Read: Economics as Religion

  • the 15th edition, then by Samuelson and Nordhaus, was the textbook assigned to the introductory economics course I took in the nineties. Hence, it often seems that Nelson does not write about the field of economics but only but this, admittingly influential, textbook. Other protagonists, the antipole, are the various members of the Chicago School, most prominently Frank Knight.

    The observation that many early economic analyses were based in (unexamined) presuppositions that were more like articles of faith is not enough to convince this reader of economics as religion. The observation that some economist assiduously follow their agenda, may it be driven by intellectual curiosity or political conviction, is not enough to convince this reader that economists are secular priests.

    Nevertheless, the links between Catholicism and leftist Progressivism on the on side and Protestantism and more right-wing Libertarianism on the other side and their respective protagonists in economics are interesting. Religion influences, of course, culture, and therefore, it will also influence (economic) thought. Still, the increasing secularization, agnosticism, atheism, non-religiousness, and the move towards scientism does not make economics a religion.

    In spite of Nelson’s failure to convince me of economics as religion I agree with him on one major point: Economics, economic analysis is not value free. Economics is often more normative than we like to admit. Those presuppositions need to be examined. Luckily, they are.

Read: Are Markets Moral?

  • A complete waste of time.

    “Are Markets Moral?” is a transcript of a one day inter-disciplinary workshop on the question that is this book’s title.

    Presenters regurgitate ideas that they have presented much more eloquently and convincingly earlier, often in other, much longer books of their own, or they speculate about issues, social phenomena that they have absolutely no clue about. The discussions are shallow; the discussants talk at cross-purposes, don’t try to synthesize, or if they respond they resort to cheap attacks, free from empirical facts with the sole purpose to discredit an opposing (and reasonable, evidence-driven) opinion.

    The composition of the group of participants is seriously biased. Everyone seems to have (just) their own pet peeve and no genuine interest in answering the workshop’s big question. I pity the poor souls who attended in the hope of gaining new insight.

    Much more enjoyable, instructive, and insightful are Daniel Friedman’s “Morals and Markets” and Paul Zak’s “Moral Markets.”

Read: Counterfactuals and Causal Inference

  • Counterfactuals and Causal Inference is a very practical book that discusses the different approaches to identify causal effects (in non-experimental and experimental data) at a very abstract level. Depending on the reader this may be a good or not so good thing. I had to expend substantial effort to work through the text and I fear that even though I understand directed acyclical graphs I have not developed any intuition in their application that would help me in my applied modelling. Often, the text remains at a too abstract level.

    What the text is missing is an even more practical guide with more concrete applied problems and their solutions. Yet, the text is good. It’s not a handbook for a quick how to do it. It’s not a textbook for undergraduates. It’s a critical survey of the state of the art of statistical approaches for the identification of causal effects. It’s a valuable reminder that the regression approach is no magic bullet.

    That being said, the text raises the important question of identification and alerted me that some effects that we estimate and report may not be the effects that we would like them to be. I guess I will have to be even more careful when I interpret regressions in the future.

    Addendum: I have read the first edition that I had for already some years sitting on my to-read shelf. I just discovered that there is a 2nd, revised edition available.

Read: How not to be wrong

  • With “How not to be wrong” being about mathematical thinking I was a bit surprised about how much of it was about statistics. And even though it (may) lack(s) the depth of critique of the (ab)use of statistics that can be found in the works of Ziliak and McCloskey or Gigerenzer it is a very good popular treatment of the topic. Worth the read.

    A particular additional added value is – in my opinion – the reminder that most things in the real world are not linear. Linearity is just an approximation, valid for only (very) small ranges. I agree with Ellenberg, we – I – forget this too often.

    The only thing that I did not like was the sports references (I can condone idiosyncratic tastes in music). The book includes lots of footnotes and endnotes with references. So many, and so many recent ones that I, indeed, found a few new sources that I added to my to-read list. That is rare.

Read: What the best College Teachers do

  • Based on a sample of effective college / university teachers in the late 1990 Ken Bain tried to identify the specific approach to teaching and characteristics of successful teachers (hence there is no systematic control group). This is not necessarily the professors with the best teaching evaluations but rather those teachers with students who learn, understand, and succeed.

    The bad news is: There is no secret trick. It’s not the flipped / inverted class room, it’s not the use of fully animated power points, it’s not the extensive use of videos in class, it’s not overly generous grading practices, and it’s not paying students for their participation in class and doing their assignments.

    Still, there was a common trait. It’s their approach to teaching that rather focusses on the who and not on the what. In brief, it’s student centered teaching and the teachers’ attitude towards their students.

    I believe smaller classes (and a lower teaching load) facilitate developing this trait, though it is obviously true that also large classes benefit from such an attitude and the resulting approach. I am not quite there yet.

Read: The Calculus of Selfishness

  • Karl Sigmund’s The Calculus of Selfishness applies basic evolutionary game theory to the analysis of cooperation in strategic interactions. Though it is published in the Princeton Series in Theoretical and Computational Biology it is rather addressed to social scientist, economist and psychologist, and in particular undergraduates.

    The Calculus starts simple enough and Sigmund introduces whatever mathematics he needs without being too formal in his approach. For a text in applied math the book reads surprisingly well. However, it is still a book in applied math and I fear it is as such not really appealing to an undergraduate in the social sciences. Indeed, I do not believe there are many undergraduate economics students who would enjoy this book and not put it aside after the first few pages, the first chapter at the latest. While this may be a good example of a text in applied math it is not “good enough” for the nascent social scientist.

    On the other hand, it is an excellent introductory text on the evolutionary game theory of cooperation, direct and indirect reciprocity, fairness, reputation, and trust. I only wished Sigmund would have expanded on structured interaction and the co-evolution of subpopulations. He only hints at what results would be obtained when one would look at these things more carefully.

    I also particularly appreciate that each chapter ends with a briefly annotated list of references for further, in more depth, reading on the topic and the game theoretic approach that was introduced in the respective chapter. While the terse exposition of the chapter can only serve to raise one’s interest these references are the real treasure trove of The Calculus of Selfishness.

    Hence, while I would not recommend the book to any of my undergraduates in economics or social sciences I would happily point any graduate student in its direction.

Read: Adapt

  • I really liked Tim Harford’s The Undercover Economist and The Logic of Life. His recent Adapt is good but not on par with his two other books.

    The idea of failure as a driver of success it not new. Fail early, fail often, fail cheep is a well and long known slogan that sums up the gist of the book pretty well. Rapid prototyping (was hip when I learned programming) is a related development methodology that applies exactly this mantra to the development process.

    Tim Harford presents a number of case studies, each focusing on a different aspect of the falling forward process. First, he shows how a lack of the willingness to adapt leads to devastating and utter failure. Then, how experimentation, the willingness to fail, can lead to success …eventually.

    Each case study is linked to name. There is a face for each of the failures, trials, and successes. This helps to emotionally connect. You boo the rigid non-adaptors, you cheer the daring and successful adaptors. And this is where Tim Harford, at least from my perspective, fails. Adapt becomes an entry in the long list of self-improvement guidebooks.

    By focusing so much on the extraordinary individuals, heros, and blockheads the more skeptic reader may get the feeling that Harford is talking about outliers, non-generalizable singular events (he is not; at one point he also cites and discusses a more rigorous study with lots of data; this gets completely lost later on). This is even more so as he mentions the same individual(s) over and over again at different places and in different contexts. It diminishes the credibility of main thesis. This is bad because I believe the idea of fail early, fail often, fail cheep to be good and true. I did not want to read a self-improvement book. A little bit more supporting data, a little bit more variation would have been nice.

    A minor quarrel: why dispraise Hayek (I have the paperback edition) after using his work for supporting a point? What does this add to the thesis of the book?

Read: Experimental Economics - Rethinking the Rules

  • In contrast to what some economist today still say and believe, economics is an experimental science. At the latest, when the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was award to Daniel Kahemann (a psychologist) and Vernon Smith (an economist) in 2002 they should have acknowledged it.

    Economic experiments have been proven useful in informing theory and testing (new) economic institutions before their implementation on a broader scale, e.g. the design of spectrum auctions that generated unprecedented revenues for the states running them. Unfortunately even within the community of experimental economist their use and purpose is not without controversy. Some, let’s call them experimental economists in a narrower sense see the main use of experiments in economics in showing that the theory works (well) and finding instances of when it works best. The other group, let’s call them behavioral economists see the economic experiment as one method to investigate the underlying assumptions of economic theory in order to inform theory building and inspire the revision of economic theories so that they may move more towards a positive than a normative model of the world.

    With Experimental Economics a group of six British experimental economists now tried to critically assess the current state of the field that constitutes an invaluable tool for research in all areas of economics.

    In a series of chapters they address the method and methodology of experimental economics, the domain of economic theory (where and when does it apply?) and the limits of experimental tests in terms of what can be said about the theory and the external validity of the experimental observations; and also how experiments are used as rhetorical devices, “exhibits” that reliably show some particular behavior of their participants illustrating a specific point. Two further chapters address the important issue of financial incentives in experiments (when are they needed, how should they be implemented?) and different sources of noise in the data that requires bespoke statistical treatment.

    The last point, noise in the data and heterogeneity between subjects is in my opinion a very important one as this is still often a neglected topic in most experimental studies today. Of course, a well designed experiment may allow the authors to show their main point without any fancy statistics. On the other hand, in order to move to a positive theory of economic behavior the individual and not the aggregate behavior should be the focus of the analysis. This necessarily requires a more advanced statistical treatment of the data. As well as laboratory and field experiments (and happenstance data) are complements so are theory, experiments, and statistics complements.

    In sum, even though I may not agree with some of the more specific points Bardsley, Cubitt, Loomes, Moffatt, Starmer, and Sugden make their book is an excellent text that will make it on the reading list for my courses in experimental economics.

Read: Game Theory - A Very Short Introduction

  • Very recently I came across Oxford University Press’ Very Short Introduction series. The series comprises now of almost 300 titles ranging from Archaeology and Art to Medicine and Social Sciences. Of course, there are also some titles dealing with economics and other more quantitative topics; Game Theory is one of them. There could not be a more obvious and substantial difference to popular science books covering Game Theory (in a good sense).

    Binmore covers a broad range of topics, from conflict and cooperation to conventions, bargaining and auctions. Most important he links the theory to observed behavior and evolutionary dynamics that may explain deviations from some of the normative predictions of standard Game Theory (under assumptions of perfect rationality and opportunistic preferences). It is these discussions of evolutionary dynamics that made the small book (less than 200 pages) worthwhile for me.

    For the most part Binmore’s writing style is crystal clear. However, I had, of course, substantial training in Game Theory and need to apply it quite often. Even though Binmore explanations and definitions are easy to follow I fear that there is still too much jargon, too few definitions and a lack explanations of some of the essential concepts of Game Theory that would be needed for a real introduction.

Read: Rock, Paper, Scissors -- Game Theory in Everyday Life

  • Len Fisher provides an entertaining glimpse at Game Theory, or at least a part of it. Rock, Paper, Scissors focuses on coordination problems, social dilemmas and possible solutions. The book is very non-technical. Indeed, the reader may not learn any new game theoretic concepts – given that those who will pick up a book with Game Theory in its title are likely to know already the most basic ingredients of Game Theory.

    Nevertheless, the book adds some value. The everyday examples of applied Games are as instructive as they the writing is witty. The focus on social dilemmas facilitates attracting some attention. And research results – not his own; he gives, for instance, a recount of Axelrod’s The Evolution of Cooperation – are presented in an easy to understand way. You may hold against Fisher that the favored solution to these dilemmas is presented as something seemingly simple even though it is actually hard to implement: Change the game.