Can economists predict the future?

[Interventionists] are pleased to think that by proceeding experimentally and therefore “scientifically” they will succeed in fitting together in piecemeal fashion a desirable order by choosing for each particular desired result what science shows them to be the most appropriate means of achieving it. This “realistic” view which has now dominated politics for so long has hardly produced the results which its advocates desired. “ – F. A. Hayek  1973

When you look at a complex economy like that of the United States it can be pretty confusing. Prices, interest rates, investment, savings, Gross Domestic Product. government deficits, taxes, foreign trade. What influences what? Which are the causes, and which are the effects?  What is going to happen next year? In search of simple answers, many economists have turned to a concept which they call Aggregate Supply and Demand — something that rolls all of the above into a couple of curves on a graph which promises to make everything clear:


In this diagram, the AD line is supposed to show total demand for products in the economy. The AS line shows the supply of those same products. The equilibrium point, e points to a spot where the economy has come to rest below full employment: some workers are unemployed, and some factories operating at less than capacity.

Economists developed these AD-AS diagrams to solve a crisis in Keynesian economics. In the 1970′s economists relied on the Phillips Curve which was intended to show an inverse relationship between price inflation and unemployment. If prices rose, unemployment was supposed to go down. If they fell, unemployment was supposed to go up. But as the 1970′s and 1980′s unfolded, they found that the Phillips Curve didn’t exist.

 

The energy crisis (rising oil prices) and government inflation of the currency combined to put a lot of people out of work while prices zoomed. It wasn’t supposed to happen that way.

One reason the situation took many economists by surprise was that, following Keynesian principles, they ignored the supply side of the economy. Businessmen were supposed to continue to turn out products, regardless of what happened. The real issue to these economists was, whether consumers spent their money on goods, or saved it. If money was spent, goods would be purchased, and employment (workers working to produce the goods) would go up.

When prices rose at the same time that unemployment grew, and this kept happening year after year in the 1970′s, many economists went back to the drawing board and produced aggregate supply and aggregate demand diagrams to explain the situation. The curves were supposed to be derived from aggregate analysis of the economy: from collecting reams of statistics on price changes and movements from players in the market, and objectively constructing aggregate supply and demand curves based on real objective facts.

It is a nice theory, but it does not work out in practice. These lines are not descriptions of the economy as it is, in practice, but completely unreal accumulations of unrelated statistics.

The AD line is somehow supposed to combine consumer demand, business demand, exports, and government demand for goods and services. The AS line contains all the sources of the goods and services such as production of consumer goods, investment goods, intermediate goods, and imported goods. The two lines together are supposed to tell us what is happening, or going to happen in the economy. Unfortunately, such diagrams are very misleading and almost useless in practice, for a number of reasons:

Aggregate demand is not an independent force or variable in the economy. You cannot add together the demand for Florida oranges, the demand for apartments in Milwaukee, and the demand for bus service in Alaska and get any number that makes any sense. There may be a strong demand for bus transportation in Alaska for reasons that are purely local. They certainly have nothing to do with the new rent control ordinance in Milwaukee, nor the book that was just published saying that orange juice prevents cancer. Yet these things are vital to understanding the demand for particular products in each of these areas.

Aggregate supply is also made up of thousands of unrelated facts which cannot be added together. A new company has just installed a call management center in Boise which promises to make Idaho a major supplier of nationwide telemarketing services. The XYZ clothing chain, with 300 stores nationwide just went bankrupt, closing all of its stores. Nissan just opened a new assembly plant in the South which is capable of turning out a thousand cars a day.  How can you add these up into a meaningful statistic or curve?

The answer, of course, is that you cannot add these things up. If you do, you will get gibberish, not economics.

So what is the answer to understanding our complex economy? How can we get some aggregate measures that will help to determine what is happening and likely to happen?

Back to Basics

To understand aggregate diagrams we have to understand why they were constructed in the first place. For the last one hundred years, many economists, politicians, and government officials have been fascinated with the workings of the economy, particularly the distribution of goods and services. They want to learn how the economy works — and then to tinker with it to make it work better, or at least to make it produce some desired outcome such as full employment, more tax revenue, lower prices, economic growth, or income redistribution.  They are looking for a “scientific” way of explaining what is happening, and therefore controlling and directing it. As soon as they try to get a handle on it, they run up against the knowledge problem.

What is knowledge about economic facts? Can we collect information scientifically as physicists and chemists would? Information in economics is about the actions of people. If you study what people are doing in the world, they are all reacting to local situations. They go to work, meet with their bosses and co-workers, and proceed to conduct joint operations producing goods and services to please their customers, in competition with other companies which are trying to do the same.

Accountants in Memphis can prepare an individual’s tax return for $200 and make a profit. Accountants in New York charge $600 for the same service, and struggle to get by. Both can continue to operate in this way, without knowing about or interfering with eachother, until the Memphis firm decides to open a branch in New York. They meet with customers in New York, and process the returns in Memphis. They can price their New York returns at $500 which gives them a good profit, and begins to steal customers from the New York firm.

When the New York firm discovers the $500 price, they are shocked, angered, and worried. They cannot compete. They have to come up with some radical solution, or they will soon be out of business.

Is this an unusual situation? No. It is the normal operation of the market. It is happening every day. It is why aggregate supply and demand analysis is not only difficult, it is impossible.

Aggregate computation assumes that there are some facts that can be added together to get the aggregate. But what facts can these possibly be?  We have three prices for an identical tax return: $200, $500, and $600. To an aggregate economic statistician, they are three numbers. But to the participants, they are terribly important vital facts with great meaning.

Inside the New York firm there is intense activity and planning. Can they shift operations to Nebraska where wage rates are lower? How much will an office cost in Nebraska? Can they find capable workers and train them there? Should they drop their prices to $500 and take a loss for a year to keep their customers while they get the Nebraska operation going? Is there some other way to cut costs?

Much of what is going on in the minds of the New York firm is subjective understanding rather than objective facts. To you or I a number like $500 is just a number. To the New York firm it is has a sound of a doomsday bell. They know what it means. It means that they are finished unless they can meet this price. The accountants in New York know what it takes to produce a tax return. They know the cost of rent, of computers, of advertising, of management, of programmers, of tax counselors.

Aggregate analysts in Washington or Boston can collect numbers like the price of tax preparation in various cities, but they cannot make any sense out of them. They cannot relate them to any specific situation, like keeping the New York firm from going under. In other words, to know anything in economics, you have to not only know facts, you have to know what the facts mean in thousands of particular situations.

Insect Colonies

The market can be compared to a giant insect colony. In such colonies, the insects are divided into workers who forage for food, soldiers who fight off invaders, nurses that care for the young, carpenters who build the nests — and many other categories. As each ant, termite or bee passes the others in the hive, they exchange signals by passing chemicals called pheromones from mouth to mouth. These signals tell a worker, for example, that he should stop work, and go to fight an external invader. He, in turn, passes on slightly modified signals to the hundreds that he meets in the hive which indicate to others that vital work was stopped, and someone must be sent to replace the worker.

None of these ants knows the overall situation: what is happening in the colony, and why his instructions have been changed. He is just reacting to the situation as he sees it, and passing on to others his modified view of the world. In total, therefore, the insect colony acts like a massive intelligence: caring for babies, keeping the temperature of the nest regulated, determining how many cells are to be constructed, and where they are to be located. Yet the individual ant or termite, alone, knows none of these things, and can accomplish very little without contact with the others.

In the market we are doing similar things. Each individual person is carrying out specific tasks as a member of some unit in the structure of production. The person meets others in his company — and in the outside world — and exchanges information. It may be helpful information or it may be hostile: a lower bid on a job which steals the rival’s customer. In turn, each person receiving information evaluates it, modifies his behavior, and passes on the modified information to others that he meets.

Much of the information passed around by people in the market is in the form of prices, rather than pheromones. Entrepreneurs rely on these prices, and other data, which result from independent decisions being made simultaneously by other entrepreneurs elsewhere in the system to make choices about what to do, what to supply to the market, what processes to use.

Many aggregate analysts, to compile their aggregates, assume that the individuals in the market are merely price takers who have no influence over prices, but simply learn them, and then react passively. The analysts learn that $600 is what it costs to produce a tax return in New York. They learn, and write down the possible production processes for a tax return. Production processes say that to achieve a given output, for example, you need 10A, 5B and 2C. You can also make the same output with 5A, 5B and 5C. You make your choice by learning the current price of A, B, and C. From these consumer prices, plus production functions, aggregate analysts believe that they can derive factor prices: what rent, labor, delivery services, software and other factors cost in New York.

But factor prices in the real world cannot be derived from consumer prices, since the set of specific production processes from which choices are to be made are not given, but are constantly in flux: they are what the whole market process is designed to work out. Factor prices can be derived from consumer goods prices only if factors (tax counselors, programmers, managers) are perfect substitutes for one another and are perfectly specific. Since these conditions do not apply in the real world, no producer can know in advance of his participation in competition whether his production technique is economically adequate.

The New York tax firm’s production technique was economically adequate yesterday, but it is no good today. Today, different processes must be used to survive, and participants are struggling to find out what those processes should be.

Types of Facts

No one has the big picture, but in total, the market is able to put together the products and services needed so that every customer in New York City can find the things that he wants to eat, wear, or use in his home or business, every business day (and weekends too!).

There are thus too kinds of facts: objective data, and subjective interpretation of data.

 

Objective fact: completing a tax return takes four hours of data gathering at $27 per hour and 38 hours of analysis and processing at $13 per hour.

Subjective interpretations: Joanne is sick this week, and Patty is too new to meet with customers. Bob will have to stop work on the new software, and take over Joanne’s work. We will hire a temporary to do Bob’s work this week.

The objective facts, which an aggregate planner can obtain, are only the visible tip of the iceburg of information in the market. They represent what we can say objectively and store in our computer. But the sort of knowledge necessary for real understanding of these facts as they apply in the thousands of individual situations in which they are being applied every day lie buried deep in the minds of millions of people.

Objective facts and posted prices have meaning only when used by millions of individual actors in the market. A price is not just a number. It is an indicator of the relative scarcity of some particular good or service whose qualities are hard to describe.

The driving force of market activity is the competitive groping for profit opportunities in which the best methods can be learned by applying the prices of things to the individual’s interpretation of the meaning of the prices.

The present, the future and the pursuit of dreams

An aggregate planner can only gather data about the past. The prices and quantities that he stores in his computer are about transactions that took place yesterday, or last week. He assumes that there are some scientific laws to which the prices he has recorded apply.

The market doesn’t care about the past. It is interested only in the future. Tax computation software cost $2,599 yesterday. A new program does the same job today for $2,100. But telephone charges have gone up 12%. The market ignores yesterday’s prices as it speculates on today’s and tomorrow’s.

The market cares only about the local situation. The cost of processing a tax return in Memphis was of no interest in New York yesterday. It is all anyone can think about today. Profits and truth in the market are not visible, they are imagined. What entrepreneurs are doing is pursuing their dreams and trying to convert them into reality.

Why study aggregate planning?

We are discussing aggregate planning — not because it is important, or useful — what you have read so far indicates that it is not. We are concentrating on it because a whole generation of economists, and government policy makers were trained in it — and many economists still use it today. They have assumed that these aggregate numbers have real meaning and significance, and are using them to formulate government policies which control the way each of us lives and works today.

Economic theories themselves are like the market. No one has the whole truth. We each have a part of it, and we try to make sense out of what we have learned and believe. But unlike the market, economic theories used by those who wield government power can be used to deprive millions of people of their freedom and income. Government leaders often act to carry out policies based on theories — like aggregate supply and demand — which would not survive in a free exchange of views.

So you, the citizen of tomorrow, need to know about aggregate supply and demand because your life will be controlled by policymakers who believe that it is scientific fact.  To understand your world, you must understand what other people are thinking, and the theories behind their actions.

How aggregate planning is supposed to work

Most aggregate planners concede that the details of what is happening in the market are too complex to store in even the largest computer in the world. They admit that the knowledge problem presents too many details to permit a detailed control of the economy. What they say is that the details do not matter! They seek to steer the economy’s “broad paths of development”.  But if the steering agency is less knowledgable than the system it is trying to steer, then we have set up a system in which less informed people are telling better informed people what to do.

The key difference between the market and the government planning process is that government aggregate planners can use force to carry out their plan, whereas the market must use persuasion.

Wassily Leontief — A critic of Aggregate Planning

The leading academic critic of aggregate planning was Wassily Leontief, a Nobel Prize winner in economics, and the inventor of the input-output method of statistical organization which underlies the GDP analysis. He admitted the knowledge problem, but advocated a planning agency, staffed with disinterested professional economists who would simply draw up a set of alternative scenarios from which other parties can choose. He assumed that a single agency would be able to establish objectively what future paths the economy can pursue. To him, the paths were scientific and objective. There are only a given number of ways of preparing tax returns, or making steel. The objective price takers learn what the prices are, and choose the correct process.

Leontieff pointed out that policymaking based on aggregates involves unforseen consequences. Overall rational planning is not possible so long as the government lacks comprehensive and detailed information about how the economy is working including the ability “to anticipate potential trouble spots, the parts of the economy where…energy shortages, technological unemployment, population movements, or sudden needs for long-term credits may arise….”

 

He criticized most aggregate planners for trying to create simplistic AD-AS diagrams composed of “a relatively small number of bundles labeled “Capital”, “Labor”, “Raw Materials”, “Intermediate Goods”, “General Price Level”, and so on. These bundles are then usually fitted into a “model”, that is a small system of equations describing the entire economy in terms of a small number of corresponding “aggregative” variables.

The money value of the capital goods owned by an individual firm can be added together to give a meaningful number only because these goods are all part of a single plan. Once you try to add capital goods from competing firms together, the numbers lose their validity since they add up components of mutually incompatible plans. Rivalrous competition means that one company’s plan can succeed only at the expense of some other, incompatible plan. In such circumstances (which always exist in the real world) adding together the values of the capital used by rival firms has about as much meaning as adding to the value of a bridge, the value of a bomb being built to blow it up.

As Leontief says, “the difference between copper and nickel vanishes as soon as both are treated as ‘nonferrous metals’, and both become indistinguishible from steel as soon as the qualifying specification ‘nonferrous’ has been dropped too.”

When such loss of sharpness in description as treating “metals” as a single category is put into a model, as is common in aggregate planning, the results are a model that exists only in an analyst’s mind, and has nothing to do with the real world it is supposed to describe.  When the models are then used to guide government policies, the aggregates move from being “meaningless” to being “dangerous”.

Leontief’s alternative is called the “input-output method”. Instead of a few aggregates, he breaks the economy down into a large matrix in which the “horizontal rows of figures show how the output of each sector of the economy is distributed among the others” while “the vertical columns show how each sector obtains from the others its needed inputs of goods and services.” By breaking the economy down into a table with a hundred or more variables on each side (a table with 10,000 or more individual numbers) he believes that he has captured the “fabric of our economy, woven together by the flow of trade which ultimately links each branch and industry to all others.”

Why Input-Output Does Not Explain the Market

Unfortunately, even Leontief’s detailed tables have little relevance to the real actions of the market, because his many numbers are still aggregates. They are smaller aggregates than such numbers as Capital, and Labor, but they are still aggregates. He is right that a concept like changes in national “Capital” has no meaning to the manager of a steel mill. But neither does a Leontief variable like “Electrical Machinery”.

In complex processes like life or a modern economy, it is impossible to build a precise, deterministic model. The closest we can get is to explain the principles under which people are operating. Leontief believed that he could reduce everything to numbers. While “great economists had to content themselves with verbal description and deductive reasoning, we can measure and we can compute.” But numbers cannot be used unless we can agree on what they mean.

Arbitrary bundles of goods whose prices we can sum under some general category that we can invent cannot be said to mean much of anything, if they do not mean anything to the transactors in the marketplace themselves.  Leontief’s tables include such breakdowns as “North America” and “Eastern Europe” and reduces products to such categories as “textiles” and “communication”.

No matter how many columns and rows you use to construct a detailed model — thousands by thousands — the categories are invariably aggregated constructs in terms of which no transaction is ever actually carried out. But the problem is more serious: Any data that you collect for any table must be made up of objective facts. But only a tiny fraction of the actual knowledge that guides decision makers in the economy can ever be put into explicit form. The businessman who is about to buy an expensive tool has far more going on in his mind than he could ever reduce to data that you could put into a chart. He looks on the tool as an integral part of a plan that fits into his own scenario of how he is going to deal with a market situation that has meaning only for him. Without this subjective context, the facts about trade between sectors of the economy are almost meaningless: by-products of choices already made, and insufficient to understand, much less guide and direct the economy.

How Aggregates Are Used

Leontief explained why his tables are needed: “The real trouble is that, at present, not only does the government not know what road it wants to follow, it does not even have a map. To make things worse, one member of the crew in charge presses down on the accelerator, another pumps the brakes, a third turns the wheel, and a fourth sounds the horn. Is that the way to reach one’s destination safely?”

Of course, if the economy were a single plan or a car trying to get from here to there, his arguement would make sense. But the economy is far more complex than an automobile. The market is already steering itself by the market’s discovery process. All the self-appointed “crew in charge” can do is to obstruct what is currently going on.

The economy is not an automobile, or even a computer. It is 300 million people all freely determining their own course of action based on their subjective interpretation of signals they are getting from the actions of the other 299,999,999 people expressed as price changes and other events.

The economy is the product of millions of individual actions and adjustments made on a daily basis. Each person is not selecting one of a set of scientifically determined methods of reaching his goal. He is determining his goal, his method and his level of effort.

Conclusion

What can we conclude from our analysis so far?

The economy is the result of millions of individuals reacting every day to a changed situation for them: the actions of millions of other people.

The objective facts about what each person does every day do not properly describe what is really happening because even the actors themselves cannot write down the subjective meaning of their actions in a form that a central aggregate planner could use.

Anything that the actors in the market could write down would only be about what happened yesterday. What is important to them, and guides their actions, is what is happening today and what they believe will happen tomorrow.

Even Leontief input-output tables, while more complex than simple AD-AS diagrams, are still aggregates which do not describe real transactions.

Therefore: the activity in the market cannot be described by a set of numbers — no matter how detailed and complex the numbers may be.

The market is not like an automobile or a computer. It is a self regulating process more intelligent than the brains of the millions of people which compose the market.

Any attempt by a central aggregate planner to use “objective facts” derived from the market to guide his actions in controlling the market cannot be successful, because the central planner cannot know what is really going on.

Predicting the future

Many economists set themselves up in business as predictors of the future. You can pick up any business newspaper or magazine and read articles saying things like “GNP expected to drop 2% next quarter”, “Prices will rise only 4% during the next year”, “Consumer spending will be 6 percent more than last year.”  Why economists should make such predictions is no mystery: they get paid for this work.

But why anyone would pay for this type of prediction is the real mystery. Consider this:

Would you go to a psychologist to find out whether you will meet a husband next year? Or ask a doctor many children you will have in the next five years?

The person who gives you these answers would be an astrologer, not a psychologist or a doctor.

Yet an economist who tells you that the Gross National Product will drop 2% next year is no better than an astrologer. He is guessing, based on aggregate supply and demand numbers which we know to be very inaccurate descriptions of a complex process. There is one additional thing wrong with what the economist is doing:

He is basing his prediction on the assumption that the future is determined by what happened in the past.

What’s wrong with that? Answer: it conceals what is happening today. Anyone looking at the price of tax return preparation in New York over four years might see a steady progression: $420, $495, $550, $600. What will he predict for two years from now, based on these numbers? Certainly some number over $600.

But we know that it might, actually, be closer to $500 because of the Memphis firm’s initiative.

Conclusion: aggregate data cannot and should not be used to predict the future. Economists should stick to economics, and not try to become astrologers.

What can economists say about the economy?

If we cannot collect numbers that we group into aggregates; if we cannot make numerical predictions about the future, what can we do as economists that is legitimate and helpful to others?

There are a very wide range of valid statements that can be made about the market process which are of great benefit in understanding it, and guiding government officials who assume that they should try to direct it.

Rather than using an inductive method of collecting numbers, putting them into a computer, and using them to predict the future, sound economists use a deductive method. They study how the economy works, and develop a set of true statements from which can be deduced the result of any proposed governmental actions or market events.

What are examples of these statements?

 

Real income growth can only come from saving and investment.

Inflating the currency of a country will not increase real wealth; it will discourage investment, and reduce real income.

To price and output indicies in the economy, we must add the dimension of time to understand what is happening.

How the Aggregate Production Structure can replace AD-AS Diagrams

The Aggregate Production Structure (APS) can be used to illustrate a more complete description of inflationary recessions and other market movements.

Any economy’s structure can be divided into a series of generalized stages of production such as:

1. Raw commodities stage.

2. Manufacturing stage.

3. Wholesale distribution stage.

4. Retail consumption stage.

These stages are related by a new dimension: time. Manufacturing comes after the raw commodities are mined or harvested. Manufacturers process the commodities and sell them to wholesalers who arrange for nationwide distribution. Each step takes time. It may be a year or more from the time the first raw material is mined until the product appears in a retail store. Each participant in the aggregate production structure is thinking only of pleasing his customer — someone at the next lower level stage.

The horizontal line represents the value of the output of each stage of production. Since both price and quantity are linked together on the horizontal axis, the APS cannot measure real output precisely. Relative changes between stages will indicate expanding or contracting markets.

The new dimension here, compared to the earlier AD-AS diagram illustrating the same phenomenon, is time. At each stage of production, output (not demand, not supply) is aggregated. The stage is separated from the previous and following stages by time.

There are no numbers. We are not setting up a national statistical bureau to collect these aggregates. We are merely developing a picture of what we know actually happens. Iron ore is mined and processed to produce iron. Iron is made into steel. Steel is rolled into sheets. Sheets are stamped into automobile bodies. Bodies are assembled with other parts into cars. Cars are shipped to dealers. Dealers sell the cars to customers.

These are stages of production. They happen sequentially in a time dimension.

The next step is the important one: we recognize that the monetary inflation produces different results on the different stages. On higher orders of production: the mining of the ore, and the making of the steel, the monetary inflation has raised the cost of doing business. Interest rates have gone up, as lenders try to build into their required return their anticipated loss through inflation.

These higher interest rates affect the primary producers at higher stages. They operate by borrowing money. With the high rates of interest, they cut back on output which does not give them a positive return on their investment.

At the lowest stage of production, consumers react differently. The inflation means to them that their money is losing value the longer they hold it. They had better buy goods now, before the prices go up. So consumers spend their money at the same time that high order producers are cutting back their output. The new APS curve is the result.

We have a recession, with steel workers joining the ranks of the unemployed, at the same time that prices are going up, and consumers are using their melting money to buy while they can.

Summary

1. Aggregate Supply and Aggregate Demand curves were developed by some economists to explain a phenomenon they did not understand: unemployment combined with high rates of inflation. They replaced the Phillips Curve which showed the opposite.

2. To get the data for the AD-AS curves, economists used aggregate statistics: the AD curve is supposed to reflect the sum of all demand for all products and services. The AS curve represents the supply of all products and services.

3. Such diagrams are not based on reality, and are very misleading. Aggregate demand cannot be an independent force or variable since it adds together many inconsistent and often contradictory things. Aggregate supply fails for the same reason.

4. The compilers of aggregate statistics assume that market participants are passive “price takers”. They find out how much factor prices are (labor, machinery, rent), and how much consumers are willing to pay. From these data they choose a scientifically determined production process to produce their output.

5. None of this corresponds to the real world. Market participants are not passive “price takers” and the production processes are not scientifically determined, but recreated and reformulated every day by the market participants.

6. Part of the problem is that market facts cannot be described by objective numbers alone. It is the subjective understanding of these numbers by the participants that gives the numbers meaning. This subjective understanding cannot be converted into computer data.

7. The only facts that can be collected for an aggregate analysis are facts about past transactions. These facts are often irrelevant to market participants who are worrying only about today and tomorrow.

8. Aggregate supply and demand were developed by economists who hope to understand and control the economy using these aggregates as a base for their policies. Despite their faults, the aggregates are considered by many economists to be objective descriptions of reality. This is why we have to study them.

9. The knowledge problem is that the meaning of economic data is in the details which can never be captured in aggregates. Admitting that, many economists still want to use aggregates to guide national policies.

10. A key critic of aggregates was Wassily Leontief who substituted his own system: the input-output method. This method is used to create the GNO tables discussed in this book. Unfortunately the data in the input-output tables themselves are aggregates which fail to describe the reality of the transactions behind the numbers.

11. Leontief likend the economy to a car with a self-appointed crew in charge (economists working for the government) making errors in acceleration, braking and steering. He felt that his input-output method would help government officials to drive the car properly.

12. Unfortunately, the economy is much more complex than an automobile. It is a self-regulating process involving millions of independent actors who are each modifying their actions based on daily information on prices and possibilities. Attempts to manage the economy as if it were a car, based on input-output tables will do nothing by obstruct a highly intelligent and complex process.

13. Many economists use aggregates and input-output tables, inserted into computer models, to predict the future.  Economists cannot correctly predict the future, and should not be debasing the profession by trying to do so.

14. Economics does not provide valid predictions by collecting numbers, building models, and pretending to be scientifically precise at predicting the future. Instead, economists study the production process and develop valid statements about relationships. They use these valid statements to deduce the results of possible courses of action.

 

15. The reasoning behind the Aggregate Production Structure is an example of a valid statement about the production process. It says that goods and services are produced in stages through time with intermediate goods producers selling their output to producers further down in the structure of production.

About Arthur Middleton Hughes

Arthur is currently Vice President of The Database Marketing Institute based in Fort Lauderdale, FL. Arthur is the author of 11 books, the latest of which is Strategic Database Marketing 4th Edition (McGraw-Hill 2012). A BA graduate of Princeton with an MPA in Economics and Public Affairs, Arthur taught economics at he University of Maryland for 32 years. He is an Austrian Economist.
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