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REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/checks-lose-market-share-to-electronic-paymentsandthe-economy-gains President's Message: Checks Lose Market Share to Electronic Payments—and the Economy Gains William Poole Do you still think Americans are addicted to their checkbooks and have reservations about using electronic forms of payment? Think again. A new study by the Federal Reserve shows that e-payments in this country are growing at a rapid rate and at the expense of checks. Replacing checks with electronic payments is good for the economy; electronic payments are just plain more efficient. E-payments are cheaper to process—mills vs. cents for checks. Moreover, some forms of epayments, such as direct deposit and debit cards, clear almost instantly, whereas checks can still take a few days. The study was the first comprehensive one since 1979. One of the more interesting findings is that the number of checks written in 2001 was estimated to total 49 billion—far below the estimate of 60-70 billion commonly used by those in the industry, including the Fed. This new figure was still much higher than the 32 billion of two decades ago. But compare that growth—55 percent—to the growth in electronic payments—more than 500 percent since 1979! Granted, it's easier to achieve such growth when starting from a small base. Some forms of e-payments, such as debit cards, weren't even around in 1979. Others, such as direct deposit, were in their infancy. But, like a teen-ager hitting a growth spurt, the use of these new payment methods has shot up. More than 8 billion transactions are now conducted every year with debit cards, second only to the longtime king of e-payments, the credit card. Automated Clearing House (ACH) payments, such as direct deposit, rank third with 5.6 billion transactions. (When ranked by the dollar value of transactions, ACH leads, accounting for three-fourths of the $7 trillion in e-payments.) With 30 billion transactions a year, e-payments are clearly more than a Gen X fad, and the switch to epayments might be further accelerated by the recent scares involving the safety of U.S. mail. Although the Fed has long encouraged the use of e-payments, we're not ready to predict that a checkless society is around the corner. We don't even know if the number of checks has stopped growing. Although the check share of all non-cash payments has fallen to 60 percent from 85 percent, the total number of non-cash payments has more than doubled since 1979 to 80 billion. The Fed will conduct another payments study in two or three years—not another 20—to get a better idea of where the various forms of payment are headed. Meanwhile, we hope that all stakeholders in this issue can use this study to pick out the best form of payment to use in the future for themselves and for their clients. For those who want to stick with checks, rest assured that the option will not be taken away. Count me among those who can't imagine ever using a "smart card" to pay for Girl Scout cookies, although it may happen! In the end, we shouldn't fool ourselves about the popularity of e-payments: Even the nation's largest printer of checks long ago branched out into the electronic payments business. For details on the retail payments study, go to www.frbservices.org. REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/predicting-inflation-food-for-thought Predicting Inflation: Food For Thought William T. Gavin , Rachel J. Mandal "When I was your age, I walked 20 miles uphill in the snow to get to school and a gallon of milk only cost a nickel."Who doesn't remember grandparents and relatives sharing similar stories with us at family gettogethers? Today, a gallon of milk at the grocery store will cost more than a nickel, as will other goods that our grandparents paid considerably less for in their day. The overall rise in prices is known to economists as inflation. Over the long run, inflation is caused by too much growth in the money supply. Monetary inflation is bad because it obscures the price signals that make our market system work efficiently. The job of monetary policy is to supply just the right amount of money so that the average price level remains stable. Over short periods, however, inflation can be influenced by large changes in the market for particular goods and services. Because these bouts of inflation tend to be short-lived and self-correcting, the proper monetary policy response is to ignore them. The problem for the Federal Reserve is to know when inflation is due to excessive monetary growth (requiring a policy response) and when it is due to transitory market fluctuations. To sort out the short-run real effects caused by disruptions to particular markets from the long-run monetary effects caused by Federal Reserve policy, economists have developed techniques to filter the inflation news. Traditionally, economists have excluded food and energy prices in their filtering process, but we find that by filtering out food prices, we might be losing valuable information about inflation. What's in the Basket? Economists looking at inflation generally track a price index, which is the average price of a consistent "basket" of consumer goods. The two major price indexes are the Consumer Price Index (CPI) and the Personal Consumption Expenditures Price Index (PCEPI). The CPI, reported by the Bureau of Labor Statistics, was created for the specific purpose of adjusting veterans' pension benefits for inflation following WWI, while the PCEPI, reported by the Bureau of Economic Analysis, is used to compute the nation's Gross Domestic Product. Both indexes measure the rate of inflation faced by consumers, but the PCEPI is more comprehensive. Approximately 25 percent of the items in the PCEPI basket are excluded from the CPI basket. A guiding principle for deciding whether an item belongs in the CPI basket is whether it is paid for "out of pocket." The main items in the PCEPI that are not included in the CPI are things that consumers get but don't pay for out of pocket, such as free checking, employer-funded medical care and medical services paid through Medicare and Medicaid. Also, the CPI is an index of inflation for urban dwellers; so, it excludes spending by rural households. The PCEPI, then, is a larger and broader index that includes a more varied bundle of goods than the CPI does. Although both are valid for gauging inflation, in 2000 the Federal Reserve began reporting its inflation forecasts in terms of the PCEPI instead of the CPI. Because of the PCEPI's wider basket of goods and the Fed's focus on it, we'll look only at the PCEPI, although our conclusions also apply to the CPI.1 When tracking inflation, people monitor data releases to predict the underlying inflation trend, which is driven solely by monetary policy. However, information about the inflation trend has been compared to a radio signal that is obscured by static. Just as noise filters are used to remove the static in radio signals, economists filter inflation data to remove the static caused by supply and demand changes. One way to filter the inflation news is to measure the change in prices over a long period, such as a year, to eliminate the short-run fluctuations. But then, the useful information is delayed for a year. Another way that economists filter out the static is to delete the items in the price index that are sensitive to large, frequent disturbances to supply and demand and, therefore, have highly volatile prices. After deleting these items, what is left is core inflation, that is, inflation in the basket of goods excluding the more volatile components. Since the 1970s, core inflation has typically been measured by excluding food and energy from the basket of goods. This is because the early 1970s saw highly volatile food prices and, soon afterward, a rapid rise in the prices of gas, oil and other energy products. The core measure of inflation, the PCEPI excluding food and energy, has been less sensitive to temporary shocks to the economy and has seemed to have been a better barometer of the underlying trend in inflation than the all-item PCEPI. Looking at Figure 1, we see that the rate of inflation measured by the PCEPI excluding food and energy has been less volatile than with the all-item index. During times of high inflation, such as the mid-1970s and early 1980s, the PCEPI excluding food and energy did not increase nearly as much as the all-item PCEPI.When inflation dropped considerably in the middle of 1986, the index excluding food and energy did not show the same massive drop. Let's take a closer look at the changes in the prices of components excluded from the core: food and energy. From Figure 2, we see that inflation in energy prices indeed has been very volatile, increasing and decreasing much more than the food component or the all-item PCEPI. We also see that food prices have become increasingly stable recently, while energy prices continue to fluctuate significantly. What has caused the recent increase in the stability of food prices? Improvements in technology and a change in consumer eating habits have both contributed.2 Major advancements in the food distribution system have led to shorter lag times between picking produce at the farm and getting it into the hands of urban consumers. It is not unusual, as it once was, for a shopper in a supermarket in Chicago to be buying fresh produce grown in South America. As technological advances have reduced the cost of air freight and refrigeration, their use has become widespread and commonplace in the food industry, increasing the geographic size of the market for food and reducing the volatility of food prices. Another change in the food distribution system is that many more people now buy their food from large grocery store chains. These large chains have an advantage over smaller specialty retailers in that they have the ability to stock larger quantities of many more different types of items. Large supermarkets purchase food directly from the producers in huge quantities, cutting the cost to themselves and their consumers. Eating habits of the American consumer also have changed. With the hectic schedule many Americans have, people are less inclined to buy fresh fruit, vegetables, meat and poultry that may go bad in their refrigerators or require time and energy to prepare. People are much more likely to buy prepared meals at the grocery store or to eat at restaurants. The prices that consumers pay for these meals are largely expenditures on the labor used to prepare and serve the food. The price of these labor services is less volatile than is the price of the raw food products. Should We Put Food Back into the "Core" Basket? Because volatility in food prices has dropped in recent years, does it still make sense to exclude food from our measure of core inflation? Are we losing information about the underlying trend in inflation by removing such a stable component from the core? Indeed, by excluding food prices in our traditional analysis of core inflation, we lose more knowledge about the trend in inflation than we gain. The reason for creating a core measure of inflation is to learn about the underlying trend. The inflation trend is caused by monetary policy and should be reasonably stable over time. Thus, a good core measure will be a good predictor of future inflation. The all-item inflation rate reported in the news is a flawed predictor of future inflation because it contains some items, such as energy products, that are quite volatile, causing the all-item index to deviate from the underlying trend. We exclude energy from the core in order to get a better measure of the trend, or equivalently, a better forecast of future inflation. The question here is whether food is like energy. We find that it is not. Not only is the food component of the PCEPI one of the least volatile components, but it also has been a relatively good predictor of future inflation. Figure 3 compares the food component of the PCEPI with the PCEPI excluding food and energy in terms of their abilities to predict inflation two years into the future. This comparison is made by going back in time to simulate a forecasting exercise. Each quarter, we record the previous year's inflation in the food component of the PCEPI and in the PCEPI excluding food and energy. We then use these two past inflation rates to forecast inflation over the next two years. For example, in January 1992, we use the inflation rate for 1991 from both of these indexes to make forecasts of the average inflation rate for 1992 and 1993. The better forecast is simply the one that is closest to the actual inflation rate that occurred in those two years. Figure 3 plots the forecast errors (predicted inflation minus actual inflation) for the two indexes. Looking at Figure 3, we see that past inflation in food prices has been a better forecaster of future inflation than has the popular core measure. Core inflation was more often above actual inflation than below it, meaning that it had a tendency to predict a higher rate of inflation than actually occurred. On average, the all-item index rose at a 3.0 percent annual rate, while predicted inflation from the PCEPI excluding food and energy averaged 3.7 percent per year. In contrast, inflation in food prices appears to be an unbiased forecast; it was below actual inflation about as often as it was above it, with approximately equally sized errors. Its average predicted inflation of 2.8 percent was only two-tenths of a percentage point below the actual inflation rate. Now that we have identified inflation in food prices as a relatively good indicator for future inflation, we must see how it stacks up against other components of the PCEPI. Forecasters compare results by measuring the size of the forecast error. A standard measure of comparison is the root-mean-square error (RMSE), which tends to penalize large forecast errors—the difference between the actual and forecasted values—more heavily than small forecast errors.3For example, in Figure 3, the PCEPI excluding food and energy would be highly penalized for the big errors in 1983. As we did with the food component, we use the previous year's inflation in various components of the PCEPI as alternative forecasts of future inflation. We then calculate the RMSEs to evaluate the relative accuracy of these forecasts. Comparing the past year's inflation in food prices to the prices of other components that comprise the PCEPI (as in Table 1), we find that the food component still ranks the best among them all. Food has the smallest RMSE (0.99), while energy has the largest RMSE (10.52). This implies that past inflation in food has been a good predictor of overall inflation. The New Core: PCEPI excluding Energy To assume that the food shocks of the 1970s will never be repeated is probably dangerous. A glance back at Figure 3 shows that the core measure was not really too bad if we exclude 1983. We include the core measure excluding food and energy in Table 1 to show that, with the exception of food, it really is much better than looking at most of the other component measures. We also show that the measure could be improved by putting food back into the mix. The core measure excluding only energy is about 10 percent more accurate than the standard measure. (Its RMSE was only 1.10 percentage points, while the RMSE of the forecast error using inflation in the PCEPI excluding food and energy was 1.23 percentage points.) With the decreased volatility in food prices and their ability to predict future inflation, it no longer makes sense to exclude food from our measure of core inflation. Too much valuable information is lost with the exclusion of food from the core PCEPI. A better measure of core inflation would be the PCEPI excluding just energy. Looking at Table 1 again, we see that the PCEPI excluding food and energy has a higher RMSE than the PCEPI excluding energy only. Energy remains a highly volatile component and masks the underlying inflation trend. Removing energy alone, as opposed to food and energy, gives us a clearer picture of the inflation trend. Figure 1 Inflation in PCEPI vs. PCEPI Excluding Food and Energy Consistently volatile components of the PCEPI obscure economists' ability to evaluate monetary policy and the true inflation trend. To get a better idea of the underlying inflation trend, economist look at core inflation, which is traditionally measured by the PCEPI excluding food and energy. Removing food and energy from the PCEPI results in a less volatile series and a better gauge of the underlying inflation trend. [back to text] Figure 2 Inflation in Food Prices vs. Energy Prices Typical measures of core PCEPI inflation have excluded food and energy prices because of their volatility. However, due to advances in food distribution technology and changes in consumer eating habits, food prices have stabilized recently, while energy prices continue to fluctuate dramatically. By continuing to exclude food from core inflation, we might be losing information about the underlying inflation trend. [back to text] Figure 3 Forecast Errors of Food and PCEPI Excluding Food and Energy The PCEPI excluding food and energy is typically used as an indicator of the underlying inflation trend, and a good indicator of the underlying trend should also be a good predictor of future inflation. Using past inflation in the price of food and the PCEPI excluding food and energy as a prediction for overall inflation in the next two years, we see that past food prices have been a better forecast of future overall inflation than the PCEPI excluding food and energy. The forecast errors (predicted inflation minus actual inflation) for food prices are smaller than those for the PCEPI excluding food and energy, and the PCEPI excluding food and energy was more often above actual inflation than below (as seen by the preponderance of points above the zero line), meaning that it had a tendency to predict a higher rate of inflation than actually occurred. [back to text] Table 1 The Ability of PCEPI Components to Predict Inflation Component RMSE Food 0.99 PCE excluding Energy 1.10 PCE excluding Food and Energy 1.23 Non-durable Goods 1.70 Motor Vehicles and Parts 1.71 Transportation Services 1.91 Services 2.01 Housing 2.02 Durable Goods 2.42 Clothing and Shoes 2.76 Medical Care Services 3.43 Gasoline, Fuel Oil, Other Energy Goods 10.52 (Q3: 1983-Q2: 2001) The better that past inflation in a component of the PCEPI is able to forecast overall inflation, the better an indicator it is of the true inflation trend. The root-mean-square-error (RMSE) measures how far away a forecast is from the actual measured value and is, therefore, a measure of how good a forecast is. Components with a smaller RMSE are better at forecasting future overall inflation. Here, we see that food has the lowest RMSE, indicating that we might be losing valuable information about trend inflation by removing it from our measure of core inflation. [back to text] Endnotes 1. For a detailed analysis of the components of the CPI, see Clark (2001). [back to text] 2. For further discussions on the change in consumer food preferences and advances in food distribution technology, see Johnson, Rogers and Tan (2001); Jacobs and Shipp (1990); and Paulin (1998). [back to text] 3. The RMSE tests how far away a forecast is from the observed/actual value. The test first finds the difference between the actual value and the forecasted value. It then squares this difference and takes an average of all of these squared differences. Finally, it takes the square root of the average, and the resulting number is called the RMSE. The better a forecast is, the closer to zero the RMSE will be.[back to text] References Clark, Todd E. "Comparing Measures of Core Inflation" Federal Reserve Bank of Kansas City, Economic Review, Second Quarter 2001, Vol. 86, No. 2, pp. 5-31. Jacobs, Eva and Shipp, Stephanie. "How Family Spending Has Changed In The U.S." Monthly Labor Review, March 1990, Vol. 113, No. 3, pp. 20-7. Johnson, David S.; Rogers, John M. and Tan, Lucilla. "A Century of Family Budgets in the United States." Monthly Labor Review, May 2001, Vol. 124, No. 5, pp. 28-45. Paulin, Geoffrey D. "The Changing Food-at-Home Budget: 1980-1992 Compared." Monthly Labor Review, December 1998, Vol. 121. REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/the-futures-market-as-forecasting-tool-an-imperfectcrystal-ball The Futures Market as Forecasting Tool: An Imperfect Crystal Ball William R. Emmons , Timothy J. Yeager Many commodities are traded in both spot and futures markets. The spot market is for trading today, whereas the futures market is for future delivery. Press reports sometimes imply that futures prices provide a good forecast of future spot prices. Does the futures market really provide us with a crystal ball? The short answer is yes and no: Futures markets sometimes forecast future spot prices, but sometimes they do not. When, how and why do futures markets provide reliable forecasts? To answer these questions, we must first understand the concepts of forward contracting, hedging and speculation. Forward Contracting Can Decrease or Increase Risk A forward contract is a firm legal commitment made by a seller to deliver a pre-specified amount at an agreed time at a particular price. Contract details are agreed at the outset, but no money or commodities are exchanged until the settlement (delivery) date. A standardized forward contract that is traded on an organized exchange such as the Chicago Board of Trade (CBOT) is a futures contract. Agricultural futures contracts were first traded in Chicago during the mid-1800s; later, futures contracts on industrial commodities, precious metals, stock indexes, currencies and interest rate instruments were added, and other exchanges were opened. Forward contracting is used for hedging a pre-existing risk and for speculating on price movements. A farmer with a corn crop in the ground is exposed to the risk that corn prices in the spot market will be low when his crop actually is harvested and sent to market. To hedge this risk, the farmer could sell a corn futures contract for delivery at harvest time. This contract locks in a price today for corn that will be delivered in the future; so, the price risk is hedged away.1 A speculator, on the other hand, buys or sells corn futures with no other risk exposure to the price of corn. A corn futures buyer profits when the price rises but loses when it falls. When Do Futures Markets Forecast Spot Prices? Prices in futures markets sometimes function well as forecasts of spot prices. In other cases, they do not. For example, the federal funds futures market can be used to calculate market forecasts of Federal Open Market Committee (FOMC) interest rate changes. A bank loan officer, however, should not use soybean futures prices alone to forecast future spot prices when making a soybean production loan. To complicate matters further, a firm that needs to forecast oil prices six months from today sometimes can look to the futures market for a reliable forecast but sometimes cannot do so. To account for these different scenarios, we need to separate commodities into three categories: non-storable commodities, storable commodities with large inventory "overhangs" and storable commodities with modest inventories. Non-storable Commodities Futures prices of non-storable commodities embody only market expectations of future supply and demand conditions. These commodities are the only ones for which futures prices serve as perfectly straightforward forecasting tools. Non-storable commodities are perishables--things whose quantity or quality characteristics change rapidly. Eggs, for example, are considered non-storable because they spoil quickly; a fresh egg is quite different from a month-old egg. Futures prices of non-storable commodities can deviate significantly from spot prices because of anticipated changes in supply or demand. Suppose the market expected a reduced supply of eggs three months from now. The three-month futures price would be driven higher than the current spot price. Spot prices would not be affected because vendors cannot store the eggs (take them out of the spot market) to sell in the future. They must sell today's eggs based on today's market conditions. Conversely, if the market expected egg production to increase in three months, the futures price would be driven lower than the unchanged spot price. A futures market also exists for federal funds, the interbank market for reserves (deposit balances held by banks at the Federal Reserve). These instruments are non-storable because a bank cannot hold reserves today to satisfy future reserve requirements. One can use federal funds futures prices to infer market expectations of the FOMC's future interest rate changes.2 Current conditions in the federal funds market are irrelevant for future conditions and vice versa. Storable Commodities with Large Inventories For storable commodities with large inventory overhangs--say, several months' worth of consumption of the commodity--futures prices simply reflect the current spot price plus carrying costs. Carrying costs are the interest and storage costs that would be incurred between the current date and the maturity date of the futures contract if one held the commodity in inventory. For example, the Nov. 1, 2001, spot price for soybeans was $4.26 per bushel; the January 2002 futures quote on Nov. 1 was $4.34.3 The difference of 8 cents represents the per-bushel carrying costs of soybeans for approximately two months. Why must spot and futures prices be linked by carrying costs? If the soybean futures price exceeded the spot price by more than carrying costs, then an arbitrageur could earn a sure profit by selling a soybean futures contract, purchasing the soybeans in the spot market with borrowed funds and delivering the soybeans to the buyer of the futures contract on the settlement date. Because the difference between the futures price received and the spot price paid would more than cover carrying costs, a risk-free profit would be guaranteed. Conversely, if the futures price fell below the spot price plus carrying costs, then market participants would sell their inventories in the spot market and buy futures contracts, putting simultaneous downward pressure on the spot price and upward pressure on the futures price. Thus, traders' pursuit of riskless profit opportunities would move spot and futures prices quickly back to the relationship we stated above: The futures price will be the spot price plus carrying costs. In effect, traders allocate the large existing inventory through time, governed by the cost of carrying inventory. Storable Commodities with Modest Inventories Interpretation of futures prices is somewhat more complicated for storable commodities in which current inventories are low relative to current consumption needs. In these markets, we must make a distinction between two cases. If futures prices are lower than spot prices (a pricing structure termed backwardation) then the non-storable commodities analysis applies: The futures price provides the market's forecast of the future spot price. If futures prices are higher than spot prices (a contango market), then the analysis of storable commodities with large inventories applies. The oil futures market provides a good example of a storable commodity with typically modest inventory levels. If the supply of oil is expected to increase in the future, then futures prices will fall relative to spot prices. Although arbitrageurs theoretically could profit by selling oil in the spot market when that price is higher than the futures price, the shortage of inventory prevents it. As of Nov. 1, 2001, the spot price for a barrel of crude oil was $21.70; the November 2002 futures price was $21.27.4 Clearly, an arbitrageur could profit by selling spot oil in 2001 before the spot price declines, but inventory shortages prevent it. If, on the other hand, supply is expected to be low in the future, expected future spot prices will be higher than the current spot price. The futures price could not go arbitrarily high above today's spot price, however, because arbitrageurs could buy "cheap" spot oil with borrowed money, sell oil futures contracts and store the oil for future delivery. By taking advantage of the expected high prices in the future and the storability of oil, the arbitrageur pushes the spot price higher and the futures price lower. This scenario is exactly the situation we described above for commodities with large inventory overhangs. In this case, the difference between the futures price and the spot price reflects merely the carrying costs, not the market's forecast of future spot prices. Thus, futures market prices for storable commodities with typically modest inventory overhangs must be interpreted with particular care. Conclusion Although futures contracts primarily exist to hedge risk or to speculate in commodities and financial markets, a side benefit is that they sometimes also produce good price forecasts. Care must be taken, however, to interpret these prices. Futures prices reflect market expectations regarding future supply and demand conditions for non-storable commodities. For storable commodities with sufficiently large inventories, however, futures prices simply reflect the spot price plus carrying costs. Yet another category of commodities, such as oil, effectively resembles a non-storable commodity under some circumstances and a storable commodity with a large inventory overhang under other circumstances. Thus, the futures markets are not perfect crystal balls after all. Endnotes 1. Of course, the farmer still bears the production risk associated with uncertain crop yields. [back to text] 2. Robertson and Thornton (1997) describe in detail the process involved in extracting interest rate predictions from the federal funds futures market. [back to text] 3. Chicago Board of Trade, www.cbot.com. [back to text] 4. New York Mercantile Exchange (NYMEX), www.nymex.com. [back to text] References Livingston, Miles. Money and Capital Markets: Financial Instruments and Their Uses. Englewood Cliffs, N.J.: Prentice-Hall Inc., 1990. Robertson, John C. and Thornton, Daniel L. "Using Federal Funds Futures Rates to Predict Federal Reserve Actions." Federal Reserve Bank of St. Louis Review, November/December 1997, Vol. 79, No. 6, pp. 45-53. Tomek, William G. and Robinson, Kenneth L. Agricultural Product Prices, 2nd Ed., Ithaca: Cornell University Press, 1981. ABOUT THE AUTHOR William R. Emmons Bill Emmons is an assistant vice president and economist in the Supervision Division at the Federal Reserve Bank of St. Louis. REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/the-federal-reserves-response-to-the-sept-11-attacks The Federal Reserve's Response to the Sept. 11 Attacks Christopher J. Neely The terrorist attacks on the World Trade Center and the Pentagon were not only a human tragedy but also had potentially serious ramifications for the economy. The most immediate economic effect of the attacks was a temporary inability to clear checks, caused by the suspension of flights. In addition, the New York Stock Exchange and other financial markets closed for the rest of the week. Many individuals, perhaps fearful of further attacks, withdrew money from the bank. Similarly, businesses moved money from illiquid assets, like stocks and bonds, to liquid assets, like checking accounts. In the medium term, the attacks have reduced consumption and investment through their effects on consumer confidence and the temporary fall in stock prices. This reduction in consumption and investment exacerbated the economic slowdown that was already developing. In the month after the attack, for example, the Blue Chip Consensus GDP growth forecast for 2001 was revised down from 1.6 percent to 1.1 percent, and the same figure for 2002 fell from 2.7 percent to 1.5 percent. In the longer term, resources will shift to law enforcement and defense, away from the production of other goods and services. As law enforcement and defense are mostly provided by the government, taxes will rise somewhat to pay for them. Also, many of the productive resources destroyed in the attacks will be replaced. The size of these effects can easily be overstated, however. Compared to the whole U.S. economy, the increased security outlays will be very small. The attacks will also shift resources among industries in the longer term by raising the costs of activities like travel, postal services, security and insurance. That is, travelers will require more security to fly, and firms will have to pay more for a given level of property insurance for a downtown office building. These higher costs will reduce the quantity of travel, tourism and construction produced and consumed. The Fed Provides Liquidity The Federal Reserve's response to the immediate effects of the attacks was to provide liquidity—the ability to make payments—to firms and individuals. Particularly important was providing liquidity to financial firms, which constantly buy and sell assets, because they must make payments with either funds from recently sold assets or money borrowed from banks. During times of crisis, however, banks avoid making such loans because falling asset prices threaten the value of the collateral. An interruption in bank lending to financial firms could potentially set off a domino chain of bankruptcies that would bring the financial system to a halt. Such an event would quickly disrupt the whole economy through its effect on investment, including new homes, and on durable consumer goods. To avoid such a disaster, the Federal Reserve provided emergency liquidity in five ways: 1. The Fed's New York Trading Desk bought a very large amount of U.S. Treasury securities, either outright or through repurchase agreements.1 These transactions provided liquidity to markets by transferring money (a liquid asset) to the public in exchange for Treasury securities (a less liquid asset). The Fed held $61 billion of securities acquired under repurchase agreements on Sept. 12, vs. an average of $27 billion on the previous 10 Wednesdays and about $12 billion a year earlier. 2. The Fed directly lent funds to banks through the discount window. The $45 billion in discount loans outstanding on Sept. 12 dwarfed the $59 million average of the previous 10 Wednesdays. 3. As a regulator, the Federal Reserve—along with the Comptroller of the Currency—urged banks to restructure loans for borrowers with temporary liquidity problems. To assist such restructuring, the Fed made additional funds available. 4. The Fed passively extended credit to the economy through its role in clearing checks. When the Fed clears checks, it credits the receiving bank before debiting the bank making the payment. Float describes the amount of money that has been credited to check depositors but has not yet been debited from the check writers. The float totaled almost $23 billion on Sept. 12, for example, some 30 times the average float over each of the 10 previous Wednesdays. 5. The Fed took steps to boost liquidity for foreign banks with offices or subsidiaries in the United States. To enable foreign central banks to provide these resources in U.S. dollars, the Federal Reserve quickly established "swap lines" with the European Central Bank and the Bank of England and augmented the swap line with the Bank of Canada. Swap lines are similar to lines of credit; they enable central banks to temporarily exchange currencies. The accompanying chart illustrates the scale of the Fed's liquidity injection by depicting the value of deposits at Federal Reserve banks in the six weeks following Sept. 11.2 This measure, which conveniently summarizes the ability to make payments, stood at $102 billion on Sept. 12, more than five times the average of the previous 10 Wednesdays. The emergency provision of liquidity quickly passed, however. Within three weeks, the available liquidity and the channels through which it was provided—repurchase agreements, discount lending, float, etc.—were indistinguishable from pre-attack figures. Current Monetary Policy The immediate extraordinary effects of the attacks were over by October. Forecasters almost unanimously predict, however, that the attacks will exacerbate the slowdown through their effects on consumer confidence, asset prices and temporary disruptions of law enforcement, defense spending, transportation and communications. In addition, because of the extraordinary and temporary effects on some sectors, like air travel, September and October economic statistics are likely to be less informative than usual regarding longer-run trends. With this in mind, the Federal Reserve has continued to conduct monetary policy to achieve its objective of full employment through an environment of stable prices. In the past, the Federal Open Market Committee (FOMC) has responded to weaker economic conditions, which are often associated with downward pressure on the price level, with a lower federal funds target. The present case has been no exception; the FOMC reduced the federal funds rate target four times in the three months following the attacks. On Sept. 17, the FOMC lowered the target by one-half percentage point, to 3 percent, while publicly stating that future risks were weighted more heavily to economic weakness than the reverse. This action was interpreted as a confidence-boosting measure for the reopening of the New York Stock Exchange later that morning. The FOMC reinforced this action with two more 50 basis point reductions on Oct. 2 and Nov. 6 and with a 25 point reduction on Dec. 11, lowering the rate target to 1.75 percent. Looking Ahead Over a period of many years, the growth of any economy depends on a nation's stock of human and physical capital—that which can be used to produce goods and services—and on the legal environment for economic activity. These fundamentals were strong for the U.S. economy before the attack, and they have been little affected. Estimates of the value of the World Trade Center, the destruction at the Pentagon and of the associated physical capital have been valued between $10 billion and $70 billion. A mid-range estimate of $50 billion would be only 1/600th of the U.S. capital stock, which stood at almost $30 trillion in 2000.3 The longterm fundamentals for the U.S. economy remain very solid; long-run productivity growth is unlikely to be much changed. The events of Sept. 11 provide no reason to fundamentally change monetary policy. Conclusions The Fed has a mandate, by law and tradition, to provide monetary conditions for maximum sustainable growth and price stability. The Fed reacted quickly to provide liquidity during a crisis. In the aftermath of the attacks, monetary policy has been complicated by difficulty in interpreting data from September and October; however, policy has otherwise been conducted as usual. The long-term fate of the U.S. economy depends on the ingenuity and industriousness of Americans, as well as on a stable legal environment. Although the attacks may have temporarily exacerbated the slowdown, the long-term prospects for the U.S. economy are as bright as before. Charles Hokayem provided research assistance. Figure 1 Liquidity Provided in Response to Sept. 11, 2001 Immediately following the terrorist attacks of Sept. 11, the Federal Reserve provided huge amounts of liquidity to the economy. As a result, deposits at Federal Reserve banks more than quintupled over their average level the previous two months. SOURCE: Board of Governors' H.4.1 releases, July 5 to Oct. 25, 2001. [back to text] Endnotes 1. In a repurchase agreement, or repo, the Federal Reserve agrees to purchase assets and hold them for a time and sell them back at a predetermined price in the future. [back to text] 2. Deposits at Federal Reserve banks are the sum of "Service related balances and adjustments" and "Reserve balances with FR banks." [back to text] 3. Macroeconomic Advisers (2001) quote estimates of the physical damages from other sources. Data on the U.S. capital stock were taken from Haver Analytics.[back to text] References Blue Chip Consensus. Moore, Randell E., ed. Blue Chip Economic Indicators, Aspen Publishers Inc., 10 October 2001, Vol. 26, No. 10. Macroeconomic Advisers. "Preliminary Analysis of the Macroeconomic Effects of the September 11 Terrorist Attacks on the U.S." Macroeconomic Advisers Economic Outlook, 21 September 2001, Vol. 19, No. 8. REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/different-generations-generate-economy-in-kirksvillemo Community Profile: Different Generations Generate Economy in Kirksville, Mo. Stephen P. Greene Photo Gallery | Article Photo Gallery Students on campus at Truman State University. Kirksville, Mo. is making a concerted effort to attract senior citizens through amenities like this fitness center run by the Northeast Regional Medical Center. Water tower for The Kirksville College of Osteopathic Medicine (KCOM), the nation's first osteopathy school, founded in 1892. No matter how one defines the word "senior," it is a person whose presence is deeply appreciated in the town of Kirksville, Mo. In an academic sense, seniors and their fellow students inhabit the campus of Truman State University, the town's largest employer and an institution that has reinvented itself to emphasize high quality. Then there are those seniors, as in senior citizens, for whom Kirksville is placing a renewed emphasis on developing housing and services. Despite being generations apart and likely holding contrasting views on everything from music to fashion to politics, these two population groups have one thing in common: a strong economic significance in this town of 17,000 residents in the northeastern section of the Show-Me State. "Moving a Cemetery" Directionally challenged or not, many Missourians at one time or another have mixed up the regionally named universities in the state's four corners. A bit of that confusion was lifted in 1996 when Northeast Missouri State University in Kirksville changed its name to Truman State University in honor of the state's only native son to become president of the United States. More meaningful than the new name, however, were the reasons the university chose to distinguish itself in such a way. Ten years earlier, the Missouri General Assembly decided that Northeast would adopt rigorous academic requirements and focus on liberal arts and sciences. The ramifications of this shift in mission have been dramatic. The university has slashed the number of programs it once offered by almost 100 (from 140 to 43), while increasing the number of faculty from 265 to 375. In addition, the academic requirements for incoming freshmen are much tougher now, and the number of students involved in undergraduate research with faculty members is up sevenfold. University President Jack Magruder says that many of the decisions to comply with the school's new designation were difficult, including eliminating all two-year certificate degrees and divisions such as industrial sciences and home economics. "Transforming a university is like moving a cemetery," he says. "It's just not an easy thing to do." Magruder says that resistance to the change came from two groups: alumni who saw their programs disappear and residents who resented tighter state controls on the local university. "It was a controversial time," agrees Jeff Romine, an accounting professor who has been with the university for 25 years. "Change is always hard. But there is not anyone who would look back now and say that it was the wrong thing to do." Stricter admission standards and a refocused commitment to fewer areas of study enable Truman to compete with more expensive private universities. Less and less, people are comparing the school to comprehensive public universities that offer open admission, as Truman once did. This change in focus has paid off, as the university continues to bask in glowing praise from national media. For five straight years, U.S. News and World Report has ranked Truman as the No. 1 public university in the Midwest in the Universities-Master's category. Other accolades have come from Kiplinger's Personal Finance magazine, Money magazine and The New York Times, which in January 2000 called Truman "a small liberal arts version of flagship institutions like the University of California at Berkeley and the University of Michigan. ...Truman State offers small classes and an honors program and continually tests its 6,000 students with national examinations to determine where it needs to improve instruction." The university clearly has enjoyed a sustained period of momentum, which has led to campus improvements like a new fine arts building, set to open in early 2002, and a new science building, scheduled for completion in late 2004. Nevertheless, as a public institution, Truman is still subject to state budgetary considerations. Magruder says that belt-tightening by the state government resulted in a 5 percent shortfall for fiscal year 2002. Areas that were trimmed as a consequence included travel and visiting scholar programs. "If we had to deal with these kinds of cuts for a long period of time, it would hurt," Magruder says. "We're competing with very expensive schools with tremendous endowments. We do a lot with a little. Yet, if our resources can't keep pace, then we're in trouble as an institution." Targeting Older Residents Sprinkled throughout the Kirksville/Adair County Strategic Plan are references to making the area a more enticing place for senior citizens to live. "Our senior population will continue to grow at a fast rate due to aging baby boomers especially," says Mari Macomber, the city's economic and community development director. "So, we're going to need to focus services on this segment." One way to improve in this area is to increase the amount of senior housing and the coordination of services. Vacancy rates at most senior properties in Kirksville are low; some have waiting lists of two to three months. But help is on the way, thanks to The Kirksville College of Osteopathic Medicine (KCOM), the nation's first osteopathy school, founded in 1892. In September, KCOM broke ground on a senior living campus on 100 acres to the west of the college. The complex will consist of 100 apartments, 20 cottages and a senior wellness and community center providing amenities that include a multipurpose room, computer lab, library and health screening rooms. A handful of KCOM students will also live in the retirement community as part of their training in geriatric medicine, but all students will have the opportunity to work with seniors. "Often times, our students are studying the disease side of aging," says Elsie Gaber, assistant vice president for community developments at the college. "There is a growing number of people over the age of 65 who are active adults engaged in meaningful activity. This will give students a chance to know the healthy side of aging." The first phase of the complex is scheduled for completion in 2003. The Missouri Division of Aging has designated the project as one of four "Aging in Place" pilot programs because it will not require senior citizens to leave home to receive services. Next door to the KCOM campus is the Northeast Regional Medical Center, a hospital whose areas of interest to seniors include a cancer treatment center, a wide range of cardiac services and a health club with special rehabilitation programs for cardiac and pulmonary patients. Tennessee-based Community Health System, one of the largest operators of nonurban hospitals in the country, purchased Northeast Regional in October 2000. The hospital organized a Senior Circle club last May. Senior Circle, a national organization for people 50 and older sponsored by Community Health System, provides activities like health education classes, bingo and coffee gatherings. The Kirksville chapter consists of about 150 members. "Participants are able to meet a group of people and get social and emotional support that they may not ordinarily get," says Laura Gruber, coordinator for Senior Circle. Another benefit to senior citizens was the opening of a satellite Veterans Administration clinic in Kirksville three years ago. "Our veterans in town used to have to travel to Columbia for a monthly medical visit," says Martaun Ownbey, a social service worker with the Missouri Department of Health and Senior Services. "Some of them get to a point where they just can't take a 90-mile trip. Now, they can at least get their monthly medical care here." Macomber hopes that the attractions of Kirksville will become known to retirees in other cities. She says that in her job as economic development director, she is occasionally asked why someone would want to retire here. She responds that Kirksville's low cost of living, together with the improving senior services and cultural events through Truman, makes the area a viable choice. And for those who face brutal winters in states to the north, Kirksville offers a break. "Certainly, Kirksville isn't Florida," she says. "But for people who live north of here, our climate is more appealing and doesn't take them that far away from their hometown, where they still have family." Kirksville, Mo., by the numbers Population 16,988 Labor Force 12,529 Unemployment Rate 2.5% Per Capita Personal Income $18,938 Top Employers Truman State University 936 Northeast Regional Health System 700 Kirksville College of Osteopathic Medicine 417 Hollister Inc. (maker of medical devices) 408 Adair Foods Co. 530 REGIONAL ECONOMIST | JANUARY 2002 https://www.stlouisfed.org/publications/regional-economist/january-2002/road-to-recovery-longer-than-average National and District Overview: Road to Recovery Longer Than Average? Kevin L. Kliesen The nation's record-long business expansion ended in March 2001, exactly 10 years after it started, according to the Business Cycle Dating Committee of the National Bureau of Economic Research (NBER). If historical averages hold, it is reasonable to assume that the expansion will begin anew sometime early this year. Certainly, the majority of forecasters are of this opinion. Still, there are some who believe a more prolonged recession should not be so easily discounted. What is a Recession? The NBER says that a recession is "a significant decline in activity spread across the economy, lasting more than a few months, visible in industrial production, employment, real income and wholesale-retail trade." Although highly subjective, this definition encompasses the three features common to all recessions: depth, dispersion and duration. Depth refers to a decline in economic activity; dispersion means that the downturn is felt across a broad swath of industries; duration means that the decline lasts for a certain amount of time. Most business cycles--the period of activity that stretches from recession to recession or expansion to expansion--do not exhibit regularly occurring patterns, nor are they all caused by the same set of forces. Accordingly, recessions typically vary in the degree of their severity. Another complication is that many of the key indicators of economic activity do not turn down at the same time. For example, two key indicators that the NBER looks at peaked in 2000--industrial production peaked in June and real manufacturing and trade sales peaked in August--while another, nonfarm payroll employment, peaked in March 2001. The remaining indicator--real personal income less government benefits--has yet to reach peak (through October 2001). Interestingly, real GDP growth did not turn negative until the third quarter of 2001. Will This Recession Be Average? Designating when an expansion ends is key to determining when another one might begin. Since the NBER started dating them in 1854, recessions have gotten progressively shorter over time, while expansions have gotten longer. This is particularly true since World War II. For example, the average post-WW II downturn lasted 11 months, whereas from 1854 to 1945 the average contraction lasted 20 months. Hence, if the current recession is of the average post-WW II variety, then the economy should start to expand sometime early this year. At present, the majority of forecasters, whose views are compiled in the Blue Chip Consensus, expect real GDP growth to turn positive some time during the first quarter of this year. This view of the near-term outlook can best be expressed in the November 2001 Outlook issued by the National Association for Business Economics: "The rapid easing of monetary and fiscal policy this time around should enable the economy to return to positive growth more quickly than usual and with lower interest rates and inflation than during the 1990s expansion." Often, though, the severity of the recession depends on the set of forces that combined to cause it. In this instance, the NBER Committee did not speculate why the recession started in the first place. This is not unusual because recessions typically arise for a variety of reasons. One factor that the current downturn appears to have in common with most previous post-World War II downturns, however, is that it was preceded by a sharp run-up in energy prices. Still, inflation remained relatively low this time around. At the same time, this contraction appears to be unique in that it was preceded by a plunge in equity prices and, hence, household wealth. This plunge was followed by steep reductions in corporate profits and, especially significant, in business spending on capital goods, particularly high-tech equipment and software. If the investment bust and the set of forces that caused it prove to be the smoking gun behind this recession, then a recovery may not begin in earnest until earnings and profits start to grow again and until businesses feel comfortable making long-term commitments. With the events of Sept. 11 creating substantial uncertainty about the prospects of additional terrorist attacks and with the ongoing government response to these threats, this recession may last a bit longer than usual, even though monetary and fiscal policies have been very stimulative of late. Thomas A. Pollman provided research assistance. ABOUT THE AUTHOR Kevin L. Kliesen Kevin L. Kliesen is a business economist and research officer at the Federal Reserve Bank of St. Louis. His research interests include business economics, and monetary and fiscal policy analysis. He joined the St. Louis Fed in 1988. Read more about the author and his research. National and District Data Selected indicators of the national economy and banking, agricultural and business conditions in the Eighth Federal Reserve District Commercial Bank Performance Ratios third quarter 2001 U.S. Banks by Asset Size ALL $100 million$300 million Return on Average Assets* Net Interest Margin* Nonperforming Loan Ratio Loan Loss Reserve Ratio 1.2 1.18 1.11 1.29 1.18 1.3 1.24 1.18 3.82 4.43 4.4 4.44 4.41 4.36 4.39 3.53 1.34 0.98 1.02 0.93 0.98 1.1 1.04 1.51 1.76 1.35 1.36 1.44 1.39 1.88 1.64 1.83 less than $300 million $300 million$1 billion less than $1 billion $1billion$15 billion Net Interest Margin* Return on Average Assets * 1.17 1.18 1.04 1.11 0.95 0.97 1.03 1.10 1.11 1.24 1.05 1.29 1.10 1.19 1.42 1.22 0 .25 .50 .75 1 1.25 1.50 4.00 4.16 3.98 4.13 Eighth District Arkansas 3.68 3.83 3.77 Illinois Indiana Kentucky Mississippi 4.20 4.19 4.06 Tennessee 2 3 percent 3.50 1.28 Illinois Indiana Kentucky Mississippi Missouri 1.39 0.99 .5 .6 .7 .8 Arkansas 1.16 0.87 0.84 0.79 0.90 0.80 .9 1 1.1 1.2 1.3 4.50 5 5.50 6 1.35 1.33 1.29 1.24 1.25 1.22 1.29 1.22 1.39 1.34 1.36 1.33 1.39 1.40 1.35 1.35 Eighth District 1.13 1.13 1.06 0.76 4 Loan Loss Reserve Ratio 1.17 0.96 4.99 3.89 Missouri 1.75 4.44 3.92 3.99 4.14 Nonperforming Loan Ratio 0.91 less More than than $15 billion $15 billion 1.4 Tennessee 1.5 percent 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 Third Quarter 2000 Third Quarter 2001 NOTE: Data include only that portion of the state within Eighth District boundaries. SOURCE: FFIEC Reports of Condition and Income for all Insured U.S. Commercial Banks *Annualized data  For additional banking and regional data, visit our web site at: http://www.stls.frb.org/fred/data/regional.html. 1.8 1.9 2 The Regional Economist January 2002 ■ www.stls.frb.org Regional Economic Indicators Nonfarm Employment Growth year-over-year percent change third quarter 2001 Goods Producing United States Arkansas Illinois Indiana Kentucky Mississippi Missouri Tennessee Service Producing 1 total mfg cons 0.3% 0.2 –0.4 –1.0 0.5 –1.7 –1.3 0.3 –5.0% –4.3 –3.8 –4.5 –5.1 –7.2 –6.4 –4.7 2.4% 5.7 4.0 0.2 0.9 –2.4 0.3 2.2 2 govt 1.7% 1.0 0.0 1.1 1.1 0.7 0.6 0.2 tpu fire3 services trade 0.9% 0.9 0.3 –0.4 –0.9 –1.5 –0.8 1.5 1.0% 0.7 0.3 –0.9 0.5 0.1 1.3 –0.5 1.2% 1.6 0.6 0.6 3.7 –0.7 –1.0 2.2 0.6% 1.1 –0.9 –1.1 0.9 –0.4 –0.9 1.7 Unemployment Rates Total Government Revenue percent Fiscal-year-over-fiscal-year percent change United States Arkansas Illinois Indiana Kentucky Mississippi Missouri Tennessee III/2001 II/2001 III/2000 4.8% 4.7 5.4 4.1 5.1 4.9 4.1 4.1 4.5% 4.7 5.3 3.3 4.4 4.8 4.0 4.2 4.0% 4.4 4.4 3.1 4.1 5.5 3.5 4.0 5.5 United States 3.3 Arkansas 4.3 2.2 Illinois – 1.0 Indiana 7.8 2.9 2.9 3.8 Kentucky 6.2 5.8 Mississippi Missouri 3.2 4.3 1.8 Tennessee –4 –2 0 2 7.7 4 6 2001 third quarter 8 10 Real Personal Income year-over-year percent change 2.4 – 20.5 0.4 2.1 1.8 0.3 2001 2.5 Kentucky 0.0 0 1.8 3.1 1.8 Tennessee 5 10 15 20 25 percent 0 2000 Transportation and Public Utilities 1 Finance, Insurance and Real Estate  2.5 2 2001 3 3.4 1.1 Missouri 0.3 2.2 1.8 Mississippi – 30 – 25 – 20 – 15 – 10 – 5 2 Arkansas Indiana 0.2 3.7 1.3 1.2 Illinois – 0.7 – 4.0 – 5.9 – 7.1 Construction 1.9 United States 19.7 – 4.0 14 second quarter Housing Permits – 15.0 – 10.1 – 12.6 12 2000 year-over-year percent change in year-to-date levels – 4.1 1 10.8 All data are seasonally adjusted. 3 2000 4 Major Macroeconomic Indicators Real GDP Growth Consumer Price Inflation percent percent 9 8 7 6 5 4 3 2 1 0 –1 –2 1996 4.0 3.5 all items, less food and energy 3.0 2.5 2.0 1.5 97 98 99 00 all items 1.0 1996 01 NOTE: Each bar is a one-quarter growth rate (annualized); the green line is the 10-year growth rate. 97 98 99 00 01 (Nov.) NOTE: Percent change from a year earlier Civilian Unemployment Rate Interest Rates percent 6.0 percent 8 10-year t-bond 7 5.5 fed funds target 6 5.0 5 4.5 4 three-month t-bill 3 4.0 2 3.5 1996 97 98 99 00 1 1996 01 (Nov.) 97 98 99 00 01 (Nov.) NOTE: Except for the fed funds target, which is end-of-period, data are monthly averages of daily data. Farm Sector Indicators U.S. Agricultural Trade Farming Cash Receipts billions of dollars 40 billions of dollars 35 115 110 exports 30 crops 105 25 100 20 imports 15 95 90 10 trade balance 5 0 1996 97 98 99 00 85 livestock 80 1996 01 (Sept.) NOTE: Data are aggregated over the past 12 months. Beginning with December 1999 data, series are based on the new NAICS product codes. 97 98 99 00 01 (Sept.) NOTE: Data are aggregated over the past 12 months. U.S. Crop and Livestock Prices index 1990-92=100 145 135 crops 125 115 105 95 livestock 85 75 1987 88 89 90 91 92 93 94  95 96 97 98 99 00 01 (Nov.)