Economics' position in the hierarchy of sciences (hard vs soft)

Question

As a student of Economics, I often listen to the claim that Economics is a "soft science" and that its results may not be too reliable etc. The explanations are often based on personal opinion.

I have newly come to know that rigorous academic literature exists that uses bibliographic and other data to rank sciences based on their "hardness", following Comte's idea of a hierarchy of sciences.

Wikipedia cited this as an empirical investigation of the hierarchy of sciences--

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3694152/

While I find this analysis useful, it does not specifically tell us where Economics lies in the hierarchy (it does find evidence of a hierarchy based on 5/6 factors like clusters in reference graphs, length of paper etc). In most of the results, it clubs all of the social sciences together. In one of the charts, it has a category "Economics and Business", which appears to be near the other social sciences in the hierarchy. But I am not sure where Economics alone (not clubbed with business or other social sciences) will stand in the hierarchy.

Another paper tries to specifically find Psychology's place in the hierarchy-- https://journals.sagepub.com/doi/10.1037/1089-2680.8.1.59

I wanted to know, if there are any such studies that specifically tell us about where Economics stands in the hierarchy-- whether it is closer to the natural sciences or the social sciences?

Answer 1

There is actually no clear cut consensus on where Economics belongs (although it is fair to say most would likely put it into category of social science). Some authors consider it to be science, some social science, some even moral science, and some even argue it should have its own category. A good paper that tries to answer this question for economics is Hudson (2017).

According to the author:

Is economics a science or a social science? Arguments have been made for both orientations, i.e. that economics is a social science (Frey 1999), a science (Frey 1999) and even a moral science (Schabas 2009). In terms of sciences it has been linked with physics, with many physicists doubling as, or transforming into, economists and a subpart of physics, econophysics, specifically evolving which deals with economics (Stanley et al. 1999). There are also links with biology (Marshall 1920; Daly 1968). Frey (1999) argues economics is a social science as it is part of those sciences which deal with actual problems of society, i.e. it is the subject matter which makes it a social science. However, he also points out that in practice economists tend to fill the journals with axioms, lemmas and proofs, i.e. they adopt what they perceive as a scientific, and particularly a mathematical, methodology. Mayer (1980) argues that economists act as though economics is a hard science and this is reflected by their sophisticated use of mathematics. However, he then goes on to argue that econometrics is not sufficiently advanced to enable us to test theories as a hard scientist would.

The literature review above is good place to find out the different views on what economics is. In addition the paper itself is not just a literature review but also itself tries to answer the question by examining how similar economics is to other fields. Hudson (2017) further concludes:

With respect to the question posed in the title of this paper, our view, in part informed by these results, is that the subject matter of economics places it clearly as a social science, but many in the discipline act as if it were a science. Economics has gradually developed into an interdisciplinary subject that uses scientific methods, for example setting out and formally testing hypotheses, and particularly a mathematical approach, to solve social science problems. This dual aspect may explain why it fails to fit neatly with either as in fact it combines elements of both. It is a social science pursued with more quantitative rigour than much of the rest of the social sciences. This emphasis on technique then pushes economics and economists away from the other social sciences and in some sub-disciplines towards maths. Placing economics as a science, emphasises technique above subject matter. But there is then a danger that technique becomes an end in its own right, rather than a means to an end, i.e. a vehicle which allows a more refined analysis of economic issues which have wider relevance. Often, for example when developing a new econometric technique which subsequently becomes widely used, this is justified. But sometimes this is not the case, which helps explain the relative isolation of the discipline as noted earlier. This does not mean that economists should abandon their quantitative focus, but that they should always strive to ensure that their work contributes, directly or indirectly, to an understanding of a real world issue. This is consistent with Frey’s (1999) observation that economics is part of those sciences which deal with actual problems of society, but that most economists attempt to imitate the sciences and that economics can be regarded as a branch of applied mathematics. It is also consistent with the view that that economics, particularly neoclassical economics, is the most mathematical of the social sciences (Porter 1996).

However, I would not take the above conclusion immediately at face value (author also cautions against that) since the cluster analysis done there could not take into account everything what you would ideally want to and it focused only on research in one country (UK). As you can see since this is still being debated and articles about this published in 2017 this is still not completely settled question (although to be fair most would likely classify it as a social science). Also, as noted in the excerpts above the issue is that economics is quite close to the border between social and hard sciences (some authors say it is social science that acts like hard science or draw parallels with biology) making it difficult to classify.

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PS: Actually the Comte's 19th century idea of 'hierarchy of the sciences' is problematic in itself. The problem is that a field on its own cannot be neatly put into such hierarchy because it consists of many sub-fields that are heterogenous. For example, when it comes to fields like game theory economics can run lab experiments while in astrophysics researchers have to rely almost solely on observational data.

Consequently, once you break fields into sub-fields you will find that subfields from various fields can be on top of the hierarchy while other subfields from the same fields can end up at the bottom.

Answer 2

Popper

Karl Popper is more controversial than I can possibly explain. To me, it is manifestly obvious that in order for an idea to be "right", there must be some way for it to be wrong (otherwise, it's a tautology, and those are not very interesting). To this end, an experiment is a technique for demonstrating that an idea may be wrong. But if an experiment fails to invalidate a hypothesis, does that mean the hypothesis is right? What if there is a defect in the experiment? And the converse can be said if it does invalidate a hypothesis. So it is not sufficient to conduct an experiment. We must conduct it by multiple independent teams.

In my mind, the "hardness" of a science is directly related to the extent to which that science can produce experimentally validated ideas, and the reproduction rate of those experiments. Of course, there is a difference between theory and practice, and even physics, the "hardest of the hard" sciences, can suffer from non-reproducible results if they are produced by bad physicists, lab technicians, or outright cranks and frauds. However, if a field produces a predominance of non-reproducible results, then it would be quite unseemly to blame it on a preponderance of charlatans (though for some fields, that may actually be the case).

Replication Crisis

While this term is applied to science in general, there is a particular set of fields for which this is especially acute, as described in Wikipedia. Unfortunately, economics is one of fields said to be "in crisis". The article mentions that in one sample, a full third of the results could not be replicated. This source says that replication failure is 40% for economics (for the sample studied). I find it curious that an economist was comforted by the "high" replication rate of 60%. If chemistry or genomics experiments could only be replicated at a 60% rate, I dare say that DowDuPoint, BASF, and Illumina would simply not exist.

If I am curious about the chemical properties of any common substance, like, say, benzene, I can find reliable results for many properties to 5 significant figures. If experiments to determine the listed properties of benzene were only reproducible 60% of the time, I dare say few people would be foolish enough to engage in large-scale production and usage of this compound (or most industrial compounds).

Policy

But nowhere is the reliance upon science more notable or critical than public policy. When the state expends the blood, sweat and tears of the population in pursuit of a common goal, said citizens generally demand some assurance that the project is worthwhile and achievable. So let's take a brief look at how the US gov't spends money on the sciences:

This is taken from the WP article on Science policy of the United States. If we focus on the basic and applied research categories, we see that HHS and energy appear to be the biggest winners. Given that medical science is directly applicable and relevant to taxpayers, it should be no surprise that HHS receives the lion's share of research dollars. And the fundamental nature of energy to economic output should also not be surprising. Representing fields, we could say that biology/medical science and physics/chemistry are all well represented by these two categories.

NASA and the DoD also receive decent allocations, and we can presume that these both predominantly represent physics and chemistry among the sciences (although there is surely a non-trivial focus on biology/medicine as well). Which means that whatever funds go to the remaining sciences most likely appear as NSF grants and whatever is covered by "Other". While the "Other" category is fairly large, the NSF appears to be the smallest allocation. This is to say that whatever economic research is funded by the federal gov't most likely funnels through the NSF, and represents one of the smallest categories of research spending.

Of course, this is not to say that the field of economics has no impact on the Federal gov't. On the contrary, it may, in fact, have the most direct impact, given the sovereignty of the US dollar, the scope and operation of the US Treasury and the Federal Reserve, not to mention the SEC, IRS, and the fact that most of Congress' power is explicitly reserved for regulating commerce. So isn't it ironic that the printing, spending, allocation, and manipulation of money is one of the largest and most impactful functions of the US Federal Government, and yet it must also be one of the smallest actual research funding targets?

I would suggest that reflects the uncertain value of economic research relative to the higher spending targets. Just consider that when a NASA funded rocket blows up on its way to space, the exact failure mode is often identified down the the seal, wire harness, or line of code. But if a tax break or incentive fails to produce a particular desired effect, the number of possible explanations is limited only by the number of economists available to offer them.

Results in physics, chemistry, and biology often reach consensus as soon as a critical mass of experimental evidence rolls in. In economics, it is not clear what would even constitute a critical mass of evidence. Furthermore, economics is so contentious that it has "schools". While one could argue that physics has "String Theory" and "Loop Quantum Gravity" schools, among other controversies, these generally relate to the very edges of theory where our ability to separate ideas by experiment reaches fundamental limitations. The economic schools, by contrast, encompass a majority of the field, rather than the fringes. It would be like physicists divided over whether the sun revolves around the earth or not.

Black-Scholes

Just to pick on one particular somewhat well-known idea in economics, I think it is fair to say that the Black-Scholes options pricing model is one of the most sophisticated and precise models in the entire field (and quite widely used to help determine options compensation for corporate employees). Unfortunately, it is wrong. Now, let us not be too harsh on Black and Scholes. Every theory requires some simplifying assumptions, and when you get to the level of messy humans trading equities, the assumptions are going to inevitably paper over some pretty convoluted realities, or quickly become intractable. Black-Scholes is "wrong" because the phenomenon it is trying to explain is simply too complex for the number of parameters in their model. If we built a model that was perfectly accurate, it would have too many parameters for us to ever use it. But this also tells us why economics can never get too close to the "hard" side of the sciences: ultimately, it depends on the behavior of fantastically complicated and absurd human beings. And frankly, we often operate in pretty unpredictable ways. It's pretty hard to make a science out of that.

Answer 3

Economics is in an especially disadvantageous position, because it suffers from feedback effects not found in most other sciences. For example, a future stock market crash can never be credibly predicted, because if everyone believes that the market will crash in the future, it will crash immediately. One of the inputs to economic forecasts is those very forecasts, and they can thus negate themselves. Electrons do not change their behaviour based on the latest published findings from CERN.

Answer 4

According to this video:

https://www.youtube.com/watch?v=oaSLa1Ya5-M

"The law of the excluded middle states that every logical statement is either true or false." So if we state "Economics is a hard science" then either this is a logical statement, which must be true or false, or it is not a logical statement, and is neither true nor false. When knowledge does not reduce to true or false logic then we must apply a classification scheme using attributes which are subject to degrees of uncertainty, disagreement, and more than one math model.

Does the Law of the Excluded Middle apply? If so then as a matter of conventional logic economics is either a hard science or a soft science but it cannot be ranked as having some attributes of hard science and some attributes of soft science.

Is the Law of the Excluded Middle violated? If so then rank is based on an effort to list the attributes of hard science, list the attributes of soft science, and to rank economics on some scale using these potentially arbitrary or controversial list of attributes. Is this effort to rank economics an expression of hard science, soft science, both, or neither? It depends on the list of attributes.

Expert Systems, Artificial Neural Networks, and Machine Learning Algorithms refer to the domain where math is applied with computers or other machines in the effort to classify knowledge. I can imagine a bunch of distinct efforts to classify economics, hard science, and soft science none of which would have any claim to the definitive knowledge system. Then the question becomes what is the utility of efforts to pose and answer the question besides publish or perish in a social game?

Quote below from 16 page essay on Science and Human Values perhaps by Hempel:

https://thehangedman.com/teaching-files/hps/hempel-science-values.pdf

Now, when a scientific rule of acceptance is applied to a specified hypothesis on the basis of a given body of evidence, the possible "outcomes" of the resulting decision may be divided into four major types: (1) the hypothesis is accepted (as presumably true) in accordance with the rule and is in fact true; (2) the hypothesis is rejected (as presumably false) in accordance with the rule and is in fact false; (3) the hypothesis is accepted in accordance with the rule, but is in fact false; (4) the hypothesis is rejected in accordance with the rule, but is in fact true. The former two cases are what science aims to achieve; the possibility of the latter two represents the inductive risk that any acceptance rule must involve. And the problem of formulating adequate rules of acceptance and rejection has no clear meaning unless standards of adequacy have been provided by assigning definite values or disvalues to those different possible "outcomes" of acceptance or rejection. It is in this sense that the method of establishing scientific hypotheses "presupposes" valuation: the justification of the rules of acceptance and rejection requires reference to value judgments.

The question can be posed as hypothesis testing. Hypothesis 1: "Economics is a hard science". Hypothesis 2: "Economics is a soft science". Then what are the scientific criteria to test whether each hypothesis is true or false? This is an effort to make the hypothesis conform to the law of the excluded middle even though those statements are only true or false based on the definitions of the terms "economics", "hard science", and "soft science" which can vary among experts. So in the context of ambiguity concerning the defined terms "economics", "hard science", and "soft science" one must reject the law of excluded middle and apply an arbitrary rank model to what purpose since another expert would apply a distinct model so what is gained by all this effort?