The Current Situation

The Current Situation: The United States As of the summer of 1999, economic growth in the United States continued to be strong. Forecasters predicted that 1999 would see real GDP in the United States rise by 4.0%, as a 1.2% increase in the number of workers was accompanied by extremely strong growth--2.8% per year--in labor productivity. Democratic policymakers and economists advocating the Clinton deficit-reduction program in the early 1990s had claimed that deficit reduction would make possible a high-investment economic expansion, which would then become a high productivity growth expansion. Up until 1996 there had been no signs that high investment was leading to high productivity growth. But by the summer of 1999 people were beginning to hope that perhaps the political claims of the early 1990s were becoming true. In the United States, strong growth in production and sales had pushed the unemployment rate down to a level--4.2%--not seen in a generation. Such a tight labor market was good news for workers: employers appeared eager to pour resources into training them for their jobs. Yet the tight labor market and the strong demand for employees was not showing up in strong real wage growth. Real wages in the year up to June 1999 had grown at only 1.7 percent. On the other hand, relatively slow nominal wage growth--3.7 percent in the year up to June 1999--meant that inflation was low as well. This proved a puzzle to economists: practically all had confidently forecast that unemployment below 4.5 percent would surely lead to accelerating inflation. Yet it did not seem to do so--and hence the likelihood that the Federal Reserve would find it necessary to sharply raise interest rates to restrict demand and fight inflation seemed low. The effect of the employment report on Friday, September 3...

The Current Situation: Europe As of the summer of 1999, industrial production in the eleven countries belonging to the European Monetary Union--and having the "euro" for their principal currency--was 1.2 percent below what it had been a year before. Europe was not in recession exactly: GDP had grown by one percent over the preceding year. But with falling industrial production, high unemployment of ten percent of the labor force or more, and stagnant retail sales the European economy could hardly be said to be healthy. There was certainly room for economic expansion in Europe as of the summer of 1999. The preceding year had seen consumer prices throughout the euro zone rise by only 0.9 percent, and had seen producer prices actually fall by 1.4 percent. Yet central bankers seemed reluctant to engage in policies to expand demand, and eager to blame the social welfare state and an absence of incentives for high unemployment.

 How Economists Think

Questions

Why do so many people find economics a relatively difficult subject?

Is economics a science?

Why do economists use–simple–mathematical models?

What do economists’ models consist of?

Why does everything in an economics textbook seem to be repeated three times–once in words, once in diagrams, and once in algebra?

Is there a point to thinking in this strange and new way?

Trying to understand the macroeconomy

Each time you learn a new subject you learn a new pattern of thought.

Every intellectual discipline has its own ways of thinking about the world. That’s what makes it a system of thought, a subject of study, something worth learning, and something that can be taught. Thus each intellectual discipline seems new and strange to those who have not seen it before: it is new and strange, because it is made up of new–and initially strange–patterns of thought.

 

Economics: it is a science?

Economics is a science, but economics is not a natural science, it is a social science. Its subject is not electrons or elements, but human beings: people and how they behave. This has a number of important consequences. Some of them make economics easier than a natural science, some of which make economics harder, and some of which make it just different.

• First, because economics is a social science, intellectual debates within economics can last a lot longer than in the natural sciences, and are much less likely to come to clear and well-defined consensus conclusions.
• The major reason for this is that people care: people have very different views of what a free, a good, a just, or a well-ordered society would look like. (Indeed, they look for things in the economy that are in harmony with their vision of what a society should be. They ignore–or explain away–facts they run across that turn out to be inconvenient for their particular political views.
  • Economists try to approach the objectivity that characterizes most work in the natural sciences. We should be able to reach broad areas of agreement. After all, what is, is; and what is not, is no. Even if wishful thinking or predispositions contaminate the results of one single study, successor studies and reexaminations can correct the error. But economists do not approach the unanimity with which physicists embraced the theory of relativity, chemists embraced the oxygen theory of combustion, and biologists rejected the Lamarckian inheritance of acquired characteristics.
• Second, the fact that economics is about people means that economists cannot (or cannot ethically) undertake large-scale experiments. Economists cannot set up special situations in which potential sources of disturbance are reduced to a minimum, examine what happens, and then generalize from what happens in the experiment (where sources of disturbance are absent) to what happens in the world (where sources of disturbance are common).
  • The absence of the experimental method makes economics harder than many of the natural sciences. It makes economists’ conclusions much more tentative and subject to dispute.
• Third, the things that economists study–people–have minds of their own. They take a look at what is going on around them, they plan for the future, they take steps to avoid future consequences that they foresee and fear will be unpleasant, and at times they do things just because they feel like it. This means that in economists’ analyses the present often appears to depend not just on the past but on the future, or rather on what people expect the future to be.
• This additional wrinkle makes economics in some sense very hard. In the natural sciences you can almost always rely on the arrow of causality and influence flowing from the past to the future only. In economics expectations make the arrow of causality flow from the (anticipated) future back to the present almost as often as from the present to the future.

 

Economics is a quantitative social science

But spite of its political complications, its non-experimental nature, and its peculiar problems of temporal causality, economics remains a quantitative science. Most of what economists study comes in measurable form, with numbers attached. Thus–as opposed to sociology and political science–economics makes heavy use of arithmetic and algebra. Economics makes heavy use of arithmetic to measure economic variables of interest. In economics you can always ask, and usually answer, the question how much?

Economics also makes very heavy use of algebra to formulate and analyze models–small, simplified sets of relationships that are intended to illuminate more complicated processes going on in the economy.

When economists are trying to analyze the implications of how people act–how, say, consumers change (or don’t change) their spending in response to a change in income–they will almost always write down (in algebra) a behavioral relationship: an equation giving a rule for how the effect (economy-wide consumption spending) reacts to the cause (total economy-wide incomes). For example, they will write down a consumption function:

Using "C_t" to stand for economy-wide Consumption spending in some particular year t, and "Y_t" to stand for economy-wide total income. c₀ and c are the parameters of this behavioral relationship–they tell us exactly how consumption varies with income: raise total incomes by $1 and consumption will rise by $c; even if incomes were to fall to zero, total consumption spending would still be positive at $c₀.

Analyzing the consequences of how people act by writing down these algebraic behavioral relationships has proven a powerful tool. But other kinds of equations appear in economic reasoning as well. There are equilibrium conditions–things that must be true if the economy is to be in balance, and that if they do not hold then things must be changing rapidly.

In microeconomics the principal equilibrium condition is that supply must be equal to demand. If not, then either buyers who find themselves short are frantically raising their bids (and prices are rising) or sellers who find themselves with excess inventory are frantically trying to dump it (and prices are falling); only if supply equals demand can the price in a market be relatively stable. Similarly in macroeconomics: equilibrium conditions are as a rule simple statements that supply be equal to demand. For example, aggregate demand–the sum of consumption spending C, investment I, government purchases G, and net exports NX:

and aggregate supply–Gross Domestic Product [GDP], which is the same thing as total economy-wide income:

must be equal:

If not, then either inventories are rising above or falling below desired levels, and businesses are about to take action by changing their production and sales strategies.

(There is a third kind of algebraic equation: the identity. An identity is something that hold true by definition, so that we cannot even conceive of how it could not be true.)

 

The rhetoric of economics.

Economics is also heavily dependent on metaphors. Curves "shift." Money has a "velocity": if total GDP of $10 trillion is supported by $1 trillion of cash and checking account balances, economists say that money has a "velocity" of 10 (because the average piece of money changes hands as part of a final demand-related transaction some ten times a year).

When the Federal Reserve raises interest rates and throws people out of work, it "pushes the economy down the Phillips curve." When the Federal Reserve lowers interest rates and the economy booms, it "pushes the economy up the Phillips curve"–as if the economy were a dot on a diagram drawn on a piece of paper, as if it were constrained to move along a particular curve on the diagram called the Phillips curve, as if changes in Federal Reserve monetary policy really did push this dot drawn on the diagram up and to the left.

 

Most of the metaphors you will see in macroeconomics will fall into four classes:

The first is made up of hydraulic metaphors connected with the dominant image of the circular flow of economic activity.

The second is economists’ use of the word "market" to label intricate and decentralized processes of exchange–as if all the workers and all the jobs in the economy really were being matched to each other in a single open-air market.

The third is economists’ fondness for the idea of "equilibrium": their thinking about economic processes as if they were somehow bringing the two pans of an old-fashioned scale into balance (that’s what "equilibrium" means: equi-librium, equal weights on the two pans of the balance)

The fourth and last is the way of metaphorical thinking that is the branch of mathematics called analytic geometry–economists’ use of graphs and diagrams as an alternative to algebraic equations by identifying equations with curves, equilibrium with points, and changes in parameter values as shifts in the positions of curves on a diagram. This use of metaphor is central enough to economics that it is discussed not in this but the next section of this chapter.

The Circular Flow of Economic Activity

One benefit of this hydraulic metaphor is to help us see that the economy is made up of ongoing and ever-repeated patterns of activity: not one act of exchange or production, but a continuous process

The circular flow metaphor contains another important truth–that every piece of economic activity has two sides.

 

Markets

Economists talk as if all economic activity–all purchases and acts of exchange–take place in something like the great open-air marketplaces of the merchant cities of the preindustrial past.

Equilibrium

This search for equilibrium is a way to try to greatly simplify the process of analyzing an ever changing, dynamic, complicated system. The underlying principle is that things are much easier to analyze if you can first figure out "points of rest," positions and states of affairs where pressures for economic quantities to rise and to fall are evenly balanced–see, there is the metaphor again.

 

The relationship between algebra and geometry

 

We use graphs to plot two economic variables on the two axes. We draw one line (or "curve") for each behavioral relationship or equilibrium condition. The point where the curves cross will be the solution: the values at which the two economic quantities that you did not know are consistent with people’s behavior and market equilibrium.

 

Economists Use Models

Simplify, Simplify, Oversimplify

The American economy is complex: 130 million workers, 10 million firms, and 90 million households buying and selling $24 trillion worth of goods and services a year. Economists have placed the intellectual bet that the best way to understand this complexity is to simplify. Restrict your attention to a very few behavioral relationships–cause-and-effect links from one set of economic quantities to another–and a handful of equilibrium conditions–conditions that must be satisfied for economic activity to be stable and for supply and demand to be in balance in different markets. Capture these behavioral relationships and equilibrium conditions in simple algebraic equations (and analytic-geometric diagrams). See how the mathematical system made up of those equations behaves. Then try to apply the properties of the system back to the real world.

And all along hope that all the quantifying and simplifying have not made the model a bad guide to how the world really works.

Economists call this process of stripping-down of the complexity and variation of the economy into a handful of equations "building a model." And economists then use these models that they have built to try to understand what is going on in the real, complex economy out there..

It is important to understand that economists do not just use models–systems of equations that in some way are supposed to mimic the behavior of people and institutions–economists use simple models. Economists use simple models for two reasons. First, no one can understand what is going on inside complicated models. A model is of little use if it generates a prediction, but if you then do not understand the logic behind the prediction.

Second, predictions generated from simple models are nearly as good as ones from complex models. The economic models used in real life by the Federal Reserve or the Congressional Budget Office are more complex than the models in this textbook. But at the bottom they are clearly cousins of the models used here.

The same Phillips curves, IS curves, and consumption functions you see in your textbook underpin staffwork behind meetings of the Federal Reserve Open Market Committtee [FOMC] when it tries to decide whether the management of the economy requires a change in the level of interest rates.

If you hear someone say that economics is more of an art than a science, they are saying that the rules for how to build effective and useful models–models that omit unnecessary detail but retain the necessary and important factors–are nowhere written down. In this important aspect of economics, economists tend to learn by doing–or learn not at all.

 

The Utility of Algebra

This way of model building is a powerful way of thinking–if the detail that you omitted is indeed unnecessary, and if the features that your particular model focuses its attention on are in fact the most important features for analyzing the issues at hand. But the odds that this will be a fruitful intellectual strategy are good because the tools are powerful.

Algebraic equations are the best way to summarize cause-and-effect behavioral relationships in economics. Because so many of the concepts that economics deals with are easily counted, it is natural to use the fact that they can be counted: natural to say not just that consumption spending was strong, but that it was $6.25 trillion dollars that year. But arithmetic reaches limits. For example, it would be very cumbersome to carry around a large table telling you what economy-wide consumption spending is likely to be for each of a thousand different possible values of total economy-wide household incomes. It is easier to remember and to work with a single algebraic equation. As before, with C_t standing for consumption spending in some year t and Y_t standing for total incomes in some year t, economists might write:

(with both consumption and income in

$0 $2,000

$100 $2,050

$200 $2,100

$300 $2,150

$400 $2,200

…

$4,000 $4,000

$4,100 $4,050

$4,200 $4,100

$4,300 $4,150

$4,400 $4,200

$4,500 $4,250

…

$9,500 $6,750

$9,600 $6,800

$9,700 $6,850

$9,800 $6,900

$9,900 $6,950

$10,000 $7,000

…

The Power of Algebra   However, with algebra we can think more powerfully–about a whole family of different possible systematic relationships all at once. We let letters stand for unknown and potentially-varying parameters, and thus think of the systematic relationship between consumption and income not in the specific terms of: but in the general and abstract terms of: The parameters c0 and c are placeholders that can take on any of a wide set of different numerical values. Combining this equation with the national income identity leads us to: Then we can subtract c x Y from both sides: And divide by (1-c) brings us to the conclusion that: This equation is much more powerful. It allows us to rapidly determine what the level of national income Yt would be for any particular numerical values of the parameters c0 and c that summarize what the thus-and-so specific conditions happen to be. By contrast the arithmetic equation: was one single arithmetic statement about what the level of national income Yt would be under thus-and-so highly specific conditions. It was an answer that did not allow you to easily go anywhere else. Moreover, algebra is most useful because its conclusions like: allow us to do comparative statics. They let us see what would happen to the equilibrium level of Yt if the parameters were a little bit different: a $1 increase in c0 increases equilibrium total output Yt by 1/(1-c) dollars, no matter what value c happens to take on.

Keys to Model Building

Ignore Differences Between People

Difficulties with "Representative Agents" It also makes some areas of the field of study next to impossible to analyze. Consider unemployment, for instance: the key fact of unemployment is that some workers have jobs and other workers do not. Thus it is hard to say anything coherent about unemployment if one has previously adopted the simplifying assumption of a representative worker. This assumption of a representative agent also means that much of macroeconomics is helpless in situations where the distribution of income and wealth–and thus differences between different people in the economy–are important. Most of the time our judgments about social welfare are deeply tied up with distribution: an economy in which everyone works equally hard but a million lucky people received $1,000,000 a year in income and 99 million received $10,000 a year in income would be judged by most of us to be worse off than an economy in which all 100 million people received $80,000 a year in income, even though total incomes in the first economy amounted to $10.9 trillion and total incomes in the second economy amounted to only $8 trillion. As I wrote at the beginning of this chapter, every intellectual discipline sees some things very clearly and some things very fuzzily or not at all: distribution and its impact on social welfare is one thing that macroeconomics has trouble bringing into focus.

Look at Opportunity Costs

to construct behavioral relationships

Focus on Expectations

Economists tend to consider three types of expectations:

Static expectations–in which the future in the relevant dimension is not thought to be uncertain or predictable enough that it is worth spending any time thinking systematically about how the future will be different.

Adaptive expectations–in which time and attention is spent thinking about the future, and the rules-of-thumb adopted relate expectations of the future values of variables to their values now and in the recent past.

Rational expectations–in which a lot of time and attention is spent thinking about the future, and in which the decision-makers in the economic model know as much (or more) about the structure and behavior of the economy as the economist building the model does.

Depending on which type of expectations is believed to hold, the behavior of the economic model can be very, very different.

An example: a simple model.

The Keynesian cross.

We have already presented the bulk of one of the simplest models used by macroeconomists–the income-expenditure model, the so-called Keynesian Cross–in the earlier sections of this chapter. It consists of the consumption function:

the national income identity:

and the statement that investment I_t, government purchases G_t, and net exports NX_t are exogenous–exo-genous, literally "outside-generated."

The consumption function is a behavioral relationship–a cause-and-effect prediction that if income is at level X consumption will be at level Y, and that if income changes by an amount DX (where "D" is a Greek letter, capital delta, often used as a shorthand for "change in") then consumption will change by an amount DY.

The national income identity is an equilibrium condition–something that must hold for the economy to be in balance. All economic models have behavioral relationships in them–specifications of how groups of economic agents will react to a range of conditions. And all have equilibrium conditions.

Solving the model three different ways.

We can analyze this model in any of three ways.

First, we can draw the so-called income-expenditure diagram, on.

Second, we can–as was done above–do the algebra: combine the national income identity and the consumption function to produce:

Then simply substitute in the (exogenously-given) values of the variables on the right-hand side and the two parameters c₀ and c to solve the model and determine the level of total income Y.

Thus we can use algebra to analyze this model.

Third, we can talk through this model–we can use our words:

An Example: Consumers Become More Pessimistic Suppose that consumers become more pessimistic. We can say "Consumers grew more pessimistic about the future, and so they will spend $100 billion less for each possible level of total economy-wide incomes." We can reduce the value of the constant term–the c0–in the consumption function: by $100 billion Or we can move the consumption spending-as-a-function-of-income line downward on the income-expenditure graph by $100 billion.     These are all three different views of the same process, the same thing. Either we say that consumers become pessimistic and spend less, we reduce the value of a parameter–a number–in an algebraic equation is reduced, we shift a line on a diagram downward. The first uses words, the second uses algebra, and the third uses analytic geometry. The first tells what consumers do, the second describes the change in the algebraic behavioral relationship that economists use to model consumer behavior, and the third uses the metaphors of analytic geometry–the behavioral relationship between consumers’ incomes and spending is seen as a line on a graph that can and does change position as circumstances change.

Summary

Main points

1. Don’t be surprised to find economists’ ways of thinking strange and new–that is always the case when you learn any new intellectual discipline.

2. Don’t be surprised to find economics riddled with metaphorical thinking–the velocity of money, curves that shift, and most important the idea of the circular flow of economic activity.

3. Don’t be surprised to find economics more abstract than you had thought. Today’s economics courses focus more on analytic tools and chains of reasoning and less on institutional descriptions.

4. Economics is a relatively mathematical subject because so much of what it analyzes can be measured. Thus economists use arithmetic to count things, and use algebra because it is the best way to analyze and understand arithmetic.

5. When macroeconomists build models, they usually follow four key strategies:

Strip down a complicated process to a very few economy-wide behavioral relationships and equilibrium conditions.

Simplify–ignore differences between people in the economy

Look at opportunity costs as ways to understand behavioral relationships.

Focus on expectations of the future, and how such expectations affect the present

 

6. In economics, you will find that arguments are repeated in three different forms: once in words, once in equations, and once in the form of diagrams on which lines (or curves) shift and points of stable equilibrium are found "where the curves cross."