Thoughts on end-of-semester lectures (Part 1)

At the end of the semester, I like to make a splash with students. For example, in my intermediate microeconomics course I put together a fun lecture. We have some laughs talking about models. We talk Rolling Stones songs like “you can’t always get what you want” (budget constraints) as well as Queen songs like “I want it all” (monotonicity).

We wax philosophical with Robert Frost’s “The Road Not Taken” about opportunity cost. We reiterate that the arguments in utility functions can be a richer set of desires than food and shelter. As Adam Smith says, “Man naturally desires not only to be loved, but to be lovely.” We emphasize that our models are simplified because good models try to get to the heart of the matter.

Sometimes models are dangerous. Like the “monkey illusion” we become so distracted we miss the heart of the matter. One prime example is how Samuelson continued to update the projection about when the USSR would surpass the US economy (check this out for more info) or Easterly’s depiction of the World Bank notion that if you build it, growth will come.

We discuss the importance of models, how they organize our thinking, the dangers of being too wed to a model but also the importance of empirical testing. We use MobLab in class to test our models as I’ve written about here. But, MobLab can’t give us an empirical test of all the important questions. We have to look elsewhere, out in the world to find evidence. One of my favorite examples of this are cross-border comparisons like East and West Germany, North and South Korea, Haiti and the Dominican Republic, etc.

I remind students that incentives matter. Economic institutions influence the costs and benefits of human action. When costs and benefits change, we expect for behavior to change. Throughout the semester we learned to formalize these ideas and they are not without consequence. As this New York Times piece discusses the work of Amartya Sen,

“Nature causes floods and droughts, but most societies have found ways to get food to those afflicted most of the time. Human folly causes famine, which occurs when those ways are blocked. Amartya Sen, a Harvard economist, argued that there has never been a serious famine in a country — even an impoverished one — with a democratic government and a free press. The press acts as a warning system and the pressures of democracy dissuade rulers from famine-producing policies.”

While economics is fun, interesting, and can be light-hearted, economics can also be deadly serious. The stakes of economic illiteracy are enormous.

Next week we go on to Part 2 where I pivot from this section of the end-of-semester talk to the applications of economic ideas to the everyday life of students.

Rationality and economics

Lately I have been thinking a lot about rationality and economics. In my Economics of the Family and Religion course I exhort students to take the approach, “crazy is lazy”. Like archeologists that brush away the dust from artifacts we should brush away the dust of human decision-making and find the rationality. This is especially useful when it comes to understanding observed patterns in religious practice across time and space. You don’t get very far with, “people are nuts”.

Humans make decisions on purpose. They weigh the costs and benefits of an action and make the choice that seems best to them given their available opportunities. Some students have struggled to integrate this message with their other classes. At FSU we have a deep bench of experimental and behavioral economists so there are ample opportunities for students to see courses with a more psychological approach.

In one famous study, Khaneman and Tversky manipulate whether there is a positive or negative frame on a treatment for a deadly disease. In the positive frame, there was a 33 percent chance that treatment could save the 600 people with the deadly disease. In the negative frame, there was a 66 percent chance the treatment could kill the 600 people with the deadly disease. Notice that both of those probabilities result in 200 people being saved. However, people were far more favorable to the positive frame (72%) compared to the negative frame (22%).

Then there are numerous other behavioral economics findings about seemingly small things that impact the decisions people make. For example, in research about bidding behavior psychologists Dan Ariely and Drazen Prelec and economist George Loewenstein passed out sheets of paper and had students write the last two digits of their social security number (SSN) at the top before they placed a bid for each item on a sheet. Students with SSN in the top 20 percent of the distribution bid 216 to 346 percent higher for the items compared to those with SSN in the bottom 20 percent.

We could go on. In the face of those kind of results, it is no wonder that students pause to reflect about how these findings fit into the larger corpus of economics. Are they useful observations to the extent they help us improve the predictions of our models? Are they damning demonstrations that cut out the heart of the economic approach?

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Date-onomics

This short spark plug of a book written in 2015 by author Jon Birger was hard to put down. The book is informative on the idea of “marriage markets” and makes the case that, “college and post-college hookup culture, the decline in marriage rates among college-educated women, and the dearth of marriage-material men willing to commit are all by-products of lopsided gender ratios and a massive undersupply of college educated men.” (p. 5)

Recall from an earlier blog post, when there are more women relative to men, women compete with each other and effectively lower their “asking price” (their share of the marital benefits). This also applies to dating markets too. If you’re having trouble seeing how sex ratios matter, consider this example from the book,

“Among undergrads at UNC there are 50 percent more women than men …” That is for every 40 men there are 60 women which means 3 women for every 2 men, “If you want to visualize what 3:2 looks like, imagine you’re back in college. Imagine it’s late at night, and you’re hanging out with friends in someone’s dorm room. Imagine everyone has had a few beers, the mood is flirty, and people are thinking about pairing off. Now imagine there are three women and two men.” 

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Education and Marriage

In class today we discuss education and marriage. While we see a general trend toward fewer and later marriages there are substantial differences across education. More educated men and women are marrying more than less educated men and women. They are also divorcing less. So highly educated people who are well-paid are combining their incomes and securing the benefits that come from marriage. Meanwhile less educated individuals are either not forming relationships (single parents) or forming relationships and living arrangements that are less durable (e.g. cohabitation). So on average there is either a low single income or two low but combined incomes. This is a topic that has been discussed substantially in news outlets. For example, here are articles from The Atlantic, Forbes, and Freakonomics.

You can imagine this has lead to substantial income inequality. For example, this study from a few years ago in the NBER reports that, “Data from the United States Census Bureau suggests there has been a rise in assortative mating….[I]f matching in 2005 between husbands and wives had been random, instead of the pattern observed in the data, then the Gini coefficient would have fallen from the observed 0.43 to 0.34, so that income inequality would be smaller.”

That assortative mating refers to people sorting into relationships with people like them. In this case, people with high education marrying people with high education. But, even for its coverage in the media, we probably do not discuss enough how rising income inequality is driven by patterns in marriage and divorce among those with high and low education.

Economics of Romance

In the immortal words of Haddaway, “What is love?” Despite being in bed all of Tuesday, and not being up-to-the-task of teaching Wednesday, I mustered enough energy to talk with the Economics Club at FSU about the “Economics of Romance”.

In that talk, I started with some good economics jokes — some of which can be found here. Skipped some really bad economics pick-up lines, and waxed about the dangers of thinking at the margin in a world that thinks about levels. For example, the next time your spouse asks whether the presentation you’re writing is more important than them …. well, don’t try to explain marginal thinking to them.

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Helpful Teaching Resources

In this brief post, I want to commend a few teaching resources that have been helpful over the past few months of teaching.

For teaching students the nuts and bolts of causal inference, the new Mastering Metrics videos with Josh Angrist on Marginal Revolution University are terrific. The causal animations from Nick Huntington-Klein (and other resources) are also very helpful. This app on linear regression from Luke M. Froeb and Keyuan Jiang is a helpful way to help students gain econometric intuition. They have a companion paper to the app on SSRN.

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Sex Ratios and the Marriage Market: WW1

Last week I wrote about the “marriage market“. In many ways, the marriage market is like a labor market: there are search costs, match quality, competition for mates, and so on. When one side of the market becomes more abundant, that side become less picky — their minimum willingness to accept goes down.

Today we examine war as a shock that makes women more abundant than men. The marriage market predicts this shock will mean a smaller fraction of women will marry but those that do receive a smaller share of the benefits from marriage. Also, a larger fraction of men will marry and receive a larger share of the benefits from marriage.

Ran Abramitzky, Adeline Delavande, and Luis Vasconcelos investigate marriage in pre-and-post World War 1 (WW1) France where an estimated 16.5 percent of the French male population died or were missing in WW1. You can see from the map below that some “departments” suffered greater losses than others. Across France, the sex ratio was nearly even before the war and after the war, “If we focus on singles, widows, and divorces who were 30 years old or younger but of marriageable age, there were approximately 2 men for every 3 women.”

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The idea of a “marriage market”

For those not familiar with the idea of a “marriage market”, consider the following quote from Gary Becker from his paper “A Theory of Marriage, Part 1” (emphasis own),

“Two simple principles form the heart of the analysis. The first is that, since marriage is practically always voluntary … the theory of preferences can be readily applied, and persons marrying can be assumed to expect to raise their utility level above what it would be were they to remain single. The second is that, since many men and many women compete as they seek mates, a market can be presumed to exist. Each person tries to find the best mate, subject to … market conditions” (p. 814)

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Taxes and Commitment

An American tourist in a foreign land surveys the surroundings. Down on the river he sees a boat at a distance coming into town. The men are being whipped as they row the boat filled-to-the-brim with fresh produce. Angered at the sight, the tourist rushes down to the dock to meet them as they unload. He tells the men of their value and worth. He yells at the man who whipped them. Then, a twist happens. The men explain that they were concerned they would not row fast enough and therefore were worried the fresh produce would spoil before getting to market. They hired the monitor to ensure they all rowed fast.

The source of that apocryphal story is unclear, but the economic content is rich. The men were concerned with the free-rider problem and sought a commitment device to ensure their fast rowing. How often are we willing to suffer the lashes of inefficiency to obtain some measure of the public good?

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The Church and Public Assistance

When the unexpected happens, who are you going to call? One of the important social functions of religion is that it operates as social insurance. For example, someone who cannot afford groceries, rent, or some other staple like their utility payment might contact their local church leader and ask if there is possibility for assistance during this difficult time. At this point, some might be saying, “They shouldn’t have to do this. The government should provide a safety net for these people.”

There is certainly a connection between the social insurance function of the government and churches. For example, Daniel Hungerman (2004) uses the 1996 Welfare Reform Act to document that the church and state are substitutes in the provision of social services. Part of welfare reform was to restrict welfare payments made to immigrants. Therefore, churches in states with a larger share of immigrants should see a greater decline in welfare payments and, if the church and state are substitutes, a larger increase in church spending on social activities. That is exactly what Hungerman finds. For every one dollar reduction, churches increased spending by 20 – 38 cents.

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