ZIFFPAGE TITLEDigging DeeperBy Mel Duvall | Posted 2005-04-06 Print
How does Federal Reserve chairman Alan Greenspan decide to raise rates a quarter point? By analyzing a potent mixture of raw pecuniary data and computerized economic intelligence against first-hand reports from key hubs of U.S. financial activity and five
Previous Fed chairmen, such as Greenspan's predecessor, Paul Volcker, had been primarily interested in aggregated metrics like the Consumer Price Index. That is a monthly measure of the change in prices urban shoppers pay for a fixed set of goods and services, including department store products and apartment rents.
But Greenspan thinks differently. When he arrived, economists started getting more requests from the chairman's office for disaggregated dataindividual points of information like the price of hot-rolled steel, construction-grade plywood or circuit boards.
Greenspan wants such data points to seek out telling shifts in the U.S. economy that large aggregated figures like the GDP sometimes disguise. A significant drop in demand for steel, for example, might not be noticed because it could be masked by increases in demand for non-steel-based products like furniture, clothing and shoes. But a dip in steel consumption may indicate that manufacturers of cars, dishwashers, microwaves and freezers are girding for a drop in demand for their products.
Wal-Mart does something similar, drilling down to compare, for example, sales of lightweight spin-casting fishing rods to determine subtle shifts in consumer tastes, perhaps brought on by a Hollywood movie such as A River Runs Through It, about fly-fishing in Montana. That might be invisible looking only at total sales of fishing rods.
For Greenspan, the summer of 1996 was spent studying U.S. productivity data. He was perplexed by figures showing a steady drop in productivity, or the output per hour of a worker.
The data didn't make sense next to his anecdotal evidence. His staff's ground reports and his own industry contacts indicated that new technology was helping companies dramatically boost productivity.
Greenspan had the Fed's economists conduct a massive research project, calculating the change in productivity in every major sector, from manufacturing to mining, finance, agriculture, education, health care and services. They found a number of flaws in how productivity was measured, particularly in service businesses such as insurance, law and banking, where technology had made a tremendous impact.
Automated teller machines, for example, let banks serve more customers faster. But because the main service they offeredmoney withdrawalswas largely provided for free, the benefits were not being recognized. The traditional productivity stat measures the amount of output in dollars that comes from an hour of labor. Because there was no output or income generated by these machines, there was no recognition of the increase in productivity banks achieved.
The research led Greenspan to conclude that productivity gains in the service industries were at least as high as, and probably higher than, the 3.6% average annual gains recorded in the manufacturing sector between 1994 and 1997, even though the data did not show it. That compared to average gains of 1% to 1.5% in the previous two decades.
As a result, Greenspan decided not to raise interest rates, even though many of his colleagues pressed for increases. Based on history, they feared, inflation would jump if interest rates did not slow down the economy. Instead, Greenspan theorized that gains in productivity would prevent prices from risingan informed hunch that the data would later prove correct.
"I was on the opposite side of the chairman in that debate," Meyer says. "But he was right. He deserves the credit for figuring it out."
Greenspan goes through a similar process of checking incoming data against insights gathered from the field before each Federal Open Market Committee meeting.
In the weeks leading up to the Feb. 1 gathering, economists with the San Francisco Federal Reserve Bank placed a number of calls to executives with the Long Beach and Los Angeles ports and at local shipping companies.
The ports, which combined are the nation's busiest, had been plagued by delays in the months leading up to Christmas. The concern for Greenspan was whether those delays would have trickle-down effects. Manufacturers might be waiting on parts and retailers might not be able to restock shelves, which might in turn mean consumers would hold off opening their wallets until those big-screen TVs arrived in stores.
The ports went through their own version of the perfect storm: A surge of new production from China of everything from toys to consumer electronics, and parts for larger products like computers, had the ports working at full capacity in the summer months. Then, heading into the fall, a sharp increase of imports from retailers like Wal-Mart and Target, whose fine-tuned supply chains have stores receiving merchandise just in time to be placed on shelves for Christmas, pushed the infrastructure and workforce past their limits.
Normally a ship arrives at a scheduled time, pulls into an open dock and is unloaded in three to four days. In late October, ships were often waiting more than six days to dock, then taking more than 10 days to unload because of a shortage of longshoremen, cranes and trains.
At its worst, as many as 86 ships were lined up offshore to be unloaded at the two ports. The result was a seaside traffic jam. "It was unbelievable," says David Arian, president of Local 13 of the International Longshore and Warehouse Union. "There was an armada of ships out in the harbor waiting to be unloaded."
Not only were the ports overwhelmed, the rail lines couldn't move containers from the ships fast enough. Union Pacific was left understaffed when an unexpectedly large number of employees accepted an early retirement plan.
Months might pass before the effects of this type of logjam would show up in national statistics like the GDP, retail sales or inventory figures. But near-real-time anecdotal reports from economists with the San Francisco reserve bank kept Greenspan informed.
"What we look for is major developments in our regions that may have national implications," says Fred Furlong, vice president of financial and regional research for the San Francisco Fed, whose region encompasses California, Arizona, Nevada, Utah, Oregon, Washington, Idaho, Hawaii and Alaska.
"Our position [as an arm of Greenspan] provides us with access to a large number of people on the ground with first-hand access to what's going on with the economy," he adds.
Prior to each open market committee meeting, San Francisco economists make close to 100 calls to key contacts, such as chief executives, finance officers and controllers with major employers in the region, such as Boeing, Intel, Union Pacific and the ports. Other reserve banks do the same.
Similarly, Wal-Mart's employee-led program to collect eyewitness intelligence on rivals' sales helped clinch its decision to slash prices before Christmas.
What Furlong's team found right before the February meeting was that the worst was over. Two thousand full-time and 7,000 part-time longshoremen had signed on to help the existing 5,000. Union Pacific had hired 4,000 workers, eliminating most of its staffing bottlenecks.
The message San Francisco Fed president Yellen delivered to Greenspan was that port delays were no longer an immediate threat to the economy.
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