sample economic model research paper

Kristin A. Van Gaasbeck

Department of economics, college of social sciences and interdisciplinary studies, california state university, sacramento, writing in economics :: components of a research paper.

An economics research paper includes the parts listed below. Some of these may be, and often are, combined into sections of the research paper. Depending on the nature of the research question, some parts may be emphasized more than others.

I've condensed information from several different sources. This is cursory content on how to write in economics, please make use of the additional resources . Also, every researcher has his or her own opinion about the best way to proceed. The information I've collected below is one of many possible ways to approach an undergraduate or graduate research project in Economics.

The abstract is a description of your research paper. The writing style of the abstract is very condensed - it should be no more than 350 words (or 5-6 sentences). The abstract is designed to identify the following to a potential reader:

• The research question What is the question that is the focus of your research? A good research question is one that (i) doesn't have an obvious answer (otherwise, why bother researching it?) and (ii) is testable using data.
• Your contribution to the research on the subject What has the previous literature found and what is your contribution to general understanding of the economic problem/question.
• How you answer the research question How you use theoretical and/or empirical analysis to answer the research question.
• Results Your findings based on the aforementioned analysis

The abstract is written when the paper is completed. It should not be the same as your introduction - the audience is different.

Introduction

The introduction is designed to both identify and motivate your research question. Like an essay you would write in other subjects, the introduction begins with a broad statement, and then narrows down to your specific research question.

In the end, make sure that you've done the following in your introduction:

• State your research question
• Motivate why the subject of your research is important to economists and other stakeholders
• Explain to the reader where your research fits into the subject.
• Identify your contribution to general understanding on the subject/research question
• Summarize how you intend to answer the research question
• State your general results and answer to your research question.

The first paragraph of the introduction is used to motivate why this research is important and of interest to economists and other stakeholders (e.g., parents and teachers in education economics, central bankers in monetary policy, and residents and businesses affected by pollution). It may conclude with a statement of your research question, followed by a discussion of who is affected by the economic issue under study. It is not appropriate to include personal anecdotes in a written research paper. Remember, you are motivating why the research should be of interest to the reader.

The second paragraph typically has more detail about how you plan to answer the research question, possibly citing other work closely related to your own research. In fact, many authors combine the literature review with the introduction in order to streamline this discussion. This paragraph may conclude with your general findings.

You should be able to write the first paragraph when you begin your research. The second paragraph can be written as you are concluding your research, as it draws on information from subsequent sections of your paper.

Literature Review

The literature review serves two main purposes:

• motivate why your research question is important in the context of the broader subject
• provide the reader with information on what other researchers have found (highlighting your contribution)

If someone has done a similar analysis to yours, tell us, and then explain how yours is different. Explain their findings, and then follow up with what you expect to find in your own research, and compare.

Some things to keep in mind for your literature review:

• Conduct a comprehensive search of the research on your subject Familiarize yourself with search engines in Economics (ECONLit is the most comprehensive) - do not rely on Google or other general search engines because they will link to you information that is not peer-reviewed research. A good general rule is as follows: if it is a paper not listed on ECONLit, it is probably not appropriate for a research paper in economics. Of course, there are exceptions. See my ECON 145 resources for more information on search engines .
• Create an annotated bibliography for the papers you plan to cite in your research paper. More information on annotated bibliographies is given below . This is a good step to take early on in your literature review search because it helps you keep track of the papers you plan to cite, and helps you to summarize information in one place. This will help you with the subsequent steps below.
• Identify which papers are most relevant to your research question It is easy to find lots of articles on one topic, but difficult to sort out which ones are important and relevant to your specific topic. You need to find the most relevant articles for your topic, and tell the reader why these are relevant articles for your topic specifically.
• Make an outline of your literature review Write an outline of your literature review. When writing your literature review, you want to organize the research of others into themes that you want to convey to the reader. Do not simply list papers chronologically and summarize the results of others. You should group papers by common themes.
• Critically read research papers You cannot read research papers like novels or the newspaper. Economics research papers are often dense and technical, requiring carefully reading. If you are not actively engaged as a reader, taking notes and writing questions to yourself as you go along, you are making poor use of your time and will not get much out of your literature review. See my page on Critical Reading for more information on strategies for how to read economics research papers.
• Be aware of plagiarism. This is very difficult for the novice researcher because some information is generally taken as known, while other information is not. The best way to get a sense for how to appropriately cite and attribute material is to read economics research articles. Avoiding plagiarism doesn't mean rewriting someone else's ideas in your own words. If you are using someone else's idea, whether in quotes or not, you must cite it. When in doubt, cite.
• common research questions in the subject (introduction),
• economic models used to answer related research questions (economic model),
• empirical methodologies common in the field (empirical methodology),
• data sources you may use in your analysis (data description),
• how to report your results (empirical analysis), and
• how to identify your contribution to understanding of the research question/subject (conclusion/analysis).

Economic Model/Empirical Methodology

This section (or sections) or your paper are designed to show how you intend to answer your research question using economic theory (economic model) and empirically (using statistical tests). For the novice researcher, it is useful to think of these two approaches as separate. This avoids the temptation to confuse them.

Economic Model

This is what you have studied in most of your other economics classes. For example, what happens to the price of housing when the population increases? Using demand-supply model, we know that an increase in population leads to an increase in the demand for housing, increasing the equilibrium price. In reading economics research papers, the economic model is often not identified because it is assumed the reader (economic researchers) are familiar with the underlying model. However, to the novice researcher, the model may not be obvious, so it is important to outline the model and include it in your research paper.

Your economic model is how you make predictions of what you expect to find in the data. Based on the simple example above, we'd expect to see a positive relationship between housing prices and population, ceteris paribus (e.g., holding all other variables in the demand-supply model unchanged).

Another important point is that your economic model is what implies a causal relationship between the economic variables. While you may detect a positive or negative relationship in the data, this alone tells you nothing about which variable is causing a change in the other variable. The economic model can be used to model this relationship. In the example above, we assume that in the model, a change in population causes a change in the housing price.

The economic model should make no mention of data, regression analysis, or statistical tests. The model is a purely theoretical construct, based on an abstract notion of how the world works. The empirical methodology section of your paper is how you plan to test these relationships in the data. An economic model is NOT a regression equation.

Finally, you should use an economic model that is common in the literature on your subject. Unless you are proposing a new model, you should rely on those used by other researchers in the field. This will allow you to use your literature review to justify your choice of model. Also, this is why the economic model is often embedded in the literature review of the paper. For novice researchers, I recommend keeping it separate, to make sure you understand how to use your economic model to conduct theoretical analysis.

Empirical Methodology

This is where you describe to the reader how you plan to test the relationships implied by your economic/theoretical model. First, you want to identify your dependent variable. This is the variable you are seeking to explain the behavior of. Next, you want to identify possible explanatory variables. These are the variables that could potentially affect your dependent variable.

Often in economic models, there are abstract notions of how some variables affect others. For example, human capital affects production, but how would we measure human capital in the data? You can find suitable proxies for a variable like human capital by familiarizing yourself with the literature.

So, how could a researcher go about testing the relationship between housing prices and population? First, we know that housing price is the dependent variable. Population is one explanatory variable, but are there others that affect housing prices? Yes. We know this from the demand and supply model that there are other variables that shift demand for housing (income, prices of substitutes and complements, expectations, tastes and preferences, etc.) and the supply of housing (input costs, expectations, the number of sellers, etc.). In order to isolate the effect of population on house price, we need to control for these other factors.

The most common strategy for empirical work regression analysis because it allows the researcher to isolate the correlation between two variables, while holding other explanatory variables constant (e.g., ceteris paribus from the model above). Often in the empirical methodology section, the researcher will point out potential estimation issues, highlighting the need for more advanced econometric techniques that go beyond ordinary least squares (OLS).

This section does not actually do any statistical analysis, but it may include a description of the data (see below). In advising students on research papers, I usually recommend the following breakdown for the empirical methodology section:

• Data description This is a description of the data you plan to use for your analysis. It usually includes a citation of the primary source, data frequency, how the data are measured, the frequency of the data, etc. The amount of detail depends on the nature of the data. Also, this is the section where you would report any modifications you make to the data.
• Preliminary data analysis This section reports summary statistics, histograms, time series plots, and other similar information. This section is designed to give the reader a sense of what your sample looks like. In reporting this information, you should be selective - more is not always better. You need to decide which information you need/want to convey to the reader and how to best convey it. See my Empirical Methods in Economics page for ideas on basic statistical analysis.
• Regression Equation Now, you're ready to remind the reader of your particular test and how you are going to go about using regression to test it. This section should include a regression equation, a discussion justifying this equation, and a description of the expected signs on the coefficients for each of the explanatory variables (spending more time on those that are of particular interest for your study). Remember, the regression coefficient measure the marginal effects of the explanatory variable on the dependent variable (holding the other variables constant, ceteris paribus). When justifying your regression equation and discussing the expected signs for the coefficients, you should make some clear connections back to your theory section and the literature review section of your paper. Also, make sure that you are using your regression equation to answer your research question. What is the testable hypothesis? Does this test answer your research question? See my Empirical Methods in Economics page for a simple primer on regression analysis.

Data Description

An alternative to the ordering mentioned above is as follows. You can begin with a regression equation, then provide a detailed description of the data, along with some preliminary data analysis. It is most common to have the data description as its own section of the paper - mainly to make it easier for readers to reference it if they plan to do similar research. You could then follow this Data section with an Empirical Methodology section that consists of the #3 Regression equation described above.

Empirical Analysis

This section is often titled "Results" in economic research papers, as it reports the results from your regression analysis above. There are commonly-used templates for reporting regression results. The best way to familiarize yourself with these templates is from the papers you cite in your literature review. You will see that it is common to report multiple regressions in one table, with the explanatory variables listed vertically on the left. See my page on Empirical Methods in Economics for more details.

The empirical analysis should include a table with your regression results, and your written analysis of these results. Note, this does not mean repeating the information in your regression tables. It means interpreting these coefficients in light of your economic model and comparing your findings to other papers from your literature review.

The conclusion usually consists of about three paragraphs. The first begins with a restatement of the research question, followed by a description of what we know about this research question from the literature (very concisely). Then the paragraph concludes with a brief description of the theoretical answer to the question.

The second paragraph begins with an answer to the research question, based on your empirical analysis. The researcher then proceeds to compare his/her findings to the consensus in the literature, pointing out possible reasons for differences and similarities. For example, perhaps you studied a different time period, or a different country. Perhaps you used a different measure of the dependent or explanatory variables.

In the final paragraph, it is common to draw policy implications from your research. In a practical sense, who cares about this research question (remember the stakeholders from the introduction..) and what can they do with this knowledge? Often the conclusion will point toward directions for future research, based on possible extensions to your research.

Bibliography/References

The bibliography contains complete references of the works that cited and referred to in your research.

It is essential that you give proper credit to all works that you cite, even if they are not included in your literature review. For example, if you obtained data from a publication that is not easily available, it would be appropriate to cite it in your data description and include it in your bibliography. Incomplete or inaccurate citations are akin to plagiarism, so please be sure to carefully check your references and keep track of them while completing your literature review.

In economics, it is most common to use APA style in citing references in the text of your paper and in creating a bibliography. For more information, see the APA style guide provided by the Library , or simply pick up a copy of the APA style guide if you will be using it frequently.

Annotated Bibliography An annotated bibliography is one that includes the reference (mentioned above), along with a few sentences describing the research and how it relates to your research paper. Often the description will begin with a statement of what the research found, followed by one or two sentences that are relevant to the research question you are studying.

Even though APA style calls for a double-spaced annotated bibliography, many researchers prefer a single spaced one. The Library has information on annotated bibliographies and I have posted an outstanding example from undergraduate Economic Research Methods .

The best annotated bibliographies are those written by students who have read the literature critically. See my page on Critical Reading for more information on strategies for how to read economics research papers. Even if an annotated bibliography is not assigned as part of your research project, it is a useful exercise for you to engage in, especially if you have to present your research orally or using a poster. If you are unable to write an annotated bibliography, then you are probably writing a poor review of the literature on your subject and a less than satisfactory research paper.

The Young Economist’s Short Guide to Writing Economic Research

Attributes of writing economics.

• The discourse is often mathematical, with lots of formulas, lemmas, and proofs.
• Writing styles vary widely. Some authors are very dry and technical while a few are quite eloquent.

Economics writing is different from many other types of writing. It is essentially technical, and the primary goal is to achieve clarity. A clear presentation will allow the strength of your underlying analysis and the quality of your research to shine through.

Unlike prose writing in other disciplines, economics research takes time. Successful papers are not cranked out the night before a due date.

General Guidelines for Quality Research

Getting started.

The hardest part of any writing assignment is starting. Economics research usually begins with a strong understanding of literature, and papers require a section that summarizes and applies previous literature to what the paper at hand. This is the best way to start.

Your writing will demonstrate that you understand the findings that relate to the topic.

Economists use the first few paragraphs to set up research questions and the model and data they use to think about it. Sure, it can be dry, but this format ensures the write and reader have strong grasp on the subject and structure of the work that follows.

Clear and Concise Work

Clarity is hard to achieve, but revising and reworking a paper ensures it is easy to read

• Organize your ideas into an argument with the help of an outline.
• Define the important terms you will use
• State your hypothesis and proceed deductively to reach your conclusions
• Avoid excess verbiage
• Edit yourself, remove what is not needed, and keep revising until you get down to a simple, efficient way of communicating
• Use the active voice
• Put statements in positive form
• Omit needless words (concise writing is clear writing)
• In summaries, generally stick to one tense

Time Management

Poor time management can wreck the best-planned papers. Deadlines are key to successful research papers.

• Start the project by finding your topic
• Begin your research
• Start and outline
• Write a draft
• Revise and polish

The Language of Economic Analysis

Economic theory has become very mathematical. Most PhD students are mathematicians, not simply economics majors. This means most quality economic research requires a strong use of mathematical language. Economic analysis is characterized by the use of models, simplified representations of how economic phenomena work. A model’s predictions about the future or the past are essentially empirical hypotheses. Since economics is not easily tested in controlled experiments, research requires data from the real world (census reports, balance sheets), and statistical methods (regressions and econometrics) to test the predictive power of models and hypotheses based on those models.

The Writing Process

Finding a topic.

There are a million ways to find a topic. It may be that you are writing for a specific subfield of economics, so topics are limited and thus easier to pick. However, must research starts organically, from passive reading or striking news articles. Make sure to find something that interests you. Be sure to find a niche and make a contribution to the subfield.

You will also need a project that can be done within the parameters of the assignment (length, due date, access to research materials). A profoundly interesting topic may not be manageable given the time and other constraints you face. The key is to just be practical.

Be sure to start your research as soon as possible. Your topic will evolve along the way, and the question you begin with may become less interesting as new information draws you in other directions. It is perfectly fine to shape your topic based on available data, but don’t get caught up in endlessly revising topics.

Finding and Using Sources

There are two types of economic sources: empirical data (information that is or can be easily translated into numerical form), and academic literature (books and articles that help you organize your ideas).

Economic data is compiled into a number of useful secondary sources:

• Economic Report of the President
• Statistical Abstract of the United States
• National Longitudinal Survey
• Census data
• Academic journals

The Outline

A good outline acts as an agenda for the things you want to accomplish:

• Introduction: Pose an interesting question or problem
• Literature Review: Survey the literature on your topic
• Methods/Data: Formulate your hypothesis and describe your data
• Results: Present your results with the help of graphs and charts
• Discussion: Critique your method and/or discuss any policy implications
• Conclusions: Summarize what you have done; pose questions for further research

Writing a Literature Review

The literature review demonstrates your familiarity with scholarly work on your topic and lays the foundations for your paper. The particular issues you intent to raise, the terms you will employ, and the approach you will take should be defined with reference to previous scholarly works.

Presenting a Hypothesis

Formulate a question, problem or conjecture, and describe the approach you will take to answer, solve, or test it. In presenting your hypothesis, you need to discuss the data set you are using and the type of regression you will run. You should say where you found the data, and use a table, graph, or simple statistics to summarize them. In term papers, it may not be possible to reach conclusive results. Don’t be afraid to state this clearly and accurately. It is okay to have an inconclusive paper, but it is not okay to make overly broad and unsupported statements.

Presenting Results

There are essentially two decisions to make: (1) How many empirical results should be presented, and (2) How should these results be described in the text?

• Focus only on what is important and be as clear as possible. Both smart and dumb readers will appreciate you pointing things out directly and clearly.
• Less is usually more: Reporting a small group of relevant results is better than covering every possible statistical analysis that could be made on the data.
• Clearly and precisely describe your tables, graphs, and figures in the text of your results section. The first and last sentence in a paragraph describing a result should be “big picture” statements, describing how the results in the table, graph or figure fit into the overall theme of the paper.

Discussing Results

The key to discussing results is to stay clear of making value judgments, and rely instead on economic facts and analyses. It is not the job of an economist to draw policy conclusions, even if the research supports strong evidence in a particular direction.

Referencing Sources

As with any research paper, source referencing depends on the will of a professor a discourse community. However, economists generally use soft references in the literature review section and then cite sources in conventional formats at the end of papers.

This guide was made possible by the excellent work of Robert Neugeboren and Mireille Jacobson of Harvard University and Paul Dudenhefer of Duke University.

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Methods Used in Economic Research: An Empirical Study of Trends and Levels

• Economics E-Journal 15(1):28-42
• 15(1):28-42

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Methods Used in Economic Research: An Empirical Study of Trends and Levels

The methods used in economic research are analyzed on a sample of all 3,415 regular research papers published in 10 general interest journals every 5th year from 1997 to 2017. The papers are classified into three main groups by method: theory, experiments, and empirics. The theory and empirics groups are almost equally large. Most empiric papers use the classical method, which derives an operational model from theory and runs regressions. The number of papers published increases by 3.3% p.a. Two trends are highly significant: The fraction of theoretical papers has fallen by 26 pp (percentage points), while the fraction of papers using the classical method has increased by 15 pp. Economic theory predicts that such papers exaggerate, and the papers that have been analyzed by meta-analysis confirm the prediction. It is discussed if other methods have smaller problems.

1 Introduction

This paper studies the pattern in the research methods in economics by a sample of 3,415 regular papers published in the years 1997, 2002, 2007, 2012, and 2017 in 10 journals. The analysis builds on the beliefs that truth exists, but it is difficult to find, and that all the methods listed in the next paragraph have problems as discussed in Sections 2 and 4. Hereby I do not imply that all – or even most – papers have these problems, but we rarely know how serious it is when we read a paper. A key aspect of the problem is that a “perfect” study is very demanding and requires far too much space to report, especially if the paper looks for usable results. Thus, each paper is just one look at an aspect of the problem analyzed. Only when many studies using different methods reach a joint finding, we can trust that it is true.

Section 2 discusses the classification of papers by method into three main categories: (M1) Theory , with three subgroups: (M1.1) economic theory, (M1.2) statistical methods, and (M1.3) surveys. (M2) Experiments , with two subgroups: (M2.1) lab experiments and (M2.2) natural experiments. (M3) Empirics , with three subgroups: (M3.1) descriptive, (M3.2) classical empirics, and (M3.3) newer empirics. More than 90% of the papers are easy to classify, but a stochastic element enters in the classification of the rest. Thus, the study has some – hopefully random – measurement errors.

Section 3 discusses the sample of journals chosen. The choice has been limited by the following main criteria: It should be good journals below the top ten A-journals, i.e., my article covers B-journals, which are the journals where most research economists publish. It should be general interest journals, and the journals should be so different that it is likely that patterns that generalize across these journals apply to more (most?) journals. The Appendix gives some crude counts of researchers, departments, and journals. It assesses that there are about 150 B-level journals, but less than half meet the criteria, so I have selected about 15% of the possible ones. This is the most problematic element in the study. If the reader accepts my choice, the paper tells an interesting story about economic research.

All B-level journals try hard to have a serious refereeing process. If our selection is representative, the 150 journals have increased the annual number of papers published from about 7,500 in 1997 to about 14,000 papers in 2017, giving about 200,000 papers for the period. Thus, the B-level dominates our science. Our sample is about 6% for the years covered, but less than 2% of all papers published in B-journals in the period. However, it is a larger fraction of the papers in general interest journals.

It is impossible for anyone to read more than a small fraction of this flood of papers. Consequently, researchers compete for space in journals and for attention from the readers, as measured in the form of citations. It should be uncontroversial that papers that hold a clear message are easier to publish and get more citations. Thus, an element of sales promotion may enter papers in the form of exaggeration , which is a joint problem for all eight methods. This is in accordance with economic theory that predicts that rational researchers report exaggerated results; see Paldam ( 2016 , 2018 ). For empirical papers, meta-methods exist to summarize the results from many papers, notably papers using regressions. Section 4.4 reports that meta-studies find that exaggeration is common.

The empirical literature surveying the use of research methods is quite small, as I have found two articles only: Hamermesh ( 2013 ) covers 748 articles in 6 years a decade apart studies in three A-journals using a slightly different classification of methods, [1] while my study covers B-journals. Angrist, Azoulay, Ellison, Hill, and Lu ( 2017 ) use a machine-learning classification of 134,000 papers in 80 journals to look at the three main methods. My study subdivide the three categories into eight. The machine-learning algorithm is only sketched, so the paper is difficult to replicate, but it is surely a major effort. A key result in both articles is the strong decrease of theory in economic publications. This finding is confirmed, and it is shown that the corresponding increase in empirical articles is concentrated on the classical method.

I have tried to explain what I have done, so that everything is easy to replicate, in full or for one journal or one year. The coding of each article is available at least for the next five years. I should add that I have been in economic research for half a century. Some of the assessments in the paper will reflect my observations/experience during this period (indicated as my assessments). This especially applies to the judgements expressed in Section 4.

2 The eight categories

Table 1 reports that the annual number of papers in the ten journals has increased 1.9 times, or by 3.3% per year. The Appendix gives the full counts per category, journal, and year. By looking at data over two decades, I study how economic research develops. The increase in the production of papers is caused by two factors: The increase in the number of researchers. The increasing importance of publications for the careers of researchers.

The 3,415 papers

2.1 (M1) Theory: subgroups (M1.1) to (M1.3)

Table 2 lists the groups and main numbers discussed in the rest of the paper. Section 2.1 discusses (M1) theory. Section 2.2 covers (M2) experimental methods, while Section 2.3 looks at (M3) empirical methods using statistical inference from data.

The 3,415 papers – fractions in percent

The change of the fractions from 1997 to 2017 in percentage points

Note: Section 3.4 tests if the pattern observed in Table 3 is statistically significant. The Appendix reports the full data.

2.1.1 (M1.1) Economic theory

Papers are where the main content is the development of a theoretical model. The ideal theory paper presents a (simple) new model that recasts the way we look at something important. Such papers are rare and obtain large numbers of citations. Most theoretical papers present variants of known models and obtain few citations.

In a few papers, the analysis is verbal, but more than 95% rely on mathematics, though the technical level differs. Theory papers may start by a descriptive introduction giving the stylized fact the model explains, but the bulk of the paper is the formal analysis, building a model and deriving proofs of some propositions from the model. It is often demonstrated how the model works by a set of simulations, including a calibration made to look realistic. However, the calibrations differ greatly by the efforts made to reach realism. Often, the simulations are in lieu of an analytical solution or just an illustration suggesting the magnitudes of the results reached.

Theoretical papers suffer from the problem known as T-hacking , [2] where the able author by a careful selection of assumptions can tailor the theory to give the results desired. Thus, the proofs made from the model may represent the ability and preferences of the researcher rather than the properties of the economy.

2.1.2 (M1.2) Statistical method

Papers reporting new estimators and tests are published in a handful of specialized journals in econometrics and mathematical statistics – such journals are not included. In our general interest journals, some papers compare estimators on actual data sets. If the demonstration of a methodological improvement is the main feature of the paper, it belongs to (M1.2), but if the economic interpretation is the main point of the paper, it belongs to (M3.2) or (M3.3). [3]

Some papers, including a special issue of Empirical Economics (vol. 53–1), deal with forecasting models. Such models normally have a weak relation to economic theory. They are sometimes justified precisely because of their eclectic nature. They are classified as either (M1.2) or (M3.1), depending upon the focus. It appears that different methods work better on different data sets, and perhaps a trade-off exists between the user-friendliness of the model and the improvement reached.

2.1.3 (M1.3) Surveys

When the literature in a certain field becomes substantial, it normally presents a motley picture with an amazing variation, especially when different schools exist in the field. Thus, a survey is needed, and our sample contains 68 survey articles. They are of two types, where the second type is still rare:

2.1.3.1 (M1.3.1) Assessed surveys

Here, the author reads the papers and assesses what the most reliable results are. Such assessments require judgement that is often quite difficult to distinguish from priors, even for the author of the survey.

2.1.3.2 (M1.3.2) Meta-studies

They are quantitative surveys of estimates of parameters claimed to be the same. Over the two decades from 1997 to 2017, about 500 meta-studies have been made in economics. Our sample includes five, which is 0.15%. [4] Meta-analysis has two levels: The basic level collects and codes the estimates and studies their distribution. This is a rather objective exercise where results seem to replicate rather well. [5] The second level analyzes the variation between the results. This is less objective. The papers analyzed by meta-studies are empirical studies using method (M3.2), though a few use estimates from (M3.1) and (M3.3).

2.2 (M2) Experimental methods: subgroups (M2.1) and (M2.2)

Experiments are of three distinct types, where the last two are rare, so they are lumped together. They are taking place in real life.

2.2.1 (M2.1) Lab experiments

The sample had 1.9% papers using this method in 1997, and it has expanded to 9.7% in 2017. It is a technique that is much easier to apply to micro- than to macroeconomics, so it has spread unequally in the 10 journals, and many experiments are reported in a couple of special journals that are not included in our sample.

Most of these experiments take place in a laboratory, where the subjects communicate with a computer, giving a controlled, but artificial, environment. [6] A number of subjects are told a (more or less abstract) story and paid to react in either of a number of possible ways. A great deal of ingenuity has gone into the construction of such experiments and in the methods used to analyze the results. Lab experiments do allow studies of behavior that are hard to analyze in any other way, and they frequently show sides of human behavior that are difficult to rationalize by economic theory. It appears that such demonstration is a strong argument for the publication of a study.

However, everything is artificial – even the payment. In some cases, the stories told are so elaborate and abstract that framing must be a substantial risk; [7] see Levitt and List ( 2007 ) for a lucid summary, and Bergh and Wichardt ( 2018 ) for a striking example. In addition, experiments cost money, which limits the number of subjects. It is also worth pointing to the difference between expressive and real behavior. It is typically much cheaper for the subject to “express” nice behavior in a lab than to be nice in the real world.

(M2.2) Event studies are studies of real world experiments. They are of two types:

(M2.2.1) Field experiments analyze cases where some people get a certain treatment and others do not. The “gold standard” for such experiments is double blind random sampling, where everything (but the result!) is preannounced; see Christensen and Miguel ( 2018 ). Experiments with humans require permission from the relevant authorities, and the experiment takes time too. In the process, things may happen that compromise the strict rules of the standard. [8] Controlled experiments are expensive, as they require a team of researchers. Our sample of papers contains no study that fulfills the gold standard requirements, but there are a few less stringent studies of real life experiments.

(M2.2.2) Natural experiments take advantage of a discontinuity in the environment, i.e., the period before and after an (unpredicted) change of a law, an earthquake, etc. Methods have been developed to find the effect of the discontinuity. Often, such studies look like (M3.2) classical studies with many controls that may or may not belong. Thus, the problems discussed under (M3.2) will also apply.

2.3 (M3) Empirical methods: subgroups (M3.1) to (M3.3)

The remaining methods are studies making inference from “real” data, which are data samples where the researcher chooses the sample, but has no control over the data generating process.

(M3.1) Descriptive studies are deductive. The researcher describes the data aiming at finding structures that tell a story, which can be interpreted. The findings may call for a formal test. If one clean test follows from the description, [9] the paper is classified under (M3.1). If a more elaborate regression analysis is used, it is classified as (M3.2). Descriptive studies often contain a great deal of theory.

Some descriptive studies present a new data set developed by the author to analyze a debated issue. In these cases, it is often possible to make a clean test, so to the extent that biases sneak in, they are hidden in the details of the assessments made when the data are compiled.

(M3.2) Classical empirics has three steps: It starts by a theory, which is developed into an operational model. Then it presents the data set, and finally it runs regressions.

The significance levels of the t -ratios on the coefficient estimated assume that the regression is the first meeting of the estimation model and the data. We all know that this is rarely the case; see also point (m1) in Section 4.4. In practice, the classical method is often just a presentation technique. The great virtue of the method is that it can be applied to real problems outside academia. The relevance comes with a price: The method is quite flexible as many choices have to be made, and they often give different results. Preferences and interests, as discussed in Sections 4.3 and 4.4 below, notably as point (m2), may affect these choices.

(M3.3) Newer empirics . Partly as a reaction to the problems of (M3.2), the last 3–4 decades have seen a whole set of newer empirical techniques. [10] They include different types of VARs, Bayesian techniques, causality/co-integration tests, Kalman Filters, hazard functions, etc. I have found 162 (or 4.7%) papers where these techniques are the main ones used. The fraction was highest in 1997. Since then it has varied, but with no trend.

I think that the main reason for the lack of success for the new empirics is that it is quite bulky to report a careful set of co-integration tests or VARs, and they often show results that are far from useful in the sense that they are unclear and difficult to interpret. With some introduction and discussion, there is not much space left in the article. Therefore, we are dealing with a cookbook that makes for rather dull dishes, which are difficult to sell in the market.

Note the contrast between (M3.2) and (M3.3): (M3.2) makes it possible to write papers that are too good, while (M3.3) often makes them too dull. This contributes to explain why (M3.2) is getting (even) more popular and the lack of success of (M3.3), but then, it is arguable that it is more dangerous to act on exaggerated results than on results that are weak.

3 The 10 journals

The 10 journals chosen are: (J1) Can [Canadian Journal of Economics], (J2) Emp [Empirical Economics], (J3) EER [European Economic Review], (J4) EJPE [European Journal of Political Economy], (J5) JEBO [Journal of Economic Behavior & Organization], (J6) Inter [Journal of International Economics], (J7) Macro [Journal of Macroeconomics], (J8) Kyklos, (J9) PuCh [Public Choice], and (J10) SJE [Scandinavian Journal of Economics].

Section 3.1 discusses the choice of journals, while Section 3.2 considers how journals deal with the pressure for publication. Section 3.3 shows the marked difference in publication profile of the journals, and Section 3.4 tests if the trends in methods are significant.

3.1 The selection of journals

They should be general interest journals – methodological journals are excluded. By general interest, I mean that they bring papers where an executive summary may interest policymakers and people in general. (ii) They should be journals in English (the Canadian Journal includes one paper in French), which are open to researchers from all countries, so that the majority of the authors are from outside the country of the journal. [11] (iii) They should be sufficiently different so that it is likely that patterns, which apply to these journals, tell a believable story about economic research. Note that (i) and (iii) require some compromises, as is evident in the choice of (J2), (J6), (J7), and (J8) ( Table 4 ).

The 10 journals covered

Note. Growth is the average annual growth from 1997 to 2017 in the number of papers published.

Methodological journals are excluded, as they are not interesting to outsiders. However, new methods are developed to be used in general interest journals. From studies of citations, we know that useful methodological papers are highly cited. If they remain unused, we presume that it is because they are useless, though, of course, there may be a long lag.

The choice of journals may contain some subjectivity, but I think that they are sufficiently diverse so that patterns that generalize across these journals will also generalize across a broader range of good journals.

The papers included are the regular research articles. Consequently, I exclude short notes to other papers and book reviews, [12] except for a few article-long discussions of controversial books.

3.2 Creating space in journals

As mentioned in the introduction, the annual production of research papers in economics has now reached about 1,000 papers in top journals, and about 14,000 papers in the group of good journals. [13] The production has grown with 3.3% per year, and thus it has doubled the last twenty years. The hard-working researcher will read less than 100 papers a year. I know of no signs that this number is increasing. Thus, the upward trend in publication must be due to the large increase in the importance of publications for the careers of researchers, which has greatly increased the production of papers. There has also been a large increase in the number of researches, but as citations are increasingly skewed toward the top journals (see Heckman & Moktan, 2018 ), it has not increased demand for papers correspondingly. The pressures from the supply side have caused journals to look for ways to create space.

Book reviews have dropped to less than 1/3. Perhaps, it also indicates that economists read fewer books than they used to. Journals have increasingly come to use smaller fonts and larger pages, allowing more words per page. The journals from North-Holland Elsevier have managed to cram almost two old pages into one new one. [14] This makes it easier to publish papers, while they become harder to read.

Many journals have changed their numbering system for the annual issues, making it less transparent how much they publish. Only three – Canadian Economic Journal, Kyklos, and Scandinavian Journal of Economics – have kept the schedule of publishing one volume of four issues per year. It gives about 40 papers per year. Public Choice has a (fairly) consistent system with four volumes of two double issues per year – this gives about 100 papers. The remaining journals have changed their numbering system and increased the number of papers published per year – often dramatically.

Thus, I assess the wave of publications is caused by the increased supply of papers and not to the demand for reading material. Consequently, the study confirms and updates the observation by Temple ( 1918 , p. 242): “… as the world gets older the more people are inclined to write but the less they are inclined to read.”

3.3 How different are the journals?

The appendix reports the counts for each year and journal of the research methods. From these counts, a set of χ 2 -scores is calculated for the three main groups of methods – they are reported in Table 5 . It gives the χ 2 -test comparing the profile of each journal to the one of the other nine journals taken to be the theoretical distribution.

The methodological profile of the journals –  χ 2 -scores for main groups

Note: The χ 2 -scores are calculated relative to all other journals. The sign (+) or (−) indicates if the journal has too many or too few papers relatively in the category. The P -values for the χ 2 (3)-test always reject that the journal has the same methodological profile as the other nine journals.

The test rejects that the distribution is the same as the average for any of the journals. The closest to the average is the EJPE and Public Choice. The two most deviating scores are for the most micro-oriented journal JEBO, which brings many experimental papers, and of course, Empirical Economics, which brings many empirical papers.

3.4 Trends in the use of the methods

Table 3 already gave an impression of the main trends in the methods preferred by economists. I now test if these impressions are statistically significant. The tests have to be tailored to disregard three differences between the journals: their methodological profiles, the number of papers they publish, and the trend in the number. Table 6 reports a set of distribution free tests, which overcome these differences. The tests are done on the shares of each research method for each journal. As the data cover five years, it gives 10 pairs of years to compare. [15] The three trend-scores in the []-brackets count how often the shares go up, down, or stay the same in the 10 cases. This is the count done for a Kendall rank correlation comparing the five shares with a positive trend (such as 1, 2, 3, 4, and 5).

Trend-scores and tests for the eight subgroups of methods across the 10 journals

Note: The three trend-scores in each [ I 1 , I 2 , I 3 ]-bracket are a Kendall-count over all 10 combinations of years. I 1 counts how often the share goes up. I 2 counts when the share goes down, and I 3 counts the number of ties. Most ties occur when there are no observations either year. Thus, I 1 + I 2 + I 3 = 10. The tests are two-sided binominal tests disregarding the zeroes. The test results in bold are significant at the 5% level.

The first set of trend-scores for (M1.1) and (J1) is [1, 9, 0]. It means that 1 of the 10 share-pairs increases, while nine decrease and no ties are found. The two-sided binominal test is 2%, so it is unlikely to happen. Nine of the ten journals in the (M1.1)-column have a majority of falling shares. The important point is that the counts in one column can be added – as is done in the all-row; this gives a powerful trend test that disregards differences between journals and the number of papers published. ( Table A1 )

Four of the trend-tests are significant: The fall in theoretical papers and the rise in classical papers. There is also a rise in the share of stat method and event studies. It is surprising that there is no trend in the number of experimental studies, but see Table A2 (in Appendix).

4 An attempt to interpret the pattern found

The development in the methods pursued by researchers in economics is a reaction to the demand and supply forces on the market for economic papers. As already argued, it seems that a key factor is the increasing production of papers.

The shares add to 100, so the decline of one method means that the others rise. Section 4.1 looks at the biggest change – the reduction in theory papers. Section 4.2 discusses the rise in two new categories. Section 4.3 considers the large increase in the classical method, while Section 4.4 looks at what we know about that method from meta-analysis.

4.1 The decline of theory: economics suffers from theory fatigue [16]

The papers in economic theory have dropped from 59.5 to 33.6% – this is the largest change for any of the eight subgroups. [17] It is highly significant in the trend test. I attribute this drop to theory fatigue.

As mentioned in Section 2.1, the ideal theory paper presents a (simple) new model that recasts the way we look at something important. However, most theory papers are less exciting: They start from the standard model and argue that a well-known conclusion reached from the model hinges upon a debatable assumption – if it changes, so does the conclusion. Such papers are useful. From a literature on one main model, the profession learns its strengths and weaknesses. It appears that no generally accepted method exists to summarize this knowledge in a systematic way, though many thoughtful summaries have appeared.

I think that there is a deeper problem explaining theory fatigue. It is that many theoretical papers are quite unconvincing. Granted that the calculations are done right, believability hinges on the realism of the assumptions at the start and of the results presented at the end. In order for a model to convince, it should (at least) demonstrate the realism of either the assumptions or the outcome. [18] If both ends appear to hang in the air, it becomes a game giving little new knowledge about the world, however skillfully played.

The theory fatigue has caused a demand for simulations demonstrating that the models can mimic something in the world. Kydland and Prescott pioneered calibration methods (see their 1991 ). Calibrations may be carefully done, but it often appears like a numerical solution of a model that is too complex to allow an analytical solution.

4.2 Two examples of waves: one that is still rising and another that is fizzling out

When a new method of gaining insights in the economy first appears, it is surrounded by doubts, but it also promises a high marginal productivity of knowledge. Gradually the doubts subside, and many researchers enter the field. After some time this will cause the marginal productivity of the method to fall, and it becomes less interesting. The eight methods include two newer ones: Lab experiments and newer stats. [19]

It is not surprising that papers with lab experiments are increasing, though it did take a long time: The seminal paper presenting the technique was Smith ( 1962 ), but only a handful of papers are from the 1960s. Charles Plott organized the first experimental lab 10 years later – this created a new standard for experiments, but required an investment in a lab and some staff. Labs became more common in the 1990s as PCs got cheaper and software was developed to handle experiments, but only 1.9% of the papers in the 10 journals reported lab experiments in 1997. This has now increased to 9.7%, so the wave is still rising. The trend in experiments is concentrated in a few journals, so the trend test in Table 6 is insignificant, but it is significant in the Appendix Table A2 , where it is done on the sum of articles irrespective of the journal.

In addition to the rising share of lab experiment papers in some journals, the journal Experimental Economics was started in 1998, where it published 281 pages in three issues. In 2017, it had reached 1,006 pages in four issues, [20] which is an annual increase of 6.5%.

Compared with the success of experimental economics, the motley category of newer empirics has had a more modest success, as the fraction of papers in the 5 years are 5.8, 5.2, 3.5, 5.4, and 4.2, which has no trend. Newer stats also require investment, but mainly in human capital. [21] Some of the papers using the classical methodology contain a table with Dickey-Fuller tests or some eigenvalues of the data matrix, but they are normally peripheral to the analysis. A couple of papers use Kalman filters, and a dozen papers use Bayesian VARs. However, it is clear that the newer empirics have made little headway into our sample of general interest journals.

4.3 The steady rise of the classical method: flexibility rewarded

The typical classical paper provides estimates of a key effect that decision-makers outside academia want to know. This makes the paper policy relevant right from the start, and in many cases, it is possible to write a one page executive summary to the said decision-makers.

The three-step convention (see Section 2.3) is often followed rather loosely. The estimation model is nearly always much simpler than the theory. Thus, while the model can be derived from a theory, the reverse does not apply. Sometimes, the model seems to follow straight from common sense, and if the link from the theory to the model is thin, it begs the question: Is the theory really necessary? In such cases, it is hard to be convinced that the tests “confirm” the theory, but then, of course, tests only say that the data do not reject the theory.

The classical method is often only a presentation devise. Think of a researcher who has reached a nice publishable result through a long and tortuous path, including some failed attempts to find such results. It is not possible to describe that path within the severely limited space of an article. In addition, such a presentation would be rather dull to read, and none of us likes to talk about wasted efforts that in hindsight seem a bit silly. Here, the classical method becomes a convenient presentation device.

The biggest source of variation in the results is the choice of control/modifier variables. All datasets presumably contain some general and some special information, where the latter depends on the circumstances prevailing when the data were compiled. The regression should be controlled for these circumstances in order to reach the general result. Such ceteris paribus controls are not part of the theory, so many possible controls may be added. The ones chosen for publication often appear to be the ones delivering the “right” results by the priors of the researcher. The justification for their inclusion is often thin, and if two-stage regressions are used, the first stage instruments often have an even thinner justification.

Thus, the classical method is rather malleable to the preferences and interests of researchers and sponsors. This means that some papers using the classical technique are not what they pretend, as already pointed out by Leamer ( 1983 ), see also Paldam ( 2018 ) for new references and theory. The fact that data mining is tempting suggests that it is often possible to reach smashing results, making the paper nice to read. This may be precisely why it is cited.

Many papers using the classical method throw in some bits of exotic statistics technique to demonstrate the robustness of the result and the ability of the researcher. This presumably helps to generate credibility.

4.4 Knowledge about classical papers reached from meta-studies

Individual studies using the classical method often look better than they are, and thus they are more uncertain than they appear, but we may think of the value of convergence for large N s (number of observations) as the truth. The exaggeration is largest in the beginning of a new literature, but gradually it becomes smaller. Thus, the classical method does generate truth when the effect searched for has been studied from many sides. The word research does mean that the search has to be repeated! It is highly risky to trust a few papers only.

Meta-analysis has found other results such as: Results in top journals do not stand out. It is necessary to look at many journals, as many papers on the same effect are needed. Little of the large variation between results is due to the choice of estimators.

A similar development should occur also for experimental economics. Experiments fall in families: A large number cover prisoner’s dilemma games, but there are also many studies of dictator games, auction games, etc. Surveys summarizing what we have learned about these games seem highly needed. Assessed summaries of old experiments are common, notably in introductions to papers reporting new ones. It should be possible to extract the knowledge reached by sets of related lab experiments in a quantitative way, by some sort of meta-technique, but this has barely started. The first pioneering meta-studies of lab experiments do find the usual wide variation of results from seemingly closely related experiments. [25] A recent large-scale replicability study by Camerer et al. ( 2018 ) finds that published experiments in the high quality journal Nature and Science exaggerate by a factor two just like regression studies using the classical method.

5 Conclusion

The study presents evidence that over the last 20 years economic research has moved away from theory towards empirical work using the classical method.

From the eighties onward, there has been a steady stream of papers pointing out that the classical method suffers from excess flexibility. It does deliver relevant results, but they tend to be too good. [26] While, increasingly, we know the size of the problems of the classical method, systematic knowledge about the problems of the other methods is weaker. It is possible that the problems are smaller, but we do not know.

Therefore, it is clear that obtaining solid knowledge about the size of an important effect requires a great deal of papers analyzing many aspects of the effect and a careful quantitative survey. It is a well-known principle in the harder sciences that results need repeated independent replication to be truly trustworthy. In economics, this is only accepted in principle.

The classical method of empirical research is gradually winning, and this is a fine development: It does give answers to important policy questions. These answers are highly variable and often exaggerated, but through the efforts of many competing researchers, solid knowledge will gradually emerge.

Home page: http://www.martin.paldam.dk

Acknowledgments

The paper has been presented at the 2018 MAER-Net Colloquium in Melbourne, the Kiel Aarhus workshop in 2018, and at the European Public Choice 2019 Meeting in Jerusalem. I am grateful for all comments, especially from Chris Doucouliagos, Eelke de Jong, and Bob Reed. In addition, I thank the referees for constructive advice.

Conflict of interest: Author states no conflict of interest.

Appendix: Two tables and some assessments of the size of the profession

The text needs some numbers to assess the representativity of the results reached. These numbers just need to be orders of magnitude. I use the standard three-level classification in A, B, and C of researchers, departments, and journals. The connections between the three categories are dynamic and rely on complex sorting mechanisms. In an international setting, it matters that researchers have preferences for countries, notably their own. The relation between the three categories has a stochastic element.

The World of Learning organization reports on 36,000 universities, colleges, and other institutes of tertiary education and research. Many of these institutions are mainly engaged in undergraduate teaching, and some are quite modest. If half of these institutions have a program in economics, with a staff of at least five, the total stock of academic economists is 100,000, of which most are at the C-level.

The A-level of about 500 tenured researchers working at the top ten universities (mainly) publishes in the top 10 journals that bring less than 1,000 papers per year; [27] see Heckman and Moktan (2020). They (mainly) cite each other, but they greatly influence other researchers. [28] The B-level consists of about 15–20,000 researchers who work at 4–500 research universities, with graduate programs and ambitions to publish. They (mainly) publish in the next level of about 150 journals. [29] In addition, there are at least another 1,000 institutions that strive to move up in the hierarchy.

The counts for each of the 10 journals

Counts, shares, and changes for all ten journals for subgroups

Note: The trend-scores are calculated as in Table 6 . Compared to the results in Table 6 , the results are similar, but the power is less than before. However, note that the results in Column (M2.1) dealing with experiments are stronger in Table A2 . This has to do with the way missing observations are treated in the test.

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Recent growth accelerations in Africa are characterized by declining shares of the labor force employed in agriculture, increasing labor productivity in agriculture, and declining labor productivity in modern sectors such as manufacturing. To shed light on this puzzle, this study disaggregates firms in the manufacturing sector by average size, using two newly created firm-level panels covering Tanzania (2008–2016) and Ethiopia (1996–2017). The analysis identifies a dichotomy between larger firms with superior productivity performance that do not expand employment and small firms that absorb employment but do not experience much productivity growth. Large, more productive firms use highly capital-intensive techniques, in line with global technology trends but significantly greater than what would be expected based on these countries’ income levels or relative factor endowments.

We advance principles for the construction of a stable and broadly beneficial world order that does not require significant commonality in interests and values among states. In particular, we propose a ‘meta-regime’ as a device for structuring a conversation around the relevant issues, and facilitating either agreement or accommodation. Participating in this meta-regime would impose few constraints on states, yet in favourable circumstances could facilitate significant cooperation. It could also encourage increased cooperation over time even among adversaries, as participation in the meta-regime builds trust. We apply these ideas to several issue areas, including US–China competition.

We distinguish between ideational and interest-based appeals to voters on the supply side of politics, integrating the Keynes-Hayek perspective on the importance of ideas with the Stigler-Becker approach emphasizing vested interests. In our model, political entrepreneurs discover identity and worldview “memes” (narratives, cues, frames) that invoke voters’ identity concerns or shift their views of how the world works. We identify a potential complementarity between worldview politics and identity politics and illustrate how they may reinforce each other. Furthermore, we show how adverse economic shocks (increasing inequality) lead to a greater incidence of ideational politics. We use these results to analyze data on 60,000 televised political ads in U.S. localities over the years 2000 through 2018. Our empirical work quantifies ideational politics and provides support for key model implications, including the impact of higher inequality on the supply of both identity and worldview politics.

We discuss the considerable literature that has developed in recent years providing rigorous evidence on how industrial policies work. This literature is a significant improvement over the earlier generation of empirical work, which was largely correlational and marred by interpretational problems. On the whole, the recent crop of papers offers a more positive take on industrial policy. We review the standard rationales and critiques of industrial policy and provide a broad overview of new empirical approaches to measurement. We discuss how the recent literature, paying close attention to measurement, causal inference, and economic structure, is offering a nuanced and contextual understanding of the effects of industrial policy. We re-evaluate the East Asian experience with industrial policy in light of recent results. Finally, we conclude by reviewing how industrial policy is being reshaped by a new understanding of governance, a richer set of policy instruments beyond subsidies, and the reality of de-industrialization. 

Using Fontana et al.’s (2019) database, we analyze levels and trends in the global distribution of authorship in economics journals, disaggregating by country/region, quality of journal, and fields of specialization. We document striking imbalances. While Western and Northern European authors have made substantial gains, the representation of authors based in low-income countries remains extremely low -- an order of magnitude lower than the weight of their countries or regions in the global economy. Developing country representation has risen fastest at journals rated 100 th or lower, while it has barely increased in journals rated 25 th or higher. Fields such as international or development where global diversification may have been expected have not experienced much increase in developing country authorship. These results are consistent with a general increase in the relative supply of research in the rest of the world. But they also indicate authors from developing countries remain excluded from the profession’s top-rated journals.

Dani Rodrik Ford Foundation Professor of International Political Economy John F. Kennedy School of Government at Harvard University 79 J.F. Kennedy Street Cambridge, MA 02138 [email protected]

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Macroeconomic Models Research Paper

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The term macroeconomics refers to study of the behavior of an economy as a whole or as a system; the phenomena explained are (1) the short-run level of economic activity—the levels of national output, income, and employment; (2) the causes of short-run fluctuation in economic activity (business cycles); and (3) the long-run growth rate of an economy. This research paper focuses on the first two aspects of macroeconomics. The models are presented in an approximate chronological order; the research paper’s organizing theme is that modern macro-economic models can be seen as based on one of two competing “visions” of the economy: (1) The economy is seen as stable, with strong market forces pushing it toward an equilibrium level consistent with full employment of labor and capital (as in the classical and new classical models), or (2) it is seen as an unstable system that grows through time in a boom-bust pattern, with its normal state being less than full employment and so less-than-potential output being produced (as in Keynes’s and the Keynesians’ models).

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Get 10% off with 24start discount code, the beginning: keynes’s critique of classical economics.

Macroeconomics as a distinct field within economics emerged in the late 1930s as a response to John Maynard Keynes’s General Theory of Employment, Interest and Money (1936/1973, referred to subsequently as GT). Keynes contrasted his views on the causes of depressions and persistent involuntary unemployment with those of his predecessors, whom he termed the classical economists. In Keynes’s view, these economists assumed that the normal condition for a market economy is one of capital-accumulation-fueled growth with full employment of labor and capital, and that periods of high unemployment were rare and temporary deviations from the norm. Keynes wrote that this assumption is empirically incorrect because economies frequently experienced prolonged periods of high unemployment and below-potential output (recessions or depressions). He presents his model by developing a critique of three dimensions of the classical theory: (1) Say’s law, (2) the quantity theory of money, and (3) continual clearing of the labor market at “full employment.”

Keynes’s informal model (informal meaning that he did not specify his model with a series of equations or represent it with a set of diagrams but, rather, mainly used verbal exposition) begins by seeing the classical economists as having all held the validity of Say’s law of markets. Say’s law denoted an argument that all income generated by production would be spent on purchasing the national product—either directly, as when workers’ wages or capitalists’ profits are spent on consumption, or indirectly, when capitalists’ savings are borrowed by firms to finance purchases of new capital goods. In modern economic language, we say that the classical economists assumed that the level of aggregate demand (Keynes’s innovative term) for products always equals the cost of producing them, including a return on their capital to the capitalists whose firms produce the products; in other words, aggregate demand is equal to aggregate supply. Because this would mean that firms would always be able to sell any quantity of goods they might produce, they would choose output levels based on their calculations of their profit-maximizing outputs. They would collectively find it profitable to employ as many workers as were willing to sell labor services at the going wage rates; full employment would result: The only unemployed workers would be those unwilling to accept the going wage rate, who were considered to be “voluntarily unemployed.” Keynes rejected this proposition; in his model, aggregate effective demand for the social product was quite likely to be less than the value of what would be produced if all workers willing to work were employed (aggregate demand could be less than aggregate supply at full employment). If the latter occurred, firms would reduce their employment and output levels until they arrived at the levels at which their sales rates equaled their production rates. So aggregate demand determines the level of actual output and employment, and significant and persistent involuntary unemployment can occur. The cause of recessions or depressions is inadequate aggregate demand. How could this occur? Keynes had a simple answer: Although workers’ wage income was generally spent, creating demand for products, profits and interest might very well be saved. And if all of those savings were not borrowed to finance demand for investment goods, aggregate demand could be less than sufficient to employ all those willing to work. Depressions are caused by “too much saving”—too much in comparison with the amount of investment that firms are willing to borrow to finance

Keynes also rejected the validity of another aspect of classical economics: the quantity theory of money (QTM). The QTM argues that the exchange value of a monetary unit is expressed in the average level of prices within the economy (P), and that increases or decreases in the quantity of money (M) in circulation would cause changes in the price level P. Sophisticated versions of the theory were presented using the equation of exchange M x V = P x Y, in which V represents the velocity of circulation of the money stock and Y represents the current (and assumed full-employment level of national product). If V and Y are assumed to be constant, changes in M would lead to directly proportional changes in P. Because the QTM assumed that V and Y were fixed in the short run, changes in the quantity of money (e.g., an increase in M) would not affect the real level of output or employment. So money is “neutral” within the economy: Changes in the money stock will not cause changes in the levels of output or employment.

In Keynes’s model, changes in the quantity of money could cause changes in interest rate levels that could influence aggregate demand for products (especially for investment spending on new capital goods) and thus could influence aggregate production and employment. Money is not generally neutral in Keynes’s model; increases in the money stock would affect only the price level and not output in the special case of the economy already being at the full-employment, full-output level.

Finally, Keynes also rejected the validity of the classical views on the working of the labor market, using Pigou’s model as an example of these views. Pigou and the other neoclassical marginalist theoreticians had argued that if wages were flexible because of competition for employment and employees, the levels of both the money and real wage (the purchasing power of the level of nominal or money wages) would adjust to “clear the market” for labor. They also argued that the equilibrium market-clearing real wage would be equal to the marginal product of labor. Keynes argued that money wages are usually fixed in the short run and that workers cannot bargain over their real wage that would clear the market, because neither they nor their employers can set output prices while bargaining over money wage levels.

Keynes’s Model Represented as a Set of Propositions

Keynes’s theory and model attempt to describe the relationship between the amount of money in circulation, the level of interest rates, and the level of employment (his model, the GT, places financial markets and interest rates at the heart of the macroeconomy).

• High unemployment is caused by insufficient aggregate demand for national product.
• Insufficient aggregate demand is the result of saving in excess of business’ willingness to borrow to finance investment in new capital goods.
• Excessive saving is done by high-income earning households, who receive interest on bonds; it is the result of an “arbitrary and excessive inequality in the distribution of income” (Keynes, 1936/1973, p. 372). Low investment is caused by low profit expectations or high interest rates, or both—both of which discourage business investment in new capital goods.
• Low levels of aggregate demand by the private sector (firms and households) can be offset by high levels of government expenditures (stimulative fiscal policy). Low levels of interest rates can also encourage more investment.
• He argues that the rate of interest should be seen as the price of liquidity (or the price of holding financial wealth as money, as opposed to less liquid financial assets, such as bonds). He termed this the liquidity preference theory of money and interest.
• The level of the rate of interest is explained as determined by the interaction of the supply and demand for money, with the supply controlled by the central bank through monetary policy and the demand determined by the level of transactions and the price level of those transactions, plus financial wealth holders’ expectations regarding the future market price of bonds.
• Another theoretical proposition advanced by Keynes was that if either government expenditures or private investment expenditures increased, total expenditures (aggregated demand) and actual output would increase by a greater amount: He termed this the multiplier effect.

Soon after the publication of his book, professional economists began discussing Keynes’s views in professional journals, most often in the form of book reviews.

Other economists attempted to describe and interpret Keynes with more formal models. The most influential example of this is John R. Hicks’s (1937) IS/LM model, which represented Hicks’s interpretation of Keynes’s theory with a set of equations and a two-dimensional diagram. Hicks argued that Keynes’s theory rested on the validity of his assumption that money wages were fixed in the short run and would not fall if unemployment increased, so Keynes’s model should be seen as valid only in the “special case” of an economy in which some institutional factors prevented wages from being downwardly flexible; ironically, Keynes had not presented a “general theory,” valid for all economies. Hicks later repudiated his evaluation of Keynes’s theory and argued that his model oversimplified Keynes’s theory (Hicks, 1957, 1967).

Other attempts at presenting a formal model of Keynes’s theory were made by Alvin Hansen (1953) and Paul Samuelson (1948). Their model became known as the Hansen-Samuelson Keynesian cross diagram. Given the levels of interest rates, money wages and prices, the parameters of the consumption function—that is, the relationship between personal income and personal consumption expenditures—and planned business investment expenditures, the economy finds a unique equilibrium level of output at the level where aggregated demand equals aggregate production.

Keynesian Economics

By the early 1950s, Keynes’s theory was widely seen as valid by most professional economists (especially among academics). Economists accepting the validity of the Keynesian short-run theory of output determination became known as Keynesians. Their published work focused on how fiscal policy could be used to prevent or end depressions, but they also developed business cycle theory and growth theory consistent with Keynes’s short-run model. Toward the end of the 1950s and in the early 1960s, some of these economists began to argue that Keynes’s theory of depression (inadequate demand causing involuntary unemployment) could be extended to explain price inflation (too much demand at full employment). Logically, there should be a level of unemployment consistent with stable prices and wages, and this was seen as a desirable target for macroeconomic policy. Full employment became defined as the lowest rate of unemployment consistent with wage and price stability. Empirical work attempting to estimate the relationship between wages, prices, and unemployment levels produced evidence of an inverse relationship between unemployment and wage or price inflation, consistent with theory. Because such a relationship is downward sloping if graphed with inflation on the vertical axis and unemployment on the horizontal axis, this curve became a part of the core of Keynesian economics (and named the Phillips curve after W. Phillips, 1958, who conducted one of the earliest econometric estimates of its parameters). Another core belief among the “original Keynesians” was that monetary policy by itself was not usually sufficient to end a severe recession; rather, a fiscal policy stimulus of higher spending by the national government was required. The increases in U.S. gross domestic product (GDP) following increases in expenditure during the 1930s and especially the dramatic increase following large increases in World War II (WWII)-related military expenditures was interpreted by the Keynesians as empirical evidence in support of their central propositions.

However, even as Keynesian economics became dominant in the academy and widely adopted as a guide to macroeconomic policy, widespread opposition to the core theory appeared within academic economics, and Keynesian economics itself divided into several quite different schools of thought, stressing different aspects of Keynes’s somewhat vague and informal model in the GT, including approaches now known as original Keynesians, post-Keynesians, and new Keynesians.

The Evolution of Macroeconomics Since the 1960s

The history of macroeconomics over the last 40 years can be interpreted as a struggle between competing visions of the economy and the proper macroeconomic roles of the state. One vision is exemplified by new classical economics, which sees the economy as essentially stable and tending toward an equilibrium characterized by high employment and an economic growth rate largely determined by the rate of technological change (the natural rate of unemployment and the steady-state rate of growth). Another, contrasting, approach taken by institutionalist and post-Keynesian economics rests on a vision of a very unstable economy, whose growth rate is the result of an open-ended transformational process taking place through economic fluctuations, characterized by excessive unemployment and inequality, and which is often threatened by incoherence and the possibility of breakdown; this approach is called evolutionary Keynesianism here.

The first approach implies a noninterventionist role for the state in the economy; the second argues for a strong interventionist state. A third approach, which acknowledges occasional episodes of instability and a limited role for the state in stabilization and the active promotion of growth, appears in new Keynesian economics and new endogenous growth theory, and appears currently hegemonic within mainstream economics.

New classical economics supports arguments against activist macroeconomic stabilization policy, whereas original Keynesian, new Keynesian, institutionalist, and post-Keynesian economics all support intervention. To a great extent, the debates within macroeconomics reflect a broader and deeper philosophical division between proponents of a radical laissez-faire economic philosophy and those who advocate a strong, interventionist state with wide responsibilities for the common good. The institutionalists and post-Keynesians share a common vision and models that are similar in many respects; their approach is designated evolutionary Keynesianism in what follows. The primary purpose of the rest of this research paper is to delineate the important differences between the new classical (NC), new Keynesian (NK), and evolutionary Keynesian (EK) approaches. This research paper suggests that although new classical economics (NC) dominated the mainstream in the 1970s and 1980s, its influence has declined recently as new Keynesian (NK) economics has become more influential, dominating the postmonetarist “new consensus” among macroeconomists. The research paper also argues that the institutionalist/post-Keynesian approach offers a third framework for economic policy.

The Rise of New Classical Economics: Monetarism, Rational Expectations, and Real Business Cycle Theory

The brief hegemony of Keynesian economics within academia and policy economics lasted for about 2 decades (perhaps from the late 1940s to around 1970) before being challenged by the new version of classical economics. The 1960s consensus approach to macroeconomics was represented with fixed-price, fixed-wage versions of Samuelson’s (1948) and Hansen’s (1953) Keynesian cross and John Hicks’s (1937) IS/LM macroeconomic models of income and employment, and was based on the assumption of a stable relationship between unemployment and price or wage inflation, represented with a Phillips curve. This approach was often referred to by Paul Samuelson’s term neoclassical-Keynesian synthesis, because its implicit microeconomic foundation was largely a form of the Marshallian price theory that Keynes had used in his GT and that then formed the core of standard neoclassical academic microeconomics, while its macroeconomics was an interpretation of Keynes’s theory of effective demand.

The first generation of Keynesian economists saw national governments as responsible for economic stability, economic growth, and full employment, with the highest short-term priority to be given to full employment. Business cycles were seen as caused by fluctuations in aggregate demand, which could be offset with fiscal policy; monetary policy should be used to support fiscal policy, but monetary policy by itself was generally seen as inadequate to stabilize the economy.

Many economists and historians see Keynesian economics as one of the cornerstones of the post-WWII consensus regarding the proper relationship between the state and the economy, and as an integral component of the argument for a more interventionist role of the state. The new political-economic system that emerged in the 1940s and 1950s in most of the wealthy capitalist nations has been described with many terms including welfare capitalism, managed capitalism, state capitalism, monopoly capitalism, and guided capitalism. The counterrevolution to the Keynesian revolution of the 1940s and 1950s began in the late 1960s with the rise of monetarism, the first component of what was to become NC economics.

Monetarism can be understood as a set of theoretical propositions and policy proposals focused on the macro-economic role of money. The core theoretical propositions are as follows:

• The economy is essentially stable and tends toward an equilibrium at a “natural rate” of unemployment that is consistent with stable wages and prices; this natural rate of employment, the stock of capital, and technology then determine the potential level of national income.
• Disturbances to equilibrium are almost always caused by changes in the money stock or its growth rate.
• If unanticipated, these monetary shocks can result in temporary fluctuations in output and employment, but the economy tends to return to the natural rate quickly as wages, prices, and interest rates adjust. Monetarists argue that anticipated monetary shocks are likely to change only the levels of wages, prices, and interest rates even in the short run. Changes in the money supply are neutral in the long run with respect to the real dimensions of the economy: the levels of output, employment, the composition of output, and the real wage. This proposition is described as the classical dichotomy between the real and nominal or monetary dimensions of the economy, and its refutation was one of the core ideas in Keynes’s GT.
• Inflation and deflation are the result of excessive or insufficient growth rates in the money stock as in the QTM.

A set of ancillary propositions agreed to by most monetarists was consistent with and supported the core distinguishing theoretical principles of their school mentioned previously.

• Most versions of monetarism assumed that fiscal policy could not be used to stabilize an economy or otherwise improve macroeconomic performance; this was described as the “ineffectiveness” of fiscal policy in the literature. Changes in government budgets (deficits) intended to stimulate the economy that were financed by borrowing and bond issue resulted in rising interest rates and “crowded out” private investment. Deficits financed by printing money led to inflation; expenditures financed by taxes lowered private spending commensurately. In any of these scenarios, output composition and the allocation of resources would change, but not the aggregate level of output or employment; surpluses reduced interest rates and stimulated private investment. Because the private sector usually used resources more efficiently than the state sector, expansionary fiscal policy would have detrimental effects; because the economy tended toward the natural rate of employment, countercyclical fiscal policy was unnecessary as well as ineffective.
• The monetarists argue that the normal state of the economy is the natural rate of employment and positive economic growth as described in Robert Solow’s (1956) neoclassical growth theory. A higher saving rate would lead to a higher capital-labor ratio and raise per capita income during a transitional period, but diminishing marginal returns to capital and the free flow of capital and technology across nations implied that growth rates should converge to a “natural rate” of growth determined by technological change.

The key policy proposal advanced by monetarists became known as Friedman’s rule: Central banks should concentrate on keeping the price level constant (or inflation very low) by setting the growth rate of money at the anticipated growth rate in real output plus the estimated change in velocity. In more sophisticated versions, Milton Friedman (1968) acknowledged that some circumstances such as financial crises might warrant a temporary abandonment of monetary growth targets by the central bank, but he argued that such episodes would not occur very often if the central bank were committed to a stable monetary growth regime, which would be consistent with a stable economy. If the chief source of fluctuations in nominal GDP were fluctuations in the money supply, economic fluctuations would largely disappear under such a regime.

Monetarists also advocated flexible exchange rate systems, arguing that they would strengthen the effectiveness of monetary policy and increase its independence by doing away with the necessity to use monetary policy to peg the exchange rate. Keynes and the Keynesians favored interest rate targets, discretionary monetary policy as a supplement to fiscal policy, and fixed exchange rates to reduce uncertainty.

As increasingly formal versions of monetarism were presented, debates centered on how expectations regarding future levels of wages and prices were formed, and how changes in expectations affected the relationship between unemployment, wages, and prices, which the first generation of Keynesians had thought to be fairly stable and described with Phillips curves. Early versions of Phillips curves (Phillips, 1958; Samuelson & Solow, 1960) described a stable inverse relationship between wage or price inflation and unemployment, which would allow policy makers to choose a level of unemployment and inflation. Edmund Phelps (1968) and Friedman (1968) argued that Phillips curves shift over time, implying unanticipated changes in the natural rate, as the economic environment changes; especially important in their view were expectations of future inflation, which were largely determined by the recent past behavior of prices.

If monetary policy caused inflation by pushing unemployment below the natural rate (by “surprising” workers who did not anticipate reductions in their real wage caused by the inflation), the increase in inflation would lead to more inflation as economic actors attempted to regain their real income by raising wages, prices, and interest rates (known as the Gibson paradox and Fisher effect in the literature). Economic actors’ inflationary expectations adapted to the actual rate of inflation as they looked backward into time trying to forecast economic conditions. These related propositions came to be known as the back-ward-looking or adaptive expectations model and were represented with inflation-augmented Phillips curves, which were vertical at the natural rate in the long run, as in the “neutrality of money” story.

By the late 1970s, monetarism, the natural rate hypothesis, shifting Phillips curves, and vertical long-run Phillips curves at the natural rate of unemployment appeared in all macroeconomics textbooks and were widely accepted as valid analytic concepts within mainstream economics. Support for the neoclassical-Keynesian synthesis and discretionary countercyclical fiscal policy declined. The Federal Reserve began targeting monetary aggregates in 1970 and increasingly emphasized control over monetary aggregates as its primary intermediate target for policy and low inflation as its primary ultimate objective throughout the 1970s and early 1980s; between 1979 and early 1982, it conducted an inflation-fighting monetarist “experiment,” targeting the growth rate of the monetary base and the monetary aggregates M1 and M2, while allowing interest rates to increase and fluctuate widely. This episode was consistent with the wide support for monetarism within economics and is often cited to indicate the high watermark of monetarist influence among policy makers in the United States.

Rational Expectations

A parallel development beginning in the early 1970s was the increasing insistence by some economists that Keynesian economics was not based on the proper micro-foundations with respect to assumptions about human behavior. If economic actors are rational and utility maximizing, and markets are complete and efficient, markets should continuously clear—including the market for labor.

Persistent involuntary unemployment seems logically inconsistent with those assumptions, since the labor market should allow utility-maximizing workers and profit-maximizing firms to find each other. Many economists began to reject Keynesian models as unscientific because they ignored these issues and seemed inconsistent with the rational expectations hypothesis.

Combining aspects of monetarism (the quantity theory) and the Walrasian microfoundations critique, Robert E. Lucas Jr. (1972, 1973, 1975, 1976), Thomas Sargent and Neil Wallace (1975), and others argued that if changes in the money stock caused inflation, and if economic actors understood the connection between money and prices— and if they were rational—they would come to anticipate inflation whenever the money stock grew (they would learn from their mistakes and change their behavior). If rational economic actors noticed that the central bank increased the money supply whenever unemployment increased, their “rational” reaction to increasing unemployment and anticipated money supply growth would be to raise wages, prices, and interest rates. Rational economic actors would be forward looking in forming their expectations regarding inflation. If so, monetary policy could not be effective in changing the real dimensions of the economy in even the short run unless the policy changes were unsystematic—irrational policy moves that rational actors would not anticipate, such as raising interest rates in a recession or lowering them in an inflationary boom.

Building on the rational expectations framework, Robert Barro (1974, 1981a, 1981b) argued that rational behavior by forward-looking economic actors would also prevent fiscal policy from stimulating the economy. For example, if the government proposes a tax cut to stimulate consumption and employment, rational consumers and tax payers will anticipate higher taxes (on themselves or their descendants) in the future to repay the increased government debt and will save more to finance those higher anticipated taxes, reducing their current consumption: Aggregate current demand cannot be stimulated with tax cuts. This proposition is known as Ricardian equivalence because Barro claims David Ricardo as an early proponent (although Ricardo himself seems not to have believed in the empirical validity of the proposition; O’Driscoll, 1977). The rational expectations hypothesis thus supports arguments for the irrelevance of both fiscal and monetary stabilization policy. Note that the critical assumptions supporting the ineffectiveness of intervention is that changes in the money supply will lead always to changes in the price level and not cause changes in the real dimensions of the economy (the monetarist quantity theory and neutrality of money hypotheses), and on a more fundamental level, that the economy is stable and tends toward the natural rate of unemployment, which is derived from the market-clearing hypothesis. Rational expectations economists often describe their models as equilibrium economics.

The rational expectations theory began to dominate economics as taught in elite graduate programs in the late 1970s, appearing in textbooks at about the same time. By the early 1980s, its radical argument against the possibility of altering the real dimensions of the economy through monetary or fiscal policy was widely accepted within the profession and became dominant by the end of the decade.

In the late 1970s, versions of the NC theories, business cycles, and inflationary episodes were mainly the result of external shocks to the economy, temporary misperceptions by workers or firms regarding the wages or prices that would clear markets (false trading), or the unintended consequences of well-intentioned but doomed attempts to stabilize the economy, and the latter were most often caused by unanticipated attempts to push the unemployment rate below the natural rate and to raise growth above the longrun trend determined by growth in resources and technological change. The resulting inflation required central banks to tighten monetary policy, forcing the economy into a recession until inflationary expectations were reduced and the economy returned to its equilibrium natural rates of unemployment and growth. The state should leave the economy alone, as in most versions of original classical economics; economic policy should be restricted to providing the proper institutional framework for a capitalist market economy and instructing the central bank to follow Friedman’s rule. This view is a profound rejection of the political economy of Keynes and the early Keynesians, who held that the state can and must improve the performance of the economy through discretionary monetary and fiscal policies.

Real Business Cycle Theory

But to many of those working within the rational expectations-Walrasian model, the “bad monetary policy” story seemed an inadequate explanation for business cycles; real business cycle (RBC) theory emerged in the early 1980s to offer an explanation consistent with both the Walrasian continuous market-clearing approach and the rational expectations theory’s definition of rational behavior. In this theory, economic fluctuations are largely the result of “real” or nonmonetary factors: changes in technology and in preferences by workers for leisure versus goods, or intertemporal substitution. Expansions and high growth rate periods are the result of the introduction of new technology sets, as in Schumpeter’s theory of economic development (and Marx’s as well); recessions occur when the economy readjusts to the diminishing influence of a set of technological changes on investment. Increases in unemployment not caused by technological change are the result of workers’ preferences shifting away from products toward leisure, or rational responses to changes in real wages and interest rates that alter the relative prices of goods and leisure.

Very importantly for present purposes, the RBC models denied any real effects of changes in the money stock on the economy; in fact, in an interesting twist, the money supply was seen as endogenous to the economy: The money stock increased in expansions and declined in contractions, passively reacting to cyclical changes in the demand for loans (as in the endogenous money supply theory advanced by the EK school). The RBC theory is based on a radical version of the classical dichotomy between the real and monetary dimensions of the economy.

The emerging new version of classical theory that attacked the previous Keynesian consensus began with an argument that only changes in the money stock could influence the economy (early monetarism); moved to the position that money mattered but only in the short run (the inflation-enhanced Phillips curve version of monetarism); then adopted the rational expectations position that only unanticipated, unsystematic, irrational monetary policy (“bad policy”) could have even short-run effects; and then finally proposed that money did not matter at all with respect to causation in the short-run or long-run behavior of the economy in the RBC models.

The NC theory presented a view of the economy consistent with the original classical story at least in its popularized form within modern economics literature: Capitalism is self-adjusting and stable; competitive markets lead to the most desirable state of affairs; the normal state is high employment with economic growth at the highest rate possible, given time and leisure-goods preferences and the exogenously determined rate of technological change. The only policy role for the state consistent with this vision is providing the necessary institutional structure; otherwise, laissez-faire and free market fundamentalism are advised. By the late 1980s, NC dominated academic economics in the United States in the elite graduate programs and in textbooks, and was widely taught to undergraduates as well.

Opposition to the New Classical Theory

Two strong currents questioning the validity and challenging the hegemony of NC macroeconomics developed even as NC emerged: the new Keynesians and the institutionalist/post-Keynesians or evolutionary Keynesians (EK). The new Keynesians operate within the mainstream, teaching at elite universities and publishing in the profession’s highly ranked journals; many of them (e.g., Ben Bernanke, Alan Blinder, Stanley Fischer, Gregory Mankiw, Joseph Stiglitz, Lawrence Summers, John Taylor, and Janet Yellen) have held important policymaking positions in institutions such as the Federal Reserve, World Bank, Council of Economic Advisors, U.S. Treasury, and the International Monetary Fund.

Meanwhile, outside of the inner circle of mainstream economics, a radical critique of both NC and NK based on a different vision of the economy, a different set of assumptions about human behavior and economic reality, and perhaps a different set of social values and priorities was developed by the EK school.

New Keynesian Macroeconomics

NKE emerged in the late 1970s and early 1980s in reaction to the criticism of consensus IS/LM Keynesianism mounted by the NC school; their emphasis was on explaining the causes of business cycles. The new Keynesians retained Keynes’s insistence that economic fluctuations can be caused by aggregate demand changes and that aggregate demand fluctuations could be caused by factors other than monetary shocks, and they retained the early consensus Keynesian approach that held that wages and prices were downwardly inflexible in the short run and that recessions could be seen as the result of “coordination failures” and “quantity adjustments” to demand or supply shocks. They retained the Keynesian view that recessions were inherent in capitalism, undesirable, socially expensive, and preventable with correct policy. But many of them accepted the NC microfoundations argument that assuming rational utility-maximizing behavior by economic actors and some version of rational expectations was necessary and useful for economic analysis.

Although some NK economists have advocated the use of countercyclical fiscal policy in severe recessions or when the threat of deflation appears (Stiglitz, 2002; comments by Auerbach, Blinder, and Feldstein in Federal Reserve Bank of Kansas City, 2002), most of them have argued that monetary policy is more efficient and generally sufficient to stabilize the economy. And although they advocate interventionist monetary policy to stabilize the economy (money is not neutral in the short run), they generally express a preference for monetary policy rules as opposed to discretion (Taylor, 1999, 2000). “Rules” means setting targets for policy (the rate of inflation, or more often minimizing the gap between actual and potential GDP, defined as the level of GDP consistent with the lowest sustainable level of unemployment without accelerating price inflation—the nonaccelerating rate of inflation [NAIRU]) and designing a policy reaction function in which the central bank would increase or decrease interest rates by a given amount if GDP exceeds or falls below potential. Most of the new Keynesians see the money supply as endogenous in the sense of its growth rate being the interaction of demand for credit and the central bank-determined level of short-term interest rates, and see money as neutral in the long run with respect to its influence over the growth path of the economy (DeLong, 2000; Parkin, 2000; Taylor, 2000).

Their primary focus and contribution with respect to understanding business cycles has been to demonstrate that (a) inflexible wages and prices could lead to quantity adjustments that were destabilizing (recessions could be understood as systemic coordination failures of the economy’s markets because markets do not always quickly find prices that “clear”) and that (b) rigid, sticky, or slowly adjusting prices and wages could be seen as the result of rational responses by economic actors within the actual institutions of capitalist economies. Much of their research focused on the latter point; they found plausible explanations for sticky wages and prices, which challenged both the NC argument that markets clear quickly (or would in a more nearly perfect world) and the NC claim that the Walrasian equilibrium approach was useful as a description of reality. NK has been described as disequlibrium economics, in that it explains why economies are usually not in equilibrium at the natural rate of unemployment and the potential level of output.

Inflexible wages and prices are explained by institutional factors such as monopolistic competition, menu costs, lengthy contracts, efficiency wage theory, wage and price staggering, markup pricing, bureaucratic inertia, and marketing strategy. Other NK lines of attack on NC involved skepticism regarding aspects of rational expectations, importantly including the assumption of inexpensive and complete information; the NC assumption that workers, managers, and owners actually think and behave like the NC economists’ models would have them; and propositions built on rational expectations, such as the Ricardian equivalence story.

In summation, the new Keynesians argue that capitalism is often unstable due to the persistence of both demand and supply shocks, and to the ways in which the market system adjusts to such shocks. They also believe that it is both desirable and necessary to use interventionist policy to stabilize the economy; these positions put them in the Keynesian camp and in clear opposition to the views of the NC school. Their preference for monetary policy over fiscal policy—(a) because they think monetary policy is usually effective, (b) because they think that automatic stabilizers are more effective than discretionary policy due to the relatively small estimates for multipliers and the long time lags for fiscal policy, and (c) because of the political problems that make timely changes in fiscal policy difficult—and for policy rules over discretion differentiates them from the original Keynesians as well as the post-Keynesians.

The views of the new Keynesians appear to be currently hegemonic within mainstream academic macroeconomics in the United States and United Kingdom from the perspectives of who has been selected for policy advice by the Federal Reserve, the Bank of England, and recent governments in both countries; whose macroeconomics texts are most widely adopted and whose theoretical views are dominant in classrooms; and whose policy views are adhered to by the Federal Reserve.

New Economic Growth Theory

Another interesting aspect of mainstream economics is the development of new neoclassical approaches to economic growth that go beyond the Solow growth models and lend support to arguments for government intervention in the economy. Solovian growth models are based on neoclassical and NC assumptions such as perfect competition (and continuous market clearing), diminishing marginal returns to capital, the free flow of information and technological change, and equilibrium between aggregate demand and aggregate supply (so that the economy is assumed to be always at full employment). In these models, diminishing returns to capital lead to the counterintuitive deduction that high rates of investment will have no effect on economic growth over the long run; conditional convergence should be obtained, in which countries with similar savings and population growth rates should converge to the same level of per capita national income and to the same rate of growth (the stationary state), while countries with different characteristics would end up with different per capita income levels but the same growth rate. The common growth rate would be determined by the exogenous rate of technological change under the assumption that technology and knowledge are mobile across countries (Solow, 1956); this leaves almost no role for the state in promoting economic growth.

The new economic growth theories (NEG) broaden the definition of capital to include knowledge (human capital) and also incorporate the spillover effects of investment in both human and fixed capital and the effects of increasing returns to scale. Under these conditions, countries with higher rates of savings and investment could have permanently higher rates of technological progress and economic growth. Because the growth rates of technological progress and output are influenced by the rate of investment, which is determined within these models, this approach is often termed endogenous growth theory.

For present purposes, the importance of the NEG models is that they present another reason for state intervention in the economy: The state can encourage economic growth (a) through its investment in human capital (education, research, and development) and in infrastructure (Aschauer, 1989), (b) by developing appropriate institutions (competitive markets, well-regulated financial systems, stable money), and (c) through policies that encourage saving and investment by the private sector.

Post-Keynesian Economics

A radical critique of original IS/LM Keynesianism, NCE— especially its monetarist core—and new Keynesianism as well has been developed by institutionalist and post-Keynesian economists, whose separate views on macroeconomics have been merging since the late 1970s. Following the much admired Joan Robinson, the first generation of economists who referred to themselves as post-Keynesians such as Paul Davidson (1978) used derogatory terms such as bastard Keynesianism, IS/LM Keynesianism, and textbook Keynesianism to refer to what they saw as a much attenuated and misleading version of the master’s views that had been developed in the 1940s and 1950s by the first generation of Keynesians. They argued that IS/LM Keynesianism ignores Keynes’s stress on uncertainty and disequilibrium; it is another form of general equilibrium theory, describing a tendency toward equilibrium that does not exist in the real world (or in Keynes’s theory).

These economists attempted to go beyond Keynes’s work (post-Keynesian) by building on what they saw as Keynes’s correct ideas and insights while rejecting what they found inadequate in his work. Included in the latter category are his GT assumption of a central bank-determined exogenous money supply (although Keynes apparently held to an endogenous theory of money in his other works), his Marshallian price theory, and the lack of a theory of economic growth. The post-Keynesian project is to construct a realistic model of modern capitalism that would be useful in designing policy to encourage full employment, stability, growth, and less inequality. A strong emphasis on finding practical solutions to economic policy problems is found throughout the work of this group, which has also been a hallmark of American institutionalism. Many of the early post-Keynesians were (and some still are) sympathetic to some versions of democratic socialism; most advocate some form of incomes policy; and all advocate a powerful, interventionist state whose economic policies should give highest priority to encouraging full employment, economic growth, and less inequality—the goals proposed by Keynes in the final chapter of his GT.

The core propositions of post-Keynesian economics (the first two form their “pre-analytic vision,” in Schumpeter’s [1954, pp. 41-42] term) include the following:

• The recognition of fundamental or absolute uncertainty as radically different from statistical or probabilistic risk; fundamental uncertainly does not allow us to make precise calculations of risk. Keynes observed that many of the most important economic decisions—such as whether to invest in fixed capital, purchase a bond, or hold money—are made in situations in which the information necessary to evaluate risk probabilistically will always be absent. The post-Keynesians’ understanding of uncertainty is related to their stress on the importance of historical time and the irreversibility of many important decisions, and is antithetical to the NC approach to knowledge and uncertainly.
• The economy is inherently unstable because of uncertainty and the instability of expectations, especially expectations regarding profit from investment and the future prices of assets. The classical and NC’s equilibrating mechanism of flexible prices is weak (prices are not very flexible downward), and it would actually increase instability if prices could somehow be made more flexible with institutional change, because falling prices in a recession would depress profit expectations and investment. Full employment is less likely than widespread unemployment. Financial speculation and financial instability are inherent in the structure of modern financial institutions and financial markets, and can be the cause of instability in the “real” economy. Society needs to impose stabilizing constraints on the economy, including institutions that stabilize prices, wages, and interest rates. Most important, a large government sector whose expenditure can quickly increase in slumps is necessary to prevent downward instability (Minsky, 1982); small state sectors reduce stability.
• Economic growth, economic fluctuations, and income distribution are dialectically related and mutually reinforcing: Inequality enhances instability; instability (especially recessions) reduces investment and growth, while recessions and low growth increase inequality. This centrality of demand in post-Keynesian theory leads to the proposition of demand-led growth: The long-run growth path of the economy is determined by its short-run behavior.
• Economies are best understood as “complex systems” that are “self-organizing” and exhibit “emerging properties” (see Moore, 1999, for a clear statement of this proposition and its implications; it is related to the institutionalist economists’ insistence that society’s institutions evolve through time, so that theory must be institutionally specific to be useful).
• Moving to another core proposition on a lower level of abstraction, the entry point into macroeconomics for the EK school is a “monetary theory of production” (Keynes, 1936/1973). Money is created (by banks) to finance an increase in production, which requires more fixed and circulating capital. Money is necessary for production to take place because production takes time and because money is the social institution that transfers and stores purchasing power over time. Because of the existence of money, interruptions in the circular flow of income and expenditure can take place (by holding wealth in the form of money), which are unlikely in a barter economy.

According to the EK school, the NC’s axiom of reals (also held to a lesser extent by the NK school as well)—the dichotomy between the monetary and real dimensions of the economy—is misleading; capitalism must be understood as a monetary economy, in which the circuit of money is as important as the physical flow of production and circulation of goods and services. Macroeconomics must begin with an analysis of money—its nature, origin, and functions; money is never neutral with respect to the real economy. The level of interest rates (the price of liquidity and the cost of credit) is a key price within the economy, because it influences both the willingness and the ability of entrepreneurs to invest in real capital and of financial capitalists to hold nonmonetary financial assets such as stocks and bonds.

• The levels of prices, wages, and interest rates should be understood as the result of distributional struggles that are determined by social institutions and complex processes, as opposed to their determination by the quantity theory of money as advanced by NC. Rather than determining the level of wages and prices, the quantity of money in circulation is seen as the result of changes in the level of wages and prices, reversing the quantity theory’s direction of causality. In EK economics, changes in the level of wages lead to a change in the prices of goods, because firms practice markup pricing: Prices are marked up over—primarily—labor costs of production, and estimates of average rather than marginal cost at normal output levels are used to set prices. Changes in the price level (inflation) leads ceteris paribus to an increase in the demand for working capital (credit), which banks accommodate. As more loans are made, the money supply increases (Moore, 1988).
• The endogenous money supply theory argues that anything that increases the demand for bank credit will increase the money supply; commercial banks must accommodate most of any increase in business or consumer loan demand, because most loans are made under predetermined lines of credit (Moore, 1988).
• Finally, although EK economists see the level of interest rates as important in influencing aggregate demand—especially business investment—their empirical work argues that spending and real output may not be very sensitive to interest rates in recessions, so that other demand-stimulating policies are necessary (Arestis & Sawyer, 2002a, 2002b; European Central Bank, 2002). Those same studies provide evidence that interest rate changes are not very effective in reducing price inflation either.

Post-Keynesians and New Keynesians

Although the EK and NK economists agree on aspects of macroeconomics (e.g., the endogeneity of the money supply and the need for interventionist demand management), they disagree on many important points.

• EK economists see the economy as very unstable, requiring constraints stronger than discretionary monetary policy; new Keynesians assume strong equilibrating processes in the long run, pushing the economy toward equilibrium at a socially optimal natural rate of employment and the potential level of output.
• EK economics follows Keynes (and Kalecki) in arguing that savings does not finance investment as in the old classical, neoclassical, NC, and NK models. Rather, investment is determined by profit expectations and the rate of interest, and it is financed by bank credit (and the growth in the money supply). The level of investment coupled with the variables that determine the Keynesian multiplier then determines the level of national income. National income moves toward the level that generates enough savings to equal the exogenously determined level of investment: Investment determines savings, rather than savings determining investment.

This insight has powerful implications for many aspects of policy: Most NC and NK economists argue for policies (such as low marginal rates of taxation, high real interest

rates, shrinking government, reducing the generosity of public pension systems) that should encourage higher net national savings (savings net of government budget deficits and depreciation), because in their models, this would lead to higher private investment. From the EK perspective, this is wrongheaded: Government spending— especially public investment—can increase productivity, private profits, and profit expectations, thus encouraging private investment (“crowding in” rather than “crowding out”). And the level of savings has little influence over either interest rates or investment, because interest rates are primarily determined by monetary policy and liquidity preference. In fact, ceteris paribus, a higher saving rate might depress investment and economic growth because it would lead to a lower level of consumption and aggregate demand growth.

• EK economists put a higher priority on full employment than on price stability and argue that the level of unemployment necessary to keep effective downward pressure on wages and prices entails unacceptable social costs. NK economists put a higher priority on low inflation than on full employment. EK economists are skeptical of our ability to reliably estimate the level of unemployment consistent with price and wage stability—the natural rate of unemployment or the NAIRU, which determines the potential level of national income in the NK model—and use that as a target for stabilization policy. There is no natural rate of unemployment in the sense of a strong attractor that the economy tends toward.

EK economists argue that the important goals of full employment and both wage and price stability can be reached only by developing institutions that socially control wages, prices, and the distribution of income across the social classes (the wage-profit ratio), and that link aggregate wage and profit increases to productivity gains.

In contrast, new Keynesians argue that the NAIRU can be reliably estimated (although the range of estimates is seen by some as quite wide) and the estimates used as a target for stabilization policy; NK economists are willing to tolerate whatever levels of unemployment are necessary for price stability, disagreeing with the EK view that “non-traditional” forms of intervention such as incomes policy can be effective.

• EK economists agree with both Keynes and Kalecki that the distribution of income is important for business cycles and growth; they are interested in both the functional or class distribution between labor and capital and the personal or size distribution across individuals, households, and families. One argument that Keynes and post-Keynesians make is that changes in the distribution of income can influence the composition and levels of aggregate demand (more profits means more investment, higher wages means more consumption). From this perspective, less inequality is preferred because it will stimulate production and employment in the short run and thus stimulate investment and economic growth in the long run; lower interest rates both reduce inequality and stimulate investment (Keynes, 1936/1973; Niggle, 1998, surveys and assesses some recent literature discussing the relationship between inequality and growth).

Followers of Kalecki observe that a declining wage share should be expected to reduce aggregate demand, capacity utilization, and investment, and thus reduce both employment and economic growth. Proper macroeconomic policy implies paying attention to income distribution. Again, new Keynesians do not pay much attention to these issues.

• EK emphasizes a demand-led approach to growth theory, in contrast to the NC supply-side approach, which new Keynesians and new (endogenous) economic growth theories also stress.
• Many EK economists advocate fixed exchange rate systems constructed around an international financial institution that could issue liquid financial assets as needed by deficit countries (Davidson, 1994); most new Keynesians, such as Joseph Stiglitz (2002), accept flexible exchange rates with some important and influential exceptions.
• EK economists favor financial market regulations and see unregulated financial markets as dangerous (Isenberg, 2000; Minsky, 1982, 1986); most new Keynesians are not concerned with financial market deregulation.

In the 1970s and 1980s, NC economists developed and mainstream economics assimilated a set of propositions, models, and theories that argued against both the need for and the efficiency of Keynesian forms of state intervention in the economy to promote full employment, stability, equality, and economic growth. Aspects of this economic philosophy—NC, monetarism, RBC theory, supply-side economics, and public choice theory—offered theoretical support for neoliberalism and have been very influential both within economics and within the domains of policy and politics.

Keynesian economists rejected many aspects of the neoliberal program based on their competing NK theoretical stance. EK economists present a more radical critique of NC and offer a very different perspective on the economy. In the past decade, new Keynesian and new growth theory economics have become more influential within the mainstream. This phenomenon, coupled with the persistence of economic problems that seem intrinsic to unregulated global capitalism—such as stagnation, increasing unemployment and inequality, and recurrent financial crises—opens up the possibility for EK economics to be seriously considered by mainstream economists, because it offers coherent explanations for those problems along with plausible solutions to them.

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