Movie production incentives don't pay off

I've written before about the supposed economic impact of movie production (see here and here). The argument is that movie production increases employment and contributes to growth, both in its own right, and in its ability to increase subsequent tourism. I question both of those conclusions, or at least question the idea that the benefits of movie production incentives exceed the costs of those incentives.

And now I have some new research support for my conclusions. In a new article published in the Journal of Economic Geography (sorry I don't see an ungated version online), Mark Owens (Penn State University Erie) and Adam Renhoff (Middle Tennessee State University) look at movie production incentives granted by U.S. states. They constructed a dataset of all movie productions in the U.S. over the period from 1999 to 2013 (some 16,725 movies), including filming locations and their characteristics, as well as the characteristics of the movies. They also collected data on four types of movie production incentives (emphasis mine):

A refundable tax credit allows the production studio to receive cash back when the value of the tax credit exceeds their state tax liability. A transferable tax credit allows the movie studio to sell their outstanding tax credits to a third party if the value of their tax credits exceeds their state tax liability. Standard non-refundable, nontransferable tax credits, which are not very common, offer movie producers significantly less financial flexibility. Cash grants or rebates are cash transfers (treated in this research as a percentage of the qualified production spending) from the state to the movie production studio. They are not tied to the company’s tax liability.

They also collected data on the minimum spend required to qualify for incentives. Using a reasonably sophisticated discrete choice modelling approach, they find that:

 ...movie production incentives vary in their ability to attract films, and vary with respect to firm size. The magnitude of the effect of incentives is the largest for mid-sized studios (the so-called ‘mini-major’ studios) where each incentive has a positive and significant impact on location choice. None of the production incentives significantly impact the location choice for independent studios, the smallest firms with smaller budgets, possibly because independent movies are less likely to meet minimum requirements and/or because they are less likely to be profitable. Consistent with intuition, we find that major producers respond more favorably to refundable and transferable tax credits than to standard (non-transferable, non-refundable) tax credits. Refundable tax credits are more effective than transferable tax credits in attracting major studios.

In other words, movie production incentives are effective in attracting movie productions. No surprises there - the studios are simply responding to incentives - if a particular location offers greater benefits than another location (including in the form of tax credits or other incentives), then the studio is more likely to want to produce their movies in that location.

However, Owens and Renhoff then conduct a back-of-the-envelope calculation weighing up the costs and benefits of movie production incentives for U.S. states. They have to make a number of assumptions here, because they don't have complete data on movie production spending, etc., but their results can be taken as indicative:

Based on our estimates, the movie production incentive programs are all revenue-negative, implying that a dollar awarded in tax credits leads to an increase in tax revenues, that is, less than a dollar. In this sense, the efforts to attract film production to a state do not ‘pay for themselves’ with higher resulting state tax revenues.

In other words, costs are greater than benefits. Movie production incentives do not pay back the taxpayer. However, if a state government's is simply to increase employment, Owens and Renhoff do offer some hope:

The tax incentive programs appear to increase employment at a lower cost to the state than the cost of directly increasing the number of state employees.

Of course, that doesn't mean that there aren't more cost-effective ways of increasing employment. Asking if a policy increases employment at a lower cost than if the government employed people to dig holes in the ground and then fill them in, is setting a very low bar.

Unfortunately, while this research provides justification to get New Zealand out of the Tiebout competition that is providing large movie production incentives, I fear that it will fall on deaf ears.

Read more:

• Lord of the Rings, tourism arrivals and harvesting
• More on hobbits and tourism

The minimum wage and suicide

One of the more robust findings in the happiness economics literature is the negative impact of unemployment on happiness (as just one example, see this paper). So, to the extent that unhappiness (including depression) is associated with suicide or attempted suicide, we might expect higher unemployment to be associated with more suicide.

There is ongoing debate, and there is no settled consensus, but I believe that the weight of evidence seems to suggest that higher minimum wages do reduce employment (and therefore increase unemployment) - see my most recent post on this topic here. So, to the extent that minimum wages increase unemployment, and unemployment increases unhappiness, then we might expect higher minimum wages to be associated with more suicide.

However, that isn't end of the story. Higher minimum wages are associated with higher incomes (in the simplest sense, among those that receive the minimum wage), and higher incomes might buffer against depression (and suicide). So, there are potential effects in both directions for the relationship between a higher minimum wage and suicide.

A recent article in the Journal of Epidemiology and Community Health (ungated here, and see this New York Times article as well) by John Kaufman (Emory University) and co-authors looked into this relationship using monthly state-level data from the U.S. over the period from 1990-2015. They found that:

When further controlling for state-specific time-varying economic variables, we estimated a 3.5% reduction in the suicide rate for every additional dollar in state minimum wage...

Those results were based on the suicide rate among people without a college education (who might be expected to be more affected by the minimum wage). They found a statistically insignificant effect on suicide among college-educated people. So, it appears that the positive effect of the minimum wage on incomes may outweigh the negative effect of unemployment on suicide.

Kaufman et al. also report that:

We found a statistically significant interaction between minimum wage and unemployment... indicating that the impact of minimum wage varies across the unemployment rate... When unemployment is high (>6.5%), progressively higher minimum wages are associated with lower suicide rates, while at low unemployment (3.8%–6.5%) the effect of minimum wage is attenuated, with little effect observed at very low unemployment (<3.8%). We observed the highest suicide rates when state minimum wage was no higher than the federal and unemployment was high. Curiously, the lowest suicide rates were observed when both minimum wage and unemployment were high (eg, unemployment >7% and minimum wage ≥US$1.75 above the federal).

These results are interesting, but perhaps problematic. Since it appears that unemployment and minimum wage rates are negatively related, it is difficult to disentangle the two effects in this way. So, I would put much more weight on the headline result than on this additional analysis. However, I think more work needs to be done on this research question, as the mechanisms underlying the negative relationship (which has also been found in some other studies) remains under-explained. That might usefully be achieved by looking at individual-level data, rather than aggregate state-level data.

[HT: Marginal Revolution]

This study tells us nothing about whether studying economics make students less ethical

Does studying economics make students less ethical? The research question is interesting and potentially important (and I've written about similar questions before - see here and here). Answering it, though, is pretty challenging. Simply comparing some measure of ethics between students that have studied economics and students have not studied economics is no good, because perhaps less ethical students choose to study economics. That would create a problem of selection bias. Similarly, comparing some students who chose to do economics early in their degree programme, and students who chose to leave economics for later, faces the same problem.

So, I was quite disappointed when I read this book chapter by Christian Mastilak (Xavier University) and co-authors (ungated earlier version here). Promisingly, they conduct a lab experiment with business school students, some of whom have studied microeconomics already, and others that haven't, and test how ethical their choices are across a few experiment tasks. They find that:

...participants with exposure to agency theory assumptions through either an experimental manipulation invoking a competitive, wealth-maximizing frame consistent with common agency theory or prior microeconomics coursework acted more unethically than participants who had neither exposure to agency theory.

By "agency theory" here, Mastilak et al. are really referring to economic theory more generally (and in fact that's how they refer to it in the ungated version of the paper). They started their experiment by having participants play a prisoners' dilemma game. The game had two different framings, and each participant saw only one framing: (1) as a competition between two competing firms, with an emphasis on each firm's individual payoff; or (2) as a collaboration between two NGOs, with an emphasis on the joint payoff to society as a whole.

They then went on to have their participants engage in other tasks, a few of which were used to evaluate ethical behaviour (or otherwise). They find no differences between participants on two of the tasks, but they do find statistically significant differences on one task, that involves participants overstating a budget request, where they would receive a payout that enriches them.

Mastilak et al. compare the budget request between participants who were exposed to the competitive or cooperative framing of the prisoners' dilemma, and find that participants exposed to the competitive framing made larger budget requests (thereby acting less ethically). However, comparing participants who had completed prior economics with those that had not, there were no statistically significant differences. Now, see if you can follow these bits of the paper:

Panel B reports a two-way ANOVA. The effect of the experimental condition (frame) is significant (p = 0.011).

Initially, it appears there is no effect of prior microeconomics coursework as the effect of prior microeconomics coursework is not significant (p = 0.193)... coursework. Tests of simple main effects are reported in Table 1, Panel C. For participants who had taken microeconomics, the agency frame condition had no effect (p = 0.201). For participants who had not taken microeconomics, the agency frame condition had a significant effect (p = 0.026).

We interpret our tests of simple effects as indicating that either agency frame manipulation or prior economics coursework is sufficient to increase unethical behavior...

Wait - read that last bit again. They interpret their results as indicating that "either agency frame manipulation or prior economics coursework" increases unethical behaviour. And yet, one paragraph earlier, they clearly say that "the effect of prior microeconomics coursework is not significant", and that the effect of framing on participants who had taken microeconomics was also not statistically significant.

And even their results of the agency frame having a significant effect for those who had not taken microeconomics is shaky, because their whole sample size of participants who had not taken microeconomics was 11 students. And because microeconomics is compulsory for business students, those 11 students are students who had left economics until later in their degree programme, so can be assumed to be meaningfully different from the other students (self-selection bias).

Who peer reviewed this book chapter? The headline result is basically not supported by the analysis. The effect of the prisoners' dilemma framing on subsequent unethical choices is interesting (although I have some issues with the particular way they conducted the framing), but it tells us nothing about whether studying economics affects ethical behaviour.

Experimental studies can often help us to better understand relationships in a controlled environment. However, studies like this one do not help at all.

Read more:

• Does education in economics make politicians corrupt?
• The impact of business and economics education on moral competence

Framing, loss aversion, transaction utility, and reusable coffee cups

This article in The Conversation yesterday, by Sukhbir Sandhu, Robert Crocker, and Sumit Lodhia (all University of South Australia) caught my attention, because it nicely illustrates some of the concepts from behavioural economics that I discussed with my ECONS102 class last week:

Many cafe owners offer discounts ranging from 10c - A$1 to customers who bring in their own reusable cups.

But our findings reveal these discounts are ineffective in changing consumer behaviour.

A cafe owner we interviewed described how, despite providing a 20c discount for reusable cups, she didn’t think saving money motivated her customers:

The regulars were people who’d happily drop in a dollar tip into the jar kept on the counter. They were therefore not that concerned about 20c discount.

We know from previous behavioural psychology literature consumers are more likely to be what’s called “loss averse” as opposed to “gain seekers”. In other words, people hate paying extra for takeaway coffee cups more than they like getting a discount for bringing their reusable cups.

So, if you own a cafe, focus on making consumers pay extra for choosing takeaway coffee cups rather than offering discounts for reusable cup use. It’s more likely to motivate customers.

Let's say that a cafe owner wants to encourage customers to use reusable cups. They might do this because of concern for the environmental effects of disposable coffee cups, or the cafe owner might simply recognise that disposable cups cost them money, and so offering to fill a customer's own cup must be slightly more profitable for the cafe owner, because then they don't incur the cost of providing a cup.

Putting aside any cost differences, cafe owners could discourage their customers from disposable cups by making coffee sold in disposable cups more expensive. We know that when something is more costly, rational consumers will buy less of it. This also makes coffee in reusable cups relatively cheaper, and so would encourage some consumers to switch. Let's consider two different framings of the price difference: (1) consumers who use a reusable cup receive a 20 cent discount; or (2) consumers who use a disposable cup have to pay an extra 20 cents. 

How many consumers would switch? If consumers were purely rational, it wouldn't matter how the price difference was framed. A 20-cent discount for using a reusable cup and paying 20 cents extra for a disposable cup are exactly the same (provided the prices are the same in each case). Both options would lead to the same number of customers switching to a reusable cup.

Now here's where some behavioural economics comes in. Consumers (like every decision-maker) are not purely rational, they are quasi-rational - they are affected by cognitive biases and use heuristics when making decisions. Framing makes a difference to quasi-rational consumers, but it's not clear which framing should make consumers use fewer disposable cups.

One of the cognitive biases that quasi-rational decision-makers are affected by is loss aversion - decision-makers dislike losses much more than they like equivalent gains. In this case, the loss in utility (or satisfaction, or happiness) for the consumer from paying 20 cents extra for a disposable cup, is 'worth' much more than the gain in utility (or satisfaction, or happiness) for the consumer who receives a 20-cent discount for using a reusable cup. So, we would expect the 'loss framing' (20 cents extra) to have a much bigger effect on consumer behaviour than the 'gain framing' (20-cent discount). 

However, another cognitive bias that affects consumers is transaction utility, which I have blogged about before. Transaction utility recognises that consumers not only receive utility from the good or service that they purchase, but also from the act of purchasing. If a consumer feels that they are 'getting a good deal', this makes them happier (higher utility), and makes them more likely to purchase. So, based on transaction utility, we would expect the 'gain framing' (20-cent discount) to have a bigger effect on consumer behaviour than the 'loss framing' (20 cents extra).

Given that Sandhu et al. found that the negative framing had a bigger effect overall, it appears that the loss aversion effect is larger than the transaction utility effect. It would be good to see more research on this though, that disentangles those two effects more.

Overall, the takeaway message from this research is that if you, as a seller, want to steer consumers away from something using a price difference, present it as involving a loss to them (they have to pay extra). On the other hand, if you want to steer consumers towards something using a price difference, present the alternative as involving a loss to them. At least until this has been investigated a bit more, it appears that paying extra is a more powerful motivator for changing consumer behaviour than a discount.

The coronavirus lockdown and the New Zealand market for illegal drugs

As I noted in yesterday's post, this week my ECONS102 class has been covering the model of supply and demand. So, with that in mind, here's another good example of supply and demand at work, from the New Zealand Herald a few weeks ago:

New Zealand's illicit drug market has had a major shake-up due to Covid-19 with a new report forecasting likely price increases and a drop in purity.

A post-Covid 19 drug landscape document, created by Drug Information and Alert NZ, found it was "almost certain" the changes in the country's illicit drug market would have wide-ranging social impacts.

It detailed how supply fall-offs for methamphetamine were basically a given, at least in the short-term, due to global supply chain and domestic travel difficulties.

The report said price increases for the drug were more or less guaranteed, and informal collections suggest wide-scale price increases had occurred across the board.

The effects of the reduction in the supply of methamphetamine on the New Zealand market are illustrated in the diagram below. The market was previously at equilibrium, where the demand D0 and supply S0 intersect, and where the equilibrium price was P0 and the equilibrium quantity of methamphetamine traded was Q0. Then, as a result of the coronavirus lockdown, the supply of drugs reduced to S1. The new equilibrium is where demand D0 and supply S1 intersect, where the equilibrium price has increased to P1, and the equilibrium quantity of methamphetamine traded has decreased to Q1.

You could argue that the demand for methamphetamine may have increased as well. If people have nothing better to do with their time, such as working, then perhaps they want to want to engage in some 'recreational activity'. The article notes this, in the case of MDMA:

One dealer, spoken to on the condition of anonymity, confirmed it had been harder for him to come by MDMA, but the calls appeared to be increasing.

"The demand is perhaps higher [compared to pre-lockdown], I think there's a culture in New Zealand where people are now almost abusing the substance."

In this case, the diagram below demonstrates the effect. Again starting from an equilibrium price of P0 and an equilibrium quantity of Q0, supply has decreased from S0 to S1, while demand has increased from D0 to D2. The new equilibrium is where demand D2 and supply S1 intersect, where the equilibrium price has increased to P2. The combined effect of the decrease in supply and increase on demand on the equilibrium quantity is ambiguous. In the diagram, it shows that the quantity has returned to Q0. However, if the shift in demand had been just a bit larger, then the equilibrium quantity would have increased. And, if the shift in supply had been just a bit larger, then the equilibrium quantity would have decreased. So, we can be sure that the equilibrium price of MDMA will have increased, but we cannot be sure about the change in equilibrium quantity.

 

Finally, this bit from the article is interesting:

Also noted was the risk of substituting drug types as certain products become harder to source in the short term, which could lead to more related harm as it said unfamiliarity with a substance can result in overdoses.

"If the illicit drug supply dwindles, dealers may seek to stretch their existing supply by using cutting agents. This poses a danger as people may not be aware of what they are actually using."

When the price of a good increases, sellers will want to sell more of it (what we refer to as the 'Law of Supply'). However, if sellers can't get more of the good to sell, then this appears to create an incentive to make their existing supplies stretch further, which drug sellers can achieve by cutting their drugs with something else. This is not a good situation for drug buyers, but unfortunately most buyers are not in a good position to judge the quality of the product they are buying. This problem of asymmetric information is an important point my ECONS102 class will come back to later in the paper.

Childcare adjusting to a new, lower-demand, equilibrium

This week, my ECONS102 class is covering supply and demand. Today, we talked about equilibrium, and tomorrow, we will talk about how the market shifts from one equilibrium to another. So, this story from the New Zealand Herald a few weeks ago is timely:

Childcare centres are offering big discounts for new customers as centres open up in fast-growing suburbs just as demand falls due to Covid-19.

Four out of 13 centres in the expanding Kumeū-Huapai area in northwest Auckland are offering 50 per cent discounts for new children who enrol in the next two, three or six months, and a fifth is advertising free fees until the end of July.

Early childhood planning consultant Logan Whitelaw says discounting is also occurring in Silverdale and Beachlands in Auckland, and at Rolleston near Christchurch.

In all those places, new centres have just opened or are about to open at a time when many parents have pulled back from daycare because they have lost their jobs, are working more from home or are still worried about the risk of children catching Covid-19.

Parents "pulling back from daycare" has led to a decrease in the demand for daycare. We can illustrate this using a diagram, shown below. The equilibrium price was initially P0, and there were Q0 days of childcare 'traded' in the market. Then demand decreases from D0 to D1. Childcare centres could try to keep their price high at the initial price of P0. The problem with that is that families will now only demand Qd days of childcare (that is the quantity demanded on the new demand curve D1, when the price is P0). The childcare centres are still expecting to supply Q0 days of childcare, so many of them are going to be empty. Rather than having an empty (or mostly empty) centre, it is better for the childcare centres to try to attract some of the families who do want childcare. They can do that by offering a discount, as the news story suggests is happening. The price of childcare starts to fall. How far will it fall? Childcare centres will still have more places available than children filling them all the way until the price has dropped to the new equilibrium price of P1. At that new, lower, price, the quantity of childcare days demanded (Q1) is exactly equal to the quantity of childcare days supplied (also Q1).

The discounts will likely be temporary though. When the world has returned to something more resembling normality, and employment has returned closer to previous levels, demand for childcare will increase, and the process will be reversed - the equilibrium price of childcare will go back up towards P0.

Quasi-rational students choosing their university major

How do university students select their major? We might hope that they would first identify all of the majors that are available, then carefully weigh up the costs and benefits (to them) of each available major, and then select the major that has the greatest net benefit to them. That is how a theoretically 'purely rational' student would choose, based on the cost-benefit principle. However, we know that real people are not purely rational. They are affected by a range of cognitive biases and make shortcuts in their decision-making. In other words, real people are quasi-rational.

So, how would a quasi-rational student select their major? This 2019 working paper by Richard Patterson (US Military Academy), Nolan Pope (University of Maryland), and Aaron Feudo (US Military Academy) provides a partial answer, at least in terms of identifying some of the biases that affect students in selecting their major.

Patterson et al. make use of data from 8777 students at the US Military Academy (USMA) at West Point, over the period from 2001 to 2015. At USMA, the first two years of the Bachelor's Degree are assigned to students automatically - they have no choice over the order of classes. Some classes are in the same semester and year for all students, while some are randomised between the first and second semester. Students must choose their major during the first semester of their sophomore year, and during that year they are randomised into whether they study economics and philosophy, or political science and geography, in each semester. So, during the semester that they first choose their major, students will have been studying one or other of those two pairs of courses.

Patterson et al. test whether the timing of courses matters for the selection of a major. For a purely rational student, the order in which they take courses should not matter, since the order doesn't affect either the costs or the benefits of each major. However, quasi-rational students are affected by availability bias. Availability bias arises when a decision-maker gives more weight to information that is readily available to them, which means information that they have received more recently, or information that is more salient or vivid. In either case (more recent information, or more salient or vivid information), that information will be more easily remembered and so it receives more weight in the decision.

In the case of selecting a major at USMA, Patterson et al. argue that the courses that students are taking in the first semester of their sophomore year will be more likely to be selected as a major, because of this availability bias. And indeed that is what they find:

...assignment to a course in the first semester of sophomore year increases the probability that a student will initially choose a corresponding major by 2.9 percentage points, or 110 percent. This result is highly precise and is significant at well beyond the 1 percent level.

The results continue to hold after controlling for student demographics, course and year fixed effects, demographic characteristics of classmates, and for the full course schedule. The results are the same regardless of the gender, race, or academic ability of the student. The results also hold regardless of how well the students performed in these classes, or how well they evaluated the courses at the end of the semester. Students at all levels of the grade distribution, and at all levels of course evaluation, were more likely to select the corresponding major of the courses they studied in the first semester of their sophomore year.

That's not the end of the quasi-rationality of these students though. After selecting their major in the first semester, there is very little that would stop a purely rational student from switching major in the second semester. The only cost is that they need to get a form signed by two academic advisors (one from the major they are switching out of, and one from the major they are switching into). However, a quasi-rational student is affected by status quo bias and loss aversion.

Loss aversion means that real people value losses much more than equivalent gains (in other words, they like to avoid losses much more than they like to capture equivalent gains). Loss aversion leads real people (including students) to avoid changing their minds, and to prefer the status quo. As Patterson et al. put it in this paper:

Once students select a major, they might experience psychological costs to switching majors. There may be several potential sources for this bias. For example, students might feel ownership of their initial choice and exhibit loss aversion...

Giving up something that students own (including our choice of a university major) is difficult, because it entails a loss (they lose the major that they were originally enrolled in). Patterson et al. find evidence for this status quo bias as well:

...the effects of first-semester assignment on graduating major are large and statistically significant... but about half the magnitude of the effects on initial major. First-semester assignment increases the probability that students select a corresponding major by between 1.4 and 1.5 percentage points (34 to 40 percent).

In other words, the effect of course order on selecting the major persists all the way through to graduation for some students. Some students do change major after the first semester of sophomore year, but not enough to eliminate the effect of course order on choice of major.

So, students are affected by both availability bias and status quo bias when they select their university major. They might also be affected by other biases as well, but this paper only provides evidence for those two biases. How should universities respond to this? If there are particular majors that universities want to steer students into (e.g. STEM), they could schedule students to do those courses at the time that students select their major. This might also be important if universities want to reduce gender or other biases in particular courses.

These results also suggest we should be cautious about having students select a university major before they begin their studies. Availability bias will lead students to be more likely to select into majors that are familiar because they are taught at high school (e.g. accounting) and less likely to select into majors that are not (e.g. marketing). They might also bias students in less affluent schools, where a full range of courses is less likely to be available, away from majors that are becoming less commonly taught (e.g. economics, sciences). Status quo bias then keeps those students in their initially-selected major, when some of them might be better off if they switched to a different major later.

Universities need to take care about how they set up course and major selection for students. The process itself, combined with the quasi-rationality of students, could easily lead to less desirable outcomes, for both students and for academic departments.

[HT: Marginal Revolution, last year]

Poor research doesn't help us understand the relationship between fast food availability and health

I've done quite a bit of research on the effects of alcohol outlets on neighbourhoods, focusing on the relationship between the number of outlets and an area and measures of harm, such as violence. The challenge in that sort of research is establishing causality. In particular, alcohol outlets tend to locate in poorer neighbourhoods, and those neighbourhoods tend to have more social problems. Also, people who want to drink more might want to live closer to places where they can easily access alcohol, and they might also be the kind of people who cause (or are victims of) social problems. Because of those reasons (and others), there is a lot of confounding of how large the relationship between alcohol outlets and harm actually is.

A similar problem is faced in the literature that attempts to link fast food outlets to health impacts at the neighbourhood level. So, even more than in the alcohol outlets literature, there isn't a consistent set of statistical results linking fast food outlets with obesity, for instance. However, it might be possible to deal with at least some of the issues by looking at the effects on children, because at least children aren't going to move to be closer to fast food outlets (probably!). However, that still doesn't solve all of the issues.

One example is this 2019 article by Matthew Pearce (NHS Gloucestershire Clinical Commissioning Group), Isabelle Bray, and Michael Horswell (both University of the West of England), published in the Journal of Public Health (open access). They look at accessibility to fast food outlets and obesity among children in South Gloucestershire, England, over the period from 2006 to 2013. Children were surveyed at the start and the end of the period. Essentially, Pearce et al. look at the relationship between obesity, or rather weight gain (proxied by whether each child gained 50 percentile points in a standardised weight distribution over the period between the two surveys) and access to fast food outlets (measured as a weighted score based on how many outlets are near where the child lives, and how close they are).

To me, this paper initially had a lot of promise. However, it then finds quite conflicting results that are difficult to reconcile. First:

The Spearman’s rank correlation coefficient between change in weight between Reception and Year 6 and accessibility score found no evidence of an association (r = −0.07, P = 0.768).

In essence, there was no correlation between fast food outlets and their measure of obesity. However, they then break their fast food accessibility measure into three groups, and find that:

The group of children (tertile 3) most exposed to fast-food outlets were more likely to gain significant weight (>50 percentile points) than those least exposed (odds ratio = 1.89, 95% confidence interval: 1.0–3.6, P = 0.04).

In other words, children in the top one-third (tertile) of the distribution of fast food accessibility experienced more weight gain than those in the bottom one-third. This is of course a very different finding than their initial result of no correlation.

The problem here stems from the choices the researchers have made in their analysis, and that they don't make those choices transparent to the reader of the article. Why do they use tertiles in the analysis, and not quartiles or quintiles, or indeed using the actual distribution of accessibility scores which is a continuous variable? As a journal reviewer and editorial board member, one of my pet hates is when researchers take a continuous variable and turn it into a categorical (or ordinal) variable instead. At the very least, I'd want some additional analyses to demonstrate that these results don't simply arise as a result of the researchers' choices about how they specify this variable in their analysis.

The lack of transparency is good reason to discount these results, and should be a good lesson to other researchers on what not to do if you want your research to be credible. This paper may have generated some buzz at the time of its release (including here in New Zealand), but it does nothing to help us actually understand the relationship between fast food availability and health.

The economic impact of universities

I've been quite critical of 'economic impact studies' in the past (for example, see here). These studies try to estimate the economic impact by aggregating up all of the spending associated with an event (for example). The key problem is that they don't usually properly take account of the counterfactual - what would have happened if the event hadn't taken place. In the case of the economic impact of a particular industry, it can be difficult to establish what the counterfactual actually is - what would have happened if that industry didn't exist? That is the case when you try to estimate the economic impact of a university, for example.

An alternative approach is to avoid trying to estimate the economic impact of a particular university, but instead to compare regions that have universities from those that don't. That can include comparing regions before and after a university is established there, as well as comparing regions with different numbers of universities.

Essentially, that is the approach taken in this 2019 article by Anna Valero (London School of Economics) and John Van Reenen (MIT), published in the journal Economics of Education Review (open access, but just in case there is an earlier ungated version here). Valero and Van Reenen use data on economic growth rates and the number of universities in 1498 regions across the world, covering the period from 1960 to 2010 in five-year time steps. They find that:

...on average, a 10% increase in the number of universities in a region is associated with around 0.4% higher GDP per person.

The results are robust to a variety of different specifications. However, that isn't all. Not only are universities associated with higher growth within a region, the higher growth also spills over into surrounding regions, such that:

...a 10% increase in universities in the rest of the country (which in most cases will represent a greater absolute increase than a 10% increase in home region universities) is associated with an increase in home region's GDP per capita of around 0.6 per cent.

They also find that the effect is greater for poorer regions, suggesting that:

...new universities have a stronger impact on laggard regions within a country.

Valero and Van Reenen then go on to investigate the important question of how universities might contribute to higher GDP per capita. They suggest four possible mechanisms:

(i) a greater supply of human capital; (ii) more innovation; (iii) support for democratic values; and (iv) demand effects.

The first two are obvious, but it turns out that changes in human capital (as measured by the share of university graduates) and changes in innovation (as measured by the cumulative number of patents) only explain a small proportion of the effect of universities on GDP per capita. In terms of the third mechanism, Valero and Van Reenen first note that:

Universities could promote strong institutions directly by providing a platform for democratic dialogue and sharing of ideas, through events, publications, or reports to policy makers.

This is over and above any effect that universities might have on human capital. Looking at the impact of universities on support for democratic institutions (using data from the World Values Survey), they find that:

...there is a highly significant association between university presence in a region and approval of a democratic system.

Interestingly, this result is not driven by university graduates, because they get the same result if they drop graduates from the World Values Survey sample.

Finally, Valero and Van Reenen look at demand effects, which is the only channel that a traditional economic impact study would consider - how much of an effect does the spending of students and staff and the university itself have on the economy? They find that:

...we can explain around 15% of the regression coefficient on universities.

In other words, the vast bulk of the economic impact of universities is not even going to be picked up in a traditional economic impact study.

Of course, this research isn't going to be the last word on this topic. Even though Valero and Van Reenen run a battery of robustness and other checks, their results are still based on correlations and so they cannot be definitive about universities causing higher GDP per capita. However, in their robustness checks they do seem to have eliminated many of the most plausible alternative explanations. They are also unable to definitively address questions about the extent to which the size or quality of universities matters. Universities do have a positive economic impact on a region (and neighbouring regions), and we are getting closer to understanding how large that impact is, and how it arises.

Why study economics? It causes higher incomes...

I've posted a number of times about why students should study economics (see the long list at the end of this post). Several of those posts highlight the earnings premium that economics students receive - students who study economics earn more than those studying in many other fields. Most of the evidence I've cited in those posts is observational - it involves a straight comparison between the earnings of economics majors and the earnings of other students. It could rightly be criticised as not demonstrated that economics causes higher earnings. Perhaps the types of students who study economics would earn more, even if they studied sometime else instead of economics - we refer to this as selection bias, because in this case it would mean that better students are selecting to study economics.

A recent working paper by Zachary Bleemer (University of California, Berkeley) and Aashish Mehta (University of California, Santa Barbara) sets out to solve the selection bias problem and provide causal estimates of the impact of studying economics on income. They make use of data from the University of California as Santa Cruz, which implemented a grade point threshold in 2008 that students needed to meet in order to be admitted into an economics major (a GPA of 2.8 based on grades in the first two economics courses). Students who are very close to, but above, the threshold should be very similar to students who are very close to, but below, the threshold. Effectively, whether or not those students very close to the threshold could choose to do the economics major or not is random. So, comparing the incomes of those two groups of students shows how much doing an economics major matters - this is referred to as a regression discontinuity design, because if the threshold has an effect, it will show up as a clear break in a regression line.

Bleemer and Mehta found that:

Among near-threshold students, we find that majoring in economics caused a $22,000 (58 percent) increase in students’ annual early-career wages without otherwise impacting their educational investment (as measured by difficulty-adjusted average grades and weekly hours spent studying) or outcomes (like degree attainment and graduate school enrollment).

In other words, students above the threshold (and able to study economics) earned 58 percent more. Here's part of Figure 1 that shows the break:

 

The blue dotted line is the threshold (the GPA that students needed to achieve in the first two economics courses, in order to be admitted to the major). The black lines track the relationship between GPA and income for those below the threshold, and those above the threshold. Notice that the black line jumps up significantly at the threshold - that demonstrates the $22,000 extra that economics majors earn compared with non-economics majors.

Interestingly, this gap appears for all student groups:

The estimated returns to majoring in economics are near-identical when estimated separately by student gender: $21,700 (s.e. $8,800) for men, $22,600 ($5,700) for women... The return is also similar in magnitude among underrepresented minority (black, Hispanic, and Native American) students: $27,600 ($13,500).

Studying economics is clearly good for all students in this sample. Bleemer and Mehta then go on to show that about half of the wage premium arises because of differences in the industries that economics majors tend to be employed in (finance, insurance, real estate, and accounting) compared with non-economics majors.

Overall, the conclusion is that the monetary returns to studying economics are high, and as I noted above, now we can say with more certainty that it is studying economics that is a cause of those higher earnings.

[HT: Marginal Revolution]

Read more:

• Why study economics?  Return on investment edition...
• Why study economics? Improve your analytical skills edition...
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• Why study economics? Economists in tech companies edition...
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• Why study economics? Law and economics edition...
• Why study economics? More on jobs in the tech sector edition...
• Why study economics? Tech firm jobs edition...
• Why study economics? AEA video edition...
• Why study economics? Even if you won't be an economist edition...
• Why study economics? PhD edition...
• Why study economics? It could make you rich...
• Why study economics? Sheepskin effects edition
• Why study economics? NZ graduate earnings edition
• Why study economics?

Why consumers won't resist an anti-dumping ban on potatoes, even though they should

In my ECONS102 class today, one of the things we discussed was rational ignorance - the idea that some people who are negatively impacted by a policy will not fight against it, or even make themselves aware of it, because the monitoring costs of watching the government's decision-making are greater than the costs that the policy would impose on them. It is rational for people to remain ignorant of the policy and its consequences. The example I use to illustrate this in class is trade restrictions on sugar in the U.S. (as I outlined in this 2017 post). However, an example much closer to home could be arising this week, as Radio New Zealand reported:

Potatoes New Zealand is asking the government to ban heavily discounted frozen potato fries from arriving in the country.

It says global potato prices have collapsed and there is a mountain of product sitting in European cool stores.

Potatoes New Zealand chief executive Chris Claridge believed heavily subsidised European producers were eyeing up world markets to dump surplus product.

He said the EU currently had 2.6 million tonnes of surplus frozen fries.

Claridge said the local industry, whose annual production is only 150,000 tonnes, is already having to absorb its own large losses from the lack of demand in the past two months.

He said the industry could not wait for the fries to arrive at the wharf and cause long term harm that it might not recover from.

"We want the government to immediately implement short term safeguard measures to protect our industry from dumping. We are not asking for a handout, we are just asking for a level playing field," he said.

Let's be clear. Cheap potatoes from overseas are a good thing for New Zealand potato consumers. Banning discounted frozen potato fries from overseas would have the effect of increasing the price of fries, compared to what the price would have been without a ban. Should consumers care about this? As a group, New Zealand fries consumers will end up paying a lot more for their fries. However, individual consumers probably don't spend a whole lot of money on fries, so even if the price of fries was 20% higher as a result of the ban, the higher cost of fries each consumer faces is probably much lower than the cost (in time and effort) associated they would face in lobbying the government not to impose a ban. So, even though a ban would make consumers worse off, they are actually better off remaining rationally ignorant of any policy.

In contrast, potato farmers are likely to be made much better off if they don't have to compete with cheap imported fries. Each farmer (and farm worker) will likely gain substantially from a ban. The costs associated with not having a potato ban in place are likely to be very high for farmers and farm workers, and much greater than the monitoring costs those groups face. Farmers have a strong incentive to lobby the government to impose a ban on imported frozen potato fries (and indeed, that is exactly what they are doing).

Rational ignorance leads to a situation where, if the costs of a policy can be spread over many people, and the benefits concentrated among the few, inefficient policy (i.e. policy that reduces total welfare) and policy that protects the interests of favoured groups and makes the majority worse off, can be introduced by government almost without incident. Someone needs to stand up for the consumers before the government seriously considers this policy, because the consumers are not going to resist it themselves.

[HT: Mrs Piercy-Cameron, and see this post by Mark Johnston at Econfix that covers the topic as well]

Lockdown and the increased demand for cosmetic surgery

Yesterday, I wrote a post that referenced the cost-benefit principle. One of the key points of the cost-benefit principle is that people try to avoid costs. When the cost of an activity increases, people tend to do less of it. And, when the cost of an activity decreases, people tend to do more of it. The definition of cost here is broad - it includes not only monetary costs, but costs that are non-monetary such as time or effort or psychic costs (which are the costs of added stress or loss of quality of life). Which brings me to this article from the BBC a couple of days ago:

Despite the virus shutting businesses across the globe, a number of plastic surgery clinics have remained open, adopting stricter measures such as Covid-19 tests and more frequent cleaning.

Clinics in the US, Japan, South Korea and Australia have all seen a rise in patients coming in for treatment including lip fillers, botox, face lifts and nose jobs...

Rod J Rohrich, a cosmetic surgeon based in Texas, said he was seeing a lot more patients. "Even more than I would say is normal. We could probably operate six days a week if we wanted to. It's pretty amazing," he told the BBC.

He said usually people would have to factor in recovery at home when considering surgery but now that many people are working from home, this doesn't need to be considered.

"They can actually recover at home and also they can have a mask that they wear when they go outside after a rhinoplasty or facelift. People want to resume their normal lives and part of that is looking as good as they feel."

One of the costs of cosmetic surgery is the time spent recovering at home. That cost might include foregone income from not working, or simply a psychic cost of wanting to avoid being seen by other people while the patient has a bandaged or bruised face.

The coronavirus lockdown has meant that many people are working from home. So, for many people the amount of income they would forego by convalescing at home has reduced, and therefore so has the cost of cosmetic surgery. The psychic costs have likely reduced as well, as cosmetic surgery patients will face less anxiety about being seen (they can just switch their camera off in any videoconferencing). 

When the cost of something decreases, we tend to do more of it - in this case, more cosmetic surgery.

[HT: Marginal Revolution]

Voting, MMP, and the futility of the electorate vote

As I will discuss with my ECONS102 class next week, one of the characteristics of rational behaviour is that it is consistent with the cost-benefit principle. That is, a decision-maker will undertake an action if, and only if, the benefits of that action are at least as great as the costs of the action.

Economists have long noted that voting seems to present a challenge to the idea that decision-makers act rationally. I don't mean that people don't make a rational decision when voting (although recent elections and referendums in the Northern Hemisphere may present some obvious counter-examples), but the decision of whether to vote or not seems to defy the cost-benefit principle.

Consider the costs and benefits of voting. A voter incurs a cost when voting, because they have to take the time to go to a polling booth, think about who they want to vote for, and complete the voting form. All of that takes time (as well as some cognitive effort, for those who do more than just blindly tick one of the boxes based on the colour of the party insignia), and that time has an opportunity cost. The voter could have been doing something else instead, and they give up the opportunity to do that other thing when they decide to vote.

What about the benefits of voting? The simplest argument for voting is that people vote because they hope that their vote is going to affect the outcome of the election. However, for the vast majority of people, their vote for a particular candidate is not going to mean the difference between that candidate winning or losing the election. So, the chances that a vote on its own makes the difference between winning and losing is vanishingly small, and because of that, the benefit of voting is also vanishingly small.

However, under an MMP voting system like that in New Zealand, it gets even worse. Under MMP, most candidates have two chances to be elected. First, they could be elected as the candidate who receives the most votes in a particular electorate. Second, they could be elected as a 'list MP', making up the numbers so that each party has a proportion of MPs that is roughly equal to its proportion of the party votes. The list is ordered, with candidates higher on the list having a better chance of being successful.

Now consider a local electorate candidate, from one of the two main parties, who has a high position on their party's list. They are almost certain to get elected as a list MP, if they are unsuccessful at winning their electorate. So, regardless of whether a voter votes for that candidate or not, the candidate will become an MP. In other words, the benefit of voting for that candidate is not even vanishingly small, it is zero! Voters might as well not bother with voting for an electorate MP, and simply complete the party vote section of their voting paper.

Consider the Hamilton East electorate. Labour candidate Jamie Strange is 42nd on Labour's list - he is almost certain to be elected as a list MP, if he doesn't win the electorate. So, voting for Strange is essentially a waste of time. National hasn't released its list yet, but National candidate and incumbent Hamilton East MP David Bennett was 24th on the list in 2017, and has likely improved his ranking since then. So, voting for Bennett is also essentially a waste of time. If you are a Hamilton East voter, your electorate vote only matters if you vote for one of the minor parties.

In contrast, an electorate vote in Hamilton West might actually matter, because Labour candidate Gaurav Sharma is 65th on the Labour list, and unlikely to get in otherwise. National candidate Tim Macindoe was 25th on the National list in 2017, and if you count from the top of this page of the National Party website, he is 23rd, so would probably get in as a list MP if not re-elected as electorate MP.

If you are sensing that I am somewhat frustrated with the MMP voting system, you would be right. The futility of voting for electoral candidates when those candidates would get in regardless of your vote makes a bit of a mockery of the system. Are voters for Jacinda Ardern in the Mount Albert electorate simply engaged in some anonymous virtue signalling? They certainly aren't making any difference at all to the composition of parliament. Neither will voters for Todd Muller in the Bay of Plenty electorate.

What would work better? In the original MMP referendum, one of the options was called 'Supplementary Member' (which is described here). Like MMP, each voter would have two votes - one for an electorate MP, and one for a party. The party vote would only be used to calculate the proportion of list MPs each party gets, rather than the proportion of total MPs. At least then, electorate votes would count.

Another alternative, which I am quite partial to, is to have a rule that no electorate candidates can be on the party list. The reason I like this solution is that electorate MPs who are high on their party's list don't actually have to work as hard to represent their constituents as electorate MPs who are low on their party's list, because they will likely be re-elected anyway. Having electorate MPs not on the list ensures that they have the incentives to faithfully represent their electorate.

Anyway, coming back to the original point, if the benefit of voting is the chance that a voter affects the outcome of the election, then voting fails the cost-benefit test. Does that mean that all voters are irrational? Perhaps not. There is a benefit of voting other than the simple chance that a voter affects the outcome of the election, and that is the 'warm glow' feeling that a voter may receive by knowing that they have completed their civic duty. As this 2017 paper by Henrique Barros (New University of Lisbon) notes, people vote because they value the act of voting itself, rather than because they think they will influence the outcome of the election. So, perhaps voting is rational after all.

A higher minimum wage and the choice to study in higher education

We are back into teaching next week, and one of the first things we'll discuss in my ECONS101 class is the effect of opportunity costs and relative prices on decision-making. The opportunity cost of something is what you give up in order to get it. The higher the opportunity cost of something, the less likely you are to get it. The relative price of something is its price (or cost to you), relative to the price (or cost to you of something else). When the relative price of something goes up, we tend to do less of it, and when the relative price goes down, we tend to do more of it. Notice the two concepts (opportunity cost and relative price) are somewhat similar.

On that note, this article from the New Zealand Herald a couple of weeks ago provides a good example of both relative prices and opportunity cost:

Higher minimum wages have made it less worthwhile to get an education, a new study says.

The Ministry of Education study shows that your future income will still be higher if you get a degree - but the relative advantage of a degree is shrinking.

This is partly because of educational inflation - a lot more people are getting degrees, so the relative advantage of getting one over someone else is reducing.

But it also reflects big increases in the minimum wage, which have lifted the incomes of people with no qualifications faster than average wages, so incomes have become more equal.

Higher education provides gains, in terms of higher lifetime earnings (which is a point that I'll be covering with my ECONS102 class later this trimester). However, when someone weighs up the costs and benefits of higher education, as noted above a relevant consideration is the opportunity cost of that education - the earnings that they would give up while they are studying. If the minimum wage increases, then for some students (those that would have otherwise been earning the minimum wage), the opportunity cost of higher education increases. That should lead fewer students to undertake higher education.

Another way of thinking about this is that when the minimum wage increases, the relative price of higher education (the price of higher education relative to the alternative of continuing earning without higher education) has increased. That means that higher education is now more expensive in relative terms, because some students have to give up more in order to obtain it. And that should lead fewer students to undertake higher education.

Of course, it is interesting timing to release a report that seems to suggest that fewer students the net returns to higher education have decreased, just when we are entering an historic recession. Many of the jobs that are being lost (particularly in tourism and hospitality, as I noted yesterday) are at the minimum wage level, and for those people suddenly unemployed, the opportunity cost of higher education is suddenly lower than before. As I noted in yesterday's post, that suggests that now is an excellent time to be investing in retraining, for individuals as well as for government.

'Snap-back', 'gone forever', and the economic impact of the coronavirus pandemic

Ordinarily, I don't post on macroeconomic topics. However, this blog post by Bruce Wydick was so interesting, I couldn't resist following up:

My main contribution here is to categorize different types of goods and services in ways that will help us better understand the economic situation we are in.  I will do it across two dimensions.  First is the distinction between purchases of what I’ll call “Snap-Back” goods and services and those that are “Gone Forever.”  In the Snap-Back category are things that we couldn’t buy during the heaviest COVID lock-down period, but these purchases were simply delayed.  There is good reason to think that as the economy begins to open up, purchases of these items might even be higher than normal due to pent-up demand.  Even during COVID, things like household appliances break or need fixing, and because over the long run purchases tend to even out, buying less now means buying more later.

“Gone Forever” goods and services, in contrast, are just like the term suggests: gone forever.  Like me, you may have foregone several haircuts during shelter-in-place because you didn’t want to get (or give) coronavirus to your barber.  But when it becomes safe to go back to the barber chair, you’ll still only get one haircut.  The rest of your haircuts disappeared into the economic ether; they were (mutually beneficial) transactions that COVID—what we might call the “invisible anti-hand”—prevented from happening. 

The second distinction is more standard and will be familiar to anyone who has studied introductory economics.  These are the differences between goods with low versus high income elasticity.  To those untutored in navigating the dense forests of economic jargon, income elasticity measures the percentage increase in purchases of a good when incomes go up by 1%. It measures how sensitive purchases of different items are to changes in income. 

Wydick's categorisation leads to four different types of goods and services, as shown in his diagram reproduced here:

 

The key point about this categorisation is to identify what sectors of the economy are likely to be hurt most by the coronavirus pandemic lockdowns and the associated recession. The lockdown hurts the "gone forever" goods and services, because the "snap-back" goods and services receive catch-up spending after the lockdown is released, while "gone forever" goods and services don't. The associated recession and high unemployment will lower incomes, so those goods and services where purchases are more sensitive to changes in income (high income elasticity), will be worst affected longer term.

So, when goods and services are both "gone forever" and have a high income elasticity, we can expect the impact of the coronavirus pandemic to be most severe. Wydick identifies air travel, tourism, sporting events, hospitality, and transport (but not public transport). Everything else either snaps back and experiences some catch-up spending, or isn't as affected by lower incomes.

Mostly, that suggests that a lot of the economy will survive fairly intact. However, that potentially misses the key point. Tourism and hospitality is going to be crushed, and continue to be in severe trouble for a long time. That's potentially a problem for a country like New Zealand, where the economy is (maybe overly) dependent on tourism and hospitality (tourism alone, not including hospitality, generates nearly 6 percent of GDP according to Statistics NZ's Tourism Satellite Account). It is also a problem because it is a sector with relatively high employment density (the Tourism Satellite Account shows about 8.4 percent of total employment is in tourism, again not including hospitality).

That means New Zealand faces a big and lasting hit to GDP, and (perhaps more importantly) a big and lasting hit to employment. Trying to prop up those sectors (like giving millions of dollars to bungy operators) may be an overly expensive way of retaining employment. Instead, perhaps using those millions to promote re-training and up-skilling of displaced workers might be money better spent. On the other hand though, keeping an existing business at a minimum viable level and ready to ramp back up when conditions improve is potentially less costly to the economy than closing the business down, losing the specific human (and other) capital, and then setting up a new similar business later.

What is best here probably depends on what you believe about the longevity of this crisis. The government's approach suggests that they think the economy will bounce back quickly. I would have erred in the other direction, taking this as an opportunity to up-skill the workforce. Of course, given that I work in the education sector, you'll just have to accept that I may have some bias here.

[HT: Marginal Revolution for the Wydick post, and Michael Doyle on the Waikato Economics Discussion Group for the bungy subsidy article]

Book review: The Misfit Economy

I just finished reading The Misfit Economy, by Alexa Clay and Kyra Maya Phillips. The subtitle is "lessons in creativity from pirates, hackers, gangsters, and other informal entrepreneurs". Clay and Phillips define a misfit as "a person whose behavior or attitude sets them apart from others in an uncomfortably conspicuous way", and the book is essentially a collection of 30 or so case studies, ranging from camel milking in the US, to Somali pirates.

Unsurprisingly, the motivations for being a misfit include reputation and esteem, and/or financial gain. Clay and Phillips use their case studies to illustrate five principles they argue are ways of "unleashing your inner misfit":

1. Hustle (a determination to take your destiny in your own hands, and an ingenuity that allows you to make something out of nothing);
2. Copy (bring about incremental improvements and allow products and functions to evolve);
3. Hack (follow the hacker imperative: the driving need to understand how systems work and then put them back together in enhanced forms);
4. Provoke (step out of reality, imagine something different, and get others to wake up to different possibilities); and
5. Pivot (enact a dramatic change in the course of your life to pursue greater fulfillment and inspiration).

Overall, I found the book to be well written and a good read. However, I didn't really feel like the narrative cohered too well. Some of the case studies were better than others at fitting the principles that Clay and Phillips were trying to illustrate, and the distinction between the different principles is not always clear (copying and hacking are closely related, as are hustling and pivoting). The case study approach makes the book easy to read, but it results in a fairly shallow treatment. It definitely falls short of offering "lessons in creativity", other than the authors' assertion that these five key principles exist.

Some readers might find the stories inspiring, and may indeed unleash their 'inner misfit' after reading. For me, I just found it a collection of interesting stories.

The persistent impact of autocratic rule on social capital

Social capital is the capital that is embodied in inter-personal relationships. It encompasses networks, alliances, shared norms and values, reciprocity, and trust. The level and forms of social capital are determined by people's attitudes and beliefs. So, if political or economic institutions alter those attitudes or beliefs, then the level or form of social capital might also be altered.

That is the thesis underlying this working paper by Melanie Xue (Northwestern University) and Mark Koyama (George Mason University), which looks at the impact of autocratic rule in Qing dynasty China on subsequent measures of social capital. Specifically, Xue and Koyama look at the impact of literary inquisitions. As they explain:

Following the Manchu occupation of China in 1644, and the establishment of the Qing dynasty, imperial China saw a sharp increase in political repression and an entrenchment of autocratic rule. Intellectuals, the most influential figures in local society, saw new restrictions imposed on them. One watershed event was the intensification and routinization of literary inquisitions - investigations which targeted the speech and writings of intellectuals.

Essentially, Xue and Koyama compare prefectures that had had at least one literary inquisitions (the 'treatment' group in this quasi-experimental research) with prefectures that had not (or had not yet) had any literary inquisitions (the 'control' group). They look at both historical measures of social capital (e.g. the number of local charities) and more modern measures (e.g. generalised trust).

This is a very detailed paper. Their first step is to demonstrate that political repression through the literary inquisitions affected attitudes and beliefs. Looking at the number of 'reputable individuals', which is based on a compendium that listed people who were:

...well known for reasons that included prominence in science and technology, medicine and healthcare, education, classical and literary scholarship, history, art, or poetry.

Comparing matched treatment and control prefectures over the period 1640-1819, they found that:

...literary inquisitions led to fewer reputable individuals and that this decline was more pronounced among individuals who came of age in the decade of a literary inquisition... This concurs with historical accounts that individuals withdrew from public life and sought to evade attention in order to keep a low profile...

Next, they looked at the contemporaneous impact on social capital. Charities are a good measure of social capital in this context because:

...the level of charity provision reflects the degree to which individuals are willing to volunteer time and resources to help other members of society...

They found that:

...after a prefecture was first exposed to a literary inquisition case, the number of local charities in that prefecture fell by an average of 38% in the following decades, relative to prefectures that never had a literary inquisition, or prefectures that had not yet experienced a literary inquisition. Mapping out the full dynamic response of charity formation, we characterize the evolution of social capital after exposure to literary inquisitions, and show that the “charity gap” between prefectures which had and which had not been affected, kept widening for the next four decades before stabilizing. This effect did not go away towards the end of the charity data series in the early 20th century.

So, the impact of political repression on social capital was relatively large. It also endured for some time. Looking at data from the Chinese General Social Survey (CGSS), they found that:

...Qing persecutions are associated with lower generalized trust. This effect is economically significant: in our main specification, political repression is associated with a decline of 0.179 in trust, which is 16.7% of its standard deviation...

In contrast, there is no effect on trust in family members, so the impact of political repression is on trust outside of the family. Xue and Koyama also demonstrate negative effects on literacy levels among those educated in the early 20th Century, when education was decentralised and so relied more on social capital for its delivery. They also show that those effects don't depend on other political and social events such as the Taiping Rebellion, the exodus to Taiwan in 1949, and the Cultural Revolution (the latter two events might affect the earlier results because they change which people would be observed in the CGSS sample). They also provide evidence using instrumental variables analysis that their results are causal - the literary inquisitions in Qing China caused the differences in literacy rates in 20th Century China.

Finally, they also show impacts on modern political attitudes and behaviour:

Starting with attitudinal questions, we find that individuals in prefectures with a legacy of literary inquisitions are less likely to say that people like themselves can have an impact on decisions made by government... and less likely to believe that their suggestions to the government will be adopted... reflecting greater political apathy in affected prefectures... Next, we examine participatory behavior... Our main findings are that survey respondents from affected prefectures are less likely either to volunteer on local committees... or to make suggestions to local committees...

We find that individuals in prefectures with a legacy of literary inquisitions are less likely to agree with the following statements: “Western-style multi-party systems are not suitable for China”... “Free speech is ‘Western’ and will only lead to chaos”... and “Modern China needs to be guided by wisdom of Confucius”... For other questions in the survey, such as those regarding social issues, there is no systematic difference in individual responses between prefectures with a legacy of literary inquisitions and those with no such past.

There is a lot to digest in this paper. The authors conclude that:

Both the results from the historical panel and those from post-Qing cross sections suggest that political repression permanently reduced social capital. The effect of literary inquisitions on social capital has survived, even after local institutions were transformed by the modern socialist state...

We establish social capital as a missing link to understanding the dynamics of state-society relations. Autocracies can provide order and public goods when social capital is low. For this reason, autocracy may appeal to individuals in societies with low social capital. Hence, by reducing social capital, autocratic rule can introduce a self-reinforcing cycle that favors its survival and persistence.

This self-reinforcing cycle has implications for many modern societies that have tried unsuccessfully to adopt more democratic norms. It demonstrates the persistence of autocratic rule, and the norms and attitudes that sustain it.