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Regression analysis — a case of wishful thinking

July 19, 2018 1 comment

from Lars Syll

The impossibility of proper specification is true generally in regression analyses across the social sciences, whether we are looking at the factors affecting occupational status, voting behavior, etc. The problem is that as implied by the conditions for regression analyses to yield accurate, unbiased estimates, you need to investigate a phenomenon that has underlying mathematical regularities – and, moreover, you need to know what they are. Neither seems true. I have no reason to believe that the way in which multiple factors affect earnings, student achievement, and GNP have some underlying mathematical regularity across individuals or countries. More likely, each individual or country has a different function, and one that changes over time. Even if there was some constancy, the processes are so complex that we have no idea of what the function looks like.

regressionResearchers recognize that they do not know the true function and seem to treat, usually implicitly, their results as a good-enough approximation. But there is no basis for the belief that the results of what is run in practice is anything close to the underlying phenomenon, even if there is an underlying phenomenon. This just seems to be wishful thinking. Most regression analysis research doesn’t even pay lip service to theoretical regularities. But you can’t just regress anything you want and expect the results to approximate reality. And even when researchers take somewhat seriously the need to have an underlying theoretical framework – as they have, at least to some extent, in the examples of studies of earnings, educational achievement, and GNP that I have used to illustrate my argument – they are so far from the conditions necessary for proper specification that one can have no confidence in the validity of the results.

Steven J. Klees 

Read more…

Radical paradigm shifts

July 19, 2018 24 comments

from Asad Zaman

The methodology and ideology of modern economics are built into the frameworks of educational methods, and absorbed by students without any explicit discussion. In particular, the logical positivist philosophy is a deadly poison which I ingested during my Ph.D. training at the Economics Dept in Stanford in the late 1970s. It took me years and years to undo these effects. Positivism uses clever arguments to make you deny what you feel in your bones to be true, and make you believe what your heart says must be false — for example our supposed knowledge of subjective probabilities of unknown events. The roots of the problem go back to the famous Cartesian argument that “I think therefore I am”. Although it is clever piece of logic, it has a deadly effect. I know that I am alive because I can feel the blood flowing in my veins, the tingling of my skin, and a thousand other bodily sensations. “I feel therefore I am”. Denying this experience as a valid source of knowledge reduces me to a brain floating in a vat, which is exactly what logical positivism entails. In fact, despite Descartes, it is impossible to REASON our way to certainty. We can only create an illusion of certainty. Descartes’ argument is deeply flawed, and illustrates the weakness of human reason. When we formulate the concept of “I”, isn’t existence automatically part of this? Did I not exist when I was a baby, and was unable to formulate these thoughts? Do I blink out of existence when I go to sleep? This and many other difficulties make this argument incoherent. Modern economics is much like this. It starts by making assumptions which are dramatically in conflict with everything we know about human behavior (and firm behavior) and applies mathematical reasoning to situations where it cannot be applied, quantifying the unquantifiable and coming to completely absurd and ridiculous conclusions. NONETHELESS, speaking from personal experience, the brainwashing is powerful and effective. It is a slow and painful process to undo. read more

Did developing countries really recover from the Global Crisis?

July 18, 2018 3 comments

from C. P. Chandrasekhar and Jayati Ghosh

We are nearing the tenth anniversary of the collapse of Lehman Brothers in the United States that sparked a Global Financial Crisis,affecting every economy in significant ways. That crisis generated extraordinary monetary policy responses in the advanced economies, with low interest rates and unprecedented expansion of liquidity, in an effort largely driven by central banks to keep their economies afloat. By contrast, expansionary fiscal policy was barely used after the first initial stimulus. In the event, even with these incredibly loose monetary policies, the advanced economies have generally spluttered along, with periodic hopes of recovery dashed by repeated slowdowns – even as asset market bubbles have emerged once again.

But the developing world was supposed to be different;its economies were supposedly more able to continue expanding because of the “catching up” propensities assumed by mainstream theorists. There was much talk of the “decoupling” of developing and advanced economies, with China and some other countries emerging as alternative growth poles – but this proved to be wrong.

It is certainly true that China, generally following more heterodox policies with substantial state direction of the economy, continued to show rapid (but decelerated) growth; and India also continued to grow reasonably fast, although much of that growth reflected increases in finance and public administration. However, overall the developing world turned out to be much more dependent upon growth in the advanced economies, and over the past decade, their economic expansion also slowed.

Figure 1: Major developing countries had lower growth in the decade after the crisis  Read more…

The main reason why almost all econometric models are wrong

July 17, 2018 21 comments

from Lars Syll

How come that econometrics and statistical regression analyses still have not taken us very far in discovering, understanding, or explaining causation in socio-economic contexts? That is the question yours truly has tried to answer in an article published in the latest issue of World Economic Association Commentaries:

The processes that generate socio-economic data in the real world cannot just be assumed to always be adequately captured by a probability measure. And, so, it cannot be maintained that it even should be mandatory to treat observations and data — whether cross-section, time series or panel data — as events generated by some probability model. The important activities of most economic agents do not usually include throwing dice or spinning roulette-wheels. Data generating processes — at least outside of nomological machines like dice and roulette-wheels — are not self-evidently best modelled with probability measures.

EGOBILD2017When economists and econometricians — often uncritically and without arguments — simply assume that one can apply probability distributions from statistical theory on their own area of research, they are really skating on thin ice. If you cannot show that data satisfies all the conditions of the probabilistic nomological machine, then the statistical inferences made in mainstream economics lack sound foundations.

Statistical — and econometric — patterns should never be seen as anything other than possible clues to follow. Behind observable data, there are real structures and mechanisms operating, things that are — if we really want to understand, explain and (possibly) predict things in the real world — more important to get hold of than to simply correlate and regress observable variables.

Statistics cannot establish the truth value of a fact. Never has. Never will.

Corporations and mainstream media trumpet the “horrors” of higher wages

July 17, 2018 17 comments

from Dean Baker

The media have treated us to an array of stories warning us of the terrible labor shortage facing the country. Some of the pieces have been general, such as this CNBC piece on the labor shortage “reaching a critical point,” or this Wall Street Journal article on wage gains “threatening profits.”

Others have been more industry-specific, such as The Washington Post’s highlighting of the trucker shortage that threatens the “prosperous economy.” Then there is this New York Times piece noting that nursing homes have trouble attracting nursing assistants at the $13.23 an hour average pay for the occupation.

It’s clear that many in the media are terrified by the prospect that as the labor market gets tighter, workers might get a larger share of the pie. Perhaps this should not be surprising when billionaires control major news outlets, but it does mean that economic reporting might be getting pretty far out of line with economic reality.

At the most basic level, if workers did see pay increases at the expense of profits, they would just be getting back some of what they have lost in this century. The after-tax profit share of national income rose by almost three full percentage points between 2000 and 2016. That would correspond to an average loss of almost $3,000 per worker per year.

But even this calculation understates the shift from wages from profits. According to new research by Gabriel Zucman, more than a third of the foreign profits of US corporations are actually profits made in US but shifted overseas to evade taxes.

Factor this profit shift into the calculation and the loss to workers is close to $4,000 per worker per year. And this is before factoring in the corporate tax cut passed last year.  Read more…

Hard and soft science — a flawed dichotomy

July 16, 2018 14 comments

from Lars Syll

The distinctions between hard and soft sciences are part of our culture … But the important distinction is really not between the hard and the soft sciences. Rather, it is between the hard and the easy sciences. Easy-to-do science is what those in physics, chemistry, geology, and some other fields do. Hard-to-do science is what the social scientists do and, in particular, it is what we educational researchers do. In my estimation, we have the hardest-to-do science of them all! We do our science under conditions that physical scientists find intolerable. We face particular problems and must deal with local conditions that limit generalizations and theory building-problems that are different from those faced by the easier-to-do sciences …

Context-MAtters_Blog_Chip_180321_093400Huge context effects cause scientists great trouble in trying to understand school life … A science that must always be sure the myriad particulars are well understood is harder to build than a science that can focus on the regularities of nature across contexts …

Doing science and implementing scientific findings are so difficult in education because humans in schools are embedded in complex and changing networks of social interaction. The participants in those networks have variable power to affect each other from day to day, and the ordinary events of life (a sick child, a messy divorce, a passionate love affair, migraine headaches, hot flashes, a birthday party, alcohol abuse, a new principal, a new child in the classroom, rain that keeps the children from a recess outside the school building) all affect doing science in school settings by limiting the generalizability of educational research findings. Compared to designing bridges and circuits or splitting either atoms or genes, the science to help change schools and classrooms is harder to do because context cannot be controlled.

David Berliner

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Shifting attention: two ideas for a genuine micro founded macro-economic master thesis

July 16, 2018 9 comments

from Merijn Knibbe

I’m trying to write a book about the relation (not) of neoclassical macro-economic concepts to the concepts of macro-economic statistics. Which leads one to interesting places one can’t explore. If there is anybody out there in search for an interesting idea for a master thesis or something light that, these might do:

  1. A qualitative and quantitative exploration of ‘hoboism’ in the 1930’s looking at it using the lens of ‘involuntary part time unemployment’
  2. An international and historical extension of existing estimates of domestic servants and how this relates to our estimates of GDP.

Read more…

The Secrets of Happiness

July 15, 2018 Leave a comment

from Asad Zaman

Introduction — I wrote this essay a while ago, and I am adding this preface here to explain more about WHY I wrote it:

Preface:

A central problem of our age is the turning of “means” into “ends”.  It is obvious that money, by itself, is not a source of pleasure –  it is a means to this end. Similarly, freedom is useful only if it is freedom to allow us to do something we want to do. Nobody would want the freedom to sell himself into slavery — which is effectively the only free choice offered to the poor in capitalism. Yet, today, due to a long, strange, and complex, historical process, freedom and wealth have become the goals of life, and the religion of most people on the planet. By religion, I mean that morality is based on these two goals — anything which creates wealth is desirable and hence moral, while anything which allows us greater freedom to act on our desires is also moral (this is the foundational principle of utilitarianism). In order to clear our minds of traps created by false paradigms, it is very useful to contemplate the opposites, as a mental exercise. As the dialectical method suggests, let us focus on the possibility that wealth and freedom are harmful to us. Wealth tempts us into the misconception that we can buy happiness with it, and this cheap path to short-term happiness — “The Coca Cola Theory of Happiness” — prevents us from learning and understanding the sources of long-term happiness, destroying the possibility of genuine happiness. Similarly, freedom tempts us into following paths of behavior which lead to short term pleasures at the cost of our long term happiness — we pursue strategies of instant gratification, failing to understand the need for sacrifice, struggle, and voluntary acceptance of suffering, in order to achieve higher goals. Not having wealth would be useful to enable us to learn to search for happiness in more productive directions. Instead of freedom, discipleship and slavery to an established tradition which teaches devotees to act in ways that lead to self developments and enlightenment, may create long run capabilities which are beyond the reach of our current imagination and vision.  read more

What are axiomatizations good for?

July 14, 2018 21 comments

from Lars Syll

Axiomatic decision theory was pioneered in the early 20th century by Ramsey (1926) and de Finetti (1931,1937), and achieved remarkable success in shaping economic theory … A remarkable amount of economic research is now centered around axiomatic models of decision …

UnknownWhat have these axiomatizations done for us lately? What have we gained from them? Are they leading to advances in economic analysis, or are they perhaps attracting some of the best minds in the field to deal with difficult problems that are of little import? Why is it the case that in other sciences, such as psychology, biology, and chemistry, such axiomatic work is so rarely found? Are we devoting too much time for axiomatic derivations at the expense of developing theories that fit the data?

This paper addresses these questions … Section 4 provides our response, namely that axiomatic derivations are powerful rhetorical devices …

I. Gilboa​, A. Postlewaite​, L. Samuelson, ​& D. Schmeidler

‘Powerful rhetorical devices’? What an impressive achievement indeed …

Some of us have for years been urging economists to pay attention to the ontological foundations of their assumptions and models. Sad to say, economists have not paid much attention — and so modern economics has become increasingly irrelevant to the understanding of the real world.  Read more…

What did I learn from my students? Market boundaries are shifting.

July 13, 2018 2 comments

A lot of my students do internships or write theses based upon problems of companies or NGO’s. Many teachers want them to play the research game. I prefer them to design something for the company or organisation as I really want them to learn that they don’t have to learn what their teacher wants them to learn…. or wait….

Anyway: what did I learn? Read more…

The core problem with ‘New Keynesian’ macroeconomics

July 12, 2018 11 comments

from Lars Syll

Whereas the Great Depression of the 1930s produced Keynesian economics, and the stagflation of the 1970s produced Milton Friedman’s monetarism, the Great Recession has produced no similar intellectual shift.

This is deeply depressing to young students of economics, who hoped for a suitably challenging response from the profession. Why has there been none?

risk-uncertainty-03-e1508523129420-1024x550Krugman’s answer is typically ingenious: the old macroeconomics was, as the saying goes, “good enough for government work”  … Krugman is a New Keynesian, and his essay was intended to show that the Great Recession vindicated standard New Keynesian models. But there are serious problems with Krugman’s narrative …

The New Keynesian models did not offer a sufficient basis for maintaining Keynesian policies once the economic emergency had been overcome, they were quickly abandoned …

The problem for New Keynesian macroeconomists is that they fail to acknowledge radical uncertainty in their models, leaving them without any theory of what to do in good times in order to avoid the bad times. Their focus on nominal wage and price rigidities implies that if these factors were absent, equilibrium would readily be achieved …

Without acknowledgement of uncertainty, saltwater economics is bound to collapse into its freshwater counterpart. New Keynesian “tweaking” will create limited political space for intervention, but not nearly enough to do a proper job.

Robert Skidelsky

Skidelsky’s article shows why we all ought to be sceptic of the pretences and aspirations of ‘New Keynesian’ macroeconomics. So far it has been impossible to see that it has yielded very much in terms of realist and relevant economic knowledge. And — as if that wasn’t enough — there’s nothing new or Keynesian about it!  Read more…

Six lies on trade

July 11, 2018 19 comments

from Dean Baker

After 500 days of Donald Trump’s presidency, it is clear that any relationship between his statements and the truth are purely coincidental. He even boasts about his lack of interest in the truth, touting the fact that he had no idea what our trade deficit was with Canada when he confronted Canadian Prime Minister Justin Trudeau over our “$100 billion trade deficit.” (The actual figure is around $20 billion.)

But Donald Trump’s contempt for the truth should not cause the rest of us to become liars also. In fact, it is more important than ever that progressives ground arguments in reality.

This is especially the case with trade, where lying was standard fare long before Donald Trump entered politics. Here are six common lies which deserve major pushback any time they appear.

1. Everyone gains from trade.

This is not even the textbook story. The textbook tells us there are winners and losers. In the standard story, the winners gain more than the losers lose. This means that the winners could compensate the losers so that everyone is better off. In the real world, this compensation never takes place, so the losers just lose.

If this is hard to understand, suppose we arranged for 300,000 highly qualified doctors from other countries to start practicing in the United States. This influx would probably lower our doctors’ pay by around $100,000 a year each to roughly European levels. This would save us close to $100 billion annually ($700 per family) on health care costs. That’s a big gain to the rest of us, but a big loss to US doctors. That’s basically the story of trade, but the competition has been for manufacturing workers.  Read more…

I ran out of words to describe how bad the recovery numbers are

July 11, 2018 4 comments

from David Ruccio

Back in June, Neil Irwin wrote that he couldn’t find enough synonyms for “good” in an online thesaurus to describe the jobs numbers adequately.

I have the opposite problem. I’ve tried every word I could come up with—including “lopsided,” “highly skewed,” and “grotesquely unequal“—to describe how “bad” this recovery has been, especially for workers.

fredgraph

Maybe readers can come up with their own adjectives to illustrate the plight of Americans workers since the Second Great Depression began—something that captures the precipitous decline in the labor share during the past decade (from 103.3 in the first quarter of 2008 to 97.1 in the first quarter of 2018, with 2009 equal to 100).

But perhaps there’s a different approach. Just run the numbers and report the results. That’s what the Directorate for Employment, Labour, and Social Affairs seem to have done in compiling the latest OECD Employment Outlook 2018. Here’s their summary:  Read more…

The randomistas revolution

July 10, 2018 6 comments

from Lars Syll

RandomistasIn his new history of experimental social science — Randomistas: How radical researchers are changing our world — Andrew Leigh gives an introduction to the RCT (randomized controlled trial) method for conducting experiments in medicine, psychology, development economics, and policy evaluation. Although it mentions there are critiques that can be waged against it, the author does not let that shadow his overwhelmingly enthusiastic view on RCT.

Among mainstream economists, this uncritical attitude towards RCTs has become standard. Nowadays many mainstream economists maintain that ‘imaginative empirical methods’ — such as natural experiments, field experiments, lab experiments, RCTs — can help us to answer questions concerning the external validity of economic models. In their view, they are more or less tests of ‘an underlying economic model’ and enable economists to make the right selection from the ever-expanding ‘collection of potentially applicable models.’

When looked at carefully, however, there are in fact few real reasons to share this optimism on the alleged ’empirical turn’ in economics.  Read more…

Intellectual property and China: No One is back

July 9, 2018 2 comments

from Dean Baker

I sometimes go under the professional name of “No One” as in “no one saw the financial crisis coming.” I apparently need to use this identification again when it comes to trade war with China.

On Morning Edition today, Jeff Greene interviewed Jonah Goldberg, senior editor at National Review. Mr. Goldberg told Greene how conservatives are free traders so they generally are opposed to Trump’s tariffs. He then suggested that a way out for Trump would be to focus on China’s intellectual property “theft,” since everybody agrees this is a problem.

This is where I come in. I don’t particularly consider the fact that China doesn’t pay Microsoft, Pfizer, and Boeing what they think they are owed to be a problem for people who are not major stockholders in these companies. As a basic proposition, the more money China sends to these companies, the larger its trade surplus in other areas.

More generally, as a basic proposition it is more than a bit bizarre that so many economists can somehow believe both that without patent and copyright monopolies and related protections, there would be no incentive for innovation and that technology causes inequality. If we have a problem with inequality due to “technology,”  it is due to the way in which we assign property rights. Shorter and weaker patents and copyrights means less money to the people on top and more money for everyone else.  Read more…

Econometrics cannot establish the truth value of a fact. Never has. Never will.

July 9, 2018 2 comments

from Lars Syll

assumptionsThere seems to be a pervasive human aversion to uncertainty, and one way to reduce feelings of uncertainty is to invest faith in deduction as a sufficient guide to truth. Unfortunately, such faith is as logically unjustified as any religious creed, since a deduction produces certainty about the real world only when its assumptions about the real world are certain …

Assumption uncertainty reduces the status of deductions and statistical computations to exercises in hypothetical reasoning – they provide best-case scenarios of what we could infer from specific data (which are assumed to have only specific, known problems). Even more unfortunate, however, is that this exercise is deceptive to the extent it ignores or misrepresents available information, and makes hidden assumptions that are unsupported by data …

Econometrics supplies dramatic cautionary examples in which complexmodelling​g has failed miserably in important applications …

Sander Greenland

Yes, indeed, econometrics fails miserably over and over again. One reason why it does, is that the error term in the regression models used is thought of as representing the effect of the variables that were omitted from the models. The error term is somehow thought to be a ‘cover-all’ term representing omitted content in the model and necessary to include to ‘save’ the assumed deterministic relation between the other random variables included in the model. Error terms are usually assumed to be orthogonal (uncorrelated) to the explanatory variables. But since they are unobservable, they are also impossible to empirically test. And without justification of the orthogonality assumption, there is, as a rule, nothing to ensure identifiability:  Read more…

Businesses can’t find qualified CEOs, don’t know how to raise wages

July 8, 2018 5 comments

from Dean Baker

That’s the implication of this CNBC piece that claims that hiring is down because businesses can’t find qualified workers. If this is really the problem, then the solution, as everyone learns in intro economics, is to raise wages. For some reason, CEOs apparently can’t seem to figure this one out, since wage growth remains very modest in spite of this alleged shortage of qualified workers.

Businesses should be well-positioned to absorb higher wages since their profits have soared over the last two decades. In the years from 1980 to 2000, the beneficiaries of upward redistribution were higher paid workers like CEOs, Wall Street-types, and highly paid professionals like doctors and dentists. Since 2000, there has been a substantial shift from wages to profits, as the after-tax profit share of national income has nearly doubled, as shown below.

Book2 9000 image001

Read more…

The Great Gatsby Curve

from The Atlantic

Economists represent this concept with a number they call “intergenerational earnings elasticity,” or IGE, which measures how much of a child’s deviation from average income can be accounted for by the parents’ income. An IGE of zero means that there’s no relationship at all between parents’ income and that of their offspring. An IGE of one says that the destiny of a child is to end up right where she came into the world.

So much for ‘statistical objectivity’

July 6, 2018 2 comments

from Lars Syll

Last year, we recruited 29 teams of researchers and asked them to answer the same research question with the same data set. Teams approached the data with a wide array of analytical techniques, and obtained highly varied results …

All teams were given the same large data set collected by a sports-statistics firm across four major football leagues. It included referee calls, counts of how often referees encountered each player, and player demographics including team position, height and weight. It also included a rating of players’ skin colour …

unchallengable-statisticsOf the 29 teams, 20 found a statistically significant correlation between skin colour and red cards … Findings varied enormously, from a slight (and non-significant) tendency for referees to give more red cards to light-skinned players to a strong trend of giving more red cards to dark-skinned players …

Had any one of these 29 analyses come out as a single peer-reviewed publication, the conclusion could have ranged from no race bias in referee decisions to a huge bias.

Raphael Silberzahn & Eric Uhlmann

Read more…

A Tale of Three Classes in the USA

July 5, 2018 6 comments

from The Atlantic

Saez / Zucman