Making Macroeconomics a Much More Exact Science Today macroeconomics is treated as an inexact topic within the humanities, because at a first look it appears to be a very complex and easily confused matter. But this attitude does not give it fair justice--we should be trying to find a better way to approach and examine the subject, in a good way that avoids these problems of complexity and confusion.
Our knowledge is badly in need of improvement😎
This is applied logic as opposed to intuition.
A short presentation of this model is in SSRN 2865571 "Einstein's Criterion Applied to Logical Macroeconomics Modeling" on the internet.
Nobody really understand how our society works because it is too complicated.
The way scientists and engineers think is unsuitable for matters within the humanities, such as the version of social science being covered here.
The correct approach to macroeconomics is through microeconomics, of which this author has given no explanation.
It is not clear how this is a criterion to determine whether a masters programme is pluralist or not. It seems to re.ate to research requirements.
Approaching economics as an exact science to me seems characteristic of the neoclassical tendency to oversimplify human behavior. Economics can't be an exact science because humans are not exactly predictable.
Luke Stockley is right in that economics does need simplification in order to understand it. The model is not an over-simplification, but simply the result of taking aggregates of the common activities of businesses of different kinds, see ref SSRN2865571.
Henry...The trouble with a pluralistic master's program is that so much applies that an in-depth understanding of the most important parts is lost. To avoid this dilemma we need a frame-work on which all the various parts can be hung. This model and theory goes a long way to providing this.
This, or, at least, a good undergraduate grounding in technical (macro)economics really ought to be a pre-requisite for entry into a post-graduate programme. But it may well be necessary to have courses seeking to achieve this objective. An MA degree that turns out to be sociology of economics is not a pluralist economics degree!
I think the point that economics should be scientific is valid at some level but I question whether exactness is the correct criterion. One can be exactly wrong, which is the case all too frequently. Rigour is the key and this is an issue of logical method. The question is whether economists are taught to develop rigorous procedures which means (1) axiomatic reasoning that identifies presuppositions (2) robustness tests which ask whether the conclusions are sensitive to the presuppositions
that would be more of the same problem. It's not about xerting more analytical effort, becoming smarter to solve our problems. That's is actually part of the problem, and not part of the solution
I found the proposition incoherent. I couldn't understand it.
There are some very interesting new ideas floating around - ideas that students are bursting to hear. We have some great input for anyone looking to introduce the new economics, evaluated as a science, but with due recognition of the areas of human wellbeing that are not measurable. We need new techniques. How great if we can engage students in partnering/owning the emergence of these new ways of thinking.
I agree with Alan that exactness is the wrong criterion. But not that one has to be axiomatic! Economists typically confuse science with applied maths. Most science is non-mathematical. I was a biologist - we started from evidence, not axioms! The living world is complicated, like the economy, but biology is successful because its methodology is different. So simplification should not be the primary focus. One can find many regularities, despite human unpredictability, e.g. in system properties.
Mike, unlike biology and other qualitative kinds of science, here in macroeconomics we need to work with quantity of goods, money etc. This kind of science requires the use of numerical analysis along with a degree of mathematics, which is not necessarily difficult to understand.
Thanks for your comment David. Let me clarify: I am not against quantitative analysis. I spent years as an epidemiologist before becoming an economist. The point I was making was that even in highly complicated and open-ended domains, one can understand the causal processes that drive the system. This is not at all incompatible with quantifying flows, etc! Just that causal understanding is a higher priority in most sciences. The quantification is then done on the basis of that understanding.
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