 2000 a. Nominal dollars. b. Subsidies to operators as a share of total U.S. farm national income. c. Corporate profits as a share of the sum of proprietors’ income and corporate profits, with adjustments for inventory valuation and capital consumption. SOURCES: U.S. Department of Agriculture; and U.S. Department of Commerce, Bureau of Economic Analysis and Bureau of the Census. GDP growth were offset by a small decline in residential housing investment and a somewhat larger and unlikely-to-be-repeated decline in government expenditures, mostly at the federal level. The government sector typically contributes about half a percentage point to GDP growth rates, so this quarter’s decline dragged GDP growth down about one full percentage point. On the other hand, because the contribution of exports increased more than that of imports, net exports’ dampening influence on GDP growth was less than it has been over much of the current expansion. This, too, seems unlikely to continue unless the U.S. economic expansion slows dramatically relative to expansions in countries that demand our exports. Inventory accumulation was essentially unchanged from the previous quarter—an unusual event in itself. There is some question whether farmers have shared in the prosperity of the last two economic expansions. Price margins in farm production have shrunk nearly 30% over the last 15 years as the ratio of output to input prices declined. Paradoxically, the value of farm land has soared during the same period. Government subsidies have helped to offset bad years, but the general trend in assistance has been down. Just as in other industries, reduced margins have put pressure on small operators. The corporate share of farm income has risen as growing numbers of farmers find it more profitable to sell their land than to farm it. 13 • • • • • • • Labor Markets Change, thousands of workers 350 AVERAGE MONTHLY NONFARM EMPLOYMENT GROWTH Labor Market Conditions Average monthly change (thousands of employees) 300 1997 1998 1999 YTDa Oct. 2000 Payroll employment 280 Goods-producing 48 Mining 1 Construction 21 Manufacturing 25 Durable goods 27 Nondurable goods –2 251 22 –3 37 –12 –2 –11 229 4 –3 25 –18 –6 –12 182 9 1 19 –12 –4 –7 137 38 4 34 0 0 0 229 20 30 22 120 28 225 16 36 10 124 28 174 15 24 2 106 19 99 23 4 20 17 20 250 200 150 100 Service-producing b TPU Retail trade FIREc Services Government 50 0 232 16 24 21 141 17 –50 Average for period (percent) Civilian unemployment 4.9 4.5 4.2 4.0 3.9 –100 1992 1993 1994 1995 1996 1997 1998 1999 IIIQ Aug. Sept. Oct. 2000 Percent 65.0 LABOR MARKET INDICATORS d Percent 8.2 64.5 7.6 Year-over-year percent change 40 MASS LAYOFFS 30 Employment-to-population ratio 64.0 7.0 63.5 6.4 63.0 5.8 20 All industries 10 0 Civilian unemployment rate 62.5 5.2 62.0 4.6 –10 Manufacturing 61.5 4.0 3.4 61.0 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 –20 –30 1996 1997 1998 1999 2000 2001 FRB Cleveland • November 2000 a. Year to date. b, Transportation and public utilities. c. Finance, insurance, and real estate. d. Vertical line indicates break in data series due to survey redesign. NOTE: All data are seasonally adjusted. SOURCE: U.S. Department of Labor, Bureau of Labor Statistics. Total nonfarm employment showed a net gain of 137,000 workers last month, comparable to September’s gain of 148,000 (adjusted for the effect of strikes and the layoff of the last sizeable contingent of temporary census workers). Other labor market measures also show relative equability: The unemployment rate remained at 3.9%, while the employment-topopulation ratio inched up one-tenth of a percent to 64.4%. Employment gains were concentrated primarily in construction and a few service-producing industries. Construction has experienced two months of strong seasonally adjusted employment gains due to this fall’s unusually light layoffs. In the service-producing sector, transportation and public utilities showed strong gains, as did finance, insurance, and real estate. The unemployment rate has fallen steadily over the last five years, but has there been a corresponding decrease in extended mass layoffs? This series, which includes layoffs of at least 50 workers lasting at least 31 days, has been very volatile; no clear trend has emerged. The data do show that the number of mass layoffs in the manufacturing sector rose rapidly during the 1998 financial crisis. As the world economic situation improved in 1999, the number of mass layoffs fell precipitously in the export-sensitive manufacturing industry; for the overall industrial base, the decline was also steep though less dramatic. 14 • • • • • • • Poverty in the U.S. Percent 40 NATIONAL POVERTY RATES, 1973–99 Percent 30 POVERTY RATES BY GENDER, 1999 35 25 Black Male Female 30 20 25 Hispanic a 20 15 All groups 15 10 10 White 5 5 0 0 1973 1976 1979 1982 1985 1988 1991 1994 1997 Percent 22 POVERTY RATES BY AGE GROUP, 1995 AND 1999 All groups White Black Hispanic Percent 25 POVERTY RATES FOR CHILDREN AND SENIORS, 1985–99 19 1995 1999 21 Children b 16 17 13 13 10 Seniors c 9 7 4 5 Under 18 18–24 25–34 35–44 45–54 55–59 60–64 65–74 Over 75 1985 1989 1993 1997 FRB Cleveland • November 2000 a. Includes Hispanics of all races. b. All persons under the age of 18. c. All persons 65 and over. NOTE: The U.S. Census Bureau distinguishes between “all whites” and “non-Hispanic whites.” Unless otherwise noted, “whites” refers to the Census Bureau classification of non-Hispanic whites. SOURCE: U.S. Department of Commerce, Bureau of the Census. Poverty, a persistent problem in the U.S., will soon be getting more attention, both nationally and locally. Nationally, the Personal Responsibility and Work Opportunity Reauthorization Act of 1996, which has set federal welfare policy for the past five years, must be reconsidered by Congress in 2001. In Ohio, legislation enacted in 1997 set a three-year limit on the receipt of welfare cash assistance benefits. The first recipients to reach this limit were removed from the welfare rolls as of October 1. How do we define poverty? According to the U.S. Census Bureau, an individual younger than 65 was living in poverty in 1999 if his or her annual income was less than $8,667. For individuals 65 and over, the poverty threshold was $7,990. A family of four, with two adults and two dependent children under 18, was considered to be living in poverty if its household income did not exceed $16,895. These definitions were derived from estimates of minimum nutritional and housing standards that were made in 1963 and updated annually on the basis of changes in the Consumer Price Index. In 1999, 11.8% of Americans lived in poverty, the lowest rate since 1979. Although poverty rates for blacks and people of Hispanic origin were considerably higher than the national average, they were equal to or below the lowest rates recorded since 1959, when the first Current Population Survey was taken. The poverty rate for blacks fell to a record low of 23.6% in 1999; for Hispanics, the rate dropped to 22.8%, close to the lows recorded for that group in the 1970s. (continued on next page) 15 • • • • • • • Poverty in the U.S.(cont.) Percent 40 HOUSEHOLD POVERTY RATES BY WORK STATUS, 1999 Percent 20 POVERTY RATES AMONG WORKERS 35 Worked full time 16 White Black Hispanic 30 Worked part time Did not work 25 12 20 8 15 10 4 5 0 0 1995 1997 All groups 1999 Percent 80 HOUSEHOLD POVERTY RATES BY FAMILY STATUS, 1999 White Black Hispanic Percent 60 POVERTY RATES OF HOUSEHOLDS WITH CHILDREN BY FAMILY STATUS, 1999 70 Total 60 50 With no workers With one or more workers White a Black Hispanic 40 50 30 40 30 20 20 10 10 0 0 All households Married couple families Single female householder Single male householder All households Married couple families Single female householders Single male householders FRB Cleveland • November 2000 a. Includes whites of Hispanic origin. NOTE: The U.S. Census Bureau distinguishes between “all whites” and “non-Hispanic whites.” Unless otherwise noted, “whites” refers to the Census Bureau classification of non-Hispanic whites. SOURCE: U.S. Department of Commerce, Bureau of the Census. Across all races, poverty was more prevalent among women. The highest rate occurred among black women. Slightly more than one out of every four black or Hispanic women lived in poverty in 1999. That year, the incidence of poverty by age group (that is, the age distribution of those living alone or with others in households whose income is below the poverty line) was highest among individuals 18–24, who surpassed children as the most impoverished group. However, people aged 65–74 were the only group whose poverty rate rose between 1995 and 1999. Despite that increase, this group had one of the lowest rates in 1999. Poverty rates for both children (under 18) and seniors (older than 65) have been falling since 1993. Since 1996, the number of working poor has declined. Although workers’ poverty rates did not decline substantially for blacks or whites, a large reduction for Hispanics occurred in 1995–97. Poverty rates among workers changed much more noticeably in 1997–99, when they dropped more than a full percentage point for all three ethnic categories. Despite these declines, the prevalence of poverty among working blacks and Hispanics is still nearly three times that of nonHispanic whites. For households, the presence of one worker (even one with only a part-time job) significantly decreases the prevalence of poverty for all races and family types. Among blacks, individuals who did not work were over seven times more likely to live in poverty than those who (continued on next page) 16 • • • • • • • Poverty in the U.S.(cont.) Percent 18 POVERTY RATES BY REGION b Percent 20 POVERTY RATES BY AREA OF RESIDENCE, 1999 Poor Severely poor a 16 South 15 West 14 Northeast 10 12 Midwest 5 10 8 0 Metropolitan (total) Metropolitan (central city) 1995 Metropolitan Nonmetropolitan (outside central city) Percent 30 POVERTY RATES BY REGION, 1999 1996 1997 1998 1999 Percent 22 POVERTY RATES IN FOURTH DISTRICT STATES c White Black 25 20 Hispanic West Virginia 20 18 15 16 Kentucky 10 14 Ohio 5 12 0 10 Pennsylvania Northeast Midwest South West 1994 1995 1996 1997 1998 1999 FRB Cleveland • November 2000 a. The Census Bureau defines the “severely poor” as those living in households whose income is no more than half the amount set as the poverty threshold. b. Regions are those defined by the Census Bureau. c. To compare poverty rate changes at the state level, the Census Bureau uses two-year moving averages. So, for example, the 1999 figure is the two-year average for 1998–99. NOTE: The Census Bureau distinguishes between “all whites” and “non-Hispanic whites.” Unless otherwise noted, “whites” refers to the Census Bureau classification of non-Hispanic whites. SOURCE: U.S. Department of Commerce, Bureau of the Census. worked full time. Households headed by single females of all races had a 30.4% poverty rate, the highest of any household category. This figure skyrockets to 67.9% if no one in the house worked during the year. Among households with children, poverty rates were lowest for marriedcouple families. They were highest for single female householders, among whom rates for blacks and Hispanics were almost 20 percentage points higher than those for whites. Like race, gender, and family structure, place of residence also showed differences in both poverty and severe poverty. Individuals living in metropolitan areas, but not within the central city’s limits, had a significantly lower poverty rate than those living in a central city or nonmetropolitan area. Nationally, poverty was most prevalent in the Northeast (a change from 1995, when poverty was highest in the South), and least prevalent in the West. Rates in both the Midwest and Northeast increased in 1998–99, despite a decline in the U.S. as a whole. Racial differences in poverty varied widely across regions. Poverty rates have declined in every Fourth District state but Ohio, which saw an increase of 0.5 percentage point in 1998–99. The precipitous drop in Kentucky’s poverty rate has moved the state from the fourthhighest poverty rate in 1994 to 13th in 1999. West Virginia remains the Fourth District’s highest ranking state (4th), while Pennsylvania enjoys the lowest rank (30th). Ohio, although below the national poverty rate, ranks 24th among the states. 17 • • • • • • • Banking Conditions Percent 50 CONSUMER LOAN MARKET SHARE a Percent 16 UNPROFITABLE INSTITUTIONS 45 14 Large banks 40 12 35 10 30 25 8 Pools of securitized assets Credit unions 20 6 15 All banks Credit unions 4 10 2 5 Small banks 0 0 1990 1991 1992 1993 1994 1995 Percent RETURN ON EQUITY 1996 1997 1998 1990 1999 1991 1992 1993 1994 1995 1996 1997 1998 1999 Percent 1.6 RETURN ON ASSETS 1.4 Credit unions 1.2 Small banks 1.0 0.8 0.6 All banks 0.4 0.2 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 FRB Cleveland • November 2000 a. Shares do not total 100%. The difference includes finance companies, savings institutions, and nonfinancial businesses. NOTE: Bank data are for FDIC-insured commercial banks; credit union data are for federally insured credit unions. Small banks are defined as commercial banks with total assets less than $100 million. SOURCES: Board of Governors of the Federal Reserve System, Federal Reserve Bulletin; Federal Deposit Insurance Corporation, Quarterly Banking Profile and Statistics on Banking; and National Credit Union Administration, Year-end Statistics for Federally Insured Credit Unions. The dominant trend in the consumer loan market is toward securitized loans (loans that are packaged and sold off as securities). Their market share jumped from 9.52% to 30.51% in the last decade. However, the decline in the market share of large commercial banks may give an inaccurate impression because the data are based on balance sheets after securitized assets are taken off the originating bank’s books. We would obtain a more precise picture by assigning to each institution its share in the pool of securitized assets, but unfortunately, we lack this information. Still, we note that although banks control a larger share of the consumer loan market than do credit unions, this is not true across all bank sizes. In fact, the market share of small banks (those with total assets under $100 million) is smaller than that of credit unions. Moreover, the Supreme Court ruling of February 1998, which capped credit unions’ expansion by limiting their mem- bership pool, does not seem to have affected their performance or their presence in the consumer lending market. The rise in the percent of unprofitable institutions over the last five years may be explained by greater competition in the consumer loan market. This figure rose from a low of around 4% in the first half of the 1990s to 7.24% for banks and 9.39% for credit unions. This explanation is reinforced by evidence of flatter return on assets and equity for banks (continued on next page) 18 • • • • • • • Banking Conditions (cont.) Percent 70 NET LEASES AND LOANS/TOTAL ASSETS b Percent 7 TOTAL OPERATING PROFIT/TOTAL ASSETS a 65 6 Credit unions 60 Credit unions 55 5 Small banks 50 Small banks 4 45 40 3 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Percent 2.5 DELINQUENT LOANS/TOTAL LOANS 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1996 1997 1998 1999 Percent 0.8 NET CHARGE-OFFS/TOTAL LOANS 0.7 2.0 0.6 Small banks Credit unions 0.5 1.5 0.4 1.0 Small banks 0.3 Credit unions 0.2 0.5 0.1 0 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1990 1991 1992 1993 1994 1995 FRB Cleveland • November 2000 a. Operating profit is calculated before cost of funds. b. Leases and loans for credit unions equal loans only, since credit unions do not provide leases. NOTE: Bank data are for FDIC-insured commercial banks; credit union data are for federally insured credit unions. Small banks are defined as commercial banks with total assets less than $100 million. SOURCES: Federal Deposit Insurance Corporation, Quarterly Banking Profile and Statistics on Banking; and National Credit Union Administration, Year-end Statistics for Federally Insured Credit Unions. and declining returns for credit unions. Credit unions were star performers in the first half of the 1990s but seem to have lost their competitive edge: Their return on assets declined from 1.4% in 1993 to 0.9% in 1999. In the banking industry, we notice again that bank size affects performance measures. Despite the industry’s high return figures overall, small banks’ returns trend downward, closely following credit union data. This suggests that increasing competition mostly affects the performance of small institutions. We focus on small banks and credit unions because they are comparable in size and business line. The weak performance of credit unions, observed in their equity and return on assets, is also evident in their assets’ deteriorating ability to generate profit. Starting in the mid1990s, small banks have continuously generated more operating profit per dollar of assets than have credit unions. The difference is less than half a penny on each dollar, but the trend is persistent. Credit unions lend more aggressively than small banks. Although small banks closed the wide gap in the share of loans in total assets (from 12.71% in the late 1980s to 6.28% in 1999), the difference is still higher than the 2.43% difference in 1993. The percent of delinquent loans in banks’ total loan portfolio improved significantly over the last decade. For small banks, this figure declined from 2.03% in 1990 to 0.9% in 1999. For credit unions, the decline was from 1.7% to 0.75% over (continued on next page) 19 • • • • • • • Banking Conditions (cont.) Percent 75 TOTAL LOANS AND LEASES/TOTAL ASSETS a.b,c Total assets (billions of dollars) 125 ASSETS a,b 100 Small banks Credit unions Small banks Credit unions 70 75 65 50 60 25 55 50 0 Northeast Mid-Atlantic Southeast Central Midwest Northeast Pacific Mid-Atlantic Southeast Central Midwest Pacific Central Midwest Pacific Return on equity (percent) 15 RETURN ON EQUITY a,b Return on assets (percent) 1.5 RETURN ON ASSETS a,b Small banks Credit unions Small banks Credit unions 1.0 10 5 0.5 0 0 Northeast Mid-Atlantic Southeast Central Midwest Pacific Northeast Mid-Atlantic Southeast FRB Cleveland • November 2000 a. The states are divided into the following six regions, following the usage of the National Credit Union Administration. Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont. Mid-Atlantic: Delaware, District of Columbia, Maryland, New Jersey, Pennsylvania Virginia, West Virginia. Southeast: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee. Central: Illinois, Indiana, Michigan, Missouri, Ohio, Wisconsin. Midwest: Arizona, Colorado, Iowa, Kansas, Minnesota, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Utah, Wyoming. Pacific: Alaska, California, Hawaii, Idaho, Montana, Nevada, Oregon, Washington. b. Figures are for the end of 1999. c. The ratio of total loans and leases to assets for credit unions equals total loans to assets, since credit unions do not provide leases. NOTE: Bank data are for FDIC-insured commercial banks; credit union data are for federally insured credit unions. Small banks are defined as commercial banks with total assets less than $100 million. SOURCES: Federal Deposit Insurance Corporation; and National Credit Union Administration, Year-end Statistics for Federally Insured Credit Unions. the same period. On net charge-offs, both industries achieved a small but significant improvement. The ratio of net charge-offs to total loans is down to 0.49% for credit unions and 0.37% for small banks. In every region except the Midwest, credit unions surpass small banks in total asset size. The difference is especially striking in the Pacific region, where credit unions’ total assets average $91 million and those of small banks $14 million. Credit unions also are distributed more uniformly across the regions. The difference in asset size between the region with the largest amount and the region with the smallest amount is $99 million for banks and $44 million for credit unions. In all regions, credit unions hold a larger share of their assets in loans than do small banks. Measures of equity and return on assets show that credit unions’ performance is more homogeneous across the country, while small banks do well in the central (ROA: 1.02%) and midwestern (ROA: 1.16%) states but do poorly in the mid-Atlantic (ROA: 0.15%), northeastern (ROA: 0.65%), and Pacific (ROA: 0.59%) states.
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