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Read: How to Read a Book

I believe you can get an idea on how to write well by reading. Not just by reading the “right” books that set an example, that provide you with a blue print for your own writing, but also by reading well.

Adler and van Doren’s How to Read a Book is a guide for reading well. Their main lessons are maybe to ask a certain set of question that your reading of a book, any text really, should answer and that every text deserves its own speed of reading. Some texts should be read carefully, slow, repeatedly. Other texts should be read fast, cursorily, or not at all.

The meat of the book covers analytical reading that should lead to answers to four crucial questions:

  1. What is book about as whole?
  2. What is being said in detail, and how?
  3. Is the book true, in whole or part?
  4. What of it?

and provides a set of 15 rules or recommendations that help in the process to discover the answers and judge the text. This is considerably more detailed than my own two guiding questions so far:

  1. What is this about?
  2. So what?

The book has a little bit too much meat, it tries to convince and justifies every little recommendation. This leads to some repetitions. (There were moments when I was reminded of Monty Python’s The Holy Hand Grenade.) Nevertheless I did not dare to skip any part. This is one of the books that deserve to be read well. (See http://sachachua.com for a nice visual summary and http://www. farnamstreetblog.com for a longer discussion of the book’s content.)

It deserves to be read well for some of the hidden gems that do not necessarily (only) relate to reading well. My attention was in particular caught by:

Discovery stands to instruction as learning without a teacher stands to learning through the help of one. In both cases, the activity of learning goes on in the one who learns. It would be a mistake to suppose that discovery is active learning and instruction passive. There is no inactive learning, just as there is no inactive reading.

This is so true, in fact, that a better way to make the distinction clear is to call instruction “aided discovery.”

Teachability is often confused with subservience. A person is wrongly thought to be teachable if he is passive and pliable. On the contrary, teachability is an extremely active virtue. No one is really teachable who does not freely exercise his power of independent judgment- He can be trained, perhaps, but not taught.

Needless to say, How to Read a Book will make it onto my students’ reading list.

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: Guide to Information Graphics

Now, that was a waste of money. Don’t get me wrong. Dona Wong’s Guide to Information Graphics is a nicely designed little book with some valuable advice on how to present quantitative date. Why is it a waste of money? It does not go beyond very small data sets and few closely related time series. The data we talk about is so sparse that even the dreaded pie chart cannot distort the perception of the depicted quantities by much and consequently is discussed in this little book.

Though, book may be an overstatement; booklet seems more appropriate. And despite only being about 150 pages ‘thick’ there are some repetitions in its content. This is often a good didactic move. For a reference book not so much.

Since Dona Wong is a student of Edward Tufte it makes sense to rather refer to his work. So instead of looking into Guide to Information Graphics have a look at:

Another “Old Master” is William S. Cleveland and his

If you rather need an overview of different types of plots and ways to present data Information Graphics - A Comprehensive Illustrated Reference by Robert L. Harris is the reference you look for.

Not as nicely designed as Dona Wong’s Guide, yet with considerable more content is Naomi Robbins’ Creating More Effective Graphs.

And finally, I rather enjoyed reading Howard Wainer’s Picturing the Uncertain World. Though it is more a historic account of the development of good and effective graphical displays.

Read: Mostly Harmless Econometrics

Reading statistics or econometrics textbooks cover to cover is certainly not something any “normal” person would do. So, I am not normal. And so ain’t Mostly Harmless Econometrics by Angrist and Pischke.

You cannot learn econometrics just by reading this book, you would need another textbook for the basic econometric theory. Yet, MHE offers something often not found in your standard textbook: an applied perspective. It addresses issues that may arise from empirical work in labor and micro-economics focusing on identification of causal effects, illustrating the methods and pitfalls using empirical field studies that either rely on natural experiments (happenstance data) or field experiments.

Their brief chapter on nonstandard (i. e. nonstandard according to the theoretical ideal, the real world looks different) standard errors is, for instance, astonishingly accessible and almost makes me revise my standpoint on modelling the error structure (using multilevel designs) vs adjusting standard errors.

I do not know whether science geeks are still attracted by Adams’ Hitchhiker’s Guide to the Galaxy. Angrist and Pischke, sure, are. Not only is the title of their textbook an obvious reference to Adams’ work, they start every chapter with a little Adams quote. Something I did, too, when I was still in graduate school. This gives their book a slightly brighter, less earnest tone. All in all, it is certainly not as dry as many other econometrics textbooks.

As an additional added value, Angrist and Pischke set up a companion website to their companion where they post corrections (there are already quite a number of erratas) and comments to MHE.

Read: The Craft of Argument

Rhetoric is a craft that seems to be the natural talent of some, most (including myself) have to train to achieve any level of proficiency. Williams and Colomb’s textbook The Craft of Argument is a wonderful complement to Williams’ Style – Lessons in Clarity and Grace and Booth, Colomb and Williams’ The Craft of Research.

While the Craft of Research shows how to structure, plan, and execute the more general task of pursuing one’s research, The Craft of Argument advises on how to structure, plan, and write one’s articles (or report, or books …), and Style, finally, advises on how structure, plan, and write single paragraphs and sentences.

Good, persuasive and ethical writing is a hard task. This task is somewhat alleviated by Williams and Friends. Their textbooks are always a pleasure to read adducing evidence that they master[ed] their craft.

Gelesen: Statistical Rules of Thumb

Gerald van Belle, Prof. für Biostatistik, legt mit Statistical Rules of Thumb einen praktischen Ratgeber für die statistische Praxis in bereits der zweiten Auflage vor. Das Buch ist thematisch gegliedert und jede Regel wird nicht nur motiviert sondern auch theoretisch hergeleitet. Van Belle hat einen sehr angenehmen Stil und trotz der eher trockenen Natur des Stoffes ist man verleitet, das kleine Büchlein von Anfang bis Ende zu lesen.

Das Buch ist nicht für den Anfänger, sondern wirklich für den Praktiker gedacht, dessen Handwerk sich hauptsächlich um die Anwendung der statistischen Methoden dreht. Rules of Thumb ist kein Lehrbuch und definitiv nicht die letzte Instanz zu theoretischen Fragen. Es bietet jedoch einen interessanten Überblick über die typischen Fragen, die sich bei der täglichen Anwendung von statistischen Methoden ergibt.

Leider hat das Lektorat an einigen Stellen versagt. Bedauerlich, wenn man bedenkt, dass dies bereits die zweite Auflage ist. Nicht selten sind Sätze unvollständig (Worte fehlen) oder übervollständig (Worte sind zuviel/doppelt). Das Formelwerk ist jedoch korrekt.

Für mich war bezeichnet, dass ich es hier schon wieder mit einem Biostatistiker zu tun habe. Ich als Ökonom mit einem (Ausbildungs-)Schwerpunkt in der Ökonometrie wende mich in meiner Arbeit immer häufiger den Methoden der Biostatistik zu. Nun gut, als Verhaltensökonom sind die sonst typischen Zeitreihenmodelle der Ökonometrie eher unbrauchbar, aber auch die Mikroökonometrie hinkt ein wenige der Biostatistik hinterher.