Red light districts and house prices

Following on from Monday's post on legalised marijuana sales and house prices, it is reasonable to consider whether other legal or quasi-legal but controversial activities also have impacts that can be picked up in house prices. A recent working paper by Erasmo Giambona (Syracuse University) and Rafael Ribas (University of Amsterdam) considers the case of red light districts (RLDs) in the Netherlands.

This is a nice paper, and they exploit a change in city policy in 2007 that aimed to reduce the number of red light windows, as well as considering the geography of Amsterdam, where canals provide plausible breaks in the geography that can be used to identify the effects of red light windows, where prices change abruptly. This can be seen in the maps below, where the background colours represent house prices, the black dashed lines are the edges of the two main RLDs in Amsterdam, and the thick blue lines are the canal borders of those districts.

The maps seem to suggest that house prices are higher outside the borders of the RLDs up to 2006 (on the left), but less so from 2007 onwards (on the right). The comparison between the period before the change in red light windows and the period after is important. It means that the analysis isn't confounded by the access of properties to other amenities (that didn't change between the period up to 2006 and the period from 2007 onwards). Indeed, the authors show that the distribution of restaurants, bars, and coffeeshops did not change appreciably between those two time periods.

In their key results for Amsterdam, Giambona and Ribas find that:

...homes next to prostitution windows are sold at a discount as high as 24%, compared to similar properties outside the RLD...

They find similar results using alternative methods, and similar results for Utrecht, where the red light districts were closed entirely in 2013. Specifically, for Utrecht:

 ...we find that households paid up to 1.5% of their property value to be 100 meters further away from the RLDs.

What is the mechanism that underlies the negative impact of red light districts on house prices? Giambona and Ribas find that around half or more of the price difference relates to crime:

To understand the type of nuisance related to prostitution, we also investigate the change in crime rates after the downsizing of RLDs in both cities. In Amsterdam, the crime rate in the RLD declined by 18% relative to other parts of the city. Yet half of the house price discontinuity remains unexplained after controlling for all forms of reported crime and misbehavior. In Utrecht, the crime rate near the RLDs declined by 11%, which represents more than 300 crimes per year. While property crimes and violence can explain up to a third of the price effect in Utrecht, changes in drug-related crimes and minor nuisances explain almost all variation in house prices triggered by the end of the RLDs.

The results are clear - red light districts impose negative externalities on surrounding homeowners, and those externalities can be measured in terms of their effects on house prices. Crime is not the only negative externality that is present (at least for Amsterdam), so presumably red light districts also create other disamenities for their neighbourhood. As recent experience in New Zealand has suggested, for home-based brothels.

[HT: Eric Crampton at Offsetting Behaviour, back in January]

Ontario follows Finland's lead in dropping its universal basic income pilot

Back in May, I wrote a post about Finland cancelling its universal basic income experiment. However, I totally missed the news earlier this month that Ontario was also cancelling its basic income pilot (a point that was raised in one of the presentations in the basic income session at the European Regional Science Association congress, where I am this week). As reported in Business Insider:

Anger and outrage, shock and betrayal: Those were some of the raw emotions after one of the world's largest basic-income experiments was suddenly canceled.

Earlier this week, Doug Ford, the conservative new premier of Ontario, Canada, pulled the rug out from under the experiment, which provided 4,000 people living at or near the poverty line with a stipend.

Ford's government hasn't publicly said much about its reasoning for canceling the program, other than claiming it disincentivizes recipients from finding work...

It lasted only one year, despite Ford's campaign promise to keep the pilot project funded...

"When you're encouraging people to accept money without strings attached, it really doesn't send the message that I think our ministry and our government wants to send," Lisa Macleod, Ontario's minister of children, community, and social services, told reporters this week. "We want to get people back on track and be productive members of society where that's possible." 

This is very similar to the argument behind the cancelling of Finland's basic income experiment, as I noted back in May. Why does a basic income create a disincentive for low-income work? Consider the model of the worker's decision in the diagram below. The worker has limited time (E) that they can allocate to work (and earn income, for consumption, measured on the y-axis) and leisure (measured on the x-axis). The straight line constraint represents the trade-off between consumption and leisure, and has a slope equal to the wage (actually, -w, because it is downward sloping). The highest possible indifference curve the worker can get to is I0, and the optimal bundle of consumption and leisure is E0 (which includes C0 consumption, and L0 leisure (and E-L0 work)).

What happens when you introduce a universal basic income? Since the worker doesn't need to spend time working in order to claim the universal basic income, this simply shifts the constraint upwards by the amount of the basic income (U). The worker can now reach a higher indifference curve (I1), and their optimal bundle of consumption and leisure is now E1, which includes both more consumption (C1) and more leisure (L1). More leisure means less time spent working (because (E-L1) is smaller than (E-L0)). The introduction of the universal basic income decreases work incentives. This might manifest at the extensive margin (some people who were previously working for a low wage decide to stop working entirely), or at the intensive margin (some people choose to work a little bit less).

Would a basic income increase work incentives? It seems unlikely, unless leisure has suddenly become an inferior good (a good that people prefer to consume less of when their income increases).

Could a basic income remove barriers to work? Perhaps if there are credit constraints to obtaining work, as the Business Insider article notes:

"It is kind of hard to find a job when you are struggling for food and you don't have money to keep your phone active and it goes down out of service," she said. "You can't afford to buy job clothing. You can't even do laundry to wash job-interview clothing."

On a basic income, Baltzer could eat healthier, buy clothes, go to the gym, do laundry, and afford phone and internet service to communicate with potential employers, she said.

However, credit constraints are unlikely to be binding for all non-workers, and it is entirely consistent for a basic income to both remove barriers to work for some people and reduce work incentives for other people. The proponents and critics of basic income are simply talking past each other.

A universal basic income remains a promising idea that is very difficult to implement politically. Ultimately, it is only realistic if taxpayers (and politicians) can make peace with the work disincentives that it will generate.

Legalised marijuana sales and house prices

Does the community believe that legalising marijuana sales a good thing? There are both benefits and costs associated with legalising marijuana sales. Benefits might include easier access for recreational users (and higher consumer surplus), job opportunities in the marijuana sector, savings on policing and justice costs, and increased tax revenues (if marijuana sales or profits are taxed). Costs might include adverse impacts on public health, decreased productivity, and increases in crime. How do we weigh up these benefits and costs?

Hedonic demand theory (or hedonic pricing) 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.). You are also buying the bundle of local regulations for the area the house in located in, which includes whether marijuana sales are legal. So, controlling for all of the other characteristics of houses, comparing the price of houses in areas where marijuana sales are legal with the price of houses in areas where marijuana sales are not legal, provides one way of determining how the community views the balance of benefits and costs of marijuana sales.

And that is exactly what a new paper by Cheng Cheng, Walter Mayer (both University of Mississippi), and Yanling Mayer (FNC Inc.), published in the journal Economic Inquiry (sorry I don't see an ungated version), does. Overall, I like the approach of evaluating through the effects on house prices. I've blogged before on its use in terms of the effects of radiation following the Fukushima nuclear disaster, sunshine, and proximity to strip clubs.

In this case, Cheng et al. outline the logic for why differences in marijuana regulations would affect house prices:

As home buyers and sellers respond to changes in local amenities and disamenities... the associated benefits and costs of the public programs, such as legalizing retail marijuana, are capitalized into housing values. However, the net effect on housing values is ambiguous ex ante given the opposing effects of the benefits and costs. For example, on the one hand, the benefits of retail marijuana legalization potentially raise housing values by either increasing housing demand (e.g., attracting more home buyers) or decreasing housing supply (e.g., discouraging homeowners from selling their properties and moving). On the other hand, the costs have the opposite effects on demand and supply and, therefore, potentially lower housing values. Thus, this paper estimates the net effect of legalizing retail marijuana on housing values, which reflects the net capitalization of the benefits and costs by the housing market.

They use data from 91,943 house sales in Colorado over the period 2010 to 2015. Over this period, 46 out of 271 municipalities in Colorado chose to adopt legalisation, while the others did not. They find that:

...on average legalizing retail marijuana in Colorado increases housing values by approximately 6%, or $15,600 per property, which can explain about 27% of the overall housing price appreciation in adopting municipalities during the examination period.

Importantly, their results demonstrate that the change in prices occurred right after marijuana was legalised, so it is unlikely that other contemporaneous changes in the housing market or regulatory environment explain the results (especially since different municipalities adopted legalisation at different times).

So it appears that, in Colorado at least, the benefits of legalisation of marijuana sales exceed the costs, because house prices in those areas adopting legalisation moved higher in response to legalisation. However, some caution is warranted before over-interpreting these results. While the benefit-cost evaluation seems to come out in favour of benefits, the size of the change in house prices may not be replicable everywhere. It is notable that Colorado was one of the first two states in the U.S. to adopt legalisation, so to the extent that some people would move to areas where marijuana sales are legal, the demand side of the market has already corrected. States that were later to adopt legalised marijuana would be unlikely to see jumps in house prices to the same extent, because any pent-up demand for living in an area with legalised marijuana sales has already been satisfied.

Ravallion and Rodrik on globalisation and inequality

Back in 2015-2016, I wrote a series of posts related to globalisation and inequality (see here, here, here, here, and here). The overall conclusions from those posts was that global inequality has been decreasing over time, growth in China has been a big contributor to this, but that future continuation of growth in China may eventually lead to increases in inequality (as increases in inequality within China increasingly contribute to increases in global inequality).

An interesting aspect to the question of how global inequality has changed over time is the contribution of globalisation. So, I was interested to read this recent article (ungated) by Martin Ravallion (Georgetown University, but formerly at the World Bank), published in the Journal of Economic Literature. In the article, Ravallion reviews two important recent books on global inequality, being Branko Milanovic's Global Inequality: A New Approach for the Age of Globalization and Francois Bourguignon's The Globalization of Inequality. Both books are on my (very long) list of books-to-read-soon, so this review was timely for me to read, especially since you can always rely on Ravallion to give a very forthright opinion. His summary of the thesis of both books is:

...the present period of globalization is essentially seen as the joint cause of both falling inequality between countries and rising inequality within countries...

...the popular argument is that global economic integration has shifted relatively low-skilled jobs from the rich world (driving up its contribution to the within-country component of global inequality) to labor-abundant low-wage countries (driving down the between-country component of global inequality).

However, Ravallion isn't as convinced about the centrality of the role of globalisation in reducing global inequality:

My reading of the literature on the empirical determinants of economic growth at country level does not give me confidence that trade openness has been as an important driving force as the authors suggest. A reasonable summary of the evidence would probably be that trade has helped promote growth and poverty reduction in the developing world as a whole, but that is only one of a number of relevant factors, which include aspects of the initial distribution of income and human development...

Inequality appears to fall in some countries when they are opened to trade and increases in others. And there are clearly many other forces in play.

I, and hopefully my ECONS102 students given that was the most recent topic we covered, would note that trade is just one aspect of globalisation, among many. Although it may be important, there are many trends that together constitute globalisation. Ravallion touches only lightly on those other aspects, but overall for the two books he concludes that:

There has been considerable variance across countries in both their growth rates and the changes in inequality, and trade openness does not seem to stand out as the major generalizable causative factor that these books, and many other observers, assume. Technological change in unequal settings could well be a much stronger force than expanding trade. Policies have mattered to both growing poor economies and redressing inequality within countries. And these policies can coexist with considerable global integration. Globalization may well be getting too much credit, and being blamed for too much.

Dani Rodrik is another globalisation sceptic, and his arguments are neatly summarised in his book The Globalization Paradox (which I reviewed here). However, Rodrik isn't sceptical about the role of globalisation in inequality, and in a recent paper, he notes explicitly China's role in both declining global inequality and increases in within-country inequality:

[China] grew rapidly off the back of an export-oriented industrialization model: it created tens of millions of better-paying, more productive jobs in urban factories, the output of which flooded the markets of advanced economies. The transition from socialism to a more market-oriented system enabled income gaps to rise within Chinese society.

At the same time, the sharp rise in Chinese imports of relatively labor-intensive goods hit production workers in the rich economies particularly hard, just as standard trade theory would predict. Imports of labor-intensive goods predictably exerted a negative impact on wages at the low end of the earnings distribution.

However, the reduction in global inequality from China's growth are coming to an end, and Rodrik argues that it seems unlikely that other countries can follow China's model:

Ultimately, global inequality will be reduced only by faster economic growth in the developing world. The good news is that the last quarter century has shown this is possible, through better policies in the poor nations. The bad news is that export-oriented industrialization, the model that has produced the most rapid and sustained development successes to date, seems to have run out of steam.

Rodrik's solution is migration, which I note was one of the three ways that Branko Milanovic also argues that global inequality can be reduced (as I posted about here). Specifically, Rodrik notes that:

The quickest way to sharply reduce global inequality would be to drop all restrictions on labor mobility in rich countries. Yet this would cause the bottom of the labor market in those countries to collapse, and possibly cause severe institutional and political damage that undermines productivity levels in the host countries.

A more limited program of temporary work visas, with real carrots and sticks that ensured high rates of return, would produce substantial benefits to participants.

As Michael Clemens has also noted, more open international migration is a policy with large and clear potential benefits.

Read more:

• Chinese growth and global inequality
• More evidence of declining global inequality
• Changing global inequality, migration and open borders
• The last two centuries of global inequality
• Inequality was similar, or higher, in ancient times than it is today

The economics of corporate lobbying

In my ECONS102 class, we talk about market power and monopoly firms, and in the context of that discussion, we talk about corporate lobbying. Specifically, we discuss it in the context of rent-seeking behaviour (as I have previously blogged about here). The assumption of firms conducting lobbying for rent-seeking reasons is that they do so in order to protect (or enhance) their profits in the future. So, firms that engage in rent-seeking should be expected to be more profitable (net of their rent-seeking expenditure) than those that don't engage.

A recent paper by Zhiyan Cao (University of Washington Tacoma), Guy Fernando (SUNY Albany), Arindam Tripathy (UW Tacoma), and Arun Upadhyay (Florida International University), published in the Journal of Corporate Finance (sorry I don't see an ungated version anywhere online) challenges this result. The authors contrast between two different theories of how corporate political activity (including lobbying, but also contributions to political campaigns, etc.) would affect profitability:

The stewardship theory views lobbying as an inherent part of firm strategy. The rationale is that since government regulations and actions can shape a firm's business conditions, lobbying could be an effective means to help firms stay informed of regulatory agenda, obtain political information to adjust their business decisions in a timely fashion, and to encourage (discourage) those regulatory decisions that are beneficial (detrimental) to a firm when possible. Under this theory, lobbying expenditure is considered an outlay with a high return on investment (ROI)...

...a new paradigm that attempts to explain corporate lobbying focuses on the agency problems... Specifically, managers may divert corporate resources directly to strengthen their own political connections through lobbying activities without bringing tangible benefits to the firm.

So, the stewardship theory suggests a positive relationship between lobbying and profits, but agency theory suggests a neutral or even negative relationship between lobbying and profits, because managers are doing what is in their own personal best interests and not necessarily those of the firm. Cao et al. suggest some specific examples of principal-agent problems associated with lobbying, including:

First, lobbying may channel funds for political causes that are dear to the CEO, but do not affect (or adversely affect) the firm...

...Second, lobbyists (who are agents of their clients, the firms) may misrepresent the lobbying activities to their clients and direct corporate funds to causes dear to the lobbyists... Third, the firm (and presumably the majority shareholders) may channel firm money to political activities that are inimical to the beliefs and philosophies of the non-controlling shareholders... Finally, corporate political activity can be chosen by incompetent CEOs who are unable to lead their firms to meet new challenges in the marketplace and overestimate the effectiveness of lobbying as a means to enroll government welfare in the face of competition. Managers may also be more likely to shirk when they expect to resort to political connections through lobbying.

Using data on 18,075 firm-years from 2186 unique firms over the period from 1998 to 2016, they find support for agency theory as a dominant factor:

...we find a negative and significant association between lobbying activities and firm performance. This negative association persists when we explicitly control for the endogeneity of corporate lobbying. We further show that the negative association may be partly explained by the fact that lobbying spending by a firm overall provides limited tangible benefits when it comes to helping the firm obtain more government contracts or improve the frequency of getting a bill passed in the US Congress. This suggests that agency costs (e.g., inefficient use of corporate funds) in lobbying activities appear to dominate the strategic benefits that firms may obtain from lobbying.

This is a nice paper, and includes a very thorough set of robustness checks and checks using alternative econometric specifications. So, the results are very believable. However, two things suggest to me that this is far from the last word on the relationship between corporate lobbying and profits. First, the quality of lobbying expenditure clearly matters as much as (if not more than) the quantity of corporate lobbying. This is a very difficult problem to address in an econometric model, since high-quality corporate lobbying could be most simply defined as lobbying that results in a favourable outcome. However, definitional issues aside it is likely that firms that engage in higher quality lobbying are more likely to improve their profits as a result. So, failing to account for the quality of lobbying is a potentially important issue for this research.

Second, there is a public goods aspect to at least some lobbying expenditure, which is not accounted for in the paper. If Firm A lobbies against a particular law that would impose restrictions on their industry (or on business more generally), the all firms in the same industry (or in all industries, depending on the extent of coverage of the law) would benefit. If the lobbying was successful, Firm A would receive a benefit (higher profits), but face the cost of lobbying. Other firms in the same industry (or generally) would receive higher profits, but face no corresponding lobbying cost. To an econometric model, this would look like a negative relationship between lobbying expenditure and profits. So, for this reason I don't think we can take the negative relationship between lobbying and profits from this paper as being purely an agency problems result.

Corporate lobbying is an important feature of modern politics. The paper has some interesting figures on the extent of lobbying which illustrate this, including the peak lobbying expenditure of Pfizer, which by itself spent over US$63 million on lobbying in 2009. Clearly, this is an issue that needs to be kept in the spotlight.

[HT: Marginal Revolution, back in January]

A speculative relationship between genetics and binge drinking

Some time ago, someone pointed me to this 2006 working paper by Jason Shogren (University of Wyoming) and Eric Naedval (University of Oslo). In the paper, the authors draw a link between genetic variations and binge drinking. They authors conclude that:

...our model shows that alcohol taxes may be counter-productive in controlling the emergence of EDSS [Excessive Drinking in Social Situations] as a social norm.

However, don't rush to cancel alcohol taxes just yet. These results are based primarily on a theoretical model, and while the authors present some circumstantial evidence to support it (a survey of Norwegian students, and noting that states in the US with more historical Scandinavian immigrants are more likely to demonstrate a binge drinking culture), the conclusions are largely speculative.

There is a long chain of results required to link genetic variations with binge drinking. First, the authors note that there are studies that link shyness to genetic characteristics like blue eyes and tall ectomorphic bodies (which are typical Scandinavian traits). Second, shy people can use excessive drinking as a coping strategy in social situations. Third:

...given the first two steps, a larger fraction of the population in northern Europe should have a greater genetic disposition for EDSS...

Fourth, if the fraction of the population with EDSS genetic disposition is sufficiently large, social reinforcement mechanisms could come into play... If EDSS is atypical, it is considered anti-social. If EDSS is relatively common, it has a "legitimizing" effect and EDSS becomes acceptable.

Fifth, if steps 1-4 hold, we should observe a larger fraction of the population that engages in EDSS in northern Europe than in southern Europe.

It is a nice theoretical model, but given the number of steps required to link genetic variation with binge drinking, file this as speculative at best. At least, until there is some genuine empirical support for it. I find it hard to get past the counter-examples of countries like New Zealand, Australia, and the UK, where blue eyes are not common and yet binge drinking is.

Book Review: Factfulness

In a world of fake news, it seems increasingly important to be able to determine fact from fiction, to be able to evaluate others' claims and to use data to support our decision-making. But how well do you know basic data about the world around you? Consider the following three multiple-choice questions.

1. In all low-income countries across the world today, how many girls finish primary school? (A) 20 percent; (B) 40 percent; or (C) 60 percent.
2. What is the life expectancy of the world today? (A) 50 years; (B) 60 years; or (C) 70 years.
3. How many of the world's 1-year-old children today have been vaccinated against some disease? (A) 20 percent; (B) 50 percent; or (C) 80 percent.

The answers are at the bottom of this post, and the answers to those questions and ten others (and in particular how badly people get them wrong) provides the backdrop for the book Factfulness, by Hans Rosling (with Ola Rosling and Anna Rosling Rönnlund). The subtitle is "Ten reasons we're wrong about the world - and why things are better than you think". Hans Rosling was the man behind the Gapminder website (and if you haven't seen it already, I highly recommend it), which illustrates data in highly memorable ways. The book is in some ways a memorial to Rosling's work - he died shortly before it was published, a year after being diagnosed with cancer.

Rosling clearly took issue with people's inability to answer simple fact-based questions about the world around them. He spent years collecting data on people's answers to questions like the three at the top of this post. The book notes that, almost regardless of country or the expertise of the group answering the questions (from university students to business leaders to scientific experts), people do no better than random at answering these questions. In fact, people do significantly worse than random. For instance, only 13 percent of people get the answer to Question 3 above correct.

Rosling's insight was that it isn't ignorance that leads people to get the answers to these questions wrong. If that were the case, they you'd expect the percentage correct to be closer to 33 percent than 13 percent. Our brains must be hardwired to steer us wrong.

Specifically, the book highlights ten instincts that lead us astray. For instance, the 'negativity instinct' leads us to notice the bad more than the good, while the 'single perspective instinct' leads us to believe that there is a single simple cause for most things that we see. For each instinct though, there is an antidote. To combat the negativity instinct, we should recognise that most of the news we hear is bad news, because good news is not news, and gradual improvements are not news. He notes that:

Journalists who reported flights that didn't crash or crops that didn't fail would quickly lose their jobs.

Learn to look for the good news. To combat the single perspective instinct, have people who disagree with you test your ideas and find their weaknesses, because:

The world cannot be understood without numbers, and it cannot be understood with numbers alone.

There are a number of worthy quotes I could pick out from the book, but I'll limit myself to one more, that actually relates to my own previous research:

Most concerning is the attempt to attract people to the cause by inventing the term "climate refugees." My best understanding is that the link between climate change and migration is very, very weak. The concept of climate refugees is mostly a deliberate exaggeration, designed to turn fear of refugees into fear of climate change, and so build a much wider base of public support for lower CO2 emissions.

Clearly, Rosling has no time for misuse of data to support shaky positions or to misdirect. The text is filled with great stories from Rosling's very full life and career as a physician in Sweden and Africa, and from his time as a researcher at the Karolinska Institute and running Gapminder.

This is an excellent book and well worth reading. I recommend it if you are looking for the good news on human progress. Oh, and the answers to those three questions: C, C, and C.

A simple nudge for (online) students to complete assignments

Following on from yesterday's post about extra credit to encourage student attendance at lectures, another challenge for lecturers is to encourage students to put sufficient effort into relatively low-stakes assignments or homework. We set these homework assignments to assist with students' long-term recall of their learning, to encourage them to work throughout the semester (since it spreads the assessment load more evenly), and to help them to prepare for the high-stakes assessments like in-class tests or examinations. Small stakes do appear to have an out-sized influence on student behaviour (which was something I noticed when I introduced weekly assignments in my ECON110 (now ECONS102) class in 2006, the second year I taught that paper). However, the effort that students put into the assignments does vary significantly (presumably based on the students' workload in their other papers).

So, I was interested to read this recent article in the Journal of Economics Education (I don't see an ungated version online unfortunately) by Ben Smith (University of Nebraska at Omaha), Dustin White, Patricia Kuzyk (both Washington State University), and James Tierney (Pennsylvania State University). I originally read a working paper version of this article from 2016, which excluded the last two authors and had slightly different results (more on that in a bit).

In the paper, the authors describe a very simple 'nudge' to improve student effort on regular homework assignments. Nudge theory was brought to prominence by Richard Thaler and Cass Sunstein's excellent 2008 book Nudge. The idea is that relatively subtle changes to the decision environment can have significant effects on behaviour.

The authors' nudge involves sending a short message to each student as each assignment due date approaches (or the message could be appended to the assignment itself in Google Docs):

Hi [Name],

As of now, you have a(n) [Grade] in the class. This assignment is worth [Points] points. If you get more than [X] on this assignment, your class grade will increase to a(n) [Higher Grade]. If you get less than [Y] on this assignment, your grade will drop at least one grade. Not doing the assignment will result in a(n) [Lower Grade].

The authors then test the effect of the nudge on student performance in three online courses (two sports economics courses, and one microeconomics course), and find that the grade nudge improves student performance, by 3.8 percentage points. This suggests that the nudge induced the students to put more effort into their homework assignments. Moreover, they find that the effect is larger for the first nudge of the semester (around 10 percentage points), and they suggest that:

...[t]he first nudge could have “primed” the student to be more aware of their grade throughout the semester...

The results are quite encouraging. However, in the 2016 version of the paper, the authors presented some slightly different results. The microeconomics course was not included in that version of the paper, but a face-to-face (i.e. not online) version of the sports economics course was. Those results demonstrated no effect of the nudge on student performance in the face-to-face sports economics course. It's a pity those results didn't survive to the final paper, because they make it clear that this nudge only appears to work for online courses. This may be because online students are more likely to carefully read any emails (or other online communications) related to the course than face-to-face students.

So, the takeaway from this paper (combining the results from both versions) is that it is possible to nudge students into greater effort in homework assignments, but the context of the nudge is important.

Creating a market for in-class extra credit

I began offering extra credit in my ECON110 (now ECONS102) class in 2012. There were two reasons for this. First, as with many first-year university classes, my class had suffered from declining attendance over the previous several years, and offering extra credit for completing certain activities in lectures seemed to be one way to arrest the decline in attendance (and it worked!). Similarly, we had introduced marks for tutorial attendance in our economics papers in 2007, and that demonstrated the potential impact on attendance. We introduced extra credit for random spot quizzes in ECON100 (now ECONS101) in 2016, and it had a similar effect on lecture attendance (at least, until the current semester where attendance has been surprisingly low). Second, I already used some class time to conduct extra activities such as small experiments or surveys that I would use to illustrate various economic concepts, and it made sense to reward the students who provided the data for those illustrations.

As you can see, extra credit has been part of my practice for several years, and is now being used by several of my colleagues as well. So, I was really interested to read this 2016 paper by James Staveley-O'Carroll (Babson College), published in the Journal of Economic Education (ungated earlier version here). In the paper, Staveley-O'Carroll describes the creation of a market for extra credit, where students can buy and sell extra credit, which he has been using in his classes:

The EC [extra credit] generated by answering clicker questions, as described in this article, offers an inexpensive alternative reward to create a realistic market with properly aligned incentives. By answering questions in class, students create EC. The EC, however, is not transferred directly to the student who created it. Instead, a market system is implemented to price EC and allocate it to the students who desire it the most. This market can be manipulated by the instructor to give students hands-on experience with many economic topics such as inflation expectations and game theory. Moreover, extensions of the experiment allow the instructor to add a financial intermediary, bonds, and stocks to the basic market framework, expanding the range of topics to risk aversion, hedging, and peer-to-peer lending.

This system combines the incentives associated with extra credit with a real-world market mechanism that the teacher can use to illustrate some of the concepts being developed in class. There are many pit market experiments that teachers already use, so this provides an interesting extension of those. This sounded pretty exciting to me. However, as I delved deeper into the paper, I realised that it was very practical for the class sizes that Staveley-O'Carroll was dealing with (between 7 and 30 students), but would soon become very unwieldy without some serious back-end automation in my classes (with up to 320 students).

On top of that, the mechanism by which the extra credit currency (Gronks) converts to extra credit marks relies on balancing the supply of extra credit marks and demand for extra credit marks for each piece of assessment, to determine the price (in Gronks) for each point of extra credit. I could see that would require a lot of explanation for some students to get their heads around. So, while it sounds like a pretty cool idea, it might be something to park for classes at a slightly higher level than first-year.

Finally, the article doesn't provide any evidence that the extra credit market improves student understanding of economics. Nevertheless, Staveley-O'Carroll does find that:

...student feedback has been almost unanimously positive, with many students noting that the in-class currency is the best part of the course.

So, at least the students enjoy it!

Television viewing vs. sex

Consider two goods (A and B) that are substitutes - consumers tend to switch consumption towards the good that has become relatively cheaper when the relative price between the two goods changes. So, if the price of A falls, consumers will tend to buy more of A, and less of B. And if the price of A rises, consumers will tend to buy less of A, and more of B.

We can extend the idea of the relative price to consider the full cost of obtaining each good. So, if A becomes more difficult to find, the full cost of consuming A rises, and consumers will buy less of A, and more of B. And so on. Now consider two specific goods: television viewing and sex. Based on the basic model we just outlined, if the full cost of television viewing falls, then consumers will watch more television, and have less sex.

We can also illustrate this using the diagram below. Let's assume that the 'consumer' doesn't own a television. The 'consumer' has a choice of two goods: television viewing (on the x-axis) and sex (on the y-axis). They have limited time (say 20 hours per week), that they can spend on either activity, and this constraint is represented by the straight line (from 15 hours television viewing and no sex, to 20 hours of sex and no television viewing). They can only get to 15 hours of television watching rather than 20, because they have to find someone else who owns a television and will let them watch, and that takes up some time. The consumer will choose the point on their time constraint that is on the highest indifference curve (I0) which touches the time constraint at one point (E0), where they spend T0 hours watching television, and S0 hours having sex.

If the consumer buys their own television, they no longer have to spend time trying to find a television to watch somewhere else, so the full cost of television watching decreases. The time constraint pivots upwards (which represents a decrease in the relative price of television watching). The consumer can now reach a higher indifference curve (I1), and will maximise their utility by consuming at the point E1, where they now spend T1 hours watching television, and S1 hours having sex.

Notice that television watching has increased greatly (it is now cheaper and much more convenient), but time spend having sex has decreased. [*] So, television really might kill your sex life.

Is there evidence for this trade-off between television viewing and sex? In a new NBER Working Paper, Adrienne Lucas (University of Delaware) and Nicholas Wilson (Reed College) find suggestive evidence for a negative relationship between television ownership and coital frequency, using data from nearly 4 million individuals from 80 countries. Specifically, they find that:

...the results of the analysis are consistent with a small amount of substitutability between television viewing and sexual activity. We find that television ownership is associated with approximately a 5% reduction in sexual activity, a statistically significant yet not particularly large association.

The results are correlations rather than causal, but Lucas and Wilson at least eliminate some of the main potential confounders such as wealth or reproductive health knowledge. Interestingly, the effect seems to be concentrated among women (the coefficient of television ownership is not statistically significant for men). It's robust to the inclusion of other durable goods (refrigerator, radio, car, motorcycle, and bicycle). Interestingly though, owning a refrigerator is also negatively associated with coital frequency for women (but not men). Does that imply that night-time snacking is also a substitute for sex?

[HT: Marginal Revolution]

*****

[*] With the price change here, there are actually two effects: (1) a substitution effect (television watching has become relatively cheaper, and sex has become relatively more expensive, so the consumer should watch more television and have less sex); and (2) an income effect (the consumer now has more time because they don't have to waste time trying to find a television, so they both watch more television and spend more time having sex, because both activities are 'normal goods'). In my diagram, I've assumed that the income effect on time spent having sex is smaller than the substitution effect.

Why you might want alcohol sellers to be monopolies

In most parts of New Zealand, alcohol is sold by several firms in competition with each other. In West Auckland, that isn't the case. West Auckland has two legislated monopolies, the Portage and Waitakere Licensing Trusts, that are holdovers from 1960s legislation when alcohol monopolies were more common. Last week, the New Zealand Herald reported on a new petition to open West Auckland up to competition in alcohol sales:

A group of West Aucklanders have launched an online petition to challenge the alcohol monopoly that prevents local residents buying wine or beer at supermarkets.

West Auckland Licensing Trust Action Group (WALTAG) spokesman Nick Smale said the Portage and Waitakere Licensing Trusts had held a monopoly over hotels, taverns and bottle stores in West Auckland since the 1970s. Residents were missing out due to the lack of competition in the area...

Smale said it had been 15 years since residents last voted, and he believed a referendum was needed ahead of the next local body elections.

"We need 15 per cent of voters in the Portage and Waitakere Licensing Trusts areas to sign the petition – that's about 28,000 people. If we can achieve this it will force a referendum and allow West Aucklanders to have their say."

What effects would opening the alcohol market in West Auckland have? Consider the market diagram below, which makes the simplifying assumption (as I do in my ECONS101 and ECONS102 classes) that the monopoly seller is a constant cost firm (so the marginal cost curve is a horizontal line). The monopoly will operate at the profit-maximising quantity (where marginal revenue (MR) is equal to marginal cost (MC)), which is QM. To sell that profit-maximising quantity they will set a price of PM (because at the price PM consumers will demand exactly QM units of the product).

With that price and quantity, the consumer surplus (the difference between the amount that consumers are willing to pay (shown by the demand curve), and the amount they actually pay (the price)) is the triangle area ABF. The producer surplus (the difference between the amount the monopoly producer receives (the price), and their costs (which are shown by the marginal cost curve)) is the rectangle area FBDG. Total welfare is the combination of consumer and producer surplus, i.e. the area ABDG.

Now consider what would happen if this market was opened to competition. Let's assume it becomes a perfectly competitive market, in which case the marginal cost curve becomes the supply curve (S), and the market will operate at the equilibrium point (where supply meets demand).  The perfectly competitive market would operate at the quantity QC and price PC. Consumer surplus would be the triangle AEG, while producer surplus would be zero (because the price PC is equal to the cost of every unit produced), so total welfare is also the triangle AEG.

Ok, so what changes between these two situations (monopoly and perfect competition)? Consumer surplus is higher with more competition (AEG, compared with ABF), which is no doubt why alcohol consumers (such as Nick Smale's group) are in favour of greater competition. Producer surplus is lower (in fact it falls to zero in this model), which is why the Trusts are against the petition. No surprises there. Total welfare (a measure of economic welfare for society) is higher with greater competition (AEG, compared with ABDG).

However, that isn't the end of the story. Total welfare only shows the impacts on economic welfare in this market. With more competition, the price of alcohol is lower (PC, rather than PM), and the quantity of alcohol sold and consumed increases (from QM to QC). Greater alcohol consumption is associated with greater levels of alcohol-related harm. As the article notes:

According to the Auckland Regional Public Health Service, West Auckland has the lowest incidence of alcohol-related crashes in Auckland Council urban zone areas, the trusts' website said. Drink-driving prosecutions were also lower in the region compared to others.

It also quoted University of Otago's Health Promotion and Policy Research Unit's Tim Chambers as saying: "The sale of alcohol through retail stores controlled by a licensing trust, is an effective model for preventing childhood exposure to alcohol marketing."

So, if your goal is to minimise alcohol-related harm, you might want the alcohol monopolies in West Auckland to remain. Overall, it's ambiguous whether the proposal is to eliminate the alcohol monopolies is good or not, since there are gains in economic welfare, but probably offsetting losses in terms of alcohol-related harm.

Why taxing robots is infeasible, and an alternative proposal for a 'non-labour tax'

Back in March, I wrote a post using a simple production model to demonstrate how, as robots (and algorithms and other related technologies) became cheaper, they would increasingly displace human labour as robot-intensive technologies became the least-cost production technology for more firms and industries. An appealing fantasy is that we could tax robots and avert the coming labour crisis, but such a tax would only delay the inevitable. And, such a tax is likely to be infeasible in any case, as a recent article by Tim Harford explains:

What does a robot accountant look like? Not C-3PO with a pencil sharpener, that’s for sure. One might say that Microsoft Excel is a robot accounting clerk. A more plausible answer is that there is no such thing as a robot accountant. One day we may have androids sophisticated enough to do everything human accountants do now, but by then the very concept of an “accountant” will have changed beyond recognition.

So it is misleading of me to write of “robots” taking “jobs”. What actually happens is that specific tasks are automated, rather than the broad bundle of tasks that together constitute a human “job”. Automating tasks means reshaping jobs. The process can create jobs or destroy them, and will usually do both...

As any tax wonk can tell you, whatever we choose to tax — land, capital, profits, value-added, imports, wealth, greenhouse gas emissions — inevitably turns out to be a more ambiguous concept than it might appear, especially since ambiguity is often tax efficient.

But the category of “robot” is particularly difficult to define, and therefore to tax. We cannot tax the androids who march into our workplaces, stand by while we clear our desks, then sit down to replace us: they do not exist and it is hard to see why they ever would.

In a world of mass technological unemployment we are certainly going to need to tax something other than labour income alone. There are several plausible candidates. “Robots” is not one of them.

So, if we can't find specific robots to tax, it is difficult to tax robots effectively. What then? Give up and play Fortnite all day? An alternative proposal, which admittedly isn't fully formed in my mind yet, might be a 'non-labour tax'. The 'non-labour tax' would tax the difference between gross profit and net profit for each business, minus all labour costs that attract PAYE tax.

As any accountant will confirm, gross profits is basically what is left after the firm subtracts the cost of goods sold from total revenue. It is the gross profit that (manufacturing and retailing) firms use to pay the remainder of their costs, including the cost of labour [*]. Subtracting labour costs from gross profit, and taxing the difference between that and net profit, essentially places a tax on all non-labour expenses (which is why I dubbed it the 'non-labour tax'). Net profit is already taxed, so excluding net profit from the tax calculation avoids double-taxing.

My feeling is that such a proposal potentially creates a number of interesting outcomes. For instance, I believe that this tax proposal would:

• incentivise firms to hire more labour at the margin, since it lowers the relative cost of labour (compared with 'robots' or whatever);
• incentivise firms to hire labour in-house (since that labour would attract PAYE tax) rather than subcontracting out services like cleaning, since those subcontractor payments will now be taxed (so the relative 'price' of these services will be more in favour of in-house labour);
• incentivise firms to categorise more of their workforce as employees (labour cost attracting PAYE tax) rather than as self-employed contractors (as above, the relative 'price' will be more in favour of labour); and
• provide a means of taxing multinational firms that are profit-shifting to low-tax jurisdictions, since they would have to pay tax on international interest payments, intellectual property licensing fees and 'management services' fees, which are the main means that such firms use to shift profits overseas.

Of course, there are downsides to such a proposal, such as disincentives for research and development spending and innovation. Those disincentives might be able to be addressed through offsetting subsidies. There's probably plenty of other fishhooks I haven't considered (as I said above, it isn't a fully formed idea yet).

One of the main problems with taxes is all the activities that go on when people (or firms) try to avoid paying the tax (the unintended consequences that I often write about on this blog). In this case though, it should be clear enough to avoid such problems - if a payment attracts PAYE tax, then it is labour cost. And if not, it isn't. Labour costs are not a category that it would be easy for firms to shift other expenses into, in order to minimise their tax. Given that employers already need to report their payroll and PAYE tax payments regularly to the Inland Revenue Department, it seems straightforward that this could be used to calculate their tax liability (since they also have to report net profit and gross profit to IRD annually as well).

The pity here is that I've only recently started thinking about this, and it is now too late to make a submission to the government's Tax Working Group. I guess that just provides more time to think through the various consequences for the next time there is a working group (remembering past working groups on the same topic in 2009 and 2001).

*****

[*] Labour used in manufacturing might be subtracted from gross profit already, but we'll leave that aside for now because my recollections of accounting principles is a little shaky after many years out of the industry.

Does brideprice explain why ISIS offered wives to its members?

You may have seen the stories, such as this one from CBS News in 2015:

The honeymoon was a brief moment for love, away from the front lines of Syria's war. In the capital of the Islamic State of Iraq and Syria's self-proclaimed "caliphate," Syrian fighter Abu Bilal al-Homsi was united with his Tunisian bride for the first time after months chatting online. They married, then passed the days dining on grilled meats in Raqqa's restaurants, strolling along the Euphrates River and eating ice cream.

It was all made possible by the marriage bonus he received from the Islamic State of Iraq and Syria (ISIS): $1,500 for him and his wife to get started on a new home, a family - and a honeymoon.

I thought it was interesting at the time, but mostly put it down to an organisation that is short on money finding non-monetary ways to incentivise new membership. Indeed, it appears that is exactly what was going on, but brideprice has a key role as the source of the incentive.

A brideprice is a payment (monetary or non-monetary) from the family of the groom to the family of the bride, on the occasion of their wedding. It is the norm throughout Africa, and most of Asia (excepting South Asia), as the following map shows (though note that sub-national heterogeneity is not shown, and there are areas in Africa where brideprice is not the norm):

In a recent article published in the journal International Security (ungated version here), Valerie Hudson (Texas A&M University) and Hilary Matfess (Yale) explain the economics of brideprice, and there is a lot of good economics in the article (so forgive the number of quotes, but the story is interesting):

The status of males in patrilineal societies is strongly linked to marriage. Not only does marriage mark the transition to manhood in patrilineal societies, but it establishes the male as a source of lineage and inheritance within the larger patriline. The marriage imperative is thus deeply felt among males in such cultures. And yet, marriage is unobtainable without assets...

Marriage in patrilineal societies is accompanied by asset exchange, wherein brideprice offsets the cost to the natal family of raising the bride... In addition to patrilocal marriage and the lack of female property rights mentioned above, these societies are characterized

by arranged marriage in the patriline’s interest; a relatively low age of marriage for girls; profound underinvestment in female human capital; intense son preference, resulting in passive neglect of girl children or active female infanticide/sex-selective abortion; highly inequitable family and personal status law favoring men; and chronically high levels of violence against women as a means to enforce the imposition of the patrilineal system on often recalcitrant women...

In patrilineal systems, brideprice is essentially an obligatory tax on young men, payable to older men...

...men pay for their sons’ brideprices by first collecting the brideprice for their daughters. Such transactions are another force pushing down the age of marriage among girls in brideprice societies, in addition to the desire to stop providing for daughters who, socially, will become the responsibility of another family. Unless a family is very wealthy, daughters in general must be married off first, so that the family can accumulate enough assets to pay the sons’ brideprices... If brideprice were not standardized within the society, families could not count on the brideprices brought in by their daughters being sufficient to cover the costs of their sons’ marriages. Thus, over time, a fairly consistent brideprice emerges for the community at any given time, though the actual cost may vary somewhat over time depending on local conditions...

Given the tendency toward brideprice inflation, an unequal distribution of wealth will amplify market distortions by facilitating polygyny...

Given both low investments in women’s health and the early age of marriage for girls in these societies, maternal mortality rates in most patrilineal societies tend to be egregiously high...

Thus, both polygyny and higher rates of post-marriage female mortality increase the ratio of marriageable males to marriageable females. Sometimes this scarcity produces extreme downward pressure on the marriage age of girls in a given society, with some marrying off girls as young as eight...

The patrilineal syndrome, therefore, is primed to produce chronic marriage market obstruction because (1) brideprice acts as a flat tax on young men that they cannot refuse to pay without suffering profoundly adverse social consequences; (2) brideprice catalyzes polygyny among the wealthier segments of society; and (3) the devaluation of women’s lives leads to high female mortality...

Marriage market obstruction, in turn, can be an important factor driving young men to join violent groups. The flat and inflationary nature of brideprice guarantees that poor young men will be hard-pressed to marry... These young men are not taking up arms against the institution of brideprice. Rather, at the individual level, a young man engages in violence to become more successful within the patrilineal system...

Furthermore, if a family has many sons, it may strive mightily to get the first son married, but then the younger, higher birth-order sons (such as the third, fourth and fifth sons) are typically expected to find their own sources of funding to pay brideprice...

Being unemployed is never good, but being unemployed in a society where you can only become an adult man by marrying and in which marriage requires significant financial resources produces a clear intensification of vexation and desperation...

High levels of grievance open up an opportunity for anti-establishment groups to exploit young men attempting to gain the status and the assets needed to marry. Delayed marriage and, importantly, the threat that one may never father a son in a culture defined by patrilineality are common elements exploited by groups seeking young adult men interested in redressing the injustice they feel on a personal level, by force if necessary.

Hudson and Matfess illustrate their article with examples of Boko Haram in the Lake Chad Basin and northern Nigeria, and militia groups in South Sudan. In both cases, brideprice inflation has led armed groups to offer incentives in the form of wives to militants willing to sign up. Hudson and Matfess also offer the counter-example of Saudi Arabia, where the government has capped brideprice and also acted to reduce the cost of weddings.

The article argues that polygyny increases the scarcity of potential brides, and prices increase when 'resources' are scarcer, and this pushes up the brideprice. That puts brides out of reach of low-income men, particularly second and later sons who can't rely on their family to be able to pay the brideprice for them. This is not just a flat tax. Because the brideprice is the same regardless of income (it's not an example of the 'law of one price' I would have considered), it is a regressive tax (it takes up a higher proportion of the income of a lower income man than a higher income man). This regressive tax incentivises low income men to: (1) take up arms in order to have the insurgent group find them a wife (e.g. Boko Haram); or (2) to engage in cattle raiding with armed groups (e.g. South Sudan). Either way, their inclusion in the armed group is a way for the young men to get a wife that they otherwise could not afford.

Finally, economists usually frown on the use of price controls, since they tend to lower economic welfare (they create a deadweight loss). As the case of Saudi Arabia shows, this might be one of the few exceptions. Without controls on the brideprice, Saudi Arabia might have faced a whole lot more problems.

[HT: Marginal Revolution]

Compensating differentials are alive and well in Tokoroa

The New Zealand Herald reports:

A South Waikato District Councillor is puzzled as to why they're struggling to fill a well-paid job in the region.

The local district council is advertising for a health and safety manager in the town of Tokoroa, paying around $90,000 a year.

The council's last manager lasted just 12 weeks in the role and the officer before that 18 months.

Chairman of the Finance, Audit and Risk Committee Gray Baldwin told Larry Wiliams he's surprised more people haven't applied.

Some readers might remember a very similar story in 2016 about a general practitioner (also in Tokoroa) who was unable to attract a doctor for $400,000 per year (around double the going rate for a GP). Or the tourist operator in Taumarunui last year, offering an 'Auckland salary' of over $150,000 and similarly unable to find a good candidate.

At the risk of repeating myself, economists recognise that wages may differ for the same job in different firms or locations. Consider the same job in two different locations. If the job in the first location has attractive non-monetary characteristics (e.g. it is in an area that has high amenity value, where people like to live), then more people will be willing to do that job. This leads to a higher supply of labour for that job, which leads to lower equilibrium wages. In contrast, if the job in the second area has negative non-monetary characteristics (e.g. it is in an area with lower amenity value, where fewer people like to live), then fewer people will be willing to do that job. This leads to a lower supply of labour for that job, which leads to higher equilibrium wages. The difference in wages between the attractive job that lots of people want to do and the dangerous job that fewer people want to do is called a compensating differential.

So, why would people be unwilling to take a job in Tokoroa for $90,000? Perhaps the job comes with undesirable non-monetary characteristics (living in Tokoroa might be high on that score for many of us). You have to wonder why the last two people in the job lasted just 12 weeks and 18 months respectively. If this job was worth it for the salary on offer, why did the last two people leave so soon?

Read more:

• Reason to be wary if a job in Taumarunui offers an Auckland salary
• The compensating differential for rural GPs must be enormous

Book Review: The Flaw of Averages

I just finished reading The Flaw of Averages, by Sam Savage. Reading the blurb, I would have thought this was a book that presented arguments that I would have a lot of sympathy for. The core argument that underlies the book is that so often decision-makers are looking for a single number that they can use for decision-making (often this is the average), but using that single number results in flawed and costly mistakes, because it ignores the fact that the single number is drawn from a distribution of possible numbers. Savage essentially argues for using simulation modelling, a particular form of which he has developed, called probability management.

In my own work, preparing population projections for local councils and other decision-makers, I often struggle with the decision-makers' needs for a single magic number that they can use for decision-making. Along with Jacques Poot, we pioneered the use of stochastic models for sub-national population projections in New Zealand (see this paper, for one example, or the longer ungated version here). Stochastic models explicitly display the uncertainty in future projections of the population, and there are a few regularities that Jacques and I noticed, such as projections being more uncertain for areas with smaller populations, and surprisingly more uncertainty for slower-growing or stable populations (compared with faster growing populations).

Towards the end of the book, there is a good quote that illustrates why decision-makers prefer not to have to deal with uncertainty, and prefer to focus on a single magic number:

Unfortunately, most organizations don't know how to deal with distributions. They generally ignore that part of the forecast, relying instead on the single number, and, presto, they're back to square one with the Flaw of Averages...

So, as has been my experience, you can provide decision-makers with the extra information on the uncertainty of a projection (or forecast), but you can't make them use it!

Savage's book can essentially be broken down into three parts. In the first part of the book, he essentially tries to make us forget all of the complicated terminology used in what he refers to as 'steam era' statistics, and instead replace the complicated 'red words' with 'green words' that have the Savage stamp of approval. However, in my opinion the green words are more ambiguous and sometimes plain wrong. For instance, Savage would have us replace "utility theory" (a red word) with "risk attitude" (a green word). Now, risk attitudes and utility theory are related, but not so much that you can replace both terms with one of them! Savage is also highly uneven in his disdain for complicated 'red words' - academic terms from finance such as the Capital Asset Pricing Model seem to get a free pass. Given that a lot of the book uses examples drawn from finance, this seems a little biased.

The second section of the book is the highlight. In these chapters, Savage uses personal stories of decision-makers and firms such as the oil company Shell and the pharmaceutical company Merck, to illustrate how simulation modelling can substantially improve the quality of decision-making. This is the really interesting stuff, and if the book had stuck to this, I feel it would have been much better.

The third section is essentially an extended infomercial for Savage's particular implementation of simulation modelling, probability management. While the examples extend those from earlier in the book, they're really just trying to sell the reader on the tools that Savage has developed.

Overall, I found that the personal stories of models in the real world are great. However, the book seems to have too many purposes and as a result, it doesn't execute as well on any of them as it might. In particular, it's a pity the first part of the book was essentially just a rant against terminology that Savage finds offensive. Moreover, Savage hasn't been as careful as he might with his examples. Fairly early in the book, he presents decision-making based on decision trees. However, despite his strong encouragement for us not to reduce decision-making to single numbers, in that chapter he uses expected value calculations - which reduces the decision to being based on a single number!

Overall, I wouldn't recommend this book for the general reader. If you want to understand why simulation modelling is important (or why it is important not to reduce analyses to a single number), it is useful for that, but I would skip through and start reading from about Chapter 16, and stop when your tolerance for the infomercial at the end is exhausted.

Stocks vs. flows... $1 trillion Apple edition

It had to happen. Apple's market capitalisation passed US$1 trillion last Thursday, so of course that invites comparisons with other big numbers. Consider the following two sentences, from this Washington Post article:

If Apple sold itself for $1 trillion in cash, the money would be enough to buy all the goods and services produced in Indonesia — population 261 million — in 2017.

Apple is bigger than the economies of about 174 countries, including Turkey, the Netherlands, Saudi Arabia and Switzerland.

The first sentence is kind-of all right. You could use $1 trillion to buy all of the goods and services produced in Indonesia in 2017 (but why would you want to?). The second sentence is an example of one of my pet peeves. Apple is NOT bigger than the economies of about 174 countries. It's not even bigger than the example of Indonesia from the article. And it's easy to see why. If investors are rational, Apple's market capitalisation represents the discounted value of all future cash flows for Apple. So, you would be effectively selling off all of the future cash flows of Apple for all time, in order to get just one year's worth of Indonesia's GDP. Clearly, Apple is worth a lot less than the economy of Indonesia.

The problem (as I've mentioned many times before, such as here and here and here) is comparing stocks with flows. The size of an economy (as measured by GDP) is a flow of resources for a single year. Apple's market capitalisation is a stock (a measure of its total value), not a flow for a single year. The appropriate stock for a country is the discounted value of all future GDP, not one year's worth of GDP. If you want to compare Apple with the size of an economy, you would need to compare Apple's market capitalisation with a much bigger number for each country.

Who would want to be a landowner in South Africa right now?

From news.com.au last week:

South Africa’s ruling party says it will push ahead with plans to amend the country’s constitution to allow for the expropriation of land without compensation.

President Cyril Ramaphosa announced the decision on Tuesday following a two-day meeting of the African National Congress, which had earlier signalled its intention to redistribute land under the current laws.

The South African parliament in February voted in favour of a motion, brought by the radical Marxist Economic Freedom Fighters and supported by the ANC, to send the matter to parliament’s Constitutional Review Committee.

“It has become patently clear that our people want the constitution to be more explicit about expropriation of land without compensation, as demonstrated in public hearings,” Mr Ramaphosa said in a video message addressing “fellow South Africans, comrades, friends”.

“The ANC [has] reaffirmed its position that a comprehensive land reform program that enables equitable access to land will unlock economic growth by bringing more land in South Africa to full use and enable the productive participation of millions more South Africans in the economy.”

From the perspective of my ECONS102 class, this is great timing given that we are about to do a topic that includes property rights this coming week. Efficient (welfare-maximising) property rights have four features:

1. Universality – all resources are privately, publicly, or communally owned and all entitlements are completely specified;
2. Exclusivity – all benefits and costs accrued as a result of owning and using the resources should accrue to the owner whether directly or indirectly;
3. Transferability – all property rights should be transferable from one owner to another in a voluntary exchange; and
4. Enforceability – property rights should be secure from involuntary seizure or encroachment by others.

Obviously, if the government is about to legislate for expropriation of land without compensation, then the 'enforceability' feature is going to be absent. What does this do to the value of land? The article tells us:

Speaking to the ABC’s Foreign Correspondent on Tuesday night, cattle farmer Jo-an Engelbrecht — whose elderly parents were tortured and killed in their home on Mother’s Day — said even if he wanted to sell his farm and leave, it was now “worth zero”.

“We had several auctions in the last two or three weeks cancelled because there was no people interested in buying the land,” he said. “Why would you buy a farm to know the government’s going to take it?”

To see why land values might fall to zero, consider the land market in the diagram below (note that it is a rental market for land, as I discussed last week). Before land expropriation was likely, demand is D0 and the land rent is R0. When land expropriation becomes likely, fewer people want to have land, either because they worry that they land they have paid for will be expropriated, or because they think "why pay for land, when I can just wait and some might be redistributed to me?" Either way, the demand for land falls to D1. Notice that there is no equilibrium in this land market now, because demand and supply never meet (or if there was an equilibrium, the equilibrium price would be negative!).

To see why the lack of enforceability reduces economic welfare in the land market (i.e. why this market is inefficient), consider the areas of consumer and producer surplus. Before land expropriation was likely, the consumer (tenant) surplus is the area ABR0, producer (landlord) surplus is the area R0BCO, and total welfare is ABCO. When land expropriation becomes likely, all of these areas (consumer and producer surplus, and total welfare) fall to zero, because there is no land trading at all! Of course, if demand didn't fall so far that there was no trading, there would still be reductions in consumer surplus, producer surplus, and total welfare.

That's not the end of the story though. The South African government has its reasons for land expropriation and redistribution. South Africa has one of the highest levels of inequality in the world (it's so bad, it even has a dedicated Wikipedia page). Reducing inequality is a worthy goal, and with a bit of luck, this might go some way towards addressing that. So long as they don't follow the example of Zimbabwe, where according to this New York Times story from 2002:

...the government's chaotic and violent seizure of white-owned farms has come at a price. The economy is collapsing. The land program, coupled with severe drought, has left half the population in need of emergency food. And so far, Mr. Mugabe has failed to transform the agricultural sector into a viable system that can feed the nation and drive the economy.

Vast stretches of previously productive farmland are no longer in use because about half of the aspiring black commercial farmers have failed to take up their allotted farms since August, when most white farmers were told to leave.

The government, which seized the farms without compensation, still lacks title to most of the land. Many prospective black farmers are reluctant to occupy farms without title deeds because it is nearly impossible to get loans without them.

Meanwhile, thousands of impoverished, resettled farmers are struggling to survive without seed, fertilizer, irrigation and plowing assistance, basic services that the government has promised.

If South Africa wants to address its inequality problem, land expropriation by itself will not be enough.

Behavioural economics is a work in progress

Behavioural economics is one of the 'in things' in economics, and has been for the last several years (and evidenced by last year's Nobel Prize award for Richard Thaler, following the earlier prize for Daniel Kahneman back in 2002). However, a good article last month by Koen Smets takes issue with behavioural economics, not because he prefers models of rational decision-makers, but because behavioural economics is still just a collection of cool stories of things that get in the way of rational decision making (that's my paraphrase of Smets). He begins with:

Compared to just a few years ago, the term behavioral economics has gained tremendous currency. To say it is on everyone’s lips would be only a minor exaggeration. For the scientists and practitioners in the field, this emergence from relative obscurity should, at first glance at least, be a source of happiness.

One reason for this growing interest is the way behavioral economics has been presented and interpreted. Behavioral economics is, it seems, the field that confronts us with our deeply irrational selves. We are bamboozled by biases, fooled by fallacies, entrapped by errors, hoodwinked by heuristics, deluded by illusions...

This is all very exciting, of course, and as a result we are knee-deep in articles and infographics that gleefully point out how flawed we really are. But is that really all there is to behavioral economics?...

To a worrying extent, biases have become the defining feature of behavioral economics.

This focus on biases is unhelpful in several ways. It fails to acknowledge that biases are broad tendencies, rather than fixed traits, and it oversimplifies the complexity of human behavior into an incoherent list of flaws. This leads to misguided applications of behavioral science that have little or no effect, or which can backfire spectacularly. We need to appreciate better the role biases play on the wider behavioral-economics stage.

If you are interested in behavioural economics, I encourage you to read the whole article. It's clear that Smets' view is that behavioural economics has come a long way in describing the various decision-making quirks where we deviate from rational decision-making, but that it still fails to fully explain why those quirks appear in some circumstances and not others. But despite how that sounds, Smets isn't entirely negative towards behavioural economics. Here's the end of his conclusion:

Behavioral economics will be a work in progress for a long time to come. But with the right sculptors, there is hope yet for a masterpiece.

[HT: Marginal Revolution]

Rents are best for assessing the state of the housing market

In my ECONS102 class, we cover the market for land, but we cover it as a rental market rather than a market for the sale and purchase of land. This often raises a few eyebrows from students, who may expect us to be thinking about land using a seller-buyer perspective rather than a landlord-tenant perspective. In an article in The Conversation on Monday, Rachel Ong (Curtin University) does a great job of explaining why looking at housing markets from a rental perspective is actually a better approach:

If property prices are rising, it is commonly assumed we must be facing a shortage of supply relative to demand. So if we’re ever going to reduce housing affordability problems, we’re simply going to have to build our way out of it. After all, as anyone who’s sat in an introductory economics class would tell you, basic economics is sufficient to at least suggest that if prices are rising in the long term, then supply must be lagging behind demand.

It’s true the housing market is largely subject to the forces of supply and demand. The deficiency of this argument lies, not so much in any perceived cracks in the supply-demand framework taught in Economics 101, but in the fact that the appropriate “price” indicator is not property prices. It’s rent...

The problem with relying on rising property prices as a “price” signal of a supply shortage is that the dwelling an owner-occupier buys is both a consumption and an investment good. It offers a place to live as well as an asset in which the owner invests a substantial part of their wealth. Hence, property prices are at best a murky indicator of the balance of supply and demand for housing as a home to live in and an asset to own.

It is well established in the housing economics literature that the “price” signal for the adequacy of supply relative to demand for housing services is rent. Rent reflects the cost of consuming housing or, to put it another way, the cost of living in a home. So if housing supply is lagging behind demand for housing as a place to live in, we should expect to see rents rise.

So, there you have it. When we're trying to understand what's happening to housing we should be looking more closely at what is happening to rents, and less closely at what is happening to house prices.