Diane Coyle — Economics and philosophy

Some books on philosophy of economics.

The Enlightened Economist
Economics and philosophy
Diane Coyle | freelance economist and a former advisor to the UK Treasury. She is a member of the UK Competition Commission and is acting Chairman of the BBC Trust, the governing body of the British Broadcasting Corporation

Branko Milanovic — 1½ Adam Smiths

The recent book by Jesse Norman simply entitled “Adam Smith” is a pleasure to read. There are of course innumerable books on the founder of the political economy, so why another one? Norman’s book is directed toward that, at times elusive, general educated reader, and has, in my opinion, three objectives: (i) to situate Adam Smith in his time, both intellectually and politically, (ii) to argue that there is a remarkable consistency between the Adam Smith of the Theory of Moral Sentiments, Lectures on Jurisprudence and the Wealth of Nations, and (iii) to show that most of neoclassical and laissez-faire appropriations of Adam Smith are at best one-sided, and in many cases downright wrong....

Global Inequality
1½ Adam Smiths
Branko Milanovic | Visiting Presidential Professor at City University of New York Graduate Center and senior scholar at the Luxembourg Income Study (LIS), and formerly lead economist in the World Bank's research department and senior associate at Carnegie Endowment for International Peace

George H. Blackford — Economists Should Stop Defending Milton Friedman’s Pseudo-science

Recommended reading on the history and philosophy of science, the philosophy of economics, and Milton Friedman's instrumentalism.

Evonomics
Economists Should Stop Defending Milton Friedman’s Pseudo-science

George H. Blackford | former Chair of the Department of Economics at the University of Michigan-Flint

David Gordon — Liberalism and "Classical Liberalism" — An Unfortunate Evolution

Backgrounder in the history of the development of liberalism. While it written from a Libertarian point of view, it is useful in understanding the historical background.

For a more thorough treatment although still a summary backgrounder, see the entry on liberalism at the Stanford Encyclopedia of Philosophy.

Where it falls short is assuming the John Locke somehow discovered the foundations of genuine liberalism, when the fundamentals emerged in ancient Greece and where treated throughout the history of Western thought and manifested differently in Britain, the Continent, and America.

Both the Gordon and Stanford Encyclopedia summaries focus on liberalism as an Anglo-American phenomenon and neither mentions either the history or Continental approach to liberalism, or the antecedents. "Laissez-faire" is, of course, a French term, and the early French writers on economics and political theory were highly influential in the development of economic and political liberalism. Gordon mentions only Frédéric Bastiat.

Gordon and Stanford Encyclopedia also ignore the German contribution to the development of liberalism is ignored, which is understandable given the scope of their summary. But it is a major omission in that many consider Kant rather than Locke to be the father of modern liberalism. Prussian philosopher and educationist Wilhelm von Humboldt, who today is not adequately recognized for his contributions to the Western intellectual tradition, was also a major influence. The Stanford Encyclopedia article on liberalism does make mention of him but only in a brief sentence about his influence on J. S. Mill and it cites Humboldt's The Limits of State Action in the bibliography.

Of course, Anarchists were the the arch-liberals in the sense of advocating for complete freedom from government intrusion in the lives of individuals. While Marx and Engels disagreed with the anarchists of the time over means, they were in agreement over the principle of freedom from state control of individuals and proposed what they concluded from their analysis to be an optimal means for means of achieving this goal. 

After witnessing the French Revolution, Marx and Engels did not simply assume that getting rid of the state through overthrowing the state would lead to utopia immediately. That would take a gradual process of development that would need an interim arrangement to manage the transition as peacefully as possible under the circumstances. They also recognized that the elites in power and their regimes would not just roll over.

Another point that is interesting is that Mises, Hayek and Rothbard all wrote books specifically on liberalism from the classical liberal point of view updated in terms of modern Libertarianism.

A work I like in the tradition of welfare liberalism is John Kenneth Galbraith's The Good Society: The Humane Agenda.

In order to really understand your position, you have to think a thing through carefully using creative and critical thinking. This is best accomplished by writing. At the end of the process, there is something to share with others that may be of value — and could even change the world.

Mises Wire
Liberalism and "Classical Liberalism" — An Unfortunate Evolution

David Gordon |  Senior Fellow at the Mises Institute, and editor of The Mises Review

Lars P. Syll — The main reason why almost all econometric models are wrong

Since econometrics doesn’t content itself with only making optimal predictions, but also aspires to explain things in terms of causes and effects, econometricians need loads of assumptions — most important of these are additivity and linearity. Important, simply because if they are not true, your model is invalid and descriptively incorrect. And when the model is wrong — well, then it’s wrong....

Simplifying assumptions versus oversimplification.

Lars P. Syll’s Blog
The main reason why almost all econometric models are wrong
Lars P. Syll | Professor, Malmo University

Matthew A. Benton — Revitalizing the Epistemology of Religion [or Economics]

Read this as though it were about economics rather than religion.

OUP Blog
Revitalizing the Epistemology of Religion
Matthew A. Benton |  Assistant Professor of Philosophy at Seattle Pacific University

J. W. Mason — The Wit and Wisdom of Trygve Haavelmo

More philosophy of economics, or foundations, if you prefer. Good read if you are into this. It runes along the lines of what amateur economist and working physicist Jason Smith has been saying about foundations.

J. W. Mason's Blog
The Wit and Wisdom of Trygve Haavelmo
JW Mason | Assistant Professor of Economics, John Jay College, City University of New York

Jason Smith — A list of macro meta-narratives

In my macro critique, I mentioned "meta-narratives" — what did I mean by that? Noah Smith has a nice concise description of one of them today in Bloomberg that helps illustrate what I mean: the wage-price spiral. The narrative of the 1960s and 70s was that the government fiscal and monetary policy started pushing unemployment below the "Non-Accelerating Inflation Rate of Unemployment" (NAIRU), causing inflation to explode. The meta-narrative is the wage-price spiral: unemployment that is "too low" causes wages to rise (because of scarce labor), which causes prices to rise (because of scarce goods for all the employed people to buy). In a sense, the meta-narrative is the mechanism behind specific stories (narratives). But given that these stories are often just-so stories, the "mechanism" behind them (despite often being mathematically precise) is frequently a one-off model that doesn't really deserve the moniker "mechanism". That's why I called it a "meta-narrative" (it's the generalization of a just-so story for a specific macro event).

Now just because I call them meta-narratives doesn't mean they are wrong. Eventually some meta-narratives become a true models. In a sense, the "non-equilibrium shock causality" (i.e macro seismographs) is a meta-narrative I've developed to capture the narrative of women entering the workforce and 70s inflation simultaneously with the lack of inflation today.

Below, I will give a (non-exhaustive) list of meta-narratives and example narratives that are instances of them. I will also list some problems with each of them. This is not to say these problems can't be overcome in some way (and usually are via additional just-so story elements). None have yielded a theory that describes macro observables with any degree of empirical accuracy, so that's a common problem I'll just state here at the top.

The difference among just-so stories, handwaving, modeling for effect, and data-based modeling....

Worth looking at for the weekend — and thinking about.

Information Transfer Economics
A list of macro meta-narratives
Jason Smith

Jason Smith — Macro criticism, but not that kind

With all the tired and plain wrong critiques of economics out there that are easily shot down by even the most critical student of economics, I thought I'd try my hand at writing at one that might pass muster. I did write a book, but it was more aimed at taking a new direction; this will be a more specific critique.

First, let me avoid the common mistake of using the word "economics" but then exclusively talking about macroeconomics: my critique is being leveled at macroeconomics (macro). This is not to say I don't also have criticisms of microeconomics or growth theory, but rather let me just focus on macro because that is what most people are interested in. I'm pretty sure the comeback "Auction theory is successful!" isn't really going to cut it with the Post Crash Economics Society or in general anyone who's life was turned upside-down by the Great Recession.

Second, let me avoid the common mistake of saying macroeconomists don't think about X. They do. There's a good chance they've thought about X much more than you have. Instead, let me focus on how macroeconomists think about thinking about X — the context, the spoken and unspoken narratives, the institutional knowledge.

And finally, let me avoid the common mistake of decrying the use of math in economics (this time in general). Mathematics is an extraordinarily useful tool. I know — I'm a physicist. I don't think economists have "physics envy", but the charge does carry a nugget of truth that I'll get to later....

Information Transfer Economics

Macro criticism, but not that kind
Jason Smith

Jason Smith — The economic way of thinking?

More on the foundations of economics.

Information Transfer Economics
The economic way of thinking?
Jason Smith

Tim Johnson — The Golden Rule

Finance and philosophy.

Money, Maths and Magic
The Golden Rule
Tim Johnson | Lecturer (associate professor) in the Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh

Jason Smith — On these 33 theses

The other day, Rethinking Economics and the New Weather Institute published "33 theses" and metaphorically nailed them to the doors of the London School of Economics. They're re-published here. I think the "Protestant Reformation" metaphor they're going for is definitely appropriate: they're aiming to replace "neoclassical economics" — the Roman Catholic dogma in this metaphor — with a a pluralistic set of different dogmas — the various dogmas of the Protestant denominations (Lutheran, Anabaptist, Calvinist, Presbyterian, etc). For example, Thesis 2 says:

2. The distribution of wealth and income are fundamental to economic reality and should be so in economic theory.

This may well be true, but a scientific approach does not assert this and instead collects empirical evidence that we find to be in favor of hypotheses about observables that are affected by the distribution of wealth. A dogmatic approach just assumes this. It is just as dogmatic as neoclassical economics assuming the market distribution is efficient.

In fact, several of the theses are dogmatic assertions of things that either have tenuous empirical evidence in their favor or are simply untested hypotheses. These theses are not things you dogmatically assert, but rather should show with evidence:

I wonder whether economics should be taught as a science, especially since conventional economists seem to think that economics is more like physics than the social sciences.

There are problems with assuming that, which I won't repeat. But to my mind, the most obvious difficulty is well-known among the public. Perhaps the most powerful argument for "science" is demonstrated not in words, or through experiment, but rather in the success of technology that everyone uses all the time to change the world.

Is there anything like this with respect to economics? Not only no, but also the opposite in many cases.

The study economics is not even a required in most business schools, because business schools have discovered that time is better spent in getting results. If it got results, business schools would be hiring the top economists. They are not.

The teaching of economics needs to be rethought in light not only of the failure of economists to deliver results but also in their making bad situations worse. The dismal handling of the aftermath of the global financial crisis is a case in point. In addition, conventional economists and policymakers have literally laid waste entire European countries and their economies.

A lot of people are likely thinking, if this science we want none of it. Monkeys throwing darts could probably do better.

And ironically, Western economists and policymakers were put to shame by the positive result that China showed using a command economy to address the issues promptly and avoid contraction. But Western economists explain this by "cheating."

Information Transfer Economics

On these 33 theses

Jason Smith

Lars P. Syll — On the non-applicability of statistical models

Math is purely formal, involving the relation of signs based on formation and transformation rules. Signs are given significance based on definitions. Math is applicable to the world through science to the degree that the definitions are amenable to measurement and the model assumptions approximate real world conditions (objects in relation to others) and events (patterned changes in these relations). Methodological choices determine the scope and scale of the model, which in turn determines the fitness of formal modeling for explanation of real world conditions and events.

Contemporary science is chiefly about applying formal modeling to theoretical explanation that covers a wide enough range of phenomena worth explaining to be of interest. The scientific project is about designing useful models for explaining phenomena and also designing experiments to test the model against observation. This involves measurement.

A further challenge is identifying parameters that can be measured to produce data and constructing models based on assumptions of how parameters are related with respect to states and how they change over time.

Then, there are also presumptions that are not stated. For example, it is presumed that science is consilient and therefore, any theoretical explanation that violates the conservation laws is ruled out automatically.

Beyond that philosophical foundations relating to metaphysics, epistemology, ethics, social and political philosophy, philosophy of science, the philosophy of the particular discipline, etc., also come into play.

Quite evidently, there is a lot of room for mistake and slip-ups in the process of "doing science."

Formalization and data are not magic wands, and assuming they are leads to magical thinking. Formalization is only rigorous — necessary based on application off rules — with respect to models. How models relate to what is modeled is contingent and depends on data. Data is dependent on observation and measurement.

All this is difficult enough in the natural sciences, but more difficult in the life sciences and much so in the social sciences.

The philosophy of economics, or foundations of economics if one prefers, needs to take all this into consideration and there needs to be lively debate about it. Is there?

Lars P. Syll’s Blog

On the non-applicability of statistical models

Lars P. Syll | Professor, Malmo University

Jason Smith — In the right frame, economies radically simplify

More thoughts on economic methodology. First a framework is needed and then theories can be constructed and tested in that framework. The simplest frame and most economical theory that explains the data sufficiently to be useful is preferred.

A framework involving complexity is not necessarily better than one that doesn't as long as it gets the job done.

Smith observes that theories constructed within the conventional framework that conventional economists presume is not getting the job of explanation and prediction done very well.

He cautions that this doesn't necessarily mean that a more complex framework is better at explanation (formal theoretical model) and prediction (empirical testing of the model against adequate data).

The dynamic equilibrium frame [of Smith's information transfer economics] not only radically simplifies the description of the data, but radically reduces the information content of the data.... 

This is all to say the dynamic equilibrium model bounds the relevant complexity of macroeconomic models. I've discussed this before here, but that was in the context of a particular effect. The dynamic equilibrium frame bounds the relevant complexity of all possible macroeconomic models. If a model is more complex than the dynamic equilibrium model, then it has to perform better empirically (with a smaller error, or encompass more variables with roughly the same error). More complex models should also reduce to the dynamic equilibrium model in some limit if only because the dynamic equilibrium model describes the data.

This would suggest that the methodological debate in economics is not over, as conventional economists claim.

Information Transfer Economics
In the right frame, economies radically simplify
Jason Smith

Lars P. Syll — Methodological arrogance

On reductionism.

This is also the case in philosophy where different methods attempt to exclude other methods by reducing the debate to a lower level of data, e.g, sense data only, or lower order of abstraction, e.g., all abstraction must be reducible to first order. These methodological assumptions reduce justification to observations of objects. For example, David Hume used philosophical reduction to sense data to exclude causality, arguing that causality is nothin more than observation of constant correlation.

The idea is that everything at a higher scale must be accountable at a lower scale. This doesn't even apply in physics (yet) as the hardest science, where the scope of quantum mechanics (micro) and cosmology (macro) still fall outside each other, and questions loom about how to reconcile the micro and macro levels.

To insist on reduction to individual psychology and behavior in economics is indeed arrogant, especially when the social unit in sociology is the family and economic considers economic units in terms of households and firms, and neither human psychology nor behavior are well understood (explained) scientifically.

Reductionism is a methodological assumption that is unsubstantiated by rigorous criteria. It is a stipulation and insisting on it as exclusive is arrogant when there are alternatives in the debate. This is the arrogance of dogmatism rather than open inquiry as the basis of gaining knowledge and the origin of scientific method in an environment where theology reigned.

In short, it is not only arrogance, it is dangerous, as Popper recognized. This is the point of the open society he advocated. Freedom of thought and expression is the basis for inquiry, discovery, and creativity. The discipline of economics risks falling into irrelevance if orthodoxy insists on imposing methodological reductionism as "settled."

Lars P. Syll’s Blog
Methodological arrogance
Lars P. Syll | Professor, Malmo University

Jason Smith — Lazy econ critique critiques

I agree that "unrealistic assumptions" has to be just about the laziest econ critique in existence. I wrote a post I was particularly proud of about how a lot of econ criticism is starting to look like vacuous art criticism.

Information Transfer Economics
Lazy econ critique critiques
Jason Smith

Brian Romanchuk — Rigour And Macroeconomics

Much of my writing about macroeconomic theory is of the hand-wringing variety: it cannot be "scientific" because (useful) forecasting is essentially impossible to do. This is a negative (non-constructive) argument; but that does not mean that we cannot be rigorous.

As a comment on my previous article ("Science and Economics") André asked, "If we are unable to test macroeconomic theory, how will we know that it works?" If we use a wide definition of "test," we are able to do so. However, this notion of "testing" would probably raise eyebrows among physical scientists, who perhaps assume that "forecasting" and "testing" would be the same thing in this context. It is possible to look at macro in a rigorous way, but we need to drop the embedded assumption that rigorous means the same thing as acting like physicists.

My arguments here should not actually be surprising to economists, as they are effectively a hidden background assumption in their worldview. Instead, this viewpoint is aimed at non-economists who want to treat macroeconomics like other fields of knowledge.

Brian ventures into philosophy of macroeconomics, a subject that most economists avoid, which means that they presuppose the foundations of their discipline, which implies that they impose their view based on hidden assumptions. Foundational studies attempt to clarify these matters.

I think a good approach to scientific rigor comes from Richard Feynman's observation that a key purpose of science as rigorous thinking is to keep from fooling ourselves. See his Cargo Cult Science.

 Generally speaking, these days "scientific" means using a formal model to represent actual change of events over time in accordance with some invariance that allows for prediction and therefore testing hypotheses. The rigor comes from both rigorous thinking provided by format ionization and also from the ability to compare a model with reality in order to determine its degree of representation. since models are simplification, few models will be exact replicas of event. They don't need to be in order to be useful for the purpose constructed.

So the first step is to generate a model based on assumptions. At the macro level such models are usually understood to be explanatory models in the sense of modeling some mechanism or transmission process that captures some useful level of invariance in changing events.

This implies that the properties of models must reflect the actual pattern of changing events.

This enables testing the model against what is modeled through observational checking.

A fundamental assumption is that the future resembles the past in the area of consideration to be able to identify invariance. Analysis of data from observing the past is indicative but not definitive, and all models are contingent on future observations. Science is therefore tentative.

The greater the degree of ergodicity, the more representational models can be. As uncertainly increases, models necessarily become less rigorous in the sense that the assumptions map future events if the reasoning is correct.

In the case of non-ergodicity, no amount of rigor in model construction or reasoning can guarantee that the future will continue to resemble the past in the way that such models suggest.

The greatest degree of rigor is provided by deterministic functions, which necessitates the ability to measure variables. The next degree of rigor is provided by stochastic functions which allows for estimation based on sampling, for example.

Biology accounts for a degree of apparent determinism in human behavior. Custom, habit account and path dependence account for some observed degree of patterned behavior in human affairs, but this tends to be local rather than universal.

However, where radical uncertainty exists, contingent models are needed, including conceptual models that take matters into consideration that are difficult to impossible to model formally. For instance, science is presumed to be consilient, so that assumptions that conflict with other areas are suspect.

Moreover, there is also a tendency to overgeneralize, fit curves, fudge and nudge, and even see faces in clouds. For example, there is a tendency to overgeneralize by projecting oneself and one's in-group on humanity and concluding that local characteristics are universal. This is the basis of much that is assumed about "human nature."

The result has been that in the social science, including economics, a distinction has been drawn between the micro and macro levels of scope and scale. The micro has tended to assume dominance, since the scope and scale permit a greater degree of rigor that is confirmed at least statistically.

Grand theories that explain behavior at the societal level have fallen out of favor because they are difficult to construct formally and also difficult to measure observationally. So the usefulness of such theories questionable and they fall victim to the charge of being speculative rather than scientific.

Grace O. Okafor's "Grand Theories and Their Critiques: From C. Wright Mills to Post Modernism" explores this in the history of sociology. It is not difficult to find parallels in the history of economics. 

Gary Becker's rational choice approach has spread from economics to the other social sciences as a framework for modeling social, political and economic behavior. This has led to criticism from several angles — bounded rationality, cognitive-affective bias, different types of decision making, contextual asymmetries, reflexivity and emergence, and uncertainty, for example.

Bond Economics
Rigour And Macroeconomics
Brian Romanchuk

Peter Söderbaum — Redefining economics in terms of multidimensional analysis and democracy

A proposed new theoretical perspective starts with a partly different definition of economics:

“Economics is multidimensional management of (limited) resources in a democratic society”

Why “multidimensional” management? Multidimensional goes against the one-dimensional analysis of neoclassical theory and method. “Monetary reductionism” is no longer accepted. The idea that we should put a monetary price on all impacts, ecosystem services included, to make them commensurable and tradeable, is abandoned. Instead impacts of different kinds are kept separate throughout analysis. And non-monetary impacts are viewed as being as “economic” as monetary ones. This may make analysis more complex but also more relevant.…

Bringing trans-disciplinarity, social value, and quality of life into economic thinking at the foundational level.

Why reference to a democratic society? When reading neoclassical introductory textbooks in economics it becomes clear that “democracy” is not a theme taken seriously. These texts rather reflect an emphasis on economists as experts, i.e. a kind of technocracy....

Real-World Economics Review Blog
Redefining economics in terms of multidimensional analysis and democracy

Peter Söderbaum | Professor Emeritus In Ecological Economics,
Mälardalen University, Sweden

Jason Smith — What mathematical theory is for

Cuts to the chase on the use of math in science, including economics.

Information Transfer Economics
What mathematical theory is for
Jason Smith

Peter Turchin — What Economics Models Really Say

A Review of Economics Rules: The Rights and Wrongs of the Dismal Science by Dani Rodrik (Norton, 2015)

Evonomics
What Economics Models Really Say

Peter Turchin | professor of ecology and evolutionary biology at the University of Connecticut