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GDP comparisons across time

March 10, 2020 Leave a comment

from Asad Zaman

This continues a sequence of posts aiming to show how apparently objective statistics conceal large numbers of arbitrary value judgements.  (1) Lies, Damned Lies, and Statistics, (2) Subjectivity Concealed in Index Numbers, (3) The Values of a Market Society, (4) Cross-Country Comparisons of Wealth, (5) Purchasing Power Parity, (6) Downfall of Rhetoric in 20th Century, (7) Facts & Values: Distinction or Dichotomy?. This is the 8th post, which considers comparisons of GDP across time within a single country.

In comparisons across countries, we face the difficulty that the concept of “wealth” has varied across societies, and changed with time. The “average basket” of goods varies for each country, because different societies have different preferences and values. We cannot compare apples and oranges. It seems that these problems would be reduced if we considered a single society across time. The concept of wealth, and the average bundle of goods would remain relatively stable, at least across short periods of time. We will now discuss difficulties which arise when we consider growth across time, comparing GDP across the years for a single country.  read more

Facts & Values: Distinction or Dichotomy?

March 3, 2020 Leave a comment

from Asad Zaman

This continues from the previous post on the Downfall of Rhetoric in 20th Century

Even though our goal is to explain how apparently objective looking statistics conceal arbitrary and subjective judgments, the path we take requires a detour through “epistemology”, or the theory of knowledge. Instead of the deep discussion provided by Putnam (2002, Collapse of the Fact/Value Dichotomy), we will take a shortcut, and look at how these philosophical debates and controversies about have shaped the way that social sciences in general, and statistics in particular, have conceived of the relationship between the numbers we analyzed and the real world that generates these numbers. The wide gap between the philosophers and other intellectuals can be seen clearly in their respective views regarding logical positivism. One of the lifetime advocates of logical positivism, A.J. Ayer, eventually came to the realization that “it was all wrong”. Another sympathizer and proponent, Bas Von Fraasen, opens his book “The Scientific Image” by saying that this philosophy had a “spectacular crash”: read more

Downfall of rhetoric in 20th century

February 29, 2020 Leave a comment

from Asad Zaman

One of most effective and powerful among modern forms of rhetoric is the use of statistics to conceal the ancient methods for persuasion. How this is done is the main topic of our essay.

In a sequence of posts ( Lies, Damned Lies, and StatisticsSubjectivity Concealed in Index NumbersThe Values of a Market SocietyCross-Country Comparisons of Wealth, and Purchasing Power Parity), I have tried to explain how the statistics we use conceal arbitrary value judgments. This is the modern form of rhetoric, which is deadly, because the values are built into numbers, hidden in the process by which the numbers are manufactured, and not open to discussion and dispute. The initial post gives a brief hint as to how this state of affairs emerged. This post elaborates some more on the history of how and why ancient forms of rhetoric were rejected in the 20th Century, and replaced by this modern form of rhetoric.  read more

Purchasing Power Parity

February 26, 2020 Leave a comment

from Asad Zaman

In a sequence of posts starting with  Lies, Damned Lies, and Statistics,  I have argued that the attempt to reduce multiple indicators to one number always introduces subjective elements relating to choice of factors, and relative weights to be assigned. By using technical jargon to justify choice of weights, the value judgments involved in this choice are concealed under a cloak of objectivity. This creates a modern form of rhetoric, where the arguments are made using numbers, and the values that went into the manufacture of these numbers remain hidden, and therefore, are not discussed. This concealment of values resulted from the creation of an artificial dichotomy between facts and values which became widely accepted. Values are considered unscientific, personal opinions, and hence must be concealed.

In the previous post on Cross-Country Comparisons of Wealth, we discussed how values were inevitably involved in such comparisons. In this post, we continue this discussion in the context of the most popular device used to attempt to resolve this problem – purchasing power parity. Like all positivist methods, this creates an impressive illusion of objectivity, while being highly subjective and value-laden. read more

Cross-country comparisons of wealth

February 23, 2020 Leave a comment

from Asad Zaman

This continues a sequence of posts on how objective looking statistics conceal hidden values, because a positivist approach prohibits open expression and discussion of value judgments. Previous posts in the sequence are: Lies, Damned Lies, and StatisticsSubjectivity Concealed in Index Numbers, and The Values of a Market Society.

Countries compete with each other on the GDP numbers, without any awareness of the values which are embodied in such competitions. Such comparisons are fraught with many difficulties. We illustrate the difficulties which arise when we try to compare GDP across nations. To being with, let us examine the GDP data measured in Local Currency Units (LCU) for the countries India, Pakistan, Malaysia, Bangladesh, China and Irland from the World Development Indicator (WDI) data set of the World Bank[1] which is presented in Table 1. Firstly, look at the column for the year 1970.  The largest GDP is the one for Malaysia which is 13.10 trillion MYR. On the other hand, Irland has the smallest GDP which is 2.26 billion IEP. On this basis, can one say that in 1970 Malaysia had the largest wealth and Irland had the smallest wealth? Well obviously not, because the numbers are not comparable since they are measured in LCU. The currency units are not comparable across countries. We must learn how to translate one local currency unit into another, in order to be able to compare countries according to GDP .  read more

The values of a market society

February 21, 2020 2 comments

from Asad Zaman

Continued from previous post on Subjectivity Concealed in Index Numbers. Because modern epistemology rejects values as being just opinions, and only accepts facts as knowledge, values have be to disguised in the shape of facts. What better way to do this than by embodying them in cold hard and indisputable numbers? This post discussed how the GDP embodies the values of a market society.

From the sixteenth to the eighteenth century, the values of European societies were radically transformed by a complex combination of forces. Traditional social values, originating from Christianity, can be roughly summarized as follows:

  1. Community: All members are part of a common body, striving together for common goals.
  2. Social Responsibility: All members must take care of each other.
  3. Duties: Duty to society takes precedence over individual rights.

The transition to a market society led to a new creed, described by Tawney (1926) as: “The Industrial Revolution was merely the beginning of a revolution as extreme and radical as ever inflamed the minds of sectarians, but the new creed was utterly materialistic and believed that all human problems could be resolved given an unlimited amount of material commodities.” As Polanyi (1944) has explained, . . . read more

Subjectivity concealed in index numbers

February 19, 2020 Leave a comment

from Asad Zaman

This continues from the previous post on Lies, Damned Lies, and Statistics.

How_to_Lie_with_Statistics

More than 1.5 million copies sold, more than all other textbooks of statistics combined. Online copy

The vast majority of our life experience is built upon knowledge which cannot be reduced to numbers and facts. Our hopes, dreams, struggles, sacrifices, what we live for, and what we are ready to die for – none of these things can be quantified. However, as we have discussed, logical positivists said that what cannot be observed by our senses cannot be part of a scientific theory. As a result of this false idea, later disproven by philosophers, the attempt was made to measure everything – numbers were assigned to intelligence, trust, integrity, corruption, preferences, etc. – even though a long-standing tradition, as well as common intuition, tells us that these things are qualitative, and not measurable.  read more

Failure of Turing’s conjecture

February 13, 2020 1 comment

from Asad Zaman

Note that this is a very POSITIVIST idea —
if the surface appearances match, that is all that matters.

        DfbsF_aX4AAkczy

I quote a passage from Pearl: The Book of Why, which provides a gentle introduction to the newly developed field (largely by him) of causal inference via path diagrams:

In 1950, Alan Turing asked what it would mean for a computer to think like a human. He suggested a practical test, which he called “the imitation game,” but every AI researcher since then has called it the “Turing test.” For all practical purposes, a computer could be called a thinking machine if an ordinary human, communicating with the computer by typewriter, could not tell whether he was talking with a human or a computer. Turing was very confident that this was within the realm of feasibility. “I believe that in about fifty years’ time . . . . read more

Mistaken methodology of econometrics

February 11, 2020 1 comment

from Asad Zaman

This is the continuation of a sequence of posts on methodology of economics and econometrics (For previous posts, see: Mistaken Methodologies of Science 1Models and Realities 2Thinking about Thinking 3Errors of Empiricism 4Three Types of Models 5Unrealistic Mental Models 6The WHY of Crazy Models 7The Knowledge of Childless Philosophers 8Beyond Kant 9,). In this (10th) post, we consider the methodology of econometrics, which is based on Baconian or observational models. That is, econometric models tend to look only at what is available on the surface, as measured by observations, without attempting to discover the underlying reality which generates these observations. This is an over-simplified description, and we will provide some additional details about econometric methodology later.

The methodology of econometrics is rarely discussed in econometrics textbooks. Instead, students are taught how to DO econometrics in an apprentice-like fashion. All textbooks mentions the “assumptions of the regression model” in an introductory chapter. In later chapters, they proceed to do regression analysis on data, without any discussion of whether or not these assumptions hold, and what difference it could make to the data analysis. The student is taught – by example, not by words – that these assumptions do not matter, and we can always assume them to be true. In fact, as I learned later, these assumptions are all-important and these actually drive all the analysis. By ignoring them, we create the misleading impression that we are learning from the data, when in fact, the results of the analysis come out of the hidden assumptions we make about it. Once one realized this clearly, it becomes EASY to carry out a regression analysis which makes any data produce any result at all, by varying the underlying assumptions about the functional form, and the nature of the unobservable errors. This issue is discussed and explained in greater detail in my paper and video lecture on “Choosing the Right Regressors“.  The fundamental underlying positivist principles of econometric methodology, which are never discussed and explained, can be summarized as the following three ideas: read more

Beyond Kant

February 6, 2020 1 comment

from Asad Zaman

This is a continuation of previous post on “The Knowledge of Childless Philosophers“. I would like to clarify some aspects of the theory of knowledge which have become muddled and confused because childless philosophers did not observe how children learn about the world, and acquire knowledge starting from scratch. If they had taken this as the basic model for how we acquire knowledge, they would have been able to avoid a huge number of mistakes.

A realist methodology for science starts from the realization that scientific knowledge goes FAR BEYOND the realm of the observable. Electrons, Neutrons, Positrons have different kinds of charges, and act in different – incredible and amazing –  ways, but the link between them and observable phenomena is extremely weak and indirect. One of the readers’ comments on a previous post was: how can we learn about what we cannot observe?   read more

The knowledge of childless philosophers

February 3, 2020 6 comments

from Asad Zamzn

Continuing from the previous post on The WHY of Crazy Models, I attribute a large portion of the blame to massively wrong theories of knowledge. A little bit of study of epistemology is enough to give anyone a headache. Because of this, instead of investing the time and effort to decipher what the philosophers are saying, the rest of us are willing to take it on faith. No one is aware of the massive amount of damage done by philosophers – most philosophers themselves are unaware the tremendous influence that their failures in the past have had on the real world. Similarly, the non-philosophers are unaware of how deeply their thoughts have been affected by false and obsolete philosophies, now rejected by the philosophers. Keynes summed up the state of affairs nicely in his apt quote:  “Practical men who believe themselves to be quite exempt from any intellectual influence, are usually the slaves of some defunct economist. Madmen in authority, who hear voices in the air, are distilling their frenzy from some academic scribbler of a few years back” –  While Keynes thinks that practical men of affairs are slaves of economists, I believe that the economists and social scientists are slaves of defunct philosophers, without realizing this.

In preparing this post, I decided to review the theories of knowledge, to provide a brief sketch of how epistemology went astray, allowing us to create crazy models and to consider them as an advance on knowledge. I found a . . . read more

The WHY of crazy models

January 30, 2020 4 comments

from Asad Zaman

I was professionally trained as an economist, and learned how to build models with the best. As described in detail in a previous post on “The Education of An Economist“, it was only by accident that, a long time after graduate school, I learned of glaring conflicts between the theory I had been taught, and the historical evidence about effects of free trade and trade barriers. Further exploration along this direction dramatically widened the chasm between the economic theories I had learnt, and the historical and empirical evidence all around me. This led me to a set of puzzles which I have been struggling with for the past two decades. [1] Why is that economists are not aware of the conflict between economic theories and empirical evidence? [2] Why is it that economists do not care, when such conflicts are pointed out to them? In “Trouble With Macro“, Romer expresses these same two points as follows:  “The trouble is not so much that macroeconomists say things that are inconsistent with the facts. The real trouble is that other economists do not care that the macroeconomists do not care about the facts. An indifferent tolerance of obvious error is even more corrosive to science than committed advocacy of error.

Once we move from the easy-to-establish fact that economists use crazy models, to the much more difficult meta-question of WHY economists use crazy models, . . . read more

The WHY of crazy models

January 21, 2020 3 comments

from Asad Zaman

I was professionally trained as an economist, and learned how to build models with the best. As described in detail in a previous post on “The Education of An Economist“, it was only by accident that, a long time after graduate school, I learned of glaring conflicts between the theory I had been taught, and the historical evidence about effects of free trade and trade barriers. Further exploration along this direction dramatically widened the chasm between the economic theories I had learnt, and the historical and empirical evidence all around me. This led me to a set of puzzles which I have been struggling with for the past two decades. [1] Why is that economists are not aware of the conflict between economic theories and empirical evidence? [2] Why is it that economists do not care, when such conflicts are pointed out to them? In “Trouble With Macro“, Romer expresses these same two points as follows:  “The trouble is not so much that macroeconomists say things that are inconsistent with the facts. The real trouble is that other economists do not care that the macroeconomists do not care about the facts. An indifferent tolerance of obvious error is even more corrosive to science than committed advocacy of error.

Once we move from the easy-to-establish fact that economists use crazy models, to the much more difficult meta-question of WHY economists use crazy models, one apparently obvious answer suggests itself: read more

Simpson’s Paradox

January 19, 2020 2 comments

from Asad Zaman

Statistics and Econometrics today are done without any essential reference to causality – this is much like try to figure out how birds fly without taking into account their wings. Judea Pearl “The Book of Why” Chapter 2 tells the bizarre story of how the discipline of statistics inflicted causal blindness on itself, with far-reaching effects for all sciences that depend on data. These notes are planned as an accompaniment and detailed explanation of the Pearl, Glymour, & Jewell textbook on Causality: A Primer. The first steps to understand causality involve a detailed analysis of the Simpson’s Paradox. This has been done in the sequence of six posts, which are listed, linked, and summarized below

1-Simpson’s Paradox: Suppose that there are only two departments at Berkeley, and that they have different admit ratios for women. In Humanities 40% of female applicants are admitted, while in Engineering 80% are admitted. What will be the overall admit ratio of women to Berkeley? The overall admit ratio is a weighted average of 40% and 80% where the weights are the proportions of females who apply to the two departments.  Similarly, if 20% of male applicants are admitted to Humanities while 60% are admitted to Engineering, then the overall admit ratio is a weighted average of 20% and 60%, with weights depending on the proportion of males which apply to the two departments. This is what lead to the possibility of Simpson’s Paradox. As the numbers have been set up, both Engineering and Humanities favor females, who have much higher admit ratios than male. If males apply mostly to Engineering, then the overall admit ratio for men will be closer to 60%. If females apply mostly to humanities, their overall admit ration will be closer to 40%. So, looking at the overall ratios, it will appear that admissions favor males, who have higher admit ratios. The key question is: which of these comparisons is correct? Does Berkeley discriminate against males, the story told be departmental admit ratios? Or does it discriminate against females, as the overall admit ratios indicate? The main lesson from the analysis in this sequence of posts is that the answer cannot be determined by the numbers. Either answer can be correct, depending on the hidden and unobservable causal structures of the real world which generate the data.

2-Simpson’s Paradox: This post elaborates on Read more…

Three types of models – 5

January 11, 2020 25 comments

from Asad Zaman

It is important to understand that there are three type of models, corresponding the following diagram. The simplest type of model is a pattern in the data that we observe. A second type of model is a “mental model”. This is a structure we create in our own minds, in order to understand the patterns that we see in the observations. The third type of model is a structure of the hidden real world, which generates the patterns that we see. Some examples will be helpful in clarifying these ideas about the typology of models.

3Models

Empirical Models: The simplest kind of model consists of a pattern that we see in the observations. For example, read more

Errors of empiricism 4

January 8, 2020 Leave a comment

from Asad Zaman

Empiricism holds that observations are all that we have. We cannot penetrate through the observations to the hidden reality which generates these observations. Here is a picture which illustrates the empiricist view of the world:

ObservableReality

The wild and complex reality generates signals which we observe using our five senses. The aspects of reality which we can observe are the only things that we can know about reality. The true nature of hidden reality, as it really is, independent of our observations, is unknown and can never be known to us. Influential philosopher Kant calls it the “thing-in-itself”. Noumena is the wild reality, and Phenomena is what we can perceive/observe about the reality. Quote from Encyclopedia Britannica:  read more

Thinking about Thinking 3

January 6, 2020 1 comment

from Asad  Zaman

When we think about epistemology (theory of knowledge), then we are doing meta-thinking. That is, we are thinking about thoughts people have, which they think is “knowledge”.  Because there are many many wrong ideas, and very few right ideas, we must learn to think critically. Unless we do so, our thoughts will be captured by the enormous amounts of fake news which circulates on social media these days. Thinking about thinking, or Meta-Thought, is very different from the standard education which students receive. Instead of asking about the “models” in use, and assessing adequacy or failure of their “assumptions”, at the meta-level we ask how economists began to use these models instead of others, what kind of thoughts are promoted by such models, and what kinds of thoughts are blocked, because the models are incapable of expressing such ideas. This kind of higher-level thinking is completely missing from conventional textbooks.

To highlight the differences, we consider as an illustrative example, how Martin Osborne begins his textbook on game theory, and explains what game theory is about:  read more 

Models and Realities 2

January 3, 2020 Leave a comment

from Asad Zaman

Foundations for modern social sciences were laid in the early twentieth century, and were strongly influenced by logical positivism. The central idea of positivism is that science is true and valid because it deals (principally) with observables, while religion is false and invalid because it deals (principally) with unobservables. For a detailed discussion, see “Logical Positivism and Islamic Economics“.   Later, logical positivism had a spectacular collapse. It became clear to philosophers of science that the idea that we can base science purely on observables was seriously mistaken. Even those who were very strong proponents of positivism admitted that the philosophy was wrong. Strangely, this did not lead to rebuilding of the foundations for the social sciences. Especially in economics, the wrong philosophies about nature of human knowledge, which translate into bad theoretical models, continue to be used.  read more

Mistaken methodologies of science 1

December 30, 2019 4 comments

from Asad Zaman

The problem at the heart of modern economics is buried in the logical positivist methodological foundations created in the early twentieth century by Lionel Robbins. Substantive debates over the content actually strengthen the illusion of validity of these methods, and hence are counterproductive. As Solow said about Sargent and Lucas, you do not debate cavalry tactics at Austerlitz with a madman who thinks he is Napoleon Bonaparte, feeding his lunacy.  Modern Macro Models are based assumptions representing flights of fancy so far beyond the pale of reason that Romer calls them “post-real”.  But the problem does not lie in the assumptions – it lies deeper, in the methodology that allows us to nonchalantly make and discuss crazy assumptions. The license for this folly was given by Friedman: “Truly important and significant hypotheses will be found to have “assumptions” that are wildly inaccurate descriptive representations of reality”; see Friedman’s Methodology: A Stake through the Heart of Reason. In this sequence of posts, I will explain how economic methodology went astray in the 20th Century, abandoning empirical evidence in favor of mathematical elegance and ideological purity. Many authors have noted this problem — for instance, Krugman writes that the profession (of economists) as a whole went astray because they mistook the beauty of mathematics for truth (see Quotes Critical of Economics). To explain the flaws of economic methodology, we need to discuss the relationship between economic models and reality.  read more

Foundations of probability 1-3

December 6, 2019 5 comments

from Asad Zaman

In this sequence of posts, I will go through a recent paper of mine, which explains that BOTH of the currently dominant approaches to probability are deeply, fundamentally, and irreparably flawed. The reason for this is that probability is a real-world phenomenon which is unobservable and unmeasurable. The early 20th Century foundations for probability were built at a time when logical positivism was dominant as the philosophy of science. Furthermore, despite its abandonment by philosophers, its central ideas continue to be widely believed, especially among economists. We will see that both frequentism and subjectivism are attempts to reduce the unobservable to the observable, but this is fundamentally impossible, and all such attempts are doomed to failure. Nonetheless, the charm of positivism and empiricism is so strong, that it prevents the formulation of the ideas necessary to see the problems with the current definitions of probability. An alternative method for thinking about probability, based on  Critical Realism, will also be offered. Based on my paper draft, I estimate that there will be about ten posts of about 1000 words each, though a few of them might be longer.  Here are the first three: