On teaching the economics of inequality

In the Spring semester of 2017 I taught an undergraduate course on economic inequality for the first time. Every time I mention this to anyone, they want to know what I put in it. Now that I have a reasonable idea of what worked and what did not in the first outing of this course, I want to share here the basic structure of the course and some of the most important readings in it. To start with, here are the main topics, each with a short explanation and some reading suggestions. I regretted that there was no textbook for this course that presented the material I wanted to teach in the way I wanted to teach it; I have now embarked on writing such a book. (There does exist a huge Oxford Handbook of Economic Inequality, but it is not usable as a textbook, because it emphasizes breadth over depth of coverage and ends up with very brief discussions of difficult topics, that the reader has to work hard to assimilate by reading detailed expositions in the references.)

Course structure, including the main readings

  1. Normative reasons to care about economic inequality. You would think that why an economics student should care about inequality should be obvious to them, but I encountered, before I started the class, the question of why we should care. So I came up with this topic and the next. It didn’t hurt that I have long considered economists, in the main, much too narrow-minded regarding how to evaluate economic allocations from a normative point of view. The superb online Stanford Encyclopedia of Philosophy has an excellent article on distributive justice, with links to other articles on related topics. The Stanford Encyclopedia’s distributive justice article is a good core reading for this section of the course. The main temptation I had to stay away from when teaching this material was to include a serious survey of the voluminous work of the Nobel laureate economist Amartya K. Sen. This work deserves an entire semester for itself. Rather than extract some bits from it without all the context, I minimized references to it, with regret. For the interested reader, the following books by Sen contain a good presentation of his pathbreaking work:
    Collective Choice and Social Welfare: An Expanded Edition, 2017;
    The Idea of Justice, 2009;
    Inequality Reexamined, 1995;
    Choice, Welfare and Measurement, 1999.
    There are more books and articles by Sen and his intellectual interlocutors that arguably belong to this list, but as the list is already too long, I am leaving it as is.
  2. Positive economic reasons to care about economic inequality. “Positive” here refers to “positive economics”, the study of “what is” in the economic sphere. In this usage, “positive” is contrasted with “normative”, the study of what ought to be, which was covered in the previous section with the discussion of distributive justice. This section focuses instead on a large experimental literature that makes up a large part of what is strangely called “behavioral economics”, the literature on the way individuals assess inequality in the way they evaluate economic outcomes. The main reading for this section is roughly the first half of this survey of the literature by Ernst Fehr and Klaus Schmidt. The main conclusion here is that individuals feel a lower level of satisfaction about economic conditions when there is more income inequality, all other things equal, even when they occupy a privileged position in the income distribution. This is not to say that everyone feels this way; rather, that enough people feel this way that force economists to study the topic of inequality because economic agents in the theories that economists build take account of inequality themselves in a way that affects their economic decisions.
  3. Equality of opportunity. When we are discussing economic opportunity, we usually find that even political conservatives mainly agree that individuals are responsible for their economic outcomes to the extent these follow from the individuals’ actions, but not from the individuals’ circumstances at birth that they have no control over (such as the individuals’ race). The intuitively clear way towards equality that this idea suggests is that if we equalize the starting point of everyone, then the inequality of economic outcomes that results from their actions is morally acceptable, as it results from their free agency. The main reading for this topic is the following difficult, but rewarding, article:
    John E. Roemer and Alain Trannoy, Equality of Opportunity: Theory and Measurement, Journal of Economic Literature, 2016, 54(4), 1288‒1332.
    There is plenty of opportunity to write a more accessible exposition of this topic, and it is part of my plan to do so.
  4. Measurement of inequality. Given a set of data on the distribution of some economic variable, such as income or wealth, across people, how do we come up with a numerical scale to tell is how unequal this distribution is? Several measures have been proposed, and some, like the Gini coefficient, are popular with researchers and writers in the field. An easily digestible exposition (but with a few typos in formulas) is in chapter 6 of:
    Debraj Ray, Development Economics, Princeton University Press, 1998.
    This set of lecture slides is a good complement to the chapter from Ray’s book, if nothing else, because it corrects the typos.
    While we are discussing measurement, I simply must also point out the following online sources of data, in many cases very well presented with interactive graphics:
    World Incomes Database: http://www.wid.world/
    Chartbook on Economic Inequality: http://www.chartbookofeconomicinequality.com/
    Income inequality from the Our World in Data website: https://ourworldindata.org/income-inequality/
    Clearly a data-minded person could structure an entire semester’s course on the material from these three websites alone. I chose to put the material in a broader context, in which I present the data briefly and expect the students to use the data in their term papers, if they choose empirical term paper topics.
  5. Capital and inequality. This section is inevitable, given the enormous success of Piketty’s book Capital in the Twenty-First Century. The book became a surprise best-seller in the aftermath of the “occupy” years and there are several good critical discussions in the literature, including this excellent one by Lawrence Blume and Steven Durlauf:
    Blume, Lawrence E. and Steven N. Durlauf, Capital in the Twenty-First Century: A Review Essay, Journal of Political Economy, 2015, vol. 123, no. 4, 749‒777. Available at https://www.ssc.wisc.edu/econ/Durlauf/includes/pdf/Blume%20Durlauf%20-%20Capital%20Review.pdf
    Other good pieces in this debate include (I am trying hard to cite as few as possible):
    Acemoglu, Daron and James A. Robinson, The Rise and Decline of General Laws of Capitalism, Journal of Economic Perspectives, 2015, 29(1), 3‒28, available at http://economics.mit.edu/files/11348, as well as Piketty’s own rejoinder to his critics,
    Piketty, Thomas, Putting Distribution Back at the Center of Economics, Journal of Economic Perspectives, volume 29, number 1, Winter 2015, pages 67‒88.
  6. Globalization and inequality. In the aftermath of Brexit and the 2016 presidential election, I need not tell you why this is an issue of huge concern for the majority of voters in at least the UK and the US. The book by Branko Milanovic, Global Inequality: A New Approach for the Age of Globalization, is the central reading for this section, but one must not miss the critical discussion of this book here and the rejoinder by Milanovic and Lakner here. This debate is about Milanovic’s “elephant graph”, which became practically a meme online. This graph purports to show that the middle classes of rich societies have not kept up with income growth in Asian countries and among the rich in their own societies for a few decades now, hence the massive discontent about globalization one reads about in the press and finds reflected in election results.
  7. Technology and inequality. Robots are after our jobs, says practically everyone, or so it seems after only a few minutes of reading online about automation and its disruptive influence on work as traditionally understood. David Autor (yes, there is no “h” in his last name) has an accessible article that is the core reading for this section, in which he examines the impact of automation on employment and wage dispersion. The main lesson from this article is that the “middle-skill” occupations have been hit hard by automation, losing a lot of jobs, while jobs that need low or high skills have been treated well in terms of numbers of jobs by automation (but in terms of wages, only certain high-skill jobs have been treated well, but then these have been treated really, really well).
    Autor, David H., Why Are There Still So Many Jobs? The History and Future of Workplace Automation, Journal of Economic Perspectives, volume 29, number 3, Summer 2015, pages 3-30.
    Other readings for the ambitious reader who cares deeply about this topic include
    Acemoglu, Daron and David H. Autor, Skills, Tasks and Technologies, from the Handbook of Labor Economics, http://economics.mit.edu/files/11635; also
    Webber, Douglas A., Are college costs worth it? How ability, major, and debt affect the returns to schooling, Economics of Education Review, 2016, volume 53, pages 296-310.
    For some of the latest on robots, see
    Acemoglu, Daron and Pascual Restrepo, Robots and Jobs: Evidence from US Labor Markets, MIT Working Paper, March 2017.
  8. The impact of race and gender on inequality. There is a huge literature on the economics of discrimination. It is not possible to fit a detailed exposition of it in a small segment of a semester devoted to inequality. I found that the following two papers give enough of an introduction to these issues for anyone to pursue the topics further.
    Lawrence Kahn, Wage Compression and the Gender Wage Gap, http://wol.iza.org/articles/wage-compression-and-gender-pay-gap/long;
    Emmons, William R. and Noeth, Bryan J., “Race, Ethnicity and Wealth”, in “The Demographics of Wealth”, The Federal Reserve Bacnk of St. Louis, February 2015, https://www.stlouisfed.org/household-financial-stability/the-demographics-of-wealth.
  9. Economic policy against inequality. This topic is certainly one that students waited for eagerly while we were slogging through the theoretical and empirical context just detailed in bullet points 1 through 8. Parts two and three of Atkinson’s book Inequality have an excellent discussion of detailed policy proposals by Atkinson, whose death in the very beginning of 2017 deprived the field that studies economic inequality of one of its founders and intellectual giants. One topic that is bruited about a lot online is universal basic income. Right near the end of the semester the following book came out, devoted to this topic exclusively. It is a good book, and I plan to incorporate it better in future versions of the course, when I will have had time to prepare accordingly.
    Philippe Van Parijs and Yannick Vanderborght, Basic Income: A Radical Proposal for a Free Society and a Sane Economy, Harvard University Press, 2017.

Books used

Even though I did not use a book as a textbook, I did refer the students to chapters in the following three books (which have been mentioned above). After teaching the course once, I decided that, although I will cite Piketty’s book among these three, I will only assign readings from the other two books.

  • Atkinson, Anthony, Inequality: What Can Be Done? Harvard University Press, 2015.
  • Milanovic, Branko, Global Inequality: A New Approach for the Age of Globalization, Belknap / Harvard, 2016.
  • Piketty, Thomas, Capital in the Twenty-First Century, Belknap / Harvard, 2014.

Another great tribute to the late Kenneth Arrow

This one is by the great Indian development economist, Debraj Ray. There is a ton of great material in this, so go read it please, posthaste! I can’t resist quoting the penultimate paragraph, with some great tidbits about Arrow’s famous quirks (and genius):

There are many stories about Ken Arrow. Some are semi-apocryphal. Some we can vouch for. For instance, I have seen him nod off during talks (including one that I gave) and then wake up to ask a remarkable question. And he did flip pencils in seminars, and I have seen him on at least one occasion attend a talk with his bicycle helmet on. Once Doug Bernheim and I, convinced that a speaker was wrong, paid no further attention to the seminar and tried to construct a counterexample together. Arrow somehow knew that that was what we were up to, because after the seminar he walked into Doug’s office (where we were still at it), wrote the required example on the board, did a little jig and walked away — complete with bicycle helmet. But one story possibly is apocryphal, and yet fully sums up the Ken Arrow that I was so fortunate to know. Arrow was in class, teaching. He was speaking fast, running as he always did with his thoughts. Students were frantically taking notes as the disembodied sentences emerged. And then, suddenly: “Stop, stop! That’s all wrong!” As the students frantically began to erase their jottings, he continued: “No, no, not what I said, what I was going to say.”

A profound loss for economics

Professor Kenneth Arrow, a titan of economic theory and Nobel laureate for economics, died yesterday at the age of 95. The New York Times published an excellent obituary. Economics Nobel laureate Al Roth published a blog post about this, the comments on which I recommend reading as well. Finally, Kevin Bryan started a monumental series of four posts on his blog, explaining patiently and deeply the contributions Arrow made to economics. Here is the first of these posts.

UPDATE 2017-02-25: Here is a concise and heartfelt tribute by Lawrence Summers, a nephew of Arrow. Two personal reminiscences in this are so compelling that I am taking the liberty of quoting them here:

I remember like yesterday the moment when Kenneth won the Nobel Prize in 1972. Paul Samuelson—another Nobel economist and, as it happens, also my uncle—hosted a party in his honor, to which I, then a sophomore at MIT, was invited. It was a festive if slightly nerdy occasion.

As the night wore on, Paul and Kenneth were standing in a corner discussing various theorems in mathematical economics. People started leaving. Paul’s wife was looking impatient. Kenneth’s wife, my aunt Selma, put her coat on, buttoned it and started pacing at the door. Kenneth raised something known as the maximum principle and the writings of the Russian mathematician Pontryagin. Paul began a story about the great British mathematical economist and philosopher Frank Ramsey. My ride depended on this conversation ending, so I watched alertly without understanding a word.

But I did understand this: There were two people in the room who had won Nobel Prizes. They were the two people who, after everyone else was exhausted and heading home, talked on and on into the evening about the subject they loved. I learned that night about my uncles—about their passion for ideas and about the importance and excitement of what scholars do.


Kenneth knew more about everything than most know about anything, but he never flaunted his intelligence. It was another lesson for me when, many years ago, a paper was published correcting a famous analysis published by one of Kenneth’s teachers. At the time, it created a stir. I asked him what he thought. He said quietly that he had known of the error for decades, but such was his respect for his teacher that he did not publish his insight.

Same-sex marriage legalization linked to a decrease in teen suicide attempts

This article in The Guardian discusses in detail a paper just published in JAMA Pediatrics, co-authored by Julia Raifman, Ellen Moscoe, S. Bryn Austin, and Margaret McConnell.

The first link above leads to a nice explanation of the results of the paper, and the second leads to an extended abstract that readers who are adept in econometrics (and other statistics-savvy people) will want to read closely.

It seems to me that the marginal benefit of same-sex marriage legalization includes the saving of many lives. The marginal economic cost is negligible, if it is even positive, compared to such a marginal benefit. Individuals wishing to argue that the moral marginal cost outweighs the marginal benefit will find it very hard to convince me of their case.

UPDATE: I changed “suicides” to “suicide attempts” in the title of this post for higher accuracy.

The debate on how to teach econometrics

I am no econometrician and I don’t play one on TV. But I am keenly interested in how economists use econometrics and so when big debates on how it should be taught at university pop up, I am all ears. Apparently, lots of people care as much. Yesterday I tweeted about a blog post by Francis X. Diebold on the topic and my tweet became fay and away the most retweeted and liked of all my tweets. Since you might want to follow up and read that blog post, here is the tweet itself.


RIP Sir Tony Atkinson

Professor Sir Tony Atkinson died today. He was a giant in the field of the economics of inequality of income and wealth. His work will inform a large part of my new course on economic inequality, which starts in 16 days. Economics has been dealt a serious blow by his passing.

Why we use mathematics in economics

Economics Nobel winner Jean Tirole put it succinctly as follows:

In a mostly auto-generated translation via Twitter’s web interface, this says “[we] use mathematics not because we’re smart but because we’re not smart”.

I agree wholeheartedly. Using mathematics in our work in economics (and in so many other areas of research) allows us to stand on the shoulders of giants and use their smarts. It’s on us to make good use of this powerful tool, honed over the centuries by so many brilliant people. Criticisms of using mathematics in economics are pointless; criticisms of using mathematics badly in economics are valuable.