Maths in Philosophy — Alexander Douglas

Alexander Douglas mounts a defense of rationalism against empiricism. 

Backgrounder to understanding the issues here. The Western intellectual tradition arose in ancient Greece with dissatisfaction with mythological explanation, the favorite form of explanation in the very ancient world — god and all that. The first "philosophers" in the sense of speculation based on reason attempted to provide a "rational" explanation of the world. The Greek terms are logikos and orthologikos (ortho signifies right, correct, straight), obviously the etymological root of "logic" in English. The corresponding Latin term is ratio, meaning "reason" as the faculty of understanding, or knowing in terms of universals rather than particulars. "Rational" in Latin is rationis ("of reason), rationalis, and rationalibus (akin to English "reasonable"). Thus, "rationalism" as an approach to gaining knowledge. 

Aristotle would extend this approach in his Metaphysics to causal explanation. This became the basis of the Western intellectual tradition. Aristotle also favored relying on observation with the senses where appropriate, e.g., the proto-science that was then developing. But Aristotle emphasized the rational over sense observation, and his approach would later be seen as an obstacle to the development and acceptance of scientific method owing to the influence of his philosophy in the Church after Aquinas. Plato was the other influence through Augustine and this was an even greater obstacle to the acceptance of science. Scientists have not forgotten this. 

The advantage of the rational approach at the outset was that it is not mythological, that is, explanation by story, i.e, allegory and analogy, but by reasoning based on principles that are, like the gods, immortal. But unlike the gods, these principles are unchanging. This was the great contribution of Pythagoras and the Pythagoreans in their emphasis on mathematics, as well as Plato's in the Academy. The Western intellectual tradition began as math-based. Aristotle extended this to logic in his Organon as a prerequisite to serious study.

The other end of the knowledge spectrum from the universal and unchanging is empiricism, which is based on observation and mediated by sense data, hence particular and subject to change. Sense data provide only secondary knowledge through phenomena (appearance) rather than being immediate (unmediated) knowledge of objects and events. Moreover, sense data are unreliable, unlike the objects of reason, numbers and concepts. So reason is preferable to sense observation.

Why is this relevant to economics? Because most conventional economists are rationalists that proceed on the basis of intuitive discovery for assumption identification and rely chiefly on formal argument using mathematical models. In other words, they are behaving like speculative philosophers instead of scientists that are guided by data in addition to mathematics, with observation having the final say.

As a philosopher I am a rationalist, and in matters where scientific method is applicable, I prefer to use it as most appropriate. The challenge is determining when those condition apply. Most of the enduring question are enduring because so far no way to apply scientific method to them has been devised in a way that compelling of acceptance.

The issue is fundamentally about criteria and how to identify and apply them. 

Returning to Alexander Douglas's post. I regard most of these issues as pseudo-problems. Philosophers have recognized for a long time that the chief procedural method of philosophy is logic and logic can be formalized. Not everything of interest philosophically is quantitive or can expressed quantitively, so mathematics is of limited use. That is not the issue. The is and has been the balance between rational and empirical in gaining true knowledge. Empiricism reduces the criteria to observational (sense data) and that excludes many if not most of the enduring issues.

Why is this significant? Because macroeconomics is policy science and policy presumes values, which are essentially qualitative rather than quantitate.

Alexander Douglas at Medium
Maths in Philosophy
Alexander Douglas | Lecturer in Philosophy, University of St. Andrews

Chris Dillow — Facts vs hand-waving in economics

On Twitter this morning Jason Smith asked a good question. Is this, he asked, an “anonymous blog comment from a simpleton? ... Or analysis from a prominent financial economics professor?”...

Stumbling and Mumbling
Facts vs hand-waving in economics
Chris Dillow | Investors Chronicle

Noah Smith — "Theory vs. Data" in statistics too

Important.

I think Noah has this right. Fit the tool to the job, rather than the job to the tool.

Aristotle defined speculative knowledge in terms of causal explanation. This definition stuck although Aristotle's analysis of causality did not.

In the Posterior Analytics, Aristotle places the following crucial condition on proper knowledge: we think we have knowledge of a thing only when we have grasped its cause (APost. 71 b 9–11. Cf. APost. 94 a 20). That proper knowledge is knowledge of the cause is repeated in the Physics: we think we do not have knowledge of a thing until we have grasped its why, that is to say, its cause (Phys. 194 b 17–20). Since Aristotle obviously conceives of a causal investigation as the search for an answer to the question “why?”, and a why-question is a request for an explanation, it can be useful to think of a cause as a certain type of explanation. (My hesitation is ultimately due to the fact that not all why-questions are requests for an explanation that identifies a cause, let alone a cause in the particular sense envisioned by Aristotle.) — Stanford Encyclopedia of Philosophy

There is a distinction between reasons and causes. Some types of explanation seek only reasons, while other seek causes. Causation subsequently came to be viewed in terms of articulating mechanisms or lines of transmission (models) that are substantiated in evidence.

Explanation by reasons is different since the strict criterion of articulating mechanisms or lines of transmission that can be checked against evidence is not required.

Explanation by reasons rather than strictly by establishing causation is based on the principle of sufficient reason, which is usually credited to Spinoza and Leibnitz.

In philosophical logic, two negative criteria are foundational. Valid reasoning is vitiated by 1) arguing in a circle and 2) infinite regress.

Without recourse to checking against evidence there is no stopping point in assigning causes other than stipulation, e.g. of a first cause.

However, there may be a reason for a stopping point that doesn't involve causality based on evidence from observation or only stipulation, for example, principles that are "self-evident" based on intuition such as Aristotle's conception of intellectual intuition, or Kant's synthetic a priori propositions as articulated in the Critique of Pure Reason. 

On the other hand, Hume argued that causality is merely over-interpretation of constant correlation, there being no knowledge of the world other than that based on sense data. There is no observable causal link.

Cutting to the chase, scientific explanation based on causality is grounded in models that articulate causal mechanisms or lines of transmission that show how things change invariantly, which is the basis for deterministic functions. Where this is not possible, then there are two other avenues. The first is explanation by giving reasons, which is the domain of speculative philosophy. The second is employing statistics to explore patters of correlation. The question then is to what degree causal models can be gained from statistical methods, or whether it is possible at all. 

This is the issue that Noah Smith's post is getting at.

Noahpinion
"Theory vs. Data" in statistics too
Noah Smith | Bloomberg View columnist

Chris Dillow — Facts, frictions & "mainstream" economics

A major problem with conventional economics is that it is like doing physics without taking friction into account. OK for creating simple teaching models to illustrate fundamentals, maybe. But disastrous in doing advanced theory and especially in applications like engineering.

There are a lot of inefficiencies in economic behavior that are difficult to measure and very difficult to reduce in a cost-effective way, such as transaction cost. Ignoring these factors or pretending that they don't contribute substantially to results can render modeling quite non-representational when predictions are compared to evidence.

And this is in addition to "theonomic" assumptions!

Stumbling and Mumbling

Facts, frictions & "mainstream" economics

Chris Dillow | Investors Chronicle

Joel B. Pollak — Bloomberg Falsely Claims Breitbart Did Not Cite Independent Sources

The “without evidence” talking point has been ubiquitous this weekend, repeated by mainstream media outlets and Democratic Party representatives alike, though the evidence has been in plain sight for weeks — and was duly cited.

Breitbart News
Bloomberg Falsely Claims Breitbart Did Not Cite Independent Sources
Joel B. Pollak | Senior Editor-at-Large at Breitbart News

Sputnik International — Humiliating Billion User Hack Attack on Yahoo 'Likely Launched by a State Actor'

No evidence. Wild inference.

These people seem to have no idea of the issues surrounding identification of causal assumptions.

Conflation of a sufficient condition with a necessary condition.

Beyond lame.

Sputnik International
Humiliating Billion User Hack Attack on Yahoo 'Likely Launched by a State Actor'

Mark Thoma — 'New Experiments Challenge Economic Game Assumptions'

Dr Burton-Chellew said: …'The upshot of this is that these games are not reliably measuring motivations and therefore may not be informative of real-world behavior. This has obvious policy implications, as well as implications for our understanding of the evolution of social behavior. Furthermore, it casts doubt on the idea that there are fundamentally different social-types of people. I think it is more useful to focus on when and where people cooperate, rather than identifying who does and does not cooperate, especially in the artificial world of the lab. 

'In short, I would argue that there is too much confidence placed in the results of these economic games; too much confidence in their ability to measure social preferences.'

Economist’s View
'New Experiments Challenge Economic Game Assumptions'
Mark Thoma | Professor of Economics, University of Oregon

Lars P. Syll — ‘Rigorous’ evidence can be worse than useless

Department of doh!

"…the literature provides a compelling case that policymakers interested in minimizing the error of their parameter estimates would do well to prioritize careful thinking about local evidence over rigorously-estimated causal effects from the wrong context." —Lant Pritchett & Justin Sandefur

Solving the wrong problem.

Lars P. Syll’s Blog
‘Rigorous’ evidence can be worse than useless
Lars P. Syll | Professor, Malmo University

John Helmer — European Court Of Justice Introduces The Anti-Rasmussen Rule — Sanctions Cannot Be Imposed By Reason Of Fabrication, Lies, Disinformation

In a judgement issued in Luxembourg on Thursday, September 18, the court ruled that the European Union(EU) cannot lawfully introduce sanctions against states, corporations, state organizations, or individuals without stating reasons which can be substantiated in evidence to a standard of proof tested in court....

In October 2012, the EU banned transactions with Iranian banks and financial institutions, as well as the import, purchase and transportation of natural gas from Iran, the construction of oil tankers for Iran, and the flagging and classification of Iranian tankers and cargo vessels. 

After the sanctions campaign commenced, Bank Mellat went to court in the UK and the EU Court of Justice, challenging the allegation that it was connected to Iran’s nuclear weapons and ballistic missile programmes. The bank commenced litigating in London in November 2009. Almost five years later, in June of this year, Bank Mellat won a ruling from the UK Supreme Court, the final court of appeal, rejecting the basis in evidence for the sanctions imposed on the bank. This followed a similar condemnation by the European Court, issued in January 2013. That story, and the two court judgements, can be read here. 

“Mere allegations” were inadmissible to support sanctions, the two courts have ruled....

This week, the Central Bank of Iran won a separate lawsuit against the EU. The new ruling can be read here.

Dancing with Bears
European Court Of Justice Introduces The Anti-Rasmussen Rule — Sanctions Cannot Be Imposed By Reason Of Fabrication, Lies, Disinformation

John Helmer

Lars P. Syll — Leontief’s uneasy feeling about the state of economics

Nice quote by Wassily Leontief

Short summary: GIGO, no matter the sophistication of the modeling and the math. If the data doesn't support the model, the model is not going to add anything more than empty formalization. AKA "blinding with bullshit."

Lars P. Syll’s Blog
Leontief’s uneasy feeling about the state of economicsLars P. Syll | Professor, Malmo University

Jared Bernstein — Evidence: Is It Really Overrated?

A few weeks ago, during the evidentiary dustup between Piketty and the FT, I quasi-favorably quoted a Matt Yglesias line re empirical evidence being overrated. A number of readers were understandably unhappy with that assertion, arguing that they come here to OTE for fact-based analysis based on empirical evidence (with, admittedly, a fair bit a heated, if not overheated, commentary). If facts all of the sudden don’t matter anymore, why not just call it a day and join the Tea Party?

So let me add a bit more nuance. The statement is about the quality and durability of evidence, which is not only varied of course, but, at least in the economic policy world, increasingly problematic by which I mean that a number of developments have significantly lowered the signal-to-noise ratio.

I’d divide the evidence problem into two separable categories. First, statistical issues about what’s “true” and what’s not, and second, ideological ways in which the noise factor is amplified at the expense of the signal.

Jared Bernstein | On the Economy

Evidence: Is It Really Overrated?
Jared Bernstein