Imagine the head ranger of a small national forest whose job is to manage the park’s flora and fauna. He observes that over the years the fox and hare populations are never constant. They generally fluctuate within fairly narrow bands, but during some years the hare population takes a dangerous dip while during others the fox population does the same. The ranger worries that someday the dips might become so extreme that one or the other of the animals will completely die out.
Over many years, the population has averaged 500 hares and 100 foxes, and the ranger decides that these numbers represent the park’s optimum. He reasons that if the hare population were kept constant at 500 animals, the fox population would likewise remain constant at its optimum level of 100. To maintain the hare population, hunters are licensed to kill the excess animals as needed. By forcing the head count to be constant, the head ranger will ensure that the population swings never become so violent as to result in the extinction of either animal.
Mysteriously, though, the hare population starts to decline one year, and the foxes begin to starve. To keep the foxes fed while the problem with the hares is diagnosed, domesticated rabbits are released into the park. What the ranger doesn’t know, however, is that the hares are declining because of a food shortage thanks to the previous winter’s record cold weather. Introducing the rabbits raises competition for the remaining food, putting even more pressure on the native animals. Meanwhile, the foxes begin thriving because the tame rabbits are so easy to catch. Between competition from the rabbits and the increasing number of foxes, the few remaining hares, weakened by hunger, are soon eradicated.
The park must replenish the hares with animals brought in from neighboring areas. The ranger has learned his lesson, though. It was foolish to try to maintain the balance by controlling the population of only one set of animals. Clearly, he has to actively limit not only the hare population but also the fox population. Local hunters are happy to oblige.
For several years, the populations stay fairly constant, at or near their optimums. Unfortunately, some years into the new program, a sudden disease outbreak causes the number of foxes to drop rapidly. Normally, the hare population would rise inversely with the decrease in predators. The hunters, however, faithfully keep them in check. Had the supply of hares been allowed to rise, the foxes’ cost of catching them—that is, the energy needed to hunt and kill them—would have fallen, and the foxes, though weakened by sickness, might have been able to survive. Instead, the foxes quickly die off.
What the ranger failed to understand is that many factors, some unknowable even in hindsight, affect the small park’s animal populations. He also failed to grasp the concept of dynamic equilibrium. Left to themselves, the animal populations were never statically balanced; rather, they were always in the process of balancing as their environment continually changed around them. Had the head ranger simply left the foxes and hares alone, the animals would have fared far better.
Monetarists and Keynesians are a bit like the ranger in this thought experiment. Both hope to keep the economy in balance by manipulating either the money supply or the “price” of money (i.e., interest rates). Monetarists want to keep the money supply constant, or at least growing at a slow, steady rate regardless of demand. The problem with this scheme is that it can result in wild interest rate swings. For example, suppose that some crisis causes people to increase their cash holdings. Money is withdrawn from banks, mattresses are stuffed, and spending drops. Because the money supply does not rise to meet increasing demand, interest rates rise much higher than they would otherwise. Conversely, if the demand for money drops while the supply stays constant, interest rates will fall further than they would under a free banking system.
Keynesians are more like the ranger in the second experiment in that they try to address both the supply of and the demand for money, though indirectly through interest rates. But interest rates are the result of a complex, iterative interplay between supply and demand. Keynesians reverse cause and effect, attempting to stabilize both supply and demand by manipulating interest rates—a bit like trying to cure a child’s fever by adjusting the thermometer.
Keynes envisioned a central bank that would raise interest rates when the economy “overheated,” and lower them when the economy dipped. In practice, however, politicians try to pressure central banks to keep interest rates low and themselves in office.
In a free market, falling interest rates are the result of increased savings (i.e., delayed consumption), lower borrowing, or both. When savings rise, banks have more to lend and will drop interest rates to attract borrowers. Businessmen, seeing falling interest rates as signaling higher future consumption, may take advantage of lower rates to borrow in order to add to their companies’ productive capacities.
An artificially induced rate drop, however, does not necessarily mean more savings and more potential consumption down the road. Instead, the lower rates make saving less attractive and consumption more so. Businessmen may be fooled by the drop in rates and borrow to fund plant expansions. Prices rise as consumers and producers compete for scarce resources—resources that would have been more plentiful had the low interest rates actually been the result of delayed consumption. In the end, businesses may well discover that they have increased capacity at high costs to satisfy customers who never appear.
Even if central banks always tried to operate as Keynes wished, however, the inaccuracy of the economic indicators that guide their actions and the time lags in the banks’ feedback loops would almost guarantee unstable markets. Every month the government announces adjustments to its previously announced estimates of such indicators as GDP and the rate of inflation. Sometimes these adjustments are quite significant, yet the central banks must base their actions on such questionable data. But the banks have more than just bad numbers to deal with. They also must take into account the time between their actions and any measureable impact on the economy; such lags vary anywhere from six to 18 months. By that time, so many other things may have occurred that any observable link between cause and effect is lost. Between poor data and long time lags, a central bank may easily overcorrect, causing wild swings in the economy.
Like the ranger’s forest, an economy is an ecology—a network of interconnected individual beings and processes in which every action has myriad predictable and unpredictable effects and reactions. And like the ranger, after much hard experience, central bankers may eventually learn to let the foxes and hares sort things out for themselves.