Sex, Drugs and Economics

Tuesday, 4 March 2025

Local minimum wages and low-quality housing rents in Japan

In this 2023 post, I discussed the impact of higher minimum wages on homelessness. Part of the story related to housing rents:

There are a couple of reasons to expect that higher minimum wages might increase homelessness. If minimum wages decrease employment (a result that is contested, but I believe it is likely given the galaxy of literature we have to date; again, see the links at the end of this post), then higher minimum wages may directly increase the risk of people becoming homeless. That's because when low-income people workers lose their jobs, they may no longer be able to afford to pay rent, and may lose their homes. Second, if minimum wages increase incomes for those that are not made unemployed, they may increase the demand for housing, pushing up rents. This may indirectly increase the risk of people becoming homeless, who can no longer afford the higher market rent.

The research that I referred to in that post found that higher minimum wages increased homelessness, and that they also increased housing rents, consistent with the mechanism outlined above. However, we shouldn't believe just a single paper's research findings. This 2021 article by Atsushi Yamagishi (Princeton University), published in the journal Regional Science and Urban Economics (ungated earlier version here), provides some additional evidence, this time from Japan.

Japan provides an interesting case study for examining the effects of the minimum wage on housing, because:

Japan has forty-seven prefectures and each has a different minimum wage rate. There is no difference in the minimum wage rate within a prefecture...

And on top of that, each prefecture has little control over its local minimum wage. Yamagishi notes that:

...the minimum wage setting in Japan is highly centralized and unresponsive to trends in local housing markets due to institutional features. Japanese prefectural minimum wages are determined by the following process. First, the central government classifies prefectures into four categories, and it assigns the targeted amount of minimum wage increase to each category. The categorization is reviewed only once every five years and changes in the classification are rare.

Yamagishi uses data from 2007 to 2013, and exploits an interesting natural experiment, where:

From 2007 to 2012, a new consideration took the primary role in setting minimum wages due to the national policy change... after the revision of the Minimum Wage Law in 2007, the primary consideration in setting the minimum wage rate became closing the gap between the quality of life of minimum wage workers and people relying on Public Assistance (seikatsu-hogo, PA henceforth)...

Since the gap was generally larger in urban areas, the policy resulted in a plausibly exogenous minimum wage increase in urban prefectures...

So, not only is there variation in minimum wages across prefectures, and that variation is not related to local housing markets, there is a change in the variation driven by the policy change. Yamagishi uses data on advertised apartment [*] rents from At Home, "one of the most popular online real estate search engines in Japan". Using both an event study research design and a difference-in-differences design, Yamagishi found that:

...low-quality apartments experience around a 2.5-4.5% rent increase in response to a 10% minimum wage increase.

When looking at differences by apartment quality (proxied by the age of the apartment, with 'old' apartments being over 25 years old and 'very old' apartments being over 35 years old), Yamagishi found that:

An old apartment experiences a rent increase of around 3.3% when the minimum wage increases by 10%, which is statistically significant at the 1% level. A very old apartment experiences an increase of around 4%, which is also significant at 1% level. Overall, the result reveals the larger impact on the rents of lower-quality apartments...

Of course, the key point here is that workers on the minimum wage are more likely to live in low-quality apartments than in higher-quality apartments. So, the takeaway from this paper is that higher minimum wages may make some workers better off in terms of higher wages (while also considering the disemployment effects of the higher minimum wage), but that the gains of those workers would be offset somewhat by higher rents. Yamagishi estimates that landlords gain between 7.5-13.5 percent of the increased minimum wage, but the assumptions necessary to arrive at that estimate are a little difficult to justify.

Nevertheless, the overall point stands. The minimum wage workers lose some of their higher minimum wage to higher rents.

[HT: Marginal Revolution, back in 2023]

*****

[*] As an interesting aside, Yamagishi notes that in Japan, 'apartments' are generally low quality. A high quality apartment is referred to as a 'mansion' (see here).

15 years of US research on the minimum wage elasticity of employment

It's time to pick up my recent thread of posts on the minimum wage (most recently in this post). I want to return for a moment to more conventional research on the minimum wage, specifically looking at the effects of higher minimum wages on employment. The majority of minimum wage research has focused on estimating some variation on the minimum wage elasticity of employment - that is, the responsiveness of employment to a change in the minimum wage.

This 2019 article by Paul Wolfson (Dartmouth College) and Dale Belman (Michigan State University), published in the journal Labour (ungated version here), presents a meta-analysis of the findings of 15 years of such research in the US context. As they explain:

The beginning of the New Minimum Wage Research can be dated to a 1991 conference at Cornell University, and the exchange between Neumark and Wascher (2000) and Card and Krueger (2000) in the December 2000 issue of the American Economic Review marks the end of its first period. Our study includes analyses of US data that have appeared after December 2000. We identified 60 analyses, working papers, and published articles that both satisfied these criteria and included at least one estimate of the effect of the minimum wage on employment. In 37 of these 60, either the analysis explicitly reported one or more elasticities and their standard errors or it was possible to calculate them...

As a reminder, a meta-analysis involves combining the results from many other studies in order to estimate an overall effect. Wolfson and Belman's meta-analysis overall includes 739 estimates of the minimum wage elasticity of employment, drawn from those 37 studies. They also run analyses based on the 'best' estimate from each study, as well as the average estimate from each study. All of the analyses result in similar findings.

The starting point for Wolfson and Belman is an estimate from a survey article by Brown et al. published in 1982, which estimated that the elasticity was between -0.1 and -0.3. That would mean that a 10 percent increase in the minimum wage would result in a decrease in employment of between 1 percent and 3 percent. Brown et al.'s estimates were not based on a meta-analysis, but instead based on a narrative review of the literature up to 1982. Obviously, there literature has moved on a lot since then, and new methods and better data have been applied to the question of the employment impacts of the minimum wage.

So, what do Wolfson and Belman find? They report that:

...the range of the employment elasticity has shifted toward zero since Brown et al. (1982), from [-0.3, -0.1] to [-0.13, -0.07]... Teenagers, and eating and drinking establishments together account for more than half of the estimates in our sample. Estimating separate models for teens and for eating and drinking places has little effect on our estimated range, moving it from [-0.13, -0.10] to [-0.11, -0.07]... The minimum wage then has negative employment effects, but estimates of them have become smaller and are largely localized to teenagers, who comprise a declining share of the labor force.

The estimated elasticity range overall of -0.07 to -0.13 implies that a 10 percent increase in the minimum wage would result in a decrease in employment of between 0.7 and 1.3 percent. That effect is small, but it is not zero either. Overall, estimates from the literature do tend to show that higher minimum wages decrease employment (as also noted in some of the more recent findings in my earlier posts - see the list below).

Book review: Measuring Happiness

The field of happiness economics lost two giants of the field last December. First, Ruut Veenhoven passed away on 9 December. Veenhoven is well known among those working on happiness data, as the founding director of the World Database of Happiness, which has collated thousands of studies and datasets measuring happiness across many countries and over time. Second, barely a week later, Richard Easterlin passed away on 16 December. Easterlin is most famous for the Easterlin Paradox, the idea that while life satisfaction is higher among people with more income within a country as well as between countries, as average income increases, average life satisfaction doesn't change. The Easterlin Paradox gave rise to the idea of a hedonic treadmill, that people adapt to higher incomes and so their higher income doesn't make them any more satisfied with life.

So, it was timely for me to read the book Measuring Happiness, by Joachim Weimann, Andreas Knabe, and Ronnie Schöb. The book was published in English in 2015, with an earlier edition in German in 2011, so it had been sitting on my bookshelf for about nine years. The main focus of the book is the Easterlin Paradox, and a survey of the literature on happiness economics (as it stood in 2011).

The book largely concludes that the evidence doesn't support the Easterlin Paradox, and the reasons are primarily methodological, as well as shortcomings in the data, particularly in the sampling (of countries where life satisfaction data are collected, and of the populations within countries that make up the life satisfaction datasets). The World Values Survey comes in for particular criticism by Weimann et al, who point to the Gallup World Poll as a less biased data source. Using Gallup World Poll data, as Weimann et al. do (and as others have done as well, including this very thorough 2008 paper by Betsey Stevenson and Justin Wolfers), the key features of the Easterlin Paradox are absent.

The critiques that Weimann et al present are a precursor to many other more recent (and more technical) critiques (see this post, and the links at the end of that post). Clearly, as you may expect, the literature has moved on, but the conclusion remains that the Easterlin Paradox doesn't fully stand up to scrutiny (although many proponents of the Easterlin Paradox have not been convinced by the critiques).

I say that the Easterlin Paradox doesn't fully stand up, because one of the key implications of the Paradox does appear to hold, that people's life satisfaction depends on their position in the income distribution relative to other people in their community, and that people's life satisfaction depends on their current income relative to their income earlier in their life. Weimann et al are careful in ensuring that this point comes across in their review.

Given that it is now quite dated, this book is probably not worth reading for the review of the literature that it provides. However, there is a hidden gem in the form of the Appendix. The Appendix looks at the place of life satisfaction (and happiness economics) within the broad scope of the history of economic thought. This starts with the idea that the ultimate foal of human activity is the pursuit of happiness, as expressed by Jeremy Bentham and John Stuart Mill in the 19th Century, and concludes with (relatively) recent developments in the measurement of brain activity in neuroeconomics. Along the way, Weimann et al discuss the scientification of economics, with neoclassical economics in particular eschewing subjective measures such as life satisfaction. I very much enjoyed that section of the book, and it is that material that remains relevant, even if the literature review itself is somewhat dated.

If you are interested in happiness economics, and in particular if you are interested in the place of happiness within the broader scope of the history of economic thought, this book is well worth reading.

Saturday, 1 March 2025

The University of Auckland discovers the limits of student acceptance of AI tutoring

The New Zealand Herald reported today:

Students at New Zealand’s biggest university are outraged artificial intelligence (AI) tutors will be used in a business and economics course.

Three AI programs are set to replace lecture slides in the University of Auckland’s Digital Marketing 304 class when the first semester of the year begins on Monday.

“Complete bull****,” one student enrolled in the course said...

The Auckland business school tried to defend itself:

But the University of Auckland (UoA) says the assertion that students in the course don’t have a human teaching them is “incorrect” and AI tutors will not replace in-person teaching.

“This popular digital marketing course, led by a respected leader in AI education, includes AI-driven tutors as supplementary learning tools. This award-winning use of technology has undergone rigorous testing to provide engaging, factual content to support students’ learning and ensure they are well-prepared for the evolving job market,” a UoA business school spokesperson said.

“Students receive highly interactive two-hour tutorials in person every week.”

However, that seems to be contradicted somewhat by the information that they gave students:

Course information sent to students said: “Since we have no formal lectures, it is imperative that you are prepared for each tutorial by completing that week’s module using one of the AI tutors.

“We’re going all in on AI this semester! Instead of traditional lecture slides, you’ll be working with three AI tutors.”

That definitely sounds like in-person lectures have been replaced by AI tutoring. However, they probably didn't go directly from in-person lectures to AI tutoring. It seems more likely that, in recent years, the lectures were recordings that students were expected to watch before their tutorial. This is consistent with a blended learning format, which has become relatively common, especially since the pandemic.

On the surface, replacing recorded lectures with AI tutoring seems legitimate. There is no directly in-person component either way. However, students don't always react to our teaching initiatives in the way that we expect, and I'm sure that the reaction of Auckland students has taken the lecturers by surprise. This is clearly a cautionary tale, and it shows that AI tutors are more acceptable as a complement to good teaching, not as a substitute for good teaching.

The students' concerns are legitimate. Generative AI doesn't get everything right, and keeping an AI tutor on task is a real challenge. At least, that has been my experience so far with Harriet, our ECONS101 AI tutor. Harriet gets the important things right in her explanations, but she has a tendency to give the students too much information, and can send them down some interesting (but unnecessary for their learning) rabbit holes. I'm still trying to find an instruction set that optimises her behaviour. My students and tutors, through the feedback they are providing, are helping with that process. However, I don't see Harriet as replacing in-person or recorded lectures in the near future, or even replacing in-person tutorials. The human aspects of teaching are important. AI is another tool to support students' learning alongside that.

[HT: The most excellent Gemma Piercy-Cameron]