Positive Economics: Economics Becomes a Science How a ... · normative judgment. Many studies have shown that, for most people, their normative and positive beliefs are independent

Positive Economics: Economics Becomes a ScienceHow a moral philosophy became a tool to better people’s lives

By Steven R. Cunningham, PhD, Director of Research and Education

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Positive economics: economics Becomes a science



ContentsIntroduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Beginnings: Adam Smith and David Hume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Ricardo and the Later Classical Economists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

The Rise of Neoclassical Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

The Elements of the New Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Should Economics Be a Science? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

The Depression and Beyond . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Data Makes a Difference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Testing the Theories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

An Empirical Methodology Emerges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Economics as a Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Progress as a Science Continues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Now and the Future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

A Final Note . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

For Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Positive economics: economics Becomes a science 1

Introduction

ScIEncE IS IMPoRtAnt BEcAuSE It answers questions. It is not musing or speculation. It allows us to avoid expensive mistakes and make better decisions. It cuts through superstition and supposition, dreams and fears. It tells us what is really going on rather than what we might wish was going on—it is positive rather than normative. our lives are made better.

Science was born when natural philosophers began to test and experiment. Theoretical revelations and advances in mathematical and statistical methods went hand in hand with advances in technology and experimental methods. Galileo Galilei dropped two balls from the leaning tower of Pisa in 1589. Sir Isaac newton studied hydrodynamics with a rope tied to a bucket in 1689. Alfred north Whitehead and Bertrand Russell demonstrated that all of mathematics can be derived from pure logic in 1910. Seismic signal processing had to wait for the arrival of large-scale, high-speed digital computers in the late 20th century. Day by day, year by year, as the sciences took form, scientists gradually distanced themselves from philosophers.

For these reasons, economists have long sought to elevate their study to a science, with rigor and greater certainty, with data, computation, and testable hypotheses. Phillip Mirowski of tufts university, in his book More Heat than Light, argues that economists have long envied the advances of physical scientists and have attempted to emulate them in building a science of economics. In this effort, economists have imported the mathematical innovations of physicists, including calculus, differential equations, and statistical methods. And, they have copied the nomenclature—Einstein’s General Theory of Relativity was followed by Keynes’ General Theory of Employment, Interest and Money.

Economists face different challenges than physical scientists, and the transition has not been easy. Economics is a study of people and social interaction, not inanimate objects. As a result, from its earliest beginnings, economics was necessarily interdisciplinary. Driven by moral concerns, directed by human interaction, and influenced by and influencing the political system, the earliest thought was at the nexus of moral, social, and political philosophy.

As economics has made its way away from philosophy and toward a science, methodological and substantive advances have supported and furthered each other. At times, the special nature of the social sciences created special challenges. When technological, statistical, and mathematical advances met with greater availability of reliable data, the science of economics began to emerge.


Beginnings: Adam Smith and David Hume

A cRItIcAl PoInt In thE movement of economics toward science is found in the contrasting views of Adam Smith (1723-1790) and David hume (1711-1776), two good friends and colleagues working in 18th-century Scotland. Adam Smith created the basis of the content of economics, while David hume separated the moral philosophy from the analytical engine. Smith’s (1776) bestseller, commonly known as The Wealth of Nations, marked the beginning of classical economics and laid the foundation for much of the economic thinking for the next 200 years or so. hume, in 1739, offered the basic insight, the separation of positive and normative thought that would allow economics to eventually become a science.

Smith’s approach was not science. It was normative, replete with value judgments that assumed a common moral perspective.

After all, Smith was a professor of moral philosophy at the university of Edinburgh. his work on how market economies operate was solely to support his primary thesis that markets naturally coordinate human interaction in ways that are in the best interests of society. he argued that markets produce fair and reasonable prices, efficiently allocate resources, produce the highest standard of living, and create the fairest distribution of income. Markets do all of this, he said, while making optimal use of information, resources, and people, and also maximizing personal freedom.

But who is to say what is best for society or what is good, fair, or reasonable? Even where value judgments weren’t obvious, they were just below the surface: Efficiently allocating resources to what end? Is maximizing personal freedom a self-evident good?

normative statements are most often couched in the terms ought or should, and are nothing but value judgments. They are based on personal notions of good, bad, right, and wrong: “Any full-time job ought to pay enough for people to provide a reasonable standard of living for them and their families.” This is a value judgment. Then the inevitable question comes, “Why?” The only possible answer is that the person stating this believes it is the right thing to do.

In contrast, a positive statement related to wages might be, “If the minimum wage was higher, then output and employment would be higher.” Whether it is true or not, it is a statement about measurable, observable, causal relationships and results. It is a statement that can be tested. no matter whether such a positive statement proves true or untrue, it cannot address the rightness of certain wages.

Smith argued by offering compelling examples, history, and reason, rather than relying on the rigorous analysis of real-world experience in the form of data—what we now refer to as empirical research. In fairness, data was hard to come by in his time, and there were no computers handy for analyzing it.

hume’s insight, sometimes referred to as hume’s Guillotine, separates positive and normative analysis. A positive statement is one based on simple observation or fact. It is not an opinion, it does not proffer what ought to be, and it contains no value judgment. It is simply what is. It depends only on observables and demonstrable consequences. This is where positive economics gets its name.

adam smith

David Hume

4 american institute for economic researcH

This led to the guillotine, also referred to as the “is-ought problem.” The blade of hume’s guillotine severs the two. he argues that a normative claim can never be fully supported by a positive argument and vice-versa.

If someone claims that everyone should have free access to health care, you cannot convince him/her otherwise with arguments about current economic realities. Right is unrelated to possible, cost-effective, or even affordable. If someone believes it is right, then the cost of health care or consequences for a federal budget are irrelevant. to them, it is what should be.

likewise, it is not possible to argue convincingly and universally that personal freedom and individuality ought to be guaranteed to all human beings. You can believe it and may even think it is self-evident, but can you prove it empirically? You may be able to provide data to argue that free societies have higher growth rates of income or produce more innovation. But in many societies, stability, conformity, and cooperation are more highly valued than freedom. Different people from different societies have different values, preferences, and views of the way the world ought to be. In other words, the claim is normative.

Some philosophers have argued that hume’s construct is too simplistic, that the line between positive and normative is not so clear. They question whether normative debates in the economic world can be independent of positive economics. While a purely normative position does not rely on the current state of the world, policy choices most often are based on projections of the impact of the proposed policies. These impacts are based on empirical studies of historical data. They are based on an analysis of the causal chains that explain the way the world actually works. That is, they are based on positive economics.

In choosing policies, decision makers sometimes like to think that they estimate the economic or financial impact of policies based on differing assumptions and then weigh those expected outcomes against perceived normative gains. unfortunately, unlike objective measures of efficiency, profits, income, or prices, normative assertions don’t easily lend themselves to explicit monetary measurement. They are also very personal. Different people weigh the costs and benefits differently.

The result is often the appearance of rational decision making in the face of normative judgment. Many studies have shown that, for most people, their normative and positive beliefs are independent. other studies have shown that even working economists have normative and positive economic beliefs that are wholly disconnected from one another. In other words, what economists know about economics and the economy does not inform what they think is right and wrong.

nonetheless, hume drew the initial line in the sand, and the world has never been the same.


Ricardo and the Later Classical Economists

MoDERn EconoMIStS RAnK A lAtER classical economist, David Ricardo (1772-1823), as the second most influential economist prior to the 20th century. Ricardo was a Sephardic Jew whose family disowned him when he married a Quaker woman. Forced to fend for himself, he became a stockbroker and trader. he learned quickly. his love of economics was born from the harsh necessity of a man trying to make a living in the financial markets. ultimately, his prowess with markets allowed him to retire a rich man at age 43 and purchase an estate in Gloucestershire. Wishing to apply what he had learned to issues of national policy, he became an influential member of the British house of commons.

his background in markets made Ricardo a practical man who sought answers to real-world problems, rather than a philosopher pondering “the great questions.” This shaped his methodology. he naturally pursued positive analysis and, in so doing, advanced economic science. Ricardo systematized economics and applied simple models to revise international trade theory and policy, theories of rent, wages, and profits, and the impact of deficit spending on an economy. his method was deductive, using simplistic models supported by crudely constructed critical measurements. It was one more step from a practical-minded businessman toward a working science of economics.

William nassau Senior (1790-1864), a professor of political economy at oxford, was a friend of Ricardo’s and respectful of his contributions. however, he was critical of Ricardo’s work. Ricardo was mostly self-educated, and according to Senior, sloppy and inconsistent in his use of terms.

With Senior’s criticism in mind, all future economists would take more care with their terminology, another important step toward economics as a science. Senior based his economics on neither purely inductive reasoning nor abstract constructs. he viewed economics as a purely deductive science based upon fundamental, observable, real-world facts. together, Ricardo and Senior formed something of a bridge between the deductive method of philosophy and the practical, testable method of science based in precise terminology.

Ricardo and Senior became close as influential members of the Political Economy club, founded by James Mill (1773-1836). Members included utilitarianism founder Jeremy Bentham (1748-1832), the Rev. Thomas Malthus (1766-1834), and economist Jean-Baptiste Say (1767-1832).

Mill’s son, John Stuart Mill (1806-1873), also attended meetings as he grew to adulthood. In his autobiography, Mill described the painfully rigorous education he received at the hands of his father. he learned classical Greek at age three and latin at age eight. By age 10, he had read all the commonly taught Greek and latin works in the original. he studied scholastic logic at age 12. At age 13, he was studying the works of Smith and Ricardo and helped his father write a textbook. Mill also studied advanced mathematics, logic, and the sciences. Ricardo, a man of some leisure by then, invited the younger Mill to his house for lengthy discussions of political economy.

David ricardo

John stuart mill


unfortunately, the rigors of his training caused Mill to have a nervous breakdown at age 20. he had regrets about his lost childhood, and he sank into depression. he claimed that long rest and the reading of poetry and literature helped him heal his mind. After recovering, he went on to dominate the world of economics for 50 years.

Karl Marx and later economists often counted Mill among the classical economists. The classicals were generally market advocates, although all had a healthy respect for the value of government. They used less-rigorous mathematics and incorporated a lot of institutional and historical detail in their discussions.

understanding the nature and roles of deduction and induction is critical to understanding Mill’s methodology. There are two approaches to science—theoretical science (or theory) and empirical science, and these are related to deduction and induction. A purely empirically based economic science was to wait for quality data and the means to use it. Theoretical work usually involves assuming certain postulates or givens and then seeing deductively where those assumptions lead.

Because economics is about people, the starting point for economic deduction is usually a theory of human behavior and motivation. Before psychology was a well-developed area of study, this meant writing your own book on psychology before getting to the economics. Smith did this with his The Theory of Moral Sentiments (1759). hume did it with A Treatise on Human Nature (1739).

Mill drew heavily on the work of Smith, hume, and others—but with a critical twist that was to influence all future economics. Rather than focus on the actions of groups or social psychology, Mill focused on the motivations of individuals. he adopted an approach to economic analysis now known as methodological individualism—the guiding principle that any explanation of economic behavior must be reduced to the independent choices of individuals. That is, all theory has to begin with the individual.

to Mill, society was a fiction. Society does not make choices; rather, what we observe is the sum of the individual choices and behavior of the people who make up society. It makes no sense to characterize society separately from the individuals who make it up, and society does not change or shape individual human beings or their behavior.

ultimately, Mill sought a positive view of humankind in which economics explains a certain range of interactions. Given his broad perspective, he believed that the subject of economics is too complex to be approached without a deductive method, even though it starts with empirical inference. he was skeptical about all events beyond present experience: The only grounds we have for making inferences about the world around us are observations. We have to do it that way. It is part of what we are. We must continue iteratively refining in a learning process in which generalizations are gradually limited and qualified.

Mill’s “on the Definition of Political Economy; and on the Method of Investigation Proper to It” (1836) was one of the earliest discussions of the methodology of economics. In building his own method, he took into account his concern that the empirical practices of inductive science are often distorted. In short, researchers are subject to confirmation bias. That is, they tend to find in support of their preconceived notions or ideology.


to remedy confirmation bias, Mill formalized his iterative process by developing a series of testable hypotheses from deductive reasoning from observable premises followed by rigorous attempts to falsify the conclusions with data and empirical tests. As a hypothesis was rejected, it was systematically replaced with another, more refined conjecture. This approach anticipated the modern scientific method of Karl Popper (1902-1994) (1959) and others.

While deductive reasoning helps keep us on track in this iterative process, the rules of deduction and induction are based on normative concepts. They tell us how we ought to process information.

In his System of Logic, Book III, Mill more thoroughly laid out his scientific method. According to Mill, we build patterns of explanation, test them, and reject those falsified by testing. As we build systems of these patterns, we form laws. We also develop a broader understanding of the world and humankind by learning which facts can be subsumed under which laws.

The laws generalize and gradually form a tapestry, yielding patterns of patterns and laws about laws. using such background laws and deduction, a researcher constructs a number of competing hypotheses, along with data and experiments to eliminate false hypotheses. hopefully, at the end of the process, one hypothesis remains. Thus, the process is observation, deduction, hypothesis construction, and hypothesis testing. under testing, if the hypothesis fails (or is falsified), then a new hypothesis is constructed.

The hypotheses and tests are all based on the law about laws, the overarching model or pattern of the researcher. Both hypotheses and methods of inference can be revised as the researcher iterates through the process of discovery.

one could argue that Popper and American philosopher Thomas Kuhn (1922-1996) defined 20th-century scientific methodology. Yet, by the mid-1800s, Mill had already articulated a remarkably similar methodology that laid all the groundwork for economics to become a science. he had already introduced into economics the essential elements of Popper and Kuhn—the scientific method that forms the basis of the modern physical sciences.

Mill’s approach is essentially the same deductive-nomological model proposed by Popper in 1959 and is the standard for the scientific method that many look to today. It is commonly known as the method of falsification.

Mill’s construction of theory is consistent with Kuhn’s modern theory of normal science. Mill talks about laws about laws, while Kuhn talks about paradigms. Although they are different terms, the meaning is similar.

Both Mill and Kuhn say that paradigms are not easy to reject. They are not falsified and abandoned by simple observations. According to Kuhn, a scientific revolution occurs only when a theory no longer leads to fruitful research.

Through Mill, the methodological foundation was built for economics to advance economics as a 20th-century science. But the methodology needed technical rigor, mathematical precision, and testable hypotheses to bear fruit. For this, economists looked to natural science as a model.


The Rise of Neoclassical Economics

thE RISE oF thE nAtuRAl sciences, especially physics and chemistry, from natural philosophy had engendered a great deal of respect, not the least of which came from economic thinkers. This led to a kind of economic scientism, an arguably exaggerated emphasis on the value of an approach to social phenomena that resembles the way that physicists study nature. This gave birth to an updated version of the classical theory that became known as neoclassical economics. Philosophically, neoclassical economics was a natural extension of the classical theory. It embraced markets as ideal coordinating elements for the economy.

It differed from classical economics in its reliance on advanced mathematical models and a more rigorous application of emerging scientific methodology. These were imported into economics, along with the utility theory of Jeremy Bentham and others, most notably by mathematicians Alfred Marshall (1842-1924) and leon Walras (1834-1910) and scientist and logician William Stanley Jevons (1835-1882). The expression of economic theories in precise mathematical terms makes it easier to form empirical tests, and it makes equivocation difficult. Most of the microeconomics taught and practiced today is still based on the neoclassical approach.

Alfred Marshall was a mathematician turned economist, a trend for economists that continues to this day. he was influenced by John Stuart Mill’s Principles of Political Economy (1848). Recognizing the tight logic and rigorous approach, Marshall started translating the work paragraph by paragraph into equations. An afternoon’s amusement turned into a career. Marshall presented economics as a rigorous science in his textbook Principles of Economics (1890), destined to be the international standard on neoclassical economics for decades to come. Marshall was the first to hold the chair of economics (not political economy) at King’s college, cambridge university, dramatic recognition from perhaps the world’s leading university that economics was no longer philosophy. Marshall’s department later produced and then became home to John Maynard Keynes (1883-1946).

leon Walras first studied engineering, but he later turned to economics, eventually taking the chair of political economy at the university of lausanne, Switzerland. For a long time, his work was only available in French. So it remained less known for many years. In particular, Walras is known for his development of mathematical means of describing the interactions among markets in an economy.

William Stanley Jevons’ book The Theory of Political Economy (1871) is often described as the beginning of the mathematical method in economics. he wrote not only on economics, but also on the physical sciences, logic, probability, and statistics. For Jevons, these were all science, and each subject informed and illuminated thought in the other.

With the help of others, Marshall, Walras, and Jevons gave birth to neoclassical economics, an approach to economics marked by three elements: utility theory, marginal thinking, and the use of advanced mathematics and optimization.

alfred marshall


The Elements of the New Economics

utIlItY thEoRY IS A cRItIcAl element in the advancement of economics because it explains value and can be described mathematically. Smith had looked for a standard by which to value goods. he wanted it to argue that the market process, without external direction, generates prices consistent with fair valuation. For Smith, the answer was that a good should sell in a market economy for its cost of production plus a “normal rate of profit.” (In his early chapters, Smith simplified “normal rate of profit” to be the cost of labor used in production.)

utility theory provided a better explanation of valuation and behavior. In short, it poses that people value things because those things bring them utility—usefulness or pleasure. According to the theory, people weigh the ratios of utility to price in making purchasing decisions.

People make such decisions on the margin. They weigh whether to buy one more or produce one more of something. When I decide whether to buy a second cup of coffee in the morning, I am comparing the price of a cup of coffee to the additional satisfaction I will get from the second cup. one additional cup is “on the margin.” Because this “marginal utility” diminishes with increased consumption, I am unwilling to pay as much for the second cup as the first. For this reason, neoclassical economists are sometimes referred to as marginalists.

Applying utility theory and mathematics, classical economists constructed equations or models that sought to replicate utility-maximizing decisions. neoclassicals, like Marshall, separated the active participants, or agents, in the economy into households and firms. Adding the use of calculus, and in particular optimization techniques, it is possible to model household decision makers as utility maximizers and predict behavior. Similarly, the math allows for modeling decision makers in firms as profit maximizers. In Marshall’s mathematical models, the household optimization equation yielded the demand for goods, while the firm optimization equations yielded the supply of goods.

This allowed Marshall to extensively develop the supply-and-demand model taught in every economics class today. It is arguably the most important concept in modern economics.

While mathematical models abstract from a lot of interesting context and color, being able to express relationships in this clear-cut way is the first step toward creating testable hypotheses. Marshall also placed equal weight on empirical and deductive analysis, seeking to understand the real world. he made enormous strides in moving us toward modern economic science.


Should Economics Be a Science? thE ShIFt to ScIEntIFIc thInKInG in economics was more evolution than revolution. It didn’t happen overnight. not all economists were willing to pursue a scientific approach to economics. In fact, many clung to the philosophical approach with reason.

Gustav von Schmoller (1838-1917) and others from the German historical school and Austrian school argued that mathematically oriented marginal thinking abstracts too much from the historical and institutional framework that is important to outcomes. They argued for historical specificity, saying that principles derived from one period are not likely to apply without modification to other periods because the world is always changing and evolving. human character and wants are, to some degree, products of circumstances and shifts over time. If these are not built into the analysis, the results are meaningless. And it is simply impossible to build this into the mathematical analysis—or at least it was around the turn of the last century.

It was not all black or white with thinkers all lining up on one side of this debate or the other. Despite being a mathematician and a marginalist, Alfred Marshall was sympathetic toward the German historical school and the Austrians. he spoke fluent German and spent long spells in Dresden and Berlin studying with German economists. his methodology involved focusing on individuals (Mill’s methodological individualism), but his purpose was to build an understanding of the social organism. Marshall was neither trying to limit analysis to individuals, nor trying to abstract from the social and historical environment.

While he was interested in the past and believed much information could be derived from an examination and analysis of history, he believed that history alone could not provide all the answers. observation of history does not reveal direct causes. he believed it takes more intensive empirical analysis to uncover causes and linkages. At the same time, Marshall believed that economics cannot avoid accepting certain universal principles of human behavior and physical reality. Thus, there are limits to the inductive method and data analysis. he agreed with von Schmoller that induction and deduction are both needed for scientific thought “as the left foot and the right foot are both needed for walking.”

Marshall argued that deduction has to be limited and tested by empirical analysis, but he also warned against blind empiricism. he argued that the most “treacherous” researchers of all are those who claim to let the facts and data speak for themselves. By doing so, they often are simply avoiding telling the reader what part they have played in building the argument. to Marshall, all research and analysis is unavoidably guided by the perceptions of the writer, and hence that individual’s world view and intellectual model.

like members of the German historical school, the Austrian economists, including ludwig von Mises (1881-1973), Friedrich von hayek (1899-1992), and Frank Knight (1885-1972), argued that the economy evolves. It is structurally in motion, defying the kind of rigid definition that mathematical rigor and statistical methods require. uncertainty prevails, and according to them, the economy is also individualistic Ludwig von mises


and subjective, defying the kind of objective scientific analysis employed by natural scientists. While the Austrians accepted the idea of defensible premises and deductive reasoning, their other considerations allowed them to excuse deviations of predictions from actual outcomes. They did not believe that their premises or arguments were falsified by failed predictions.

They believed that the social sciences should not be held to the same standard as the natural sciences. Economics deals with human beings, not mindless atoms or billiard balls that go wherever they are pointed. In economics, subjects breathe and are self-determining. Deviations from the predictions of theory should be expected.

The Depression and Beyond

on thE othER SIDE oF the Atlantic ocean, the Americans were also struggling with methodological issues. In 1928, American engineer-turned-economist E. c. harwood (1900-1980) had tried to warn others of the economic collapse his models predicted. he was later horrified by the economic devastation he observed in the heart of the Great Depression. This led him to seek an approach to economics that could provide answers, an approach that could empower individuals to make better decisions even in difficult times.

Based on his own ideas and the transactional approach of philosophers John Dewey and Arthur F. Bentley, harwood called for economics to apply an objective, scientific approach. harwood’s American Institute for Economic Research (AIER) was formed in 1933 on the foundation of a scientific approach to economic research. But it was not until 1973 that harwood and Rollo handy published a fully developed presentation of AIER’s methodology as Useful Procedures of Inquiry. It called for an iterative approach to building conjectures (hypotheses or models) based on observation and deduction followed by testing to see if the explanation is adequate for resolving the immediate problem.

The authors argued that additional description may be added or that new information or revelations may motivate drastic revisions of the earlier description. They argued that research is an open-ended process.

harwood also expressed concern about the pervasive use of advanced mathematics in economics. he argued that, in many cases, it is entirely appropriate and serves the analysis. In others, it seems more a way of adding an air of scientific credibility to poor arguments. According to harwood, bad economics is not made better by mathematics. Bad economics is bad economics, no matter how it is communicated.

harwood may have been one of the first to argue for economic science in those terms, but he was not alone. Motivated by logical positivism, English economist terence hutchison (1912-2007) argued that economists need to assume the responsibility of empirical science. Probably shaped by a stint as an intelligence officer in World War II, he argued that economists sometimes make statements that are loose and vague and offer little supporting evidence. he thought of this as sloppy research. he thought it was time for economists to undertake the more challenging work of

e. c. Harwood


using precise language, making clear-cut assertions, and then testing them. This was a bold foray into a modern positive approach to economics.

Another economist whose work was motivated by the Great Depression was John Maynard Keynes (1883-1946). Keynes’ policy recommendations had fallen on deaf ears because they were not supported by the accepted neoclassical theory. Idealistic assumptions about automatic market adjustments and full employment stood in opposition to the economic holocaust on the streets. Keynes wrote his General Theory to provide the theoretical underpinnings for government actions he had proposed.

A man wholly unconstrained by conventional thinking, Keynes redefined consumer theory and explained the role of expectations in decisions involving business investments in plant and equipment. he saw spending and saving as two sides of the same coin and saving as providing the funds for investment. Yet, he highlighted the lack of a mechanism that would ensure the balance of these as necessary for full employment. The theory dazzled because it seemed at once profound and obvious.

Keynes did not perform empirical studies or test theories. Methodologically, Keynes’ views appear to have been diametrically opposite to those of harwood and hutchison. In a letter to economist and colleague Roy harrod written in 1938, Keynes argued that, first and foremost, economics is a branch of logic, a structured way of thinking about a certain class of problems. to him, in content, economics was a moral science. This puts him closer to Smith than Marshall or hutchison in approach, although his models reflect the influence of his teacher, Alfred Marshall.

Keynes was a theorist. he believed the business of economics was the progressive improvement of models, where models are a way of making sense of observations. he thought if he were to fill in real numbers for the variables in his models, it would somehow reduce their application by reducing their generality, limiting them as modes of thought. Reflecting themes like those of his Austrian colleague Friedrich von hayek, he also argued that, unlike the objects of the natural sciences, the objects of economics are not homogeneous through time. They are transitory in some sense, and the challenge is finding a system of logic that accommodates the stylized facts and sequences of the economy.

In his discussions of methodology, one might argue that rather than explaining what economics is, Keynes was describing more what he did as an economist. he was clearly a theoretician who tried to make sense of his observations so as to propose effective policies. he also famously was quoted as saying that when he was provided evidence that showed he was wrong, he changed his theory. he clearly was not opposed to having someone else produce empirical studies that falsified his theories and was willing to use that information in the reformulation of hypotheses.

In contrast, MIt professor Paul Samuelson (1915-2009), later a nobel Prize winner, promoted a rigorous scientific approach to economics. his operational positive approach was antithetical to Keynes’ moral science. According to Samuelson, not only was the objective of economics to understand and measure the economy as it is, he thought it critical that the models themselves and the assumptions on which they are based mimic the actual processes they explain. he believed that purely abstract assumptions and models would lead to erroneous conclusions. he built Paul samuelson

John maynard Keynes


analyses on assumptions that were measurable attributes of the real-world process and constructed statistical or mathematical equivalents of observable processes. he had little confidence in predictions or explanations made from unrealistic assumptions.

Samuelson also made careful use of another aspect of the scientific approach used in the natural sciences: changing one variable while holding all the other variables constant. If there are many things changing at once, it is hard to know what is causing what change. Allowing only one driving factor to change at a time makes it possible to isolate causes and effects. In pursuit of some traction, a lot of loose gravel can be overcome by judicious use of the philosophical and often vague phrase “all else equal.” one of the most commonly used phrases in economics, this is often given by the latin “ceteris paribus.”

using ceteris paribus to cover a vague collection of unknowns can be problematic. one of nobel Prize winner Milton Friedman’s (1912-2006) earliest and most popular articles was an attempt to sort out the ceteris paribus conditions underlying the demand curve taught by Alfred Marshall. It was an attempt to bring clarity and practical application to one of the most widely used theoretical notions—demand.

Data Makes a Difference

thE IncREASInG AvAIlABIlItY oF RElIABlE data and computational assistance played an important role in the development of rigorous methodologies. unmotivated by other considerations, data collection may be haphazard, not collected systematically according to a well-designed process that ensures completeness, consistency, and accuracy. Statistical analysis performed on unreliable data is misleading at best. Prior to the Great Depression, economic data was not reliable.

The world was blindsided by the Depression because data collection was almost nonexistent. Awakened to the problem, governments began systematically collecting important economic data in the aftermath. Even with the data collection process initiated, it takes many years of data to make any useful inferences. In the united States, the most important macroeconomic data series were collected by the government from 1946-47 forward. At about the same time, economists also began privately reconstructing estimates on these series for earlier years for which no official data had been collected. computing devices began to appear after World War II, with early mainframe computers becoming relatively common in the late 1960s. The first widely available personal computer with significant capacity was the IBM Pc in 1982. As data and computing machines arose, empirical testing of economic theories could begin in earnest.

Testing the Theories

AS thE DAtA AnD toolS became available, economists sought to update their approaches, and the science took another large step forward. In 1946 and 1947, Princeton university’s Richard lester (1908-1997) surveyed firms to see if they actually ran their businesses in ways suggested by the neoclassical theory of the firm.


In 1956, Austrian economist Fritz Machlup (1902-1983) argued that the evidence showed that firms do not always attempt to maximize profit, which was the accepted theory. This forced people to look at how real-world firms actually operate.

Even Keynes’ theory fell victim to the rise of economic science. The honeymoon for Keynes’ theory was cut short by world events and counter-evidence. Keynes had written The General Theory in 1936 as a theoretical basis for government intervention in the economy during the Great Depression. he defended the book briefly but suffered a heart attack in 1937. Slow to recover, he devoted what energy he had to helping the British government finance World War II and to reconstructing the international monetary system directly after the war. There was little time to provide further defenses of his theory. he died in 1946.

The early counter-evidence to Keynes’ theory came from a Russian economist at harvard who challenged one of its core elements. nobel Prize winner Simon Kuznets (1901-1985) used historical data from as early as 1869 that he had constructed for the united States government and the national Bureau of Economic Research. In studies published in 1942 and 1946, Kuznets showed that Keynes’ explanation of consumer spending behavior simply did not hold up to empirical scrutiny. consumer spending forms roughly two-thirds of total demand in the u.S. economy. If you cannot explain consumer spending, then you cannot explain how large-scale market economies operate.

limited by the data and computing facilities available in his time, Kuznets did not test Keynes’ theory with regression analysis or advanced statistics. Rather, he noted that the equations implied by Keynes required that consumer spending and disposable income should not remain in a fixed proportion over time. he simply divided one by the other and showed that the ratio did not change significantly, despite income increasing over the time period.

nonetheless, Kuznets’ method was consistent with Mill’s—state the hypothesis based on theory and assumptions, and then test empirically. This approach was widely embraced throughout the 1950s and beyond and was formalized in what some later referred to as the hendry approach, after econometrician David hendry of the london School of Economics. This approach remains one of the most widely used approaches to empirical economics even today.

nobel Prize winner Franco Modigliani (1918-2003) in 1949 and harvard economist Arthur Smithies (1907-1981) in 1954, among others, attempted to patch up Keynes’ consumer spending theory in a series of empirical studies, but they ultimately failed. however, the empirical tests led to the development of new hypotheses—in this case, the life-cycle hypothesis of Modigliani, and the permanent income hypothesis of Milton Friedman.

An Empirical Methodology Emerges

AS ShoWn In thE PREvIouS examples, economists embracing the new methods started by adopting the falsification approach of Mill, looking at existing theories or constructing new ones by deduction, and then testing them empirically


using statistical methods. This was consistent with Karl Popper’s method: construct a hypothesis from theoretical deductions, and then perform statistical tests on data in attempts to disprove or falsify the assertions.

According to Popper, one can never prove any assertion. one can only disprove it. It is a logical problem known as the problem of induction. You cannot prove a generalization, that something is universally true, with a limited number of observations. Just because we have not seen any exceptions to something doesn’t mean that those exceptions don’t exist. of course, to the extent that the assertion survives a wide variety of tests over many time periods and conditions, we become more comfortable with it. Despite this, it may ultimately be disproved or be subsumed in a larger framework.

As these methods became more widely used, economists began to produce results that raised doubts about the explanatory power of theories or the realism of assumptions. Milton Friedman attempted to address these challenges by recasting the focus of economic science. In “The Methodology of Positive Economics” (1953), he argued that the purpose of positive economics is not to explain, but rather to predict.

he asked, “What do we really want from a science of economics?” he argued that we want to understand economic relationships so that we can predict the results of changes in various factors that influence the economy. Such factors include fiscal and monetary policy, supply shocks, technological changes, and international trade shifts.

Prediction may offer an indirect understanding of causal linkages and measurable behavior. But in the final analysis, according to Friedman, we do not need to know the psychology of why a consumer spends more money when he or she feels more confident about the economy. We simply need to know that the consumer does. It is better if we know by how much they increase spending.

According to Friedman, the ultimate test of a theory is its ability to predict. Sorting out whether the assumptions or premises are realistic, in the sense that they reflect actual behavior, is useless. We do not really care whether or not consumers weigh marginal utilities and prices, he argues. We want to know how they will respond, not why. The issue is prediction. That the assumptions are unrealistic only matters if it affects the predictive power of the theory.

In billiards, if we want to predict the shot taken by an expert in the game, then we do not need to consider what is going on inside the expert’s head. It doesn’t matter if the expert does it by feel, by the stars, or by divination. Even though the expert may not know anything about math or physics, a simple model using geometry and mechanics will give an amazingly accurate result. That is what matters to Friedman.

If economists focus on this, he says, economic science is possible. Positive economics can be an objective science like chemistry or physics. As such, positive economics can balance normative thinking and aid policy making.

Friedman’s form of positive economics has long had a special identity. Some economists have argued that Friedman’s methodological stand is not what it seems to be, that it is not positive but rather is instrumental. he views ideas or theories as only having meaning or value when put to action, so that the usefulness of ideas is what validates them. Moreover, he seems to argue that attempting to build models for

Karl Popper

milton friedman


more than prediction is confusing, muddled, and destined to fail. This may be a more restrictive version of the positive approach, but it provides a definition of economic science that is workable.

Friedman, like Keynes, was perhaps explaining the way he went about his work as an economist rather than writing in the broadest sense about methodology. There are specialists in economic methodology, and there are working economists trying to explain what they do. These two have quite different points of view and are attempting to do very different things. As a result, they draw decidedly different conclusions.

Methodologists tend to focus on how theories are developed, arise to acceptance, are defended, and are disproved. Working economists are more often looking for or trying to describe a mode of research that effectively and efficiently generates good results. And, as we saw with Friedman and Samuelson, they don’t always agree on what constitutes good results.

Economics as a Science

At thIS PoInt In thE evolution of economics, economists like Friedman and Samuelson were slowly making sense of what they were doing. While positive economics was finding its way, there was still a gap between positive theory and positive practice. This gap was to be addressed, at least in part, by progress in econometric theory. Econometrics is the mathematical and statistical engine that drives empirical and theoretical research in economics. The science of economic (econo) measurements (metrics), econometrics is the sum total of measurement, statistics, and mathematics applied to economic analysis.

According to one approach, rather than attempting to broadly search data sets for potential relationships between economic measurements, it makes more sense to start with what we think we know and build a hypothesis. This is, after all, the scientific method—construct the hypothesis, test the hypothesis, either falsify the hypothesis and reform the theory, or let the hypothesis stand for another test. While it is not possible to confirm hypotheses (only falsify them), after enough tests they may become, in the words of E.c. harwood, “warranted assertions.” This is also the approach outlined by Popper in 1959.

With the adoption of this approach, economists were using the same basic research approach as natural scientists, with an important exception: Economists were unable to construct reproducible experiments. Economists could not do repeated trials of experiments to allow them to perform certain kinds of tests. Without experiments, they are only able to analyze things that have occurred under the circumstances in which they occurred. Something may appear to be true only because of the limited experience we have had with it.

Most economists want to be scientific. It raises the credibility of their work, offers a means for evaluating the work of others, and creates a more structured approach to research. For these reasons, economists rushed to incorporate mathematical models that offer enormous advantages to providing precision in the statement of theories. Mathematical models are clear, unequivocal statements of systems of linkages between


measurable economic variables. From them, it is straightforward to create testable hypotheses that then can be examined and tested with statistical methods. At the same time, enormous progress was made in the statistics and computing used to perform the tests.

By 1969, at least formally, economics was a science. It was the first year that the Royal Swedish Academy selected an economist as the winner of the nobel Memorial Prize in Economic Sciences, commonly referred to as the nobel Prize in Economics. officially, it is now the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred nobel. (Sveriges Riksbank is Sweden’s central bank.) The important point, though, is that the prize is for “economic science” and not “economics.”

That economists generally regard the receipt of the nobel Prize as the pinnacle of economics suggests that economists also regard economic science as a definition of their field.

The first economists awarded the prize were Dutch and norwegian economists Jan tinbergen (1903-1994) and Ragnar Frisch (1895-1973). Frisch was a leader in the economics-as-a-science movement and invented the words econometrics and macroeconomics. tinbergen was an economist cross-trained in mathematics and physics who specialized in empirical models. tinbergen and Frisch were neither ivory-tower theoreticians nor musing philosophers. The standard for future nobel Prize winners was set high.

The prize has been somewhat controversial. unlike the natural sciences, economic science has broad political and social implications. Friedrich von hayek argued against the nobel Prize, even as he received it, because he thought that winning the prize bestowed a sense of authority on the receiver. It presents a platform for the winner to make normative assertions, even though the prize was awarded for their contributions to positive economics. The temptation might be too great for ideologically motivated prize winners.

The awards are usually given long after the key works of the recipients are published—often 25 years or more after. This is because an important test of the work is often how influential the work has been. It takes time for the influence to be felt. By then, the winner is often at a different institution, and the key results have been displaced by other research. This does not necessarily diminish the work. The issue is whether the work advanced the science.

Keynes was dead by the time nobel prizes for economics were being awarded. his friend and colleague Sir John hicks (1904-1989) did receive the nobel Prize in 1972 (along with American Kenneth Arrow, b. 1921). hicks built a testable mathematical expression of Keynes’ theory, although some people question whether it accurately captures Keynes’ prose. hicks published his “little apparatus,” as he called it, in 1939 in Econometrica, the leading journal of econometrics. A form of his model, the IS-lM model, is still included in nearly every major macroeconomics textbook throughout the world. Properly calibrated with data, it forms the basis of large-scale computer forecasting models used by government agencies, financial firms, and private economic think tanks.

Jan tinbergen

sir John Hicks


Progress as a Science Continues

WhIlE EconoMIcS coulD BE cAllED a science by 1969, the approach was arguably still tied to Mill’s deductive approach. like other sciences, it required attempts to falsify testable hypotheses with constructions based on theory.

Most people expect science to be unbiased and objective. While the falsification approach avoids confusing coincidental changes in economic variables with causal relationships, it also starts with theoretical assumptions about how the economy or market works. This means that it is possible to bias your empirical results by your theoretical assumptions and data choices. But how do you avoid this?

The falsification approach came under attack in the late 1970s and early 1980s, most notably from American economist christopher A. Sims (b. 1942). Sims won the nobel Prize in 2011 for his atheoretical approach to econometrics. In short, he attempts to make no theoretical assumptions in his empirical analysis, but rather lets the data tell him what the relationships are. to understand Sims’ approach, we need to back up just a step or two.

In the 1970s, economists became more convinced than ever that everything affects everything in the economy. to say this another way, they discarded the idea that a few exogenous forces, like government or money, were driving economic activity. They now view the economy as a sea of markets, with flows in, out, and across markets. ultimately, the economy reaches general equilibrium, the resulting balance across markets when everyone has played out their interests and individual markets have all cleared. In this world, limited models and relationships do not make sense.

Based on this notion of general equilibrium, in 1976 Robert E. lucas, Jr. (b. 1937), another American nobel Prize winner, renewed the argument that the relationship that Keynes proposed to explain consumer spending makes no sense. In a nutshell, Keynes said that it was income that determines consumer spending. The problem is that consumer spending (personal consumption expenditure) is the largest single component of aggregate demand, which determines aggregate income. In other words, the argument is circular. At the very least, income and consumer spending are mutually dependent. You can’t determine one without the other; they must be determined simultaneously. Income is also tied to other factors that must be determined simultaneously. In fact, everything must be determined simultaneously.

In this kind of environment, identifying a few simple relationships is dangerous. Statistical theorists had demonstrated that if such variables are not estimated simultaneously, the computed results are skewed—shifted by simultaneity bias. There’s no way to get around it. looking for singular causes to economic events is hazardous.

This is complicated by government policy. According to lucas, there is a fundamental problem with the math we use to perform empirical research and create forecasts. The economy restructures itself every time a policy changes—and policies are always changing. using fixed mathematical expressions in computers to predict the impact of policy changes simply cannot work. The policy change itself implies

christopher sims

robert Lucas


a change in the equations. This lucas critique casts severe doubts on the computer models used by the Federal Reserve and by private forecasting organizations. All our work was suspect.

In the midst of this comes Sims, aided by the wide availability of powerful computers. his vector autoregressive (vAR) method allows researchers to put every variable they can find into the analysis as well as all the historical values of every variable. Some call them “kitchen sink models,” because you basically put everything you know into the model and let the computer sort it out. like a giant machine, the analytical technique grinds out the relationships, makes optimal use of all of the information given, and makes forecasts. And, as Friedman argued, predictions are the most important thing.

In fact, prediction is the strength of the vAR. The method also makes it possible to estimate period by period the impact of a change in each variable on each other variable in the economy. In the presence of all other information, this tells us something about what causes what in the macroeconomy. conversely, it can tell us how much of the change in one variable is caused by a change in every another. Most importantly, all of this is done without the researcher assuming he or she knows anything about how the economy really works.

The development of the vAR method was a critical step toward an unbiased, scientific approach to macroeconomics. Recognized as such, it took the profession by storm. vAR studies on every imaginable topic in macroeconomics and finance were published in large numbers throughout the 1980s and 1990s. The technique is still widely used.

While some still remember the debates between Sims and oxford’s Sir David hendry (b. 1944) on falsification versus the atheoretical approach, most have accepted that each approach has its value and its limitations. But we now have the means to examine large-scale systems in a rigorous way without having to make assumptions potentially motivated by political or ideological beliefs that may bias the results. Through the work of Sims, it is easier to separate normative and positive arguments, further advancing economics toward a science.

In related work, Sims, and separately Sir clive W. Granger (1934-2009), another nobel Prize winner, developed statistical methods useful in explicitly testing causal relationships through data in the general equilibrium world. This was an important advance because it made causality and prediction almost synonymous, further supporting Friedman’s perspective on positive economics and economic science.

Now and the Future

thE 250 YEARS oR So recounted here reveal enormous progress in making economics a science. limitations remain, but then, science never rests. In recent years, we have begun to attack the remaining challenges. We have the analytical tools, data, and technology. Progress and possibilities have been encouraging.

clive W. Granger


Economics is a social science, yet economists have been criticized and have criticized themselves for not better incorporating the humanity of those who make up the economy. If people are not inanimate objects but are self-directing, intelligent participants in the economy, then they need to be considered explicitly as such as they function in real-world markets. Their ideas, expectations, and reactions must be incorporated into the analysis. uncertainty that is at the heart of the human condition must also be addressed.

From the earliest days, economists realized that economies, like all human relationships, constantly change and evolve. continual structural change has to be embraced as part of any rigorous social science.

People and their relationships are neither simple nor proportional, so why would we expect simple linear economic models to properly describe them?

People are different, relationships are different, and businesses and industries are different. Yet economists have not fully dealt with that.

The mention of physics or chemistry often evokes images of laboratories and test tubes. Yet economists do not directly conduct experiments to see if they can reproduce effects.

While economists have been criticized for these shortcomings in their methods, the critics are often unaware that economists have made enormous strides in each of these areas. Rather than being a poor cousin to the natural sciences, economics is rising as a model for discovery.

For at least 50 years, economists have been dealing with uncertainty—at least the kind of uncertainty that can be described by statistics. Statistics bring a kind of order to uncertainty. For example, no one can know how long any one person will live, but an actuary can do a pretty good job of estimating how long a group of people will live on average.

other approaches are emerging. one is an application of nonergodic statistical theory. This is a broad segment of statistics that deals with more radical forms of uncertainty. Possibility theory, introduced in 1978 by Berkeley mathematician lotfi Zadeh (b. 1921), is a mathematical theory of uncertainty that forms an alternative to probability theory. There are advances daily that let us deal better and more realistically with uncertainty.

Most models today are expressed in terms of simple equations that allow for random events to create change. This culminated in the rational expectations hypothesis (REh) of Indiana university’s John Muth (1930-2005) around 1960 and was extended to macroeconomics by Robert lucas in the early 1970s. It was a theory that proved very fruitful to economic science.

As Friedman said, it is all about prediction. Informal predictions of individuals are called expectations. According to the REh, the expectations of individuals are on average (over time and space) the same as those suggested by theory. People efficiently use all available information in decision making because it costs them when they make mistakes. As a result, while they are not always right, they are also not systematically wrong. In fact, on average, their predictions are correct. After all, how could they be wrong about the economy? They are the economy.


Rational expectations suggest that people do not make changes—buy something, sell something, change jobs—based on old information. They only change directions when there is new information—news—that they need to react to. In the real world, information arrives randomly, which means that people change directions randomly in response to news.

When applied to financial markets and many economic variables, rational expectations imply that the data on these measures must evolve as random walks. It appears that stock prices, exchange rates, GDP, and many other important variables are random walks. They are called random walks because the path they take is not unlike that of a drunken man when he walks: he is equally likely to step right or left or straight forward. he may take long steps or short, and where he will end up is mystery. It is the same with stock prices. They are equally likely to rise or fall, by a little or a lot, and no one can tell for certain what the stock price will be in a year.

At a minimum, this would seem to confirm the notions of the German historical school, the Austrians, and Keynes—expectations rule, and the economy is constantly changing and evolving. closer consideration of random walks in the early 1980s forced economists to question most of their earlier empirical results. The theory also implied that the long practice of dividing macroeconomics into business-cycle analysis and growth theory was impossible, and it was the source of misleading results. In many ways, the discovery of random walks in economics was not good news. It seemed destructive.

Then, clive W. Granger came up with the idea of cointegration. Basically, he argued that although economic and financial variables may evolve as random walks, two or more of them may walk together. This walking together or cointegration is equivalent to a long-term equilibrium relationship among the variables. timing doesn’t matter, nor do the specific relationships. Suddenly we were back in business, and random walks seemed less problematic. If timing and structure don’t matter to this new form of analysis, we suddenly had a tool that allows us to embrace the changing structure, loose relationships and timing, and randomness that seems to define the real world. After making our way through the fire, random walks started looking pretty good.

Economists are also dealing with the simplicity of their models despite a world of complex relationships. Since the beginnings of the mathematization of the discipline, economists have relied almost entirely on the simplest algebraic models. They relied on linear models in the face of a world that is decidedly nonlinear. linearity is the world of straight lines and proportional responses. The real world is not linear, and linear models are an unrealistic way to analyze such a world.

Differential calculus relies on linearizations to describe small, incremental changes (differentials) to perform optimization and many other tasks. Even in a nonlinear world, this works fine when changes are small. ohm’s law, relied on by electricians daily, is actually a linear simplification of a more complex relationship. linear isn’t an unreasonable place to start. It’s just not the place to stop.

Physicists had journeyed the same path. From the 1970s to the 1990s, they started examining the mathematics of nonlinear and complex relationships.


Economists noticed. catastrophe theory seemed to be a powerful tool in modeling massive breakdowns in systems, like the Great Depression or the financial crisis of 2007. chaos theory showed the world that many things are so complex that they appear random but actually are not. It seemed that the mathematics for describing more complex social and economic relationships had arrived. As economists worked to incorporate these innovations into their work, they began to realize that assuming linearity is a bit like the drunk coming home at night. he searches for his door key under the street light instead of where he dropped it in the bushes because the light is so much better there.

linear math is simple, and nonlinear math is not. Most economists are not yet trained to perform nonlinear analysis. But increasingly, they are getting that training, and economics as a science is advancing.

Some have argued that economics will never be a science like chemistry or physics until economists can conduct reproducible, lab-style experiments. This is changing, too. Thanks to American nobel Prize winner vernon Smith (b1927), advances in computers and widespread acceptance of the internet, economists can now conduct market experiments.

With the help of charles Plott (b. 1938) of the california Institute of technology, Smith was able to structure experimental markets in laboratories and on computers. Students buy and sell fictitious commodities to achieve objectives. In these controlled experiments, researchers are able to examine how markets move to equilibrium prices—from above or below, how fast, straight-line, or oscillating—for each kind of market structure. They can simulate competitive markets or monopolies. They can observe how buyers react to posted prices (as in grocery stores) or double-oral auctions (as in commodity exchanges). At last, economics is also an experimental science.

By using neural networks in other computer-based work, we can model the human brain and experiment with the way people learn, form expectations, and make decisions. There have also been forays into non-biological, virtual life. We can form individual virtual creatures that live and die, follow certain basic rules, desires, and limitations, and that feed, consume, work, and produce. These are virtual societies in our computer labs and are available for experimentation.

Economists have also struggled to capture the diversity of the real world in their models. Because the assumptions simplified the math and computing, early economists relied heavily on representative agent models. They assumed that all households, consumers, and firms looked the same.

If the representative agent is simply thought of as the average household or firm, this can allow fairly complex analysis. But it does not capture a lot of important, interesting, and revealing dynamics. It does not allow us, for example, to look at how economic policies affect different groups of people in the economy because everyone is identical in the models. Everyone is average.

obviously, everyone is not the same, nor do they live under the same circumstances. Some economists had attempted to create a few different classes of households and


firms to create some heterogeneity in their models. In many cases, the results were startling.

now that the computing power is readily available, economists have begun experimenting with agent-based models (ABMs), also called agent-based computational models. They construct computational objects that interact according to specific rules of engagement. These agents can form social groups, and entire economies can be constructed virtually in a computer program. The researcher can control the pace of interaction as agents step through time. Relationships are made and broken, transactions occur, wealth accumulated, and businesses formed. People live and die. Social psychology can drive individual behavior.

ABMs have been constructed to explain unstable systems and to show how crashes like the 2007 financial collapse can occur as the result of disproportionate responses to small changes. These have been explored in such publications as the Economist and Nature.

In each of these approaches, there are opportunities that were beyond imagination only a few decades ago.

A Final NoteMuch hAS hAPPEnED SIncE ADAM SMIth pondered the morality of the market and David hume made us separate our thoughts about the world as it is from the world as we might want it to be. Economics has become a science, as much as chemistry or physics.

Sure, it is a social science. Because it is about people and society and affects social policies, economists are often tempted to drift toward the normative to support initiatives consistent with their personal ideologies. Physicists don’t have to face legislation that would set the mass of certain subatomic particles. But that doesn’t make economics less of a science. It simply means that economists are people.

This means that we must be ever vigilant and stick to business. But, by focusing on clear-cut definitions, reliable data, and rigorous testing and guided by a positive approach to economics, economics is realizing its potential as a fully developed science.

As mathematical and statistical methods, computing technology, and data available have advanced, so has the science of economics. Economists are still strug-gling with the methodological implications. It is an exciting time to be an economist.


For Further Reading

Arrow, Kenneth J. 1951. Social Choice and Individual Values. new York : John Wiley.

Benthem, Jeremy. 1948. An Introduction to the Principles of Morals and Legislation. new York, hafner Publishing.

Bentley, Arthur F. 1954. Inquiry Into Inquiries: Essays in Social Theory, Boston: The Beacon Press.

Bentley, Arthur F. and John Dewey. 1949. Knowing and the Known. Boston: Beacon Press.

Dewey, John. 1951. Logic: The Theory of Inquiry. new York: henry holt and company.

Friedman, Milton. 1949. “The Marshallian Demand curve.” Journal of Political Economy 57, no. 6 (December): 463-95

Friedman, Milton. 1957. A Theory of the Consumption Function. Princeton: Princeton university Press.

Friedman, Milton. 1970. “The Methodology of Positive Economics” in Essays in Positive Economic, 3-43. chicago: university of chicago Press.

Frisch, Ragnar. 1925. “Kvantitativ formulering av den teoretiske økonomikks lover” [Quantitative formulation of the laws of economic theory]. Statsøkonomisk tidsskrift 40: 299–334.

Granger, c. W. J. 1969. “Investigating causal Relations by Econometric Models and cross-Spectral Methods.” Econometrica 37, no. 3 (August): 424–38.

handy, Rollo and Edward c. harwood. 1973. Useful Procedures of Inquiry. Great Barrington, MA: Behavioral Research council.

harrod, Roy. 1938. “Scope and Method of Economics.” Economic Journal 48, no. 191 (September): 383–412.

hayek, Freidrich A. 1939. Profits, Interest and Investment: and other essays on the theory of industrial fluctuation. london: George Routledge & Sons.

hayek, Freidrich A. 1948. Individualism and Economic Order. chicago: university of chicago Press.

hayek, Freidrich A. 1979. The Counter-revolution of Science: Studies on the Abuse of Reason. Indianapolis: liberty Press.

hayek, Freidrich A. 1994. The Road to Serfdom. chicago: university of chicago Press.

hayek, Freidrich A. 2012. “The transmission of the Ideals of Economic Freedom.” Econ Journal Watch 9, no. 2: 163-69.

hendry, David F. 1980. “Econometrics – Alchemy or Science?”, Economica 47, no. 188 (March): 387-406.

hendry, David F. 1995. Dynamic Econometrics. oxford: oxford university Press.

hicks, John. 1946. Value and Capital. oxford: clarendon Press.

hume, David. 1992. A Treatise of Human Nature. Buffalo: Prometheus Books.

hutchison, terence W. 1960. The Significance and Basic Postulates of Economic Theory. new York : A.M. Kelley.


Jevons, William Stanley. 1931. The Theory of Political Economy. london: Macmillan and co.

Keynes, John Maynard. 1962. The General Theory of Employment, Interest and Money. new York: harcourt, Brace, Jovanovich.

Knight, Frank. 1924. “The limitations of Scientific Method in Economics”. in Trend of Economics, edited by Rexford G. tugwell, new York, A.A. Knopf.

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Positive Economics: Economics Becomes a Science How a ... · normative judgment. Many studies have shown that, for most people, their normative and positive beliefs are independent