The cancellation of Batgirl shows Warner Bros are not fooled by mental accounting

The Guardian reported earlier this week:

The previously announced Batgirl film starring In the Heights actor Leslie Grace, Michael Keaton and Brendan Fraser will not be released at all, Warner Bros Discovery has unexpectedly announced, despite shooting already being completed and the film being in post-production.

Directed by Ms Marvel directors Adil El Arbi and Bilall Fallah, the film was initially greenlit in 2021 as part of a wider move at Warner Bros to create feature films specifically for the streaming service HBO Max. But the studio confirmed on Tuesday that the film would never get any release, either theatrically or on HBO Max...

The Hollywood Reporter said Batgirl’s budget was a factor in the decision, having risen to nearly $90m (£74.1m, A$130m) due to costs relating to it being shot during the Covid-19 pandemic. While the budget is lower than the average DC superhero film, it was reportedly decided that it did not have the “spectacle that audiences have come to expect from DC fare” and would not recoup its losses from being released.

However, the New York Post, which broke the story on Tuesday, cited an unnamed source who said the budget had actually exceeded $100m and that the film had performed so poorly during early test screenings that Warner Bros decided to cut its losses.

“They think an unspeakable Batgirl is going to be irredeemable,” the source told the New York Post.

Behavioural economics suggests that quasi-rational people are susceptible to the sunk cost fallacy. Sunk costs are costs that have already occurred and that cannot be recovered, like the US$90 million or more already spent on the Batgirl movie. Sunk costs should not affect decisions because, regardless of what the decision-maker chooses to do, those sunk costs have already been incurred. Since the US$90 million has already been spent, it has been spent if the movie is released, and it has been spent if the movie is not released. So, at the point of post-production the decision about whether to go ahead and release the movie should be made on the basis of costs and benefits that are to come. Essentially, Warner Bros was weighing up the further costs they would face (on additional post-production, marketing, etc.) against the benefits they would receive (box office receipts, and other revenue). The costs must have outweighed the benefits.

The sunk cost fallacy typically occurs because of mental accounting, which suggests that we keep 'mental accounts' associated with different activities. We put all of the costs and benefits associated with the activity into that mental account, and when we stop that activity, we close the mental account associated with it. At that point, if the mental account has more costs in it than benefits, it counts as a loss. And because we are loss averse, we try to avoid closing the account. If Warner Bros were affected by mental accounting, they may have released the movie anyway, trying their hardest to avoid banking a loss on the movie. Mental accounting is responsible for keeping us in unpromising projects for too long, as well as unhappy relationships, and bad jobs.

So, Warner Bros were not affected by mental accounting, and it appears that the viewing public will be saved from a terrible Batgirl movie. It's a pity that didn't happen to the truly horrible Moonfall (my movie ticket was a sunk cost on that one), or everyone's favourite superhero move to hate, Green Lantern.

[HT: Mark from my ECONS102 class]

Doctors and the health care of their parents

In my ECONS102 class, we talk about how health care is an unusual good, because it simultaneously has four characteristics: (1) derived demand (we demand health care but what we really want is better health); (2) positive externalities (consuming health care makes others better off as well as yourself); (3) information asymmetries (health professionals know much more about health care than patients do); and (4) uncertainty (it is uncertain whether particular health care treatments or procedures will work, or how well they will work, or what would have happened in the absence of the health care).

In relation to information asymmetry, medical knowledge is what we refer to as private information - it is known to the medical practitioner, but not to the patient. That creates a range of problems, including that patients may not always get the care that they need. For example, patients may not know when to seek care, as they may underestimate the seriousness of symptoms.

Could having better access to medical information reduce information asymmetries and improve the quality of health care? That is essentially the question that this recent article by Elisabeth Artmann (Institute for Employment Research, Netherlands), Hessel Oosterbeek (University of Amsterdam), and Bas van der Klaauw (VU University Amsterdam), published in the American Economic Journal: Applied Economics (ungated earlier version here), addresses. They use population registry data from the Netherlands, along with the results of the medical school admissions lotteries over the period from 1988 to 1999, and look at the effect on parents' health care of having a child who becomes a doctor. The idea here is that, if your child becomes a doctor, then that would reduce any information asymmetry in health care, because your child would be able to provide advice that eliminates the asymmetry.

The lottery aspect of the research is important, because it provides an exogenous source of variation in who becomes a doctor - essentially, there is a random component to becoming a doctor, because the lottery determines who is allowed into medical school. In other words, Artmann et al. use winning the first lottery (because students could apply each year afterwards) as an instrument for becoming a doctor. That means that their results can be interpreted as evidence of the causal effects of having a child who is a doctor on parents' health care. Note that this is exactly the same approach as was used in an earlier paper on doctors' prescription drug use (which I discussed here).

The instrumental variables approach is important because simply comparing parents with children who are doctors with parents who do not have children who are doctors is subject to a lot of selection bias. For instance, better-educated parents are more likely to have children who are doctors, and also more likely to have better health outcomes. So, a positive correlation would be observed between having doctor children and health outcomes, even if doctors had no effect on parents' health. Indeed, Artmann et al. demonstrate just such a correlation, finding that:

When we consider the full population independent of children’s level of education, we find strong associations between children having a medical degree and parents’ mortality and health care use. Fathers and mothers of doctors live longer, have lower health care costs, and are less likely to visit a GP, to be hospitalized, or to take any prescription medication. They are, however, slightly more likely to be treated by a specialist. These associations are weaker but still hold when we restrict the sample to parents of children with a college degree.

However, in their instrumental variables analysis, which avoids the problems of selection bias, they find:

...causal effects on mortality that are close to zero and not significantly different from zero. For health care use and costs, most estimates are not significantly different from zero, although for some outcome variables estimates are too imprecise to rule out substantial effects. Taken together, the results indicate that having access to medical expertise and services through a child who is a doctor is not an important cause of differences in parents’ health care use and mortality.

In other words, almost all of the better health outcomes for parents of children who are doctors arises from selection bias. Having a child who is a doctor doesn't improve health outcomes in the Netherlands.

In the Waikato Economics Discussion Group this week, we had an interesting conversation about this paper. The results are clear for the Netherlands, but it is likely that the particular health system matters. In the Netherlands, Artmann et al. write that:

Since the implementation of the Health Insurance Act in January 2006, all Dutch residents are legally obliged to purchase a basic health insurance package from private insurers...

The central government defines the content of the basic package. This covers medical care, including care provided by GPs, hospitals, specialists and midwives, and prescription drugs... Every insured person over age 18 pays an annual deductible of €385 (in 2019) for health care costs... including costs for hospital admission, medical transportation, and prescription drugs but excluding costs for GP consultations, maternity care, home nursing care, and care for children under the age of 18.. Voluntary supplemental health insurance is available for services not included in the basic health insurance package.

The comprehensive and universal nature of available health care in the Netherlands probably matters for whether doctor children can affect the health care (and health outcomes) of their parents. The need for a doctor to intervene on behalf of their parents in the health system is likely to be much lower in the Netherlands than it would be in, say, a typical developing country. We'd expect to see very different results when the health system is not universal. That opens an important question, though: would we see an effect for a country like New Zealand, which has a public health system, where access is rationed through waiting lists, and where a parallel private health system exists. Would having a child who is a doctor mean that parents are added to the waiting list sooner, or are more likely to be re-routed into the private system (at their own cost)? Either of those would suggest better health outcomes for parents of doctor children. It would be interesting to follow this up with other research for New Zealand.

Coming back to the Artmann et al. paper, it would be attractive to draw some conclusions in relation to inequality in access to health care. However, Artmann et al. caution against this, noting that:

...our results apply to parents of individuals who applied for medical school, so these parents have relatively high-educated children. Therefore, our results are not conclusive about equality of health care access in the Netherlands in general.

However, the results do suggest that the quality of health care in the Netherlands is such that, having a child who is a doctor cannot improve the health care that you receive. 

How working from home has affected the office real estate market

In my ECONS102 class this week, we discussed the rental market for land. In a supply and demand model of this market, the demand for land (by tenants and owner-occupiers) is determined by the value of the marginal product of land. The value of the marginal product of land is, in turn, determined by the marginal product of land and the price of the firm's output generated by the land. If land is suddenly less productive, the marginal product of land will decrease, so the value of the marginal product of land will decrease, and the demand for land will decrease. That in turn should lead to a decrease in market rents.

This recent working paper by Arpit Gupta (NYU Stern School of Business), Vrinda Mittal, and Stijn Van Nieuwerburgh (both Columbia University) puts that theory to the test. The particular context is the impact of increasing remote work in the wake of the coronavirus pandemic. If office workers are increasingly working from home, then the marginal product of land (used to site office buildings) will decrease, decreasing the demand for office buildings, and decreasing the rent of office buildings. Decreased rents will also flow through to lower values of office buildings (and associated land), because the value should be a function of the discounted future rental flows.

Mittal et al. use data from 2000 to December 2021 for 105 office markets throughout the United States. They find:

...an 8 percentage point decrease in lease revenue between January 2020 and December 2021. This decline entirely reflects decreases in the quantity of in-force leases rather than shifts in rents on in-force leases. The quantity of newly-signed leases in our data set falls from 300 million square feet per year just before the pandemic to below 100 million square feet in the last quarter of 2021. Rents on in-force lease contracts growth throughout the pandemic. Rents on newly-signed leases fell by 9.9% in real terms between January 2020 and December 2021, before reversing sharply to pre-pandemic levels by the end of 2021.

Note that a decrease in demand for office leases is consistent with both a decrease in price (rents) and a decrease in the quantity (in square feet). Interestingly, Mittal et al. also find that:

The effects on lease revenue is not seen uniformly across properties. We find some evidence of a “flight to quality,” particularly in rents. Higher quality buildings, those that are built more recently and have more amenities (informally called class A+), appear to be faring better in the pandemic. Their rents on newly-signed leases do not fall or even go up, in contrast with the rest of the office stock. This is consistent with the anecdotal evidence that firms need to improve office quality to induce workers to return to the office given new remote options.

Since firms (who are the tenants for the office buildings) are trying to encourage their workers back to the office (in the US, at least), they are demanding leased space with more amenities, that will be more attractive to their workers. Our model of the land market doesn't offer any explanation for this, but it does suggest that firms believe that workers are more productive in the office than working at home (otherwise, firms wouldn't want to attract those workers back to the office). That may be because workers are inherently more productive in the office, or because the firm can then more closely monitor their work (it's surprising to me that I haven't seen more discussion of agency problems and moral hazard in the context of work-from-home).

Mittal et al. then go on to look at the effect on the value of office buildings. Using an asset-pricing model calibrated to the market for New York City, they find:

...a 32.95% reduction in the value of the entire NYC office stock between the end of 2019 and the end of 2020.

Then, looking forward and considering different scenarios for the return to the office (and consequent reduction in work-from-home [WFH]), they find that:

...office occupancy rises from the depths of its 2021 values and the economy returns to the no-WFH state with some probability. These mean-reversion forces push office valuations towards an average value in 2029 is about 28% below 2019 values. Along paths where the economy remains in the WFH state for ten years, office values in 2029 remain about 38% below their 2019 values.

That is a substantial reduction in the value of office buildings, and:

The short-term value reduction of 33% amounts to $57.7 billion, the longer-term reduction of 28% amounts to $49 billion. Extrapolating to all properties in the U.S. in our dataset, the $72 billion annual leasing revenue results in a $631 billion office value before the pandemic using the same 8.76 value/lease revenue ratio. We estimate that pandemic-related disruptions around remote work have lowered the value of office buildings observed in our dataset by $208 billion in the short run (33%) and by $177 billion in the long-run (28%). These estimates understate the value destruction of the overall U.S. office stock since our CompStak data do not cover the universe of commercial leases. We underestimate lease revenues by a factor of about 2.8.3 The total decline in commercial office valuation might be, as a consequence, around $586 billion in the short-run and $498 billion in the long-run.

It's little wonder that the title of the paper is "Work from Home and the Office Real Estate Apocalypse". Landlords and owner-occupiers of office buildings have taken a beating.

[HT: Marginal Revolution]

Retail marijuana stores and house prices

Does having nearby retail stores affect the value of homes? Surely it does, but just as surely it depends on the type of retail stores. If your neighbourhood has a lot of payday lenders, pawn shops, and discount liquor stores, that is quite different from a neighbourhood that has health stores, pet stores, and premium wine shops. So, one way of measuring whether a community prefers to have more (or less) of particular retail stores is to measure the effect on house prices. If, when a new retail store opens, local house prices increase, then the community believes that store is a good thing. If, on the other hand, local house prices decrease, then the community believes that the store is a bad thing.

This relies on hedonic demand theory (or hedonic pricing), which recognises that when you buy some (or most?) goods you aren't so much buying a single item but really a bundle of characteristics, and each of those characteristics has value. The value of the whole product is the sum of the value of the characteristics that make it up. For example, when you buy a house, you are buying its characteristics (number of bedrooms, number of bathrooms, floor area, land area, location, etc.). As part of the location, you are buying the fact that there are a number of retail stores of different types in the local neighbourhood. So, controlling for all of the other characteristics of houses, comparing the price of houses in areas with some types of retail stores with similar houses in neighbourhoods without those same types of retail stores, provides one way of determining how the community views those retail stores.

As part of my ongoing research on alcohol outlets, I have toyed with the idea of performing this analysis for house prices and alcohol outlet locations in New Zealand. However, there are a bunch of other outlet types that we may be interested in, like vape stores. And, if New Zealand ever gets around to legalising marijuana, it would be interesting to see the effect of retail marijuana stores on house prices.

That's more or less exactly what this 2020 article by James Conklin (University of Georgia), Moussa Diop (University of Wisconsin-Madison), and Herman Li (California State University), published in the journal Real Estate Economics (ungated earlier version here, and research brief here), did. Conklin et al. look at what happened to house prices in Denver when Colorado legalised retail marijuana on 1 January 2014. Interestingly, the Colorado policy change allowed existing medical marijuana stores to become retail stores. So, the analysis doesn't compare retail store with no store, so much as what happens when an existing medical marijuana store becomes a retail store. However, this is important, as:

...since only existing medical marijuana stores were allowed to conduct recreational sales, we avoid the potential endogeneity of store location. Given the opportunity, retail marijuana stores would likely choose to locate in certain areas based on neighborhood characteristics that would also affect house prices. However, since only existing medical stores were allowed to sell retail marijuana, the siting decision was made before implementation of [legalized recreational marijuana].

Conklin et al. use a difference-in-differences approach, comparing the difference in house prices (controlling for various house characteristics) between single-family houses within 0.1 miles of at least one retail marijuana store and single-family houses between 0.1 and 0.25 miles of at least one retail marijuana store, before and after the legalisation of retail marijuana. Their initial analysis, based on properties sold in 2013 (before the law change) and 2014 (after the law change) finds that:

...being located near at least one medical facility that converts to retail in 2014 is associated with an 8.4% increase in sale price after the retail conversion occurs.

You may be worried that the number of retail marijuana stores in the neighbourhood matter, but Conklin et al. also show that the results are similar for houses where exactly one store became a retail marijuana store in the local neighbourhood (in fact, a slightly larger 11.4% increase). The results are also robust to alternative definitions of the control groups, but expanding the treatment group to include houses further away from retail marijuana conversions reduces the effect (which should be no surprise - those houses were in the control group in the original analysis).

Overall, we can conclude that local communities in Denver like retail marijuana stores. Or, more correctly, local communities in Denver prefer retail marijuana stores to medical marijuana stores (since we don't know how they feel about the medical marijuana stores, and house prices went up after those stores convert to retail). This is consistent with other evidence (as I discussed in this 2018 post), showing that legalising marijuana increased house prices across all of Colorado (rather than just Denver) by about 6 percent. The downside of this, of course, is that if you are in favour of legalising marijuana in New Zealand, one trade-off may be that house prices go up even further than they already have.

Read more:

• Legalised marijuana sales and house prices