|Forecasting America’s Destiny … and the World’s|
|HOME WEB LOG COUNTRY STUDIES COMMENT FORUM ABOUT|
System Dynamics and the Failure of Macroeconomics Theory
Mainstream macroeconomic theory, invented by Maynard Keynes in the 1930s, has failed to predict or explain anything that’s happened since the bubble started, including the bubble itself. We need a new “Dynamic Macroeconomics” theory. (25-Oct-2006)
Summary Macroeconomic theory was invented in the 1930s to develop policies to prevent a stock market bubble and Great Depression. It’s failed to predict or explain the 1990s stock market bubble or almost anything in the 2000s decade. This article proposes combining System Dynamics, invented at MIT in the 1960s, with macroeconomics to form a new Dynamic Macroeconomics theory that will predict and explain such things as recessions, inflation, and bubbles. Microeconomics (originally, just called “economics”) is the study of how individual people and businesses make decisions about such things as how much they’re willing to pay for a product or service or what products or services they’re willing to offer. The “Law of Supply and Demand” is probably the best-known law of microeconomics.
Macroeconomics is the study of aggregate prices, income, products and services for an entire nation or economy, and also for the entire world economy. It’s used by the federal government to help predict and explain how changes in tax rates or the money supply will affect such things as inflation and unemployment.
Macroeconomics was invented during the Great Depression to develop theory and policies for preventing a Great Depression from ever happening again.
Failure of mainstream macroeconomics theory
Few people seem to realize how remarkable and deviant the stock market bubble was. If you look at the adjacent graph, which shows the S&P 500 index, along with an exponential growth trend line, it shows that the index had been oscillating normally around the trend line and was leveling off in 1995 when the index took a “sharp turn” in the upward direction. This kind of anomalous behavior (which indicates a discontinuity in the derivative) has NO POSSIBLE EXPLANATION whatsoever in mainstream macroeconomic theory. (Added on 27-Oct)
There has always been some question as to how useful macroeconomics has been even in the best of times, but there’s no doubt that it’s been a complete failure in the last ten years, and has provided either no information or misleading information at almost every step of the way during that period:
- It failed to predict the 1990s stock market bubble, and still can’t explain why it occurred or why it occurred in 1995 instead of, say, 1985 or 1990 or 2000. This is especially significant, since macroeconomics was supposed to help prevent a repeat of the 1920s stock market bubble, and it’s been of no use.
- It failed to predict or explain the extremely low inflation and high unemployment in the early 2000s, despite near-zero interest rates.
- It failed to predict or explain the anemic recovery from the recession of the early 2000s.
- It failed to predict or explain why real wages didn’t go up in the last few years as productivity increased.
- It failed to predict or explain the extremely low long-term interest rates of the early 2000s (Alan Greenspan’s “conundrum”).
You can pick almost any major fiscal or monetary macroeconomic variable, and mainstream macroeconomics theory has simply failed to predict or explain its path, especially since 1995. Economists just come out with new guesses every month, but when you look at the entire picture, all of macroeconomics has become a “conundrum.”
In fact, economic theory is now going through the third major crisis in the last century. The first was when it failed to predict or explain the Great Depression of the 1930s; the second was when it failed to predict or explain the high combined inflation and unemployment (“misery index”) in the 1970s; and now it’s failed to predict or explain the 1990s bubble and the economy of the 2000s decade.
Ask almost anyone about a new Great Depression in the 2000s decade, and they’ll give you an answer like this: “It can’t happen. In the 1930s, the Roosevelt administration put in new agencies and regulations to prevent another depression from every occurring.”
What’s obvious now is that all of the agencies and regulations that were created in the 1930s to prevent another depression have already completely failed.
Take the Securities and Exchange Commission (SEC). When I was high school in the 50s, my teachers talked about the Great Depression all the time, and they told me how the SEC was going to prevent a future depression. The 1930s depression was caused by the huge stock market bubble of the 1920s, where millions of investors, driven by greed, drove up the prices of stocks by borrowing money from each other, a situation that led to a huge stock market correction in the 1930s. The SEC would prevent that from ever happening again by regulating margin rates, which would reduce buying stocks on credit, and prevent another huge stock market bubble. My 1950s high school teachers knew that because they lived through the 1930s, and understood that piece of wisdom.
Well, today all the people who remember that wisdom from personal experience are gone. And guess what? The SEC failed to prevent the huge 1990s stock market bubble. I want to emphasize this: The SEC has failed at the principal thing it was formed to do, and mainstream economists have absolutely no idea why.
The same failures permeate all macroeconomic theory. Macroeconomics theory is always ten years out of date. Researchers look at the most recent data from the preceding few years, and then spend a few years adjusting their models and theories according to the that data. So today’s macroeconomics theory reflects data from the 1980s-90s, and macroeconomics theory from the 1990s reflects data from the 1970s-80s.
It’s as if weather forecasters simply told what the weather has been in the last few days, and simply guessed at what the weather was going to be tomorrow. That’s how bad macroeconomic theory has been.
The result is that most mainstream economists appear to be fools. I’ve given many examples on this web site where economists say things that are totally absurd. For example, I recently posted an article quoting dozens of economists as saying that record high and exponentially increasing trade deficits are good news because they boost retail sales and keep the stock market bubble going up.
That’s an example of sheer stupidity, but it’s not as bad as the actual fraud that economists perpetrate continually when they refer to price/earnings ratios (or “valuations”). I won’t go into the details, since I’ve gone through it many times before. But basically they all use today’s stock prices and divide by inflated future earnings estimates, rather than dividing by last year’s earnings, which is the correct computation. They must know this, because it’s their job to know it.
Economists, analysts, and investment advisors use the wrong computation in order to sell more stocks, to make more commissions and to sell more consulting services by telling people what they want to hear, even when it’s wrong. It’s out and out fraud by the investment community, and when this financial crisis begins to wash out, it would be appropriate to bring criminal charges of fraud against many of these economists.
In this essay, we’re going to discuss the history of macroeconomic theory, and show how it hasn’t yet even come close to fulfilling its original objectives.
The main finding is that macroeconomic theory itself is going to have to make use of a discipline known as System Dynamics, invented in the early 1960s by Jay W. Forrester of the MIT Sloan School of Management with the establishment of the MIT System Dynamics Group. System Dynamics is now widely recognized as a necessary discipline when large aggregates are being measured.
This will require a new “conceptual leap,” such as the one from economics to macroeconomics, which took a conceptual leap from individuals to aggregates in the 1930s. “Dynamic Microeconomics” will take a leap from aggregates to dynamic aggregates, using such concepts as stocks and flows, time delays, feedback and nonlinearity.
Example: Savings rate
Let’s take a close look at an example, to illustrate what’s wrong with mainstream macroeconomics theory.
The savings rate is a good example of something that the government needs to understand when they make policy decisions.
For example, when the government wants to cut taxes, it’s important to government planners to know in advance how much of the tax cut will be spent by consumers and what percentage will be saved — the latter being the savings rate.
What does macroeconomics theory tell us about the savings rate? Are there any other factors we can look at that will help us predict the savings rate?
In order to illustrate how economists think, I’m going to quote the abstract of a paper. It’s not a special paper; in fact, I just picked it at random after googling the phrase “savings rate.” I wanted something that provides insight into how economists think of these things.
So, the following is the abstract of a random paper that I googled on this subject. It’s a paper called Why are Saving Rates so Different Across Countries?: An International Comparative Analysis, by Sebastian Edwards. I didn’t select this paper because it’s exceptionally good or bad; I selected it because it’s typical.
Here is the abstract:
- “This paper analyzes the determinants of savings in the world economy, and discusses why saving ratios have been so uneven across countries. A distinction is made between private and government savings, using panel data for 36 countries, from 1970 to 1992. In particular, it is assumed that government savings are not completely exogenous, and respond to both economic and political (strategic) determinants, along the lines of the recent literature on the political economy of macroeconomic policy. Using instrumental variables estimation methods it is found that per capita growth is one of the most important determinants of both private and public savings. The results indicate that government-run social security systems affect private savings negatively. In addition, the results provide some support for the political economy perspective to government finances, which evidences a different underlying process determining public savings. Public savings tend to be lower in countries with higher political instability. Higher government savings crowd out private savings, but in a less than proportional fashion. Higher levels of foreign savings – i.e. reductions in the current account balance – are associated with lower domestic (both private and public) saving rates, although the degree of offset is also less than proportional. The degree of financial development turns out to be another important determinant of private savings. The results are mixed regarding the role of borrowing constraints – a topic deserving additional research attention.”
You don’t have to understand everything in that abstract to see what’s going on. It’s known that people are going into debt much more than they used to, and so the savings rate has dropped enormously since they 1960s and 1970s. This paper is attempting to explain that collapse in the savings rate by trying to correlate it to zillions of other factors (economic and political determinants, social security stems, political instability, growth rate, etc.) against savings rates over 22 years. The hope is that there might be an “Aha!” type discovery that, say, if we adjusted the Social Security system or the tax policy, we might be able to coax people to save more money.
The problem is that this collection of factors overlooks the most obvious one: That people who grew up during the Great Depression save more. As we’ll see later, that’s one of the issues that System Dynamics addresses.
To sharpen this question even further, let me contrast two different ways of dealing with age demographics. Economists know that older people have higher savings rates than younger people. Suppose we had a savings rate table like this (these are made-up figures):
SAVINGS RATES Year Young folks Old folks Overall Savings Rate ---- ----------- --------- -------------------- 1960 5% 15% 10% 2000 4% 6% 5%
There are two completely different ways of looking at this table. Here they are:
- Static view. People in all groups are saving less in 2000 than they used to in 1960, and so the overall rate has gone down. We need to get people to save more, not less.
- Dynamic view. Young folks in 1960 had a low savings rate in 1960, and as they grew older, their savings rate barely changed at all. As older folks in 1960 grew older and died, their high savings rate was lost, and so the overall rate has gone down.
The difference between these two views is like night and day. One says that individual savings rates have gone down, and the other says that they haven’t. The static view is the disastrous view held by economists today, the one that’s led to one error after another.
The dynamic view provides a great deal more information, and DIFFERENT information. While the static view says that savings rates have changed, the dynamic view tells you that savings rates HAVEN’T CHANGED AT ALL, since individual people are saving almost exactly as much as they used to as they get older.
This is hugely important for policy reasons. The static view dictates one set of policies and the dynamic view dictates a completely different set of policies.
But economists use the static view, and that’s why macroeconomic theory is such a disaster today. Economists take recent data and create a model from it. Then the data changes, and they say, “Oh, the data’s changed,” and they create a brand new model.
Economists can’t create a model that takes dynamic changes into account because they don’t even understand the dynamic view. That’s why economists continue to get everything wrong.
System Dynamics and Macroeconomics
I’m not the only person who’s noticed this deficiency in macroeconomic theory. A number of other people have noticed it as well, but no economists that I’m aware of.
A 2002 paper entitled, All Models are Wrong: Reflections on Becoming a Systems Scientist, written by Prof. John Sterman, director of the MIT System Dynamics Group has the following abstract:
- “Thoughtful leaders increasingly recognize that we are not only failing to solve the persistent problems we face, but are in fact causing them. System dynamics is designed to help avoid such policy resistance and identify high-leverage policies for sustained improvement. What does it take to be an effective systems thinker, and to teach system dynamics fruitfully? Understanding complex systems requires mastery of concepts such as feedback, stocks and flows, time delays, and nonlinearity. Research shows that these concepts are highly counterintuitive and poorly understood. It also shows how they can be taught and learned. Doing so requires the use of formal models and simulations to test our mental models and develop our intuition about complex systems. Yet, though essential, these concepts and tools are not sufficient. Becoming an effective systems thinker also requires the rigorous and disciplined use of scientific inquiry skills so that we can uncover our hidden assumptions and biases. It requires respect and empathy for others and other viewpoints. Most important, and most difficult to learn, systems thinking requires understanding that all models are wrong and humility about the limitations of our knowledge. Such humility is essential in creating an environment in which we can learn about the complex systems in which we are embedded and work effectively to create the world we truly desire.”
If you have any doubts about Professor Sterman’s claim, then download the complete paper, and read it for yourself. It contains dozens of examples, illustrating policy areas in many areas, including economics.
I’d like to call your attention to these two sentences: “Understanding complex systems requires mastery of concepts such as feedback, stocks and flows, time delays, and nonlinearity. Research shows that these concepts are highly counterintuitive and poorly understood.”
Most economists are simply not capable of understanding systems reasoning, and it’s even worse among politicians and journalists. Perhaps, as Sterman says, it’s possible to teach it in schools, and maybe if we start in second grade then the journalists, politicians and economists will figure it out by the time they get through college. I wouldn’t mention this if there weren’t so much at stake.
To show how difficult it is to understand systems thinking, try taking the quiz below, which I’ve taken from Prof. Sterman’s paper.
This is a very simple problem, in a simple situation — a few people enter and leave a store. It requires no math, and nothing more than a little intuition.
Just to make it a little easier, we’ll explain the graph below: In the first minute, 10 people leave the store, and 14 people enter; in the second minute, 11 people leave and 16 people enter.
If you did well on this test, you should be very proud of yourself. Among MIT students who took the test, most got the first two questions right, and most got the last two questions wrong. Many students were completely stumped. (For hints, as well as answers and explanation, click here) Now, this is really a very simple problem, involving a few people going in an out of a store over a 30 minute period.
When you move to economics, involving the habits of hundreds of millions of people and businesses, the concepts are abstract enough to be beyond the abilities of most economists.
Let’s briefly describe System Dynamics.
Introduction to System Dynamics concepts
There are hundreds of descriptions of System Dynamics on the internet, and you can easily reach them with a search engine. This description is therefore brief.
Systems Dynamics was founded in the early 1960s by Jay W. Forrester of the MIT Sloan School of Management with the establishment of the MIT System Dynamics Group. The current Director is Prof. John Sterman, previously quoted.
Stocks and flows are the basic building blocks of a system.
A stock is some entity that you’re keeping track of over time. An inward flow adds to the stock and increases it, and an outward flow depletes the stock and reduces it.
Here are some examples of stocks and flows:
Stock Inward flow Outward flow ------------------ ------------------------------ --------------------- Population Births and immigration Deaths and emigration Inventory Incoming goods Outgoing goods People in a store People entering store People leaving store Water in a bathtub Water pouring in from faucet Water draining out Bank balance Deposits Withdrawals Generation Births Deaths Businesses Business opening Business closing
A feedback loop occurs when the inward and outward flows interact.
Let’s consider a slightly more complex example, involving two species of animal, a predator species (owls) and a prey species (lemmings).
In this case, the lemmings population grows, and the lemmings get eaten by the owls. The owl population grows and kills off so many of the lemmings that they’re almost extinct. That’s when the owls die off with nothing to eat. Then the lemming population can start growing again.
Here you have two different stocks (owls and lemmings) interacting with each other, with flows in each case controlled by births and deaths.
There’s a “feedback loop” not just because the populations interact, but also because the flows interact: As the population of owls increases, the population of lemmings decreases, and vice-versa.
Perhaps now you can see where all this is going.
The “conceptual leap” that macroeconomics theory requires is to introduce these kinds of feedback loops. But instead of being different species, we’ll be talking about different generations.
The generation that grows up during the Great Depression is going to have certain unique behaviors and attitudes towards personal finance. The generation of their children will inherit some of those attitudes and rebel against others of those attitudes, resulting in a completely different and unique set of behaviors and attitudes.
Similarly, the children’s children’s generation will have its own behaviors and attitudes and, as we’ll show, this generation is much more willing to take unreasonable financial risks, thus leading to a new financial crisis that completes the cycle.
Allo of these generations interact with each other and influence each other.
Macroeconomics theory today does not measure these generational interactions AT ALL. “Dynamic macroeconomics” will measure those interactions.
But first, let’s look at some history, to see how we got here.
Development of modern macroeconomic theory – 1930s
Let’s take a look at a very peculiar statement by Stephen Roach, chief economist at Morgan Stanley:
- “Modern-day central banking was born out of the Great Inflation of the 1970s. Led by Fed Chairman Paul Volcker, monetary authorities became tough and disciplined in their efforts to break the back of a deeply entrenched inflationary mindset. Price stability became the sine qua non of macro stabilization policy. Nothing else really mattered. Without inflation, it was argued, economies could realize extraordinary efficiencies that would enhance resource allocation and maximize returns for the owners of capital and providers of labor…. Who could ask for more?”
To say that modern-day central banking was born in the 1970s simply isn’t true. Modern-day central banking was born in the 1930s, as policymakers in Congress and in the Roosevelt administration implemented a whole raft of new laws and created another raft of new agencies designed to prevent the 1920s bubble from ever occurring again, so that a new 1930s Great Depression could be prevented in the future.
Obviously all of these measures failed, since the 1990s stock market bubble occurred again. But Roach is making a little joke above when he refers to the “Great Inflation of the 1970s” as the start of modern-day central banking.
Today no one doubts that the 1930s Great Depression was a total disaster for both the country and for economists. In his book, The Great Crash – 1929, John Kenneth Galbraith describes what I’ve been calling “The Principle of Maximum Ruin,” which says that the ignorance of economists, analysts and journalists guarantees that a stock market crash brings the greatest possible amount of ruin to the greatest possible number of people.
Galbraith summarized the situation as follows, noting that economists and analysts of the day gave advice based on the relative painlessness of previous recent stock market panics:
- “A common feature of all these earlier troubles [previous panics] was that having happened they were over. The worst was reasonably recognizable as such. The singular feature of the great crash of 1929 was that the worst continued to worsen. What looked one day like the end proved on the next day to have been only the beginning. Nothing could have been more ingeniously designed to maximize the suffering, and also to insure that as few as possible escaped the common misfortune.” (p. 108)
Galbraith showed how, after the initial crash on October 24, 1929, “In the first week the slaughter had been of the innocents,” in the second week it was “the well-to-do and the wealthy” who were slaughtered (p. 113), and then more and more people were sucked into ruin during the years that followed.
Galbraith particularly describes the doings of the Harvard Economic Society, a group of economists on the Harvard University faculty, possibly the most highly regarded economists in the world.
Galbraith summarizes their opinions as follows:
- “By wisdom or good luck, the Society in early 1929 was mildly bearish. Its forecasters had happened to decide that a recession (though assuredly not a depression) was overdue. Week by week they foretold a slight setback in business. When, by the summer of 1929, the setback had not appeared, at least in any very visible form, the Society gave up and confessed error. Business, it decided might be good after all. This, as such things are judged, was still a creditable record, but then came the crash. The Society remained persuaded that no serious depression was in prospect. In November it said firmly that “a severe depression like that of 1920-21 is outside the range of probability. We are not facing protracted liquidation.” This view the Society reiterated until it was liquidated.” (p. 71)
Reading the antics of the Harvard Economic Society is similar to reading a Three Stooges script. Here’s how Galbraith describes what happened:
- “The Harvard Economic Society, it will be recalled, had come up to the summer of the crash with a valuable reputation for pessimism. This position it abandoned during the summer when the stock market kept on rising and business seemed strong. On November 2, after the crash, the Society concluded that “the present recession, both for stocks and business, is not the precursor of business depression.” On November 10 it made its notable estimate that “a serious depression like that of 1920-21 is outside the range of probability.” It repeated this judgment of November 23 and on December 21 gave its forcast for the new year: “A depression seems improbable; [we expect] recovery of business next spring, with further improvement in the fall.” On January 18, 1930, the Society said, “there are indications that the severest phase of the recession is over”; on March 1, that “manufacturing activity is now — to judge from past periods of contraction — definitely on the road to recovery”, on March 22, “The outlook continues favorable”; on March 29, that “the outlook is favorable”; on April 19, that “by May or June the spring recovery forecast in our letters of last December and Novemeber should be clearly apparent”; on May 17, that business “will turn for the better this month or next, recover vigorously in the third quarter and end the year at levels substantially above normal”; on May 24 it was suggested that conditions “continue to justify” the forecasts of May 17; on June 21, that “despite existing irregularities” there would soon be improvement; on June 28 it stated that “irregular and conflicting movements of business should soon give way to sustained recovery”; on July 19 it pointed out that “untoward elements have operated to delay recovery but the evidence nonetheless points to substantial improvement”; and on August 30, 1930, the Society stated that “the present depression has about spent its force.” Thereafter the Society became less hopeful. On November 15, 1930, it said: “We are now near the end of the declining phase of the depression.” A year later, on October 31, 1931, it said: “Stabilitization at [present] depression levels is clearly possible.” Even these last forecasts were wildly optimistic. Somewhat later, its reputation for infallibility rather dimmed, the Society was dissolved. Harvard economics professors ceased forecasting the future and again donned their accustomed garb of humility.” (p. 145-46)
It sounds a lot like Alan Greenspan and his “conundrum,” doesn’t it?
During the 1930s, the branch of economics known as “macroeconomics” came into existence, largely through the work of John Maynard Keynes.
His main concept was that the government can control aggregate levels for prices, wages and employment, and thus prevent another Depression. Previously, mainstream economists had maintained that the free market in a laissez-faire economy would stabilize at full employment, an idea that the Great Depression pretty much disproved.
In simplest form, so-called Keynesian macroeconomics works as follows:
- During times of recession, with low inflation and low unemployment, the government can return the economy back to full employment by injecting more money into the economy, in two different ways: (1) Fiscal policy: By reducing taxes, consumers have more money to spend, which keeps manufacting and retail businesses going. (2) Monetary policy: When the Fed lowers interest rates, businesses are able to borrow and invest more money in their businesses, thus providing more employment.
- During times of an overheated economy, with rising prices and labor scarcity, the government raises taxes and raises interest rates, to produce the opposite effect.
Keynes added a level of abstraction to economics, by going from the study of individual prices and wages (microeconomics) to the study of aggregate prices and wages (macroeconomics). In this essay we’re arguing that it’s now time to move to one additional level of abstraction, by adding a “system dynamics” component.
Earlier in this essay I said that macroeconomics policy is always ten years out of date, since it’s based on econometric models that take several years to develop whenever new data comes out and is digested.
That’s certainly true of Keynes’ theories. He noted that during the Great Depression both employment and prices went down, and he developed policies that would raise employment and prices under such circumstances. If it had occurred to him to wonder why the Great Depression occurred just as the people who lived through the Panic of 1857 and the Civil War all disappeared (retired or died), all at once, then he might have developed something different.
And the second of the two points listed above is certainly naïve. To say, “During times of an overheated economy, with rising prices and labor scarcity, the government raises taxes and raises interest rates” ignores the reality of politics.
Development of modern macroeconomic theory – 1970s
The next crisis came in the 1970s, when Keynes’ assumptions fell apart: Both inflation and unemployment rose significantly. Keynes had assumed that disinflation would go along with high unemployment, but now the economy suffered the worst of both worlds. In order to cure high unemployment, Keynes’ theory required lowering taxes and interest, in order to inject new money into the market. But doing that would make inflation even worse.
Somehow we made it through the 1970s, and a series of ad-hoc measures were proposed to patch Keynes’ flawed theory.
When Stephen Roach says (quoted above) that “Modern-day central banking was born out of the Great Inflation of the 1970s,” he’s referring to these ad-hoc measures.
There were some on the fiscal side, especially “supply-side economics,” which geared fiscal policy toward employers rather than employees.
But when Roach refers to “modern-day central banking,” he’s talking about a switch from “Keynesian economics” to “monetarist economics,” the latter developed by Milton Friedman.
Friedman’s theories were based on analysis of decades of economic data, published in his monumental 1963 work, A Monetary History of the United States, co-authored with Anna Schwartz.
Friedman’s work took macroeconomics theory a half-step of abstraction beyond Keynes’ work. He introduced a simple level of System Dynamics by showing that changes in the money supply would affect the level of inflation years in the future in a nonlinear fashion. However, he never took it farther than that and, in particular, never seriously attempted to demonstrate how the resulting changes in inflation later fed back into the money supply, creating a feedback loop.
Still, monetarist policies did effect an important change in central banking policy, first implemented by Paul Volcker after he became Fed Chairman in 1979.
The crucial test occurred in the recession of 1982, at a time when both unemployment and inflation were very high. Keynesian theory dictated a policy of lowering interest rates to cure the unemployment problem. But monetarist policy dictated raising interest rates to cure inflation, even though a recession was on. The monetarist policy worked, and both unemployment and inflation came down. This was a great success for monetarist policy, and cemented its adoption till the present day.
Development of modern macroeconomic theory – 1987-94
The revised macroeconomics theory started falling apart in 1987, when the stock market fell 20% in one day, shortly after Alan Greenspan replaced Volcker as Fed Chairman.
A stock market panic is a problem for both Keynesian and Monetarist macroeconomic theories, and indeed for any static theory, since no static theory can explain why panics occur and when they occur. Once the dynamic component is added to macroeconomic theory, it’s possible to explain the reasons and timing of panics, as we’ll explain below.
In fact, economists commonly explain that the Panic of 1987 occurred because investors were “testing” Greenspan. Of course similar tests were not made of other Fed chairmen, so that explanation is hard to justify. We’ll show that the reason for the Panic of 1987 is entirely different.
The Panic of 1987 didn’t fit into either Keynesian or Monetarist theory, but Greenspan reacted quickly by pouring money into the economy. He particularly targeted vulnerable banks and other financial institutions by providing low cost loans. This would prevent a “domino effect” series of bankruptcies.
Greenspan’s actions worked. The stock market recovered fairly quickly, and Greenspan was hailed as the man that had saved the country from a new 1930s Great Depression.
However, we call the Panic of 1987 a “false panic,” because the stock market was actually underpriced at the time, and so it would have recovered almost as quickly even if Greenspan had done nothing. By contrast, the stock market was overpriced by a factor of more than 200% in 1929, and that’s also the case in 2006.
The Panic of 1987 was a difficult episode, but by the time it was over, economists believed that the major macroeconomic problems had finally been solved. Minor recessions could be resolved through monetary policy, and stock market panics could be resolved through targeted loans. Whew!
Another difficult period occurred in 1994 when inflation began to increase, along with bond yields (interest rates). Alan Greenspan and the Fed took a very tough stand and tightened the money supply, stopping inflation in its tracks, but also causing bond yields to crash. This caught a number of investors by surprise. Remember when Orange County, California, went bankrupt? They blame Greenspan for that.
Morgan Stanley’s Stephen Roach calls this a pivotal moment. “But I do think the 1994 experience was critical in setting the Fed up for the blunders to come,” he wrote. “That was the point when Greenspan became much more of a market-driven central banker — going out of his way to telegraph his intentions in a way that minimized any disruptions to asset prices. In that respect, the bond market crash of 1994 left more scar tissue than the stock market crash of 1987.”
According to Roach, this was the time that Greenspan apparently decided that the problem of managing the economy from the Fed had been solved, as long as he didn’t catch the investment community by surprise. He decided that he knew how to control inflation, and he knew how to continue economic growth, and a repeat of the 1930s Great Depression was no longer even anything to worry about.
The idea was simple: just use a simple formula to control inflation. If prices are rising too quickly (i.e., if the inflation rate is too high), then interest rates should be raised to make it hard for people to get credit, so they’ll purchase fewer things, so prices will moderate. If inflation is low, then do the opposite: lower interest rates to encourage consumers to buy on credit, creating demand for products, raising prices. (The formula has become known as Taylor’s Rule, although the Fed claims it does not use that precise formula.)
Roach blames our current troubles on this new 1994 policy and, as much as I like Roach, this view comes out of the “static” view of macroeconomics that he shares with other mainstream economists. I’m surprised that he believes that our troubles began in 1994, when it’s obvious that macroeconomics has gotten just about everything wrong for decades.
Development of modern macroeconomic theory – since 1995
The stock market bubble began in 1995, and was fully apparent by December 1996, when Alan Greenspan used the term “irrational exuberance” in a speech that was otherwise completely obscure.
The politicians were completely surprised as well, since stock market bubble generated enormous tax revenues.
At the beginning of 1996, President Clinton gave his State of the Union speech, saying that “The era of big government is over.” His speech was very heavy with demands that the budget deficit be cured. “Since 1993, we have all begun to see the benefits of deficit reduction. … Now, it is time to finish the job and balance the budget.”
There would be cuts in many programs, and the welfare entitlement would be removed. “I challenge this Congress to send me a bipartisan welfare reform bill that will really move people from welfare to work and do the right thing by our children. I will sign it immediately.”
Well, everyone was pretty shocked by what happened next. Tax revenues started pouring into the treasury, and soon it was clear that there would be a budget surplus. Aren’t stock market bubbles wonderful? Tax revenues started collapsing in the year 2000, the last year of the Clinton administration and, once again, no one had expected it or had any idea why it happened.
Once again, mainstream macroeconomic theory was a total failure. There was no explanation of why the bubble suddenly began, or why it began at that time, or why it ended. It was a total mystery to everyone. It just happened, and no one could do anything about it.
Greenspan, it turns out, came up with his own explanation, though it was rather fantastical. We learned about it from a November 2004 article in the Wall Street Journal.
- “Like many economists, Mr. Greenspan had long wondered why the spread of computers in the 1970s and 1980s hadn’t boosted productivity, or output per hour of work. He was taken with the argument of economic historian Paul David, who noted that electricity didn’t boost productivity for decades until working patterns adjusted. Mr. David suggested the same lag applied to computers.Mr. Greenspan now saw surging orders for high-tech equipment since 1993 — coupled with higher profits at the companies that bought the equipment — as evidence the productivity payoff had arrived. If this effect was real, it meant economists were underestimating how fast the economy could grow before inflation reared its head. Companies could produce more without incurring the cost of hiring fresh labor.
Mr. Greenspan disagreed and told the committee he wanted to hold rates firm. An important reason, he argued, was that the government’s productivity data were wrong. According to an analysis he commissioned from two Fed economists, productivity since 1990 in many services industries such as health care must have declined if the government’s numbers were accurate.
This “makes no sense,” Mr. Greenspan told the meeting. “The tremendous contraction in productivity, which all of our data show, is partially phony.” Instead, he pointed to other government reports showing that companies were recording ever-wider profit margins without raising prices, a sure sign of productivity gains. “Productivity is indeed rising a lot faster than our statistics indicate.”
Many committee members remained skeptical….”
This is a truly remarkable account because Greenspan was so wrong. He was puzzled because the bubble was occurring, since his macroeconomic models had no explanation for it. So he made up an explanation of his own, and got two interns to gin up a report supporting his explanation.
Anyone who was in the computer industry in the 1990s, as I was, knows that this is about the dumbest thing imaginable. At that time, IT (information techology) was a monetary black hole. Computer software and system development projects TYPICALLY were a year or two late — except for the ones that failed completely. There was NO WAY that computer technology was improving corporate productivity AT ALL.
(Incidentally, IT did finally start improving corporate productivity in the early 2000s, after corporations simply stopped developing new systems, and made do with what they had.)
Greenspan and the Fed decided to do nothing about the bubble. They decided that they would let the bubble grow unfettered by monetary policy, and that they would deal with any subsequent crash by standard methods — inject money into the economy by lowering interest rates.
So do you get this? The bubble was a complete surprise to everyone. Macroeconomic theory provided no explanation for it. No one had any idea what caused it. But even though they had absolutely no idea what caused it, they decided that the DID know how to cure the consequences. In other words, macroeconomic theory had failed every test so far, so they were sure it would pass the next test. It’s like flipping a coin ten times, and it comes up tails every time, so you know that it has to come up heads the next time, doesn’t it. Some people never learn, do they?
How could Greenspan and the Fed committee members possibly believe that they could manage the aftermath of the crash? The answer is the false panic of 1987 which we described above. Greenspan injected money into the marketplace and the stock market recovered fairly quickly. In the late 1990s, Greenspan decided that the same thing would work again when the bubble burst.
But the situation in the late 1990s was VERY different from the situation in 1987, as shown by the adjoining graph. In 1987, P/E ratios were at historical averages, having been below average for twenty years. This meant that stocks were underpriced and were poised to climb, irrespective of any reasonable monetary policy.
But in the late 1990s, P/E ratios were above 20 and climbing — well into the danger zone reached during the bubble of the 1920s that preceded the Great Depression. It was almost mathematically certain that a crash of the 1990s bubble would not be as benign as the false panic of 1987.
After the Nasdaq crash of 2000, Greenspan put his near-zero interest plan into effect. As late as January, 2004, Greenspan believed that his plan had been completely successful. Here’s what he said in a speech by Greenspan at that time:
- “During 2001, in the aftermath of the bursting of the bubble and the acts of terrorism in September 2001, the federal funds rate was lowered 4-3/4 percentage points. Subsequently, another 75 basis points were pared, bringing the rate by June 2003 to its current 1 percent, the lowest level in 45 years. We were able to be unusually aggressive in the initial stages of the recession of 2001 because both inflation and inflation expectations were low and stable. We thought we needed to be, and could be, forceful in 2002 and 2003 as well because, with demand weak, inflation risks had become two-sided for the first time in forty years.There appears to be enough evidence, at least tentatively, to conclude that our strategy of addressing the bubble’s consequences rather than the bubble itself has been successful. Despite the stock market plunge, terrorist attacks, corporate scandals, and wars in Afghanistan and Iraq, we experienced an exceptionally mild recession–even milder than that of a decade earlier. As I discuss later, much of the ability of the U.S. economy to absorb these sequences of shocks resulted from notably improved structural flexibility. But highly aggressive monetary ease was doubtless also a significant contributor to stability.”
The posted text of the speech contains the following footnote to the last paragraph:
- “Some have argued that, as a consequence of the 1995-2000 speculative episode, long-term imbalances remain, having been only partly addressed since early 2001, the peak of the post-bubble business cycle. For example, large residues of household and external debt are perceived as barriers to future growth. But in the past, imbalances that led to business contractions were rarely fully reversed before the subsequent economic upturn began. Presumably they were fully reversed in later periods, or they continued to fester, but not by enough to halt economic growth.Even if imbalances still persist in our current environment, the business decline that began in March 2001 came to an end in November of that year, according to the National Bureau of Economic Research. We experienced tepid recovery until the second half of last year, when GDP accelerated considerably. Hence, when the next recession arrives, as it inevitably will, it will be a stretch to attribute it to speculative imbalances of many years earlier.”
It’s hard for me to understand how Greenspan could have been so optimistic at this time. Macroeconomic theory was competely useless (as usual), and had been since the bubble started. With interest rates close to zero for three years, inflation should have been very high and unemployment should have fallen sharply. Instead, inflation remained near zero, and unemployment remained stubbornly high. Instead, the opposite happened. If you check analysts’ predictions throughout 2003 and 2004, you’ll find that they were confounded month after month about the high unemployment. I recall one TV economist pundit saying at one point, “I just don’t understand it. With interest rates this low, unemployment has GOT to start coming down some time.”
So when Greenspan said in January 2004 that “our strategy … was successful,” he was just guessing. He had no theoretical reason for that conclusion, since theory was useless. From his point of view as Fed Chairman, things felt good to him, and he said so.
After that, things started getting worse. True, unemployment was showing signs of improvement by 2005, and inflation was showing signs of rising, but the changes were much lower than macroeconomic theory predicted.
Other signs became increasingly ominous, violating macroeconomic theory. The trade deficit kept growing exponentially, even though theory said that the dollar should devalue and the trade deficit should be leveling off. Public debt kept growing exponentially, even though theory said it should be leveling off. The real estate bubble was accelerating, even though no one had expected it. And later the commodities bubble accelerated in the same way.
Alan Greenspan’s speeches after early 2004 started expressing an increasing level of alarm. In October, 2004, he said: “The persistently elevated bankruptcy rate remains a concern….”
In January, 2005, he said: “The dramatic advances over the past decade in virtually all measures of globalisation have resulted in an international economic environment with little relevant historical precedent.”
This was his first public admission, as far as I know. that macroeconomic theory had been a complete failure for over a decade. In fact, this statement was an almost complete repudiation of his own monetary stimulation policy for the preceding decade. This was also the time of Greenspan’s widely reported “conundrum” remark, referring to the puzzling worldwide fall in long-term bond rates, for which neither he nor any other economist had any explanation.
His remarks became increasingly alarming throughout 2005. In September, he privately told France’s Finance Minister that “the United States has lost control of their budget.”
The most alarming of all was Greenspan’s “swan song” speech as Fed chairman. He warned about the stock market and housing bubbles and said:
- “To some extent, those higher [stock market and housing] values may be reflecting the increased flexibility and resilience of our economy. But what [investors] perceive as newly abundant liquidity can readily disappear. Any onset of increased investor caution elevates risk premiums and, as a consequence, lowers asset values and promotes the liquidation of the debt that supported higher asset prices. This is the reason that history has not dealt kindly with the aftermath of protracted periods of low risk premiums.”
When Greenspan says that “history has not dealt kindly,” he’s referring to the 1930s Depression, and he’s telling us that he thinks it could happen again. As Fed Chairman, Greenspan could not predict a depression because it would immediately cause a worldwide panic; but he went as far as he could go in predicting that a new depression was coming.
Morgan Stanley’s Stephen Roach blames our current troubles on Alan Greenspan, and in particular his rigid application of monetary theory following the 1994 incident described above:
- “[The] road to price stability has been more perilous than the authorities envisioned. By ushering in an era of single-digit returns on financial assets at precisely the point when the demographic imperatives of retirement planning require higher returns, the resulting asset-liability mismatch has forced investors much further out on the risk curve than might otherwise have been the case.That tendency was exacerbated by two additional developments – an unusually cheap cost of “carry” (i.e., short-term funding costs) set by overly-accommodative central banks and a growing tendency toward herding by momentum-driven investors.”
It’s interesting that Roach mentions the “demographic imperatives of retirement planning.” He’s referring, of course, that the post-war Baby Boomer generation is about to enter the age of retirement. This is a tiny example, and the only one I know of, where economists ever relate anything that’s happening today to things that happened decades ago. Now if it had only occurred to him to extend his gaze two decades more, and create a feedback loop, he would have had a Systems Dynamics explanation of why we’re having our current problems.
In the same article, written in May, Roach provides a description of our current problems, along with a laundry list of current bubbles:
- “This has resulted in the now-infamous multi-bubble syndrome, as yield-hungry investors have swarmed into one high-yielding asset after another.First equities, then bonds, then spread products (emerging market and credit instruments), then property, and most recently commodities – the excesses of the super-liquidity cycle have created bubble after bubble. The tight correlation of bubble-like blow-offs in a broad array of risky assets may well be the ultimate manifestation of this liquidity-driven mania.
By its very nature, the concept of the bubble lulls investors into a false sense of security. It’s an image that conjures up the proverbial “prick of the pin” that then leads to an abrupt and worrisome deflation of a market that has gone to excess. Absent the “pin” – normally thought to be an interest rate spike – investors have no fear of bubbles.
Yet, this imagery is actually quite misleading. Yale Professor Robert Shiller has long stressed the tendency of asset bubbles to implode under their own weight (see Irrational Exuberance, second edition, 2005). In other words, it doesn’t always take that unpredictable “bolt from the blue” to send overvalued assets crashing back down to earth.”
That’s quite a laundry list of bubbles. Roach doesn’t bother to mention that the stock market is also overpriced by a factor of more than 200%. I don’t know whether this is because he doesn’t know, or whether he just doesn’t want to say.
Today, the real estate and commodities bubbles appear to be bursting, while the stock market bubble appears to be growing. There’s no way to predict exactly when a full scale panic will take place, but history tells us that it will happen, with 100% certainty. The current situation is deteriorating rapidly around the edges, and the center won’t hold forever.
The most certain thing is this: Mainstream macroeconomics theory tells you nothing, and economists have no idea what’s going to happen.
System Dynamics and Macroeconomics
Earlier in this essay we quoted Professor John Sterman, director of the MIT System Dynamics Group, as saying: “Thoughtful leaders increasingly recognize that we are not only failing to solve the persistent problems we face, but are in fact causing them. System dynamics is designed to help avoid such policy resistance and identify high-leverage policies for sustained improvement.”
As we’ve shown, macroeconomic theory has been wrong time after time, and has caused enormous actual damage by misleading policy makers into taking certain actions.
Economics theory took a major leap as a result of the Great Depression, when John Maynard Keynes took the study of individual transactions (microeconomics) to aggregate transactions (macroeconomics). Economists would not have made that leap without a major financial crisis, and once the crisis occurred, they had to make the leap.
Now, as a new worldwide financial crisis approaches, it’s not too early to start thinking about the next major leap.
And actually, System Dynamics is really the only logical possibility. Macroeconomic models must be upgraded to replace static computations with dynamics ones.
Let me give some examples of how this will work (in some cases, repeating an example previously given):
- Relating birth and death generations. Economists do this all the time with one specific case: How the large “Baby Boomer” generation, born after WW II, is now retiring, creating major problems for the economy. This is a simple but powerful example of a System Dynamics application, where you relate the inward flow (birth) of a population group to the outward flow (retirement / death) of the same population group, 50 years later.Now if economists can do that, then then can go back an additional 15-20 years to the generation of people born during the Great Depression. What happened when those people retired? Why, the 1990s stock market bubble happened.
That was easy, wasn’t it?
- The savings rate. We gave a lengthy example earlier in this essay of the difference between the dynamic and static views of savings rate figutes. It’s similar to the retirement example just described.The erroneous statement that most economists say is this: “Old people today save less than old people in the 1960s.” This is the static view. It provides misleading information and implies incorrect policy.
The statement “Old people today save almost exactly the same amount as they saved in the 1960s when they were young people” is the dynamic statement, and a more accurate and productive way of looking at it.
Understanding this will remove a major source of uncertainty in economic forecasts. As things stand now, economists can’t be sure what the average savings rate will be ten years from now, because they have no way to compare, say, today’s 40-50 year olds to 40-50 year olds in ten years. But if they change their models to recognize that today’s 30-40 year olds will be exactly the same people as the 40-50 year olds in ten years, then they can provide more accurate results.
- Trade deficit. The trade deficit has been increasing exponentially for years. According to macroeconomic theory, the trade deficit should have leveled off long ago.In the past five years, we’ve seen a massive outflowing of jobs to other countries — manufacturing jobs to China and other countries, service jobs to India and other countries. Why has this happened?
Just as there was a “Baby Boom” following World War II, there was a “Baby Business Boom” during and after the Great Depression.
Most existing businesses were destroyed during the Great Depression, and new businesses had to be formed. Even old businesses that had survived often became so stripped down that they were essentially new businesses.
Mainstream macroeconomics theory assumes that old businesses die and new businesses are created at fairly constant rates. But in fact that’s not true. There’s a huge “bulge” of businesses that were created during the Great Depression, and mainstream macroeconomics doesn’t deal with that in any way.
Human beings retire around age 65, but there’s no similar “retirement age” for a business. Nonetheless, businesses do get old. As they get old, they become more bureaucratic and inefficient, less willing to take risk for fear of “rocking the boat.”
Just as the Baby Boomers are retiring about now, the “Baby Business Boomers” — businesses that were formed during and just after the Great Depression — have become so inefficient that they can no longer survive. That’s why jobs have fled to other countries, and why the trade deficit continues to grow exponentially.
And the reason that inflation has remained so despite many years of near-zero interest rates is that the products and services provided by these aging, inefficient companies aren’t of great interest to consumers, thus forcing down demand and prices.
During the 1970s, by contrast, these businesses were all at their peak of productivity and innovation, with exciting products that were in high demand. That’s why prices and inflation rose.
This dynamic cycle has been entirely invisible to macroeconomic theory because it has a static view of the growth of businesses. A System Dynamics view would recognize that a business formed in the 1950s has highly different characteristics than one formed in the 1930s or 1970s, and would model these businesses through the decades in the same way that generations of people should be modeled.
In terms of Systems Dynamics stocks and flows, these examples illustrate two different kinds:
- Stocks of investors. Inward flows: Births. Outward flows: Deaths or retirements.
- Stocks of businesses. Inward flows: Creation of business. Outward flows: Business becomes inefficient, bankrupt.
The “False Panic” of 1987
As we’ve described, the panic of 1987 has played a pivotal role in the recent history of the Fed and of development of mainstream macroeconomic theory. It was the Panic of 1987 that convinced the Fed, and the investor community in general, that there’s no longer any danger whatsoever of a repeat of the 1930s Great Depression, since panic can be treated quickly and painlessly by releasing large amounts of money into the economy, especially to financial institutions.
The panic of 1987 is an example of a false panic, and it played a pivotal role in permitting the situation we’re in today. It occurred at a time (unlike today) when the stock market was underpriced, and so there was no rational “need” for a panic.
But why did the Panic of 1987 occur at precisely that time?
The answer appears to be because 1987 is 58 years after the stock market crash of 1929. Anyone who remembered the 1929 crash had to be 62 years or older. (Paragraph corrected on 22-Oct-2007)
Thus, the 1987 panic appears to have occurred at the time of a significant generational change. Whatever latent fears that still existed about a recurrence of the 1929 panic were focused on this moment, as those who remembered the 1929 were quickly disappearing, and were replaced by those who didn’t personally remember it.
Admittedly, a lot more research has to be done to understand this phenomenon, but there are many other similar examples. Here are two:
- In 1976, the public became hysterical over a possible “swine flu” pandemic. Responding to public demands, the government prepared millions of doses of swine flu vaccine. The pandemic amounted to nothing, and the whole thing was a political fiasco.This was a false panic that occurred exactly 58 years after the Spanish Flu epidemic of 1918. It appears to be the same kind of thing as the false panic on Wall Street in 1987. Up to that point, people were afraid of a recurrence of the 1918 epidemic. The 1976 panic was a political fiasco that reversed the public mood, and left the public with no further fear of a flu epidemic. That’s why the public today has no fear of a bird flu pandemic.
- After the Bolshevik Revolution of 1917, there was a widespread fear of a Communist attack in the United States. The “Red Scare” was precipitated by various socialist and anarchist groups who set off bombs and threatened revolution and a new civil war. In 1919, Attorney General Alexander Mitchell Palmer, who had personally almost been killed by a terrorist bomb, initiated the Palmer Raids, in which hundreds of known or suspected communists were jailed. The threat of communist rebellion and civil war amounted to nothing, and the whole thing was a political fiasco.This was a false panic that occurred exactly 59 years after the beginning of the American Civil War, during which President Abraham Lincoln suspended the right of habeas corpus, resulting in the jailing, without charges, of numerous known or suspected Southern sympathizers.
This sudden fear of a new civil war was a “false panic,” similar to the 1987 and 1976 false panics. After it was over, Americans stopped worrying about a new civil war.(Updated 27-Oct)
These three examples can be characterized in the same way: A public disaster occurs, and 58 (or so) years later, the public experiences a “false panic” that the same disaster is occurring again. 58 years later is approximately the retirement time of the youngest people who would have personal memory of the disaster.
These three examples do not prove the existence of such a relationship. On the other hand, they provide evidence of such a relationship, and hint at a more frequent and possibly more subtle relationship between “non-disastrous” political events and their effects 55-60 years later.
At the very least, macroeconomic theorists incorporating System Dynamics into their models should test for the other occurrences of this kind of relationship.
Apparently 58 years is the most frequent point where one generation passes the baton to the next generation, and it’s exactly at that point that the wisdom of the older generations is lost, and has to be relearned by younger generations the hard way. This needs further research, especially to determine whether the same 58 years applies to other countries and other times in history.
System Dynamics and Generational Dynamics
Generational Dynamics is not System Dynamics. Generational Dynamics is a subset of System Dynamics or perhaps an application of System Dynamics. Generational Dynamics is the case of System Dynamics when the stocks are of people or businesses and the flows are of births and deaths or retirements.
All the examples described in this essay have been incorporated into Generational Dynamics. However, Generational Dynamics is originally based on the work of historians William Strauss and Neil Howe in the 1980s and early 1990s on generational changes in Anglo-American history. They developed their work by studying hundreds of histories and diaries through Anglo-American history dating back to the 1400s. Their work is documented in two books, Generations: The History of America’s Future, 1584 to 2069 and The Fourth Turning: An American Prophecy.
It’s not the purpose of this essay to attempt to describe how Generational Analysis is used in the analysis of history and current events. This web site http://www.GenerationalDynamics.com has hundreds of articles on different aspects of that subject.
Here, we only wish to focus on one thing, a summary of how generational flow creates a feedback loop, generating historical cycles. There’s a similar feedback loop in macroeconomics, but more research is needed to show whether the macroeconomic feedback loop is identical to the historical feedback loop.
The historical feedback loop is illustrated by the following “diagonal flow” diagram:
The feedback loop is initially launched by a special kind of war called a “crisis war.” These are the worst, most genocidal kinds of wars, when the value of an individual human life becomes so close to zero that almost any means is used to win the war. America has had two such wars since the nation’s founding: The Civil War, in which Northern General Sherman marched through the South, and conducted the world’s first “scorched earth” war campaign, burning all buildings and crops to the ground; and World War II, in which we firebombed Dresden and Tokyo, killing millions of civilians, and dropped nuclear weapons on two other Japanese cities. (I’m not blaming America for this, only stating that it occurred.)
The Crisis Era launches three following “eras,” each approximately 20 years long — Austerity/High, Awakening and Unraveling. There are four generations of people, designated as Heroes, Artists, Prophets and Nomads, according to the generation in which they’re born. Strauss and Howe showed, through study of contemporary diaries and histories of six centuries of Anglo-American history, that people of different generational archetypes are quite dissimilar, but that people in the same archetype, even when they lived centuries apart, are remarkably similar in attitudes towards everything from gender issues to political activism to war.
Briefly, the feedback loop works as follows: the survivors of the crisis war (Civil War, WW II) are so traumatized that they spend the rest of their lives making sure that nothing like that ever happens again. During the period that follows the crisis war, they implement austere rules to guarantee that result. This period is an “Austerity era” to the survivors of the war, but it’s a “High era” to those born after the war, the Prophet generation (our Baby Boomer generation), who have no personal memory of the war, and who rebel against the austere rules. This results in a political conflict and a “generation gap” in the Awakening Era (our 1960s-70s), leading to an Unraveling Era (our 1980s-90s), during which all the austere rules completely unravel. After that, the Prophet generation leads the society into a new crisis war.
With minor changes, it should be possible to adapt this System Dynamics model to macroeconomics. The “crisis war” concept is replaced by an “international financial crisis.” Just as there can be wars that aren’t crisis wars, there are also “panics” and “recessions” that aren’t major financial crises.
The major financial crises since the 1600s have been identified as follows: Tulipomania bubble (1637), South Sea Bubble (1721), French Monarchy bankruptcy (1789), Hamburg Crisis of 1857 (Panic of 1857), and 1929 Wall Street crash.
Each major financial crisis occurred approximately 70 years after the last one — at exactly the point where the people with personal memory of the previous crisis all disappeared (retired or died), all at once.
However, this is a very broad statement, lacking all the detail of the historical feedback loop shown above. A new feedback loop for financial dynamics needs to be developed.
Important. Every researcher I’ve seen who’s tried to discern historical patterns makes the same fundamental errors. Please note the following very important points:
- A generational cycle for historical and social applications is LOCAL. Different countries can have very different timelines, depending on historical development.
- A generational cycle for international financial crises is GLOBAL. That means that all countries have these financial crises at the same time.
- There may be other non-generational cycles, local or global, related to everything from technology to the weather. However, these are SEPARATE data series, completely INDEPENDENT of the generational cycles. I’ve seen one researcher after another make the mistake of combining these independent data series into a single series, resulting in findings that are gibberish.
To illustrate what all this means, the following graph summarizes some of the findings of Generational Dynamics, not all of which have been proven:
The above graph contains several elements:
- The S&P Index curve. The squiggly line is the S&P 500 index, adjusted for inflation, graphed on a logarithmic scale.
- The two bubbles, the 1920s bubble and the 1990s bubble, are highlighted on this graph. Notice how their peaks are substantially out of line with the rest of the S&P 500 index graph.
- The exponential growth trend line is the black straight line. Over the long run, stock prices will oscillate around this line.
- The technology smoothing curve. The smooth wavy line is a smoothing of the squiggly price index line, but IGNORING the two bubbles and their immediate aftermaths. We make no claim that it’s a sine wave or has any recognizable formula, though it could be a typical “moving average” graph. What’s important is that in non-bubble times, the squiggly price index line follows a fairly smooth oscillating curve, not varying by more than 20% from the moving average. (This is the Kondratiev cycle or K-cycle.)
A lot more research needs to go into this, but I want to emphasize the following: When you compute the smoothing curve (K-cycle), you MUST subtract out the generational bubbles from the S&P index. The smoothing curve and the generational bubbles are TOTALLY INDEPENDENT data series, and must be considered separately. Every researcher I’ve seen mashes these two data series together, and the results they get are gibberish.
Other work on “Dynamic Macroeconomics”
The term “Dynamic Macroeconomics” is already being used by economists to describe a subset of what we’re proposing. The components of this form of Dynamic Macroeconomics are as follows:
- The population consists of multiple generations, with behavioral differences. For example, an older generation has a higher savings rate than a younger generation.
- Generations overlap with one another. (This is called the “Overlapping Generations Model,” or OLG.) This means that an older generation may have some behaviors in common with a younger generation with which it overlaps.
- The generations are homogeneous. This means that a generation ages, but it has the same behaviors as the same-aged generation from any time in the past.
Thus, for example, this form of Dynamic Macroeconomics would not even recognize the uniqueness (in terms of size) of the Baby Boomer generation, and the problems it will create when it retires; in this model, the Baby Boomer generation is like Generation-X and every other generation. This means that this model contains no feedback loops, and so does not use the full power of System Dynamics.
I don’t wish to imply that this model has little value. A lot of work has been done on OLGs, and this work can be adapted to serve the purposes of the full Dynamic Macroeconomics theory that this article is describing.
As I write this, the stock market is above Dow 12120, and appears to be skyrocketing upward without limit. If, as expected, the puncturing of the stock market bubble leads to a major financial crisis, then economists will be forced to reevaluate macroeconomic theory from its roots, just as a similar reevaluation was necessary after the financial crisis of the 1930s.
At that time, economic theory took a major “conceptual leap” by going from the study of individual transactions to the study of economic aggregates.
This paper makes the case that the next “conceptual leap” is to a “Dynamic Macroeconomics,” a theory that uses System Dynamics. In fact, this particular conceptual leap is the only one that makes sense.
Today’s mainstream macroeconomic theory is completely reactive. If I could paraphrase what I think most economists believe, it would be this: “There are always going to be recessions, inflation and bubbles, for reasons we don’t understand. It’s just what happens. It’s the way things are. Macroeconomic theory gives us the tools for repairing problems once they’ve occurred.”
What we’ve shown in this paper is that Dynamic Macroeconomics allows policymakers to be more pro-active, by anticipating such things as recessions, inflation and bubbles. We’re already doing that today in one particular case, where we attempt to react in advance to the retirement of the people in the huge Baby Boomer generation.
The adoption of Dynamic Macroeconomics will increase the predictive abilities of federal government planners. Undoubtedly it will expose other problems that will have to be solved, but the adoption of Dynamic Macroeconomics will first help us understand a lot more about what’s going on in today’s national and global economy and what, if anything, we can do about it.
Copyright © 2002-2008 by John J. Xenakis. Home colors fonts Slides