Can financial incentives help heavy drinkers stay sober?

Rational (and quasi-rational) decision-makers respond to incentives. If the costs of doing something go up, they tend to do less of it. If the costs go down, they tend to do more. And the reverse is true of benefits. Changing the costs and/or benefits of an activity therefore should be expected to change behaviour.

Does that logic extend as far as behaviours involving addiction and self-control problems? Consider alcohol consumption. Can heavy drinkers be incentivised to remain sober, at least temporarily, by increasing the costs of drinking, or increasing the benefits of not drinking? That is essentially the question addressed in this 2019 article by Frank Schilbach (MIT), published in the prestigious journal American Economic Review (open access).

Schilbach conducted a field experiment over three weeks with 229 cycle-rickshaw drivers in Chennai, India. In the experiment, the drivers were randomly split into three groups. The first group received a financial incentive to remain sober (the 'Incentive group'). The second group were paid an unconditional payment of similar magnitude (the 'Control group'). The third group got to choose between the sobriety incentives and the unconditional payment (the 'Choice group'). To receive their payment, the study participants had to report to the study office and submit to a breathalyser test. Schilbach was really interested in the effect of alcohol consumption on savings behaviour, so each research participant was offered the opportunity to save money at the study office each day. He was also interested in the effects on labour market participation and earnings, which were determined using surveys of the research participants.

The results reveal a number of important things about rational behaviour among heavy drinkers. First, the group that was given the choice between sobriety incentives and an unconditional payment demonstrated a strong demand for sobriety:

One-third to one-half of study participants chose sobriety incentives over unconditional payments, even when this choice entailed a potential or certain reduction in study payments...

One-third of the participants in the 'choice group' were willing to give up as much as 30 percent of their study earnings in order to be given the sobriety incentives. Schilbach isn't able to definitively determine why there was such high demand for sobriety, but he does note that:

First, study participants had significant experience with alcohol consumption and the potentially resulting self-control problems. The average study participant had been drinking alcohol for over a decade and many of them had been drinking (almost) daily...

Second, individuals perceived the costs associated with their drinking as significant. Many individuals expressed a strong desire to reduce their drinking in surveys and informal conversations. These men had spent substantial income shares on daily alcohol consumption for many years before participating in the study. Compared to these expenses, the forgone study payments due to the commitment choices may have appeared relatively small to individuals, especially if they implied a positive (perceived) chance of reducing subsequent alcohol consumption in the longer run.

So, the research participants may have perceived the experimental setting, and the money on offer, as a way to commit themselves to sobriety, at least for the period of the study. Did the incentives work, though? Schilbach finds that they did:

In the pre-incentive period, about one-half of the individuals in each of the three groups visited the study office sober. This fraction gradually declined in the Control Group to about 35 percent by the end of the study... In contrast, with the start of the incentivized period, sobriety in the Incentive and Choice Groups increased by about 10 to 15 percentage points. Subsequent sobriety at the study office also declined in these two groups, but the difference to the Control Group remained roughly constant.

Regression models confirm that the Incentive and Choice groups were approximately 13 percentage points more likely to visit the study office sober than the Control group, and the average breath alcohol content (BAC) was 2 to 3 percent lower for the Incentive and Choice groups than for the Control group (conditional on visiting the study office). Schilbach notes that the effect was largest on daytime drinking and not overall alcohol consumption, suggesting that many study participants simply shifted their drinking to later in the day (after visiting the study office).

Did sobriety affect labour market outcomes? Schilbach finds small and statistically insignificant effects on labour supply, hours worked, and earnings. As for savings, Schilbach found that the intervention increased savings, with the Incentive and Choice groups saving about 50 percent more than the Control group over the study period. Schilbach interprets this as showing that:

...increasing sobriety reduced self-control problems in savings decisions. An alternative interpretation could be that alcohol is a key temptation good for this population such that reducing alcohol consumption mitigates the need for commitment savings. However, given that the intervention only moderately reduced overall alcohol consumption and expenditures, this channel is unlikely.

My takeaway from this paper is that many heavy drinkers recognised their own self-control problems and were willing to give up some income for a commitment device that would help them remain sober. The commitment device increased the costs of drinking (or, equivalently, increased the benefits of not drinking). So, the drinkers who chose the sobriety incentives were acting rationally in response to a change in incentives. The research participants who shifted their drinking to later in the day were also acting quite rationally. By shifting their drinking to later in the day, they could receive the benefits of the sobriety incentive, while continuing to drink (albeit later in the day). In other words, the incentive changed behaviour, just not necessarily in the way it was intended to.

So, if you wanted to roll out a broader intervention based on changing incentives for heavy drinking, it might be better to measure sobriety at multiple times of the day. However, in this context even the later drinking may have reduced some of the potential alcohol-related harm, since there may have been fewer drunk-driving cycle-rickshaw drivers on the streets of Chennai (although, to be fair, the study doesn't actually show that there was less drink-driving).

It would be interesting to know how much of these study results are context-dependent, and whether a similar intervention would work elsewhere. If you tried to incentivise heavy drinkers in a high-income country to reduce their consumption, would they respond in a similar way? That question will have to wait for future research.

Egg prices will rise in New Zealand, even without a major avian flu outbreak

Last year, I posted about avian flu in the US and the impact on egg prices, noting that prices will rise. Thankfully there hasn't been a major outbreak of avian flu in New Zealand as yet, although it seems likely there will be soon. Domestic birds, such as chickens, are at risk, and as I noted in that earlier post, that affects the supply of eggs. And New Zealand egg suppliers are acting now, as the New Zealand Herald reported earlier this week:

It comes as New Zealand’s largest egg supplier Mainland Poultry, accounting for nearly 40% of the country’s eggs, is putting hundreds of thousands of free-range chickens into lockdown after the deadly bird flu virus was detected in the country last week.

Putting free-range chickens into lockdown will raise the costs of production for free-range eggs. The effect on the market for free-range eggs is shown in the diagram below. Before the chickens were locked down, the free-range egg market was in equilibrium, where demand D0 meets supply S0, with a price of P0 and a quantity of free-range eggs traded of Q0. The lockdown increases the costs of producing free-range eggs, which decreases supply to S1. This increases the equilibrium price of free-range eggs to P1, and reduces the quantity of free-range eggs traded to Q1.

Free-range eggs and colony eggs are substitutes. Once free-range eggs become relatively more expensive, some consumers will switch to colony eggs. The effect on the colony eggs market is shown in the diagram below. Before the change in the price of free-range eggs, the market for colony eggs was in equilibrium, where demand DA meets supply SA. The equilibrium price was PA, and the quantity of colony eggs traded was QA. Since some consumers switch to the relatively cheaper colony eggs, that increases the demand for colony eggs from DA to DB, increasing the equilibrium price of colony eggs from PA to PB, and increasing the quantity of colony eggs traded from QA to QB.

Overall, eggs are going to cost more, regardless of whether they are free-range eggs or colony eggs. And even without a major outbreak of avian flu. If avian flu does take hold in New Zealand, the price of eggs of both varieties will go up even further.

Are men's and women's soccer complements or substitutes?

Both my ECONS101 and ECONS102 classes touched on the subject of complementary and substitute goods this week (in different model contexts). Two goods are complements if consumers tend to consume them together. In that case, a decrease in the price of one good would increase the quantity that the consumer buys of both goods. Two goods are substitutes if consumers tend to consume one or the other. In that case, a decrease in the price of one good would increase the quantity that the consumer buys of the now-cheaper good, but decrease the quantity that the consumer buys of the other good (which is now relatively more expensive).

Often, it is easy to tell if goods are complements or substitutes. However, sometimes it is not straightforward. Consider the example of men's and women's soccer matches. Are they complements, or substitutes? If, when faced with the choice of whether to attend a men's or a women's soccer match, or both, fans tend to choose one or the other (and not both), then the matches are substitutes. On the other hand, if fans tend to go to both, then the matches are complements. Another way of thinking about this is that, when the price of one of the matches goes up, what happens to attendance at the other. So, if the ticket price for a men's soccer match increases and attendance at women's matches goes up, then they are substitutes, whereas if attendance at women's matches goes down, then they are complements.

Ultimately, whether men's and women's soccer are substitutes or complements is an empirical question. Fortunately, this 2025 article by Galila Nasser and Christian Deutscher (both Bielefeld University), published in the Journal of Sports Economics (open access), provides us with an answer. Or rather, they provide us with an answer in one particular context, which is German soccer.

Specifically, Nasser and Deutscher use data from the 2009/10 to 2018/19 seasons of the Frauen-Bundesliga, and look at the impact on match attendance when a Frauen-Bundesliga match is played on the same day as a men's Bundesliga match. They also consider whether the effect is larger when the overlapping men’s and women’s matches involve teams belonging to the same club. Their dataset contains 1,256 Frauen-Bundesliga matches, including 851 played on the same day as a men's Bundesliga match and 118 played on the same day as a match involving the men's team of the same club.

Controlling for the day of the week, week of the season, the weather, whether a UEFA Champions League match was also being played that day, and a variety of variables capturing the popularity of the match, Nasser and Deutscher find that there is:

...an approximately 15 percentage points decrease in attendance when women’s games coincide with men’s games on the same day.

A minor quibble with the paper is that when they say a 15 percentage points decrease, they really mean a 15 percent decrease. And the effect for matches played by the same club on the same day is somewhat larger, with attendance lower by about 16 percent. So, these results are consistent with men's and women's top-league soccer matches in Germany being substitutes (fans tend to go to men's or women's games, and not both). However, we can't conclude this for certain as the results are based on observational data so they are correlations, not causal. Nevertheless, Nasser and Deutscher conclude that:

For matches on the weekend, it is essential for clubs that have both men’s and women’s soccer teams in the first Bundesliga to avoid scheduling their matches on the same day.

Given that the seasons overlap substantially, and clubs in both leagues understandably want weekend matches, another option might be to make joint attendance at both men's and women's matches more attractive. Clubs with both men’s and women’s teams could offer a combined ticket covering matches played on different days, or even arrange occasional double-headers. As I note in my ECONS101 class, this sort of bundling can be an effective pricing strategy when there is heterogeneous demand across multiple products. Provided the variation in fans' willingness to pay for the ticket to the combined event is lower than the variation in fans' willingness to pay for the tickets separately, then bundling has the potential to increase total revenue overall. And that higher total revenue can then be shared between the men's and women's teams. Whether that would work here is another empirical question. Perhaps Bundesliga clubs could indulge us by running the experiment?

Farmers can't avoid high synthetic nitrogen fertiliser prices by switching to organic fertiliser

The New Zealand Herald reported yesterday:

New Zealand farmers face hefty increases in the price of fertiliser this spring as a result of the escalating US-Iran conflict and the war in Ukraine.

The Middle East plays a big role in the global fertiliser market because of its supply of natural gas and mineral resources.

Russia is also a major supplier of fertiliser.

Renewed hostilities in the Persian Gulf – and the virtual closure of the Strait of Hormuz – have driven oil prices up to about US$90 ($154) a barrel for Brent crude, the international benchmark.

Synthetic nitrogen fertiliser is generally manufactured from ammonia created using the Haber-Bosch process. This requires hydrogen, which is often derived from natural gas (mainly methane). Since the Middle East is a major supplier of natural gas, a lot of nitrogen fertiliser is manufactured in the Middle East. The current conflict in the Middle East is constraining the transport of nitrogen fertiliser from the Persian Gulf, reducing the supply of nitrogen fertiliser.

The effect of this on the market for nitrogen fertiliser is shown in the diagram below. The market was initially in equilibrium, where demand D0 meets supply S0, with a price of P0 and a quantity of nitrogen fertiliser traded of Q0. The Middle East conflict reduces shipping of nitrogen fertiliser, which decreases supply to S1. This increases the equilibrium price of nitrogen fertiliser to P1, and reduces the quantity of nitrogen fertiliser traded to Q1.

Can farmers avoid the higher price of nitrogen fertiliser by switching to an alternative product, such as organic fertiliser (compost, or manure)? Not really. Consider what happens in the market for organic fertiliser, shown in the diagram below. Before the change in the price of nitrogen fertiliser, the market for organic fertiliser was in equilibrium, where demand DA meets supply SA. The equilibrium price was PA, and the quantity of organic fertiliser traded was QA. Since nitrogen fertiliser and organic fertiliser are substitutes, and nitrogen fertiliser is now relatively more expensive (as shown above), farmers switch to the relatively cheaper organic fertiliser. That increases the demand for organic fertiliser from DA to DB, increasing the equilibrium price of organic fertiliser from PA to PB, and increasing the quantity of organic fertiliser traded from QA to QB.

So, the effect overall is that the price of both nitrogen fertiliser and organic fertiliser increase. Farmers cannot easily avoid high fertiliser prices. We can expect that to flow through into higher prices for farm produce, as well as lower profits for farmers.

Will generative AI mean the end of rational ignorance?

In this Substack post back in March, Andy Hall made the case for generative AI to create 'political superintelligence':

The more I work with and study AI, the more I believe it can give every human being on the planet access to a sort of political superintelligence, if we shape it right. And that intelligence, in turn, can make governments smarter and more effective, representatives more faithful, and institutions more responsive than anything we’ve built in over 2,000 years of experimenting with democracy.

Hall's post is worth reading in its entirety, but I want to explore a related point - will generative AI mean the end of rational ignorance for voters? Rational ignorance is the idea that it may be better for voters to not know what decisions policymakers are making on their behalf. That's because it's costly (in terms of time and effort) for voters to keep track of how the decisions that policymakers (and politicians) make on their behalf will affect them (economists call those monitoring costs). The benefit that a voter would receive by becoming informed of what policymakers (and politicians) are doing is relatively small, because their ability to change an election (and therefore policy) is very small. When the monitoring costs are greater than the benefits of being better informed, then voters would be better off not paying the monitoring costs. That is, voters would be better off not paying attention to what the policymakers (and politicians) are doing - the voters would be better off remaining rationally ignorant. This theory of rational ignorance was introduced in the 1950s by the late economist Anthony Downs.

Where does generative AI fit into this? Generative AI could meaningfully lower the monitoring costs for voters, as it gives the opportunity for voters to ask for quick summaries of policy proposals that may affect them. This will be even more effective as generative AI understands more about users' preferences. Moreover, agentic AI offers voters even greater opportunity to investigate what policymakers (and politicians) are doing, at relatively low cost.

When the monitoring costs decrease, then the rationale for voters to remain rationally ignorant weakens. We might expect voters to become more engaged with what the government is doing on their behalf, and to be more active in engaging with government to make their preferences known. Or, at least, maybe voters will delegate these activities to their favourite agentic AI model.

There are, of course, some reasons for caution. Generative AI might reduce the cost of obtaining political information without reducing the cost of checking whether that information is accurate or unbiased. Moreover, an overly sycophantic generative AI that knows the voter's preferences might reinforce the voter's existing views rather than challenging them. So, perhaps generative AI simply moves the monitoring costs from monitoring the government to monitoring the generative AI?

Hall makes the point that political superintelligence has the potential to increase the quality of governance. If generative AI enables voters to become better informed at low cost, it could strengthen political accountability. Policymakers (and politicians) who know that voters can easily scrutinise their decisions may be less willing to act against voters’ interests, or may face greater consequences when they do.

We may not have political superintelligence yet, and large numbers of voters may still be rationally ignorant. However, it may not be long before we start to see some substantive changes in the political process, driven in part by the emergence of generative AI.

[HT: Marginal Revolution for the Andy Hall post]

Could prosecuting STI transmission increase infections?

In my ECONS102 class this week, we covered unintended consequences - where an incentive is created that works against what was originally intended. One of my favourite examples is the familiar (but possibly apocryphal) story about cobras in Delhi, as I noted in this 2015 post:

The government was concerned about the number of snakes running wild (er... slithering wild) in the streets of Delhi. So, they struck on a plan to rid the city of snakes. By paying a bounty for every cobra killed, the ordinary people would kill the cobras and the rampant snakes would be less of a problem. And so it proved. Except, some enterprising locals realised that it was pretty dangerous to catch and kill wild cobras, and a lot safer and more profitable to simply breed their own cobras and kill their more docile ones to claim the bounty. Naturally, the government eventually became aware of this practice, and stopped paying the bounty. The local cobra breeders, now without a reason to keep their cobras, released them. Which made the problem of wild cobras even worse.

Just because the consequences of a policy are unintended, that doesn't necessarily mean that they are unforeseen. Sometimes, we can anticipate what will go wrong with a particular policy. And it's not just policies that can go wrong. Any change in costs or benefits that alters people’s incentives can produce unintended consequences. As an example, consider this recent article in The Conversation by Bridget Haire and David Carter (both University of New South Wales):

In an Australian first, a Canberra man has been convicted for giving genital herpes to a sexual partner...

This recent case represents a significant expansion of criminal law into sexual health. It sets an unhelpful legal precedent, and undermines successful public health messages.

Decades of research have concluded that prosecuting disease transmission doesn’t reduce infection and may make things worse...

But criminalising transmission can create perverse incentives not to seek medical care and treatment. If a person genuinely doesn’t know their status, it can be more difficult to prove “reckless” transmission.

The intuitive case for punishment is especially strong in this case: the man knew his status, denied having an STI when directly asked, and repeatedly had unprotected sex with his partner. However, the punishment itself will change incentives for other people.

Ideally, we want people to know their STI status. For curable STIs, diagnosis enables treatment. For example, for infections such as herpes, it allows people to use medication and other precautions that reduce the risk of further transmission.

At one level, it makes sense to punish people who knowingly infect others with an STI. That creates a strong disincentive to transmit STIs to other people. However, criminalising STI transmission also reduces the incentive to get tested, because a person not knowing that they are infected might be able to use their lack of knowledge of their infection status as a defence in a criminal case. So, we might expect that fewer people would get tested for STIs. So, on the one hand there are disincentives to transmit STIs, but on the other hand there are disincentives to find out whether you are infected with an STI, which leads to move STI transmission. If the latter effect is larger, then overall there could be higher prevalence of STIs and greater incidence of new infections.

And so, rather than reducing STI infections, criminalising those who transmit STIs may have the unintended consequence of increasing STI infections overall.

Why rising honey prices may increase kiwifruit orchard costs

This week, my ECONS102 class covered rational behaviour, one aspect of which is the cost-benefit principle: that when evaluating mutually exclusive alternatives, a rational decision-maker will choose the alternative that offers the greatest net benefit (the greatest difference between benefits and costs). So, it was interesting to see a good example of this in The New Zealand Herald just last month:

There’s growing competition for beehives as honey prices sweeten again and kiwifruit orchards continue to grow...

[Beekeeper Liam Gavin] said renewed confidence in honey production is seeing some pivot away from pollination.

“I sort of describe it as the tug of war between honey and pollination.

“Both are needing more beehives. So which one, where are they going to go? And that’ll all be down to, like, region-specific [stuff], and what people like to do in terms of how they beekeep.”...

With honey prices coming back up, [New Zealand Kiwifruit Growers Incorporated chief executive Colin] Bond expected more beekeepers would prioritise honey over pollination, which would create a challenge for kiwifruit growers.

Beekeepers can position their hives primarily to generate income from honey production, or primarily to generate income by providing pollination services. Thus, for a particular hive at a particular time, honey production and paid pollination are mutually exclusive alternatives.

A rational beekeeper, applying the cost-benefit principle, would compare the expected net benefit from using their hives for pollination with the expected net benefit from using them for honey production. That comparison would include pollination fees, expected honey revenue, transport and feeding costs, risks to hive health, and other relevant costs and benefits. As honey prices increase, the opportunity cost of committing hives to pollination increases. Ceteris paribus (holding all else constant), as honey prices increase fewer hives will be offered for pollination.

So, if kiwifruit growers (and other farm and orchard businesses that depend on pollination) want to secure enough hives for pollination, they will probably need to offer higher pollination fees. That would raise their pollination costs and, consequently, their overall orchard operating costs.

Two new studies on who works from home, and its mental health impacts

The pandemic caused a massive rise in working from home and now, even though lockdowns are long since over and many workers have returned to the workplace, we are beginning to understand working from home (WFH) a lot better. Two new studies have recently added to our understanding.

The first is this article by Cevat Giray Aksoy (European Bank for Reconstruction and Development) and co-authors, published in the AEA Papers and Proceedings (ungated earlier version here). They use data from the monthly US Survey of Working Arrangements and Attitudes, limiting their data to the period from January 2024 to December 2025, and document three facts about WFH. First, employees are more likely to work from home if they work for a younger firm, and peaks among those working for employers that were founded in the height of the pandemic, in 2020.

Second, employees are more likely to work from home if they work at a firm with a younger CEO. Specifically:

Firms led by CEOs under 30 have an average of 1.4 WFH days per week, compared with 1.1 days at firms led by CEOs who are 60 or older.

That doesn't seem like a lot, but an additional 0.3 days per week is a little more than three working weeks per year of WFH for those working for the youngest CEOs compared with those working for the oldest. However, this relationship between CEO age and WFH appears to be partly explained by the fact that younger CEOs are more likely to be leading younger firms. When Aksoy et al. put both CEO age and firm age in the same regression model, only firm age remains statistically significant. It is a similar story for CEO gender, which is initially statistically significant, but since female CEOs tend to be younger and to be CEOs of younger firms, CEO gender isn't statistically significant once those other variables are controlled for.

Third, the self-employed are much more likely to work from home. Specifically:

Self-employed workers report two to three times as many WFH days per week as wage and salary employees, depending on employer size. Compared to wage and salary employees, the self-employed are more than three times as likely to work in a fully remote capacity.

This last result is not entirely surprising, given that the self-employed typically have a lot more flexibility over scheduling. And, the self-employed may be the type of people who most value flexibility as well.

The second new article is this one by Natalia Emanuel (Federal Reserve Bank of New York), Emma Harrington (University of Virginia), and Amanda Pallais (Harvard University), published in the prestigious journal Science (open access). They look at the mental health impacts of WFH, using US data from a variety of sources, and a difference-in-differences approach. This involves comparing occupations that are more or less amenable to WFH, between the time before the pandemic and the time after the pandemic. They refer to the occupations that are more amenable to WFH as 'remotable'.

Emanuel et al. first document the dramatic rise of WFH:

The pandemic led to a large increase in remote work for those in remotable jobs, such that by 2024, workers in remotable jobs spent 31.1% of workdays fully remote, whereas people in nonremotable jobs spent only 8.9% fully remote... Those in remotable jobs experienced a 17.9 percentage point (pp) differential increase in fully remote work...

They then show that this rise is associated with more time spent alone:

Along with spending less time in the office, workers in remotable jobs spent more time working alone after the pandemic, logging 1.2 more work hours alone per day relative to nonremotable workers (58.0% increase; P < 0.0001).

Even for those of us who are introverts, more alone time may not necessarily be a good thing. Emanuel et al. are concerned about how WFH and working alone affects mental health. Their main outcome variable is the Kessler (K-6) Psychological Distress Scale, which is:

...based on how often in the past 30 days the respondent felt worthless, hopeless, restless, nervous, that everything is an effort, or so sad that nothing could cheer them up...

Their main source of data is the Panel Study of Income Dynamics covering the period from 2011 to 2023 (from which they exclude the pandemic years 2020 and 2021). Analysing that data, they find that:

Between the pre-and postpandemic periods, mental distress increased for everyone, but it increased significantly more for those in remotable jobs...

Among those in remotable jobs, there was a 0.3 unit increase in the K-6 distress score relative to an average score of 3.0 before the pandemic (standard deviation change = 0.08; P = 0.063) in the Panel Study of Income Dynamics (PSID). In the National Health Interview Study (NHIS), we found the same 0.3 unit deterioration (P = 0.007). We saw deterioration in each of the six subcomponents of the K-6 distress scale: feeling worthless, hopeless, restless, nervous, that everything is an effort, and so sad that nothing can cheer them up...

Importantly, the deterioration in mental health is concentrated among people living alone, which is consistent with the idea that WFH affects mental health through increasing social isolation. Emanuel et al. also find that people in remotable jobs are more likely to seek help from a mental health practitioner, and take relatively more prescription medications for mental health conditions such as anxiety or depression. These changes aren't simply the result of greater flexibility allowing more time to be devoted to health care generally, as there was no change in visits to the doctor and no change for other prescription medications such as statins.

Finally, Emanuel et al. looked at whether the rise of generative AI, rather than the increase in WFH, might explain the results (an important check, given the paper I will blog about tomorrow). They find that results from the same analysis, but substituting an AI occupational exposure index in place of the 'remotability' index, are not statistically significant.

Now, many workers are very keen on WFH - as noted in this post, about half of Australian workers would be willing to give up some salary in order to work from home. Why would people choose more WFH if it may worsen their mental health? Of course, a rational worker would weigh up the benefits and costs of WFH, and may decide that the mental health costs are more than offset by other benefits. However, Emanuel et al. point to another related possibility, which is:

...that the benefits of remote work (e.g., skipping a daily commute) are immediate and salient, whereas the costs of remote work (e.g., frayed connections with co-workers) take time to materialize.

So, a rational worker may be essentially weighing up benefits that occur today, against uncertain costs that may occur sometime in the future and therefore should be discounted (in the same way that we should discount future cashflows in a financial analysis). In that sort of exercise, where the mental health costs are discounted, it is more likely that workers would choose to work from home. They would be even more likely to do so if they are quasi-rational and heavily discount the future, as I note in the first week of my ECONS102 class. In that case, the mental health costs would be heavily discounted. Finally, maybe workers are simply unaware of the mental health costs of WFH. If that is the case, then an information intervention might be helpful in improving mental health among workers who would otherwise be WFH. In the meantime, this research suggests that the post-pandemic rise in WFH may have contributed to some part of the growing mental health crisis, especially through increased time spent alone.

[HT: Marginal Revolution for the Emanuel et al. article]

Read more:

• Remote work, wages, and compensating differentials
• Willingness-to-pay for working from home

Two papers show the bad, and some good, of rent control in San Francisco

I have been talking with my ECONS101 class this week about rent controls, which is a topic that I have blogged about many times before (see the links at the end of this post). Economists really dislike rent controls, sometimes in deliberately hyperbolic terms. In one prominent case, the Swedish economist Assar Lindbeck was quoted as saying:

“Rent control appears to be the most efficient technique presently known to destroy a city—except for bombing.”

Lindbeck's statement is based on the evidence that shows the negative impacts of rent controls. One example is described in this 2025 article by Eilidh Geddes (University of Georgia) and Nicole Holz (Northwestern University), published in the Journal of Housing Economics (ungated earlier version here). They looked at the impact of a large-scale rent control expansion in San Francisco in 1994, which removed an exemption from rent control for small (less than five units) owner-occupied buildings built before 1980, on evictions.

Their data are the number of eviction notices, as well as wrongful eviction claims and 'owner move-in' eviction notices at the zip code level, from 1990 to 2010. They apply a continuous treatment difference-in-differences, which essentially compares the change in evictions (or other measure) between zip codes that were more affected by the removal of the exemption and those that were less affected. Their measure of exposure to the treatment is the number of housing units in the zip code that became exposed to rent control policies after the passage of the voter referendum in late 1994. In zip codes where more housing units were affected by the change, we would expect to see greater impacts than in zip codes where fewer housing units were affected. One limitation of this is the data source that Geddes and Holz use, which is based on building data from 1999, five years after the change was implemented. However, they show that three main sources of problems (demolition of buildings between 1994 and 1999, splitting of land parcels, and construction that changed the number of units in each building), do not have much impact on the estimated number of units affected (and so, don't have a large impact on the treatment variable).

In their main analysis, Geddes and Holz find:

...an 83% increase in eviction notices filed with the Rent Board and a 125% increase in the number of wrongful eviction claims for ZIP codes with the average level of new exposure to rent control...

These effects are large and economically significant. We find an annual effect of an increase of 20.07 eviction notices per 1000 treated units in a zip code. Over the six years in our post period (1995–2000), this translates roughly into 12% of newly rent controlled units receiving an eviction notice.

So, the expansion of rent control leads to an increase in evictions. Geddes and Holz also find that the effects:

...are concentrated in low-income areas. These areas are not necessarily those that saw the largest increases in aggregate rents during the 1990s, suggesting that landlords may be more willing to engage in eviction activity in places where there are fewer resources to fight that behavior.

Geddes and Holz caution against taking a broad interpretation of their results though, as the removal of the exemption in 1994 primarily affected small landlords, who are often 'mom and pop' landlords and are able to take advantage of 'owner move-in' eviction provisions that are not available to large corporate landlords. However, the results are consistent with the broader literature, which suggests that tenants may be negatively affected by rent controls.

But not in all ways, it appears. In a more recent article published in the Journal of Health Economics (open access), Geddes and Holz look at the impact of the same 1994 expansion of rent control in San Francisco on intimate partner violence (IPV). They first note that that the effect of rent control on IPV is theoretically ambiguous, and there are two competing models with different predictions:

In the financial strain model, lower housing costs will decrease financial stress, leading to lower levels of violence. The effect of housing policies will thus depend on whether they lower costs for couples. However, in a bargaining model, there is a crucial distinction between policies that shift housing costs overall and those that shift the relative costs of housing inside and outside of the relationship. Policies that decrease housing costs overall will change the amount of resources in the relationship to be bargained over, but will not shift the bargaining power in the relationship. However, policies that decrease housing costs inside the relationship relative to those outside of the relationship will change the attractiveness of the outside option, shifting bargaining power away from the woman.

The empirical setup in this research is the same as for their earlier research on evictions. The difference is that the outcome variable of interest is IPV, measured as:

...the number of hospitalisations resulting from assaults that comes from California’s Department of Health Care Access and Information (HCAI, formerly OSHPD) from 1990–2000.

In their main analysis, Geddes and Holz find that:

...for every one percent increase in exposure to rent control in a ZIP code, hospitalized assaults on women decline by 0.08 percent. In levels, this translates to an almost 10 percent decrease in violence against women for the average ZIP code.

They find no corresponding decrease in assaults on men, which suggests that their results are not driven by an overall decline in assaults (including non-IPV assaults). They also find no effect on reported accidents, which suggests that their results are not driven by changes in the propensity to report IPV. Interestingly, they also find:

...no evidence of changes in household size or composition, suggesting that our results are driven by changes in violence within relationships rather than changes in cohabitation or relationship dissolution.

Overall, their results are most consistent with the financial strain model of IPV. Based on that model, we interpret these results as showing that rent controls, by reducing housing costs (and it is worth noting that housing costs in San Francisco are, and have been for some time, very high), decrease conflict within intimate relationships, and decrease IPV.

So, at least there is some evidence for positive effects of rent control. These results also sit alongside earlier evidence from the same rent control expansion, which showed short-run gains for incumbent tenants, but long-run reductions in the supply of rental housing units, as well as an increase in inequality. However, few people are advocating for rent control policies in order to reduce intimate partner violence. And benefits in terms of reduced violence have to be weighed against all of the other negative consequences of rent control policies, many of which are outlined in the posts linked below.

Read more:

• Why rent controls have worse effects over longer time horizons
• The deadweight loss of rent control
• The deadly consequences of rent control in Mumbai
• Rent control and inequality in San Francisco
• Rent control and the redistribution of wealth
• Rent control and vacant properties in India
• Rent control according to Seinfeld
• There should be no debate at all about rent controls
• Rent controls make many tenants worse off in the Netherlands

The supply-side story behind falling meth prices in New Zealand

Chris Wilkins, Marta Rychert, and Robin van der Sanden (all Massey University) wrote an article in The Conversation last month about the price of methamphetamine:

Methamphetamine has become dramatically cheaper over the past seven years, even as authorities report record seizures, according to the latest New Zealand Drug Trends Survey.

The annual online survey of over 8,800 people who use drugs shows wholesale prices of the illegal and harmful substance (per gram sold to dealers) have fallen by 41%, while street-level “point” prices (0.1 gram retail deals) have dropped by 27%.

The decreasing price of meth is not a new phenomenon. In fact, I wrote about it last year. Wilkins et al. try to tease out the reason underlying the decreasing price. Based on a simple supply and demand model of the market for meth, there are two main possibilities: an increase in supply, or a decrease in demand. Wilkins et al. go through a number of plausible factors on both sides of the market, dismissing each in turn, including:

• sellers feeling that there is less risk of arrest (which would increase supply), but Police report record seizures, which Wilkins et al. argue seems to rule that out;
• less strict enforcement by Police against people found with small quantities of drugs (which would increase supply, but probably demand as well), but that wouldn't affect large sellers;
• decreasing production costs (which would increase supply), but production costs only make up a fraction of the street price; and
• a decrease in buyers (which would decrease demand), but wastewater data suggests that meth consumption has increased.

The last point, that meth consumption has increased alongside the decrease in price, points strongly to an increase in supply as the main change. That doesn't rule out a change in demand, but the increasing consumption tells us that the increase in supply must be greater than any possible decrease in demand. But if it isn't lower risks of arrest, weaker enforcement, or decreasing production costs, that is causing supply to increase in the New Zealand meth market, then what is? Wilkins et al. point to:

...new global sources of methamphetamine supply.

New Zealand and Australia have traditionally sourced methamphetamine from lawless regions of Asia known as the Golden Triangle. More recently, however, growing seizures have been linked to Mexican drug cartels, often transiting through Canada.

Australian authorities say these cartels can supply methamphetamine at less than one-third the price of Asian producers and that about 70% of seized meth now originates from North America.

It may also explain the rising supply of cocaine in New Zealand, with Mexican cartels deeply involved in global cocaine trafficking.

So, new sources of meth have increased the supply, decreasing the equilibrium price, and increasing the quantity of meth traded in the New Zealand market. Wilkins et al. also point to competition:

On top of this, digital drug markets – including darknets and social media sales – may be lowering the cost of finding alternative sellers and better deals, increasing competition and pushing prices down.

Economists often think of competition as a good thing. However, in the market for illegal drugs, that might not necessarily be the case. How can government best respond? Fighting the supply side of the market alone is unlikely to be successful, as I have noted before. The increased supply from new sources make this even more challenging. A renewed focus on reducing demand is necessary as well, and would likely be much more effective in the long run.

Read more:

• Police are not winning the P war - they need to focus on demand
• Evidence that the supply of methamphetamine is increasing
• The coronavirus lockdown and the New Zealand market for illegal drugs
• The increase in methamphetamine use in New Zealand has been driven more by supply than demand

The Strait of Hormuz blockade, trade passes in the Panama Canal, and the cost of imported goods

The New Zealand Herald reported last month:

The war in the Middle East has boosted demand to move vital cargo through the Panama Canal to such an extent that one vessel carrying liquefied natural gas (LNG) paid US$4 million ($6.7m) to skip the line and avoid a wait that can take up to five days, according to an official report.

A surge in such payments has been recorded since the US-Israeli attacks on Iran began February 28, which led to the blockade of the Strait of Hormuz, a critical waterway for one-fifth of the world’s oil and natural gas exports from Gulf countries.

The impact on the price of transits through the Panama Canal is shown in the diagram below. Before the Strait of Hormuz was blockaded, the market for Panama Canal transits was in equilibrium, where demand DA meets supply SA. The equilibrium price was PA, and the quantity of transits was QA. The blockade increased the demand for Panama Canal transits from DA to DB, increasing the equilibrium price of transits from PA to PB, and increasing the quantity of transits from QA to QB.

This increase in the price of Panama Canal transits doesn't just affect the cost of transporting oil or natural gas. Other ships must also pay the higher price. That increases the cost of shipping, which will flow through to the prices of imported goods, as shown in the diagram below. The market was initially in equilibrium, where demand D0 meets supply S0, with a price of P0 and a quantity of imported goods traded of Q0. The higher cost of Panama Canal transits increases the 'costs of production' of imported goods, which decreases supply to S1. This increases the equilibrium price of imported goods to P1, and reduces the quantity of imported goods traded to Q1.

So, it's not just oil and natural gas prices that will be pushed up by the blockade of the Strait of Hormuz. The resulting higher shipping costs will flow through to all sorts of other goods that are traded internationally and require shipping, including and especially those passing through the Panama Canal.

Changing their minds could be a good thing for economists

People don't like to change their minds. This may partly be an expression of loss aversion - we really want to avoid losses, including the loss of an idea that we previously thought was true. This leads to status quo bias - we prefer not to change things, and keep them the same, because changing things entails a loss. But what if changing our minds could make us better off? Would we be so reluctant to do so?

This 2025 paper by Matt Knepper (University of Georgia) and Brian Wheaton (UCLA) suggests that economists, at least, should not be afraid to change their minds, because doing so increases the number of citations to their research. Knepper and Wheaton investigate authors who undergo an 'ideological reversal' - previously publishing research that could be considered right-wing, before switching and publishing a paper that draws a left-wing-consistent conclusion, or the reverse (switching from left-wing to right-wing). Their main data source is every economics paper ever published in the top 100 economics journals indexed in Web of Science - some 200,000 articles. They also have a narrower dataset of papers referenced in meta-analyses on policy topics, including:

...the minimum wage, the economics of unions, the taxable income elasticity, the fiscal multiplier, intergenerational transfers, trade and productivity, trade and domestic employment, crowd-out, the gender wage gap, unemployment insurance, disability benefits, universal preschool, childcare and employment, immigration and wages, and more.

Knepper and Wheaton use this narrower dataset to train a machine learning model to categorise the rest of the papers in the dataset, as to how left-wing (or right-wing) the conclusions are. For instance, a paper that concludes that the minimum wage reduces employment is more right-wing, whereas one that concludes that there is no disemployment effect of the minimum wage is more left-wing. Knepper and Wheaton define an author as left-wing if they published more left-wing papers than right-wing ones over the previous five years, and the reverse for right-wing authors. They then use the larger dataset to investigate what happens to each economist who undergoes an 'ideological reversal'. They first outline some descriptive facts based on their dataset, including:

• Fact #1: The typical author mostly publishes results on one side of the political spectrum.

• Fact #2: Ideological reversals are not rare; they occur at least once for 40% of authors.

• Fact #3: Ideological reversals become much more common later in an author’s career, with authors essentially never undergoing a reversal in the first decade of their career.

• Fact #4: Most ideological reversals do not represent a permanent defection to the other side of the political spectrum, but rather the beginning of repeatedly publishing results on both sides of the spectrum.

• Fact #5: Ideological reversals occur much more frequently amongst authors who are (initially) classified as right-wing.

That does seem like a surprisingly high proportion of economists who undergo at least one ideological reversal. However, perhaps we should take comfort in that - if the results point in a particular direction, our conclusions should say that, even if that conclusion is inconsistent with our previous conclusions on the same topic.

Do these ideological reversals matter though? Knepper and Wheaton employ a difference-in-differences analysis, comparing the difference in citations (and other metrics) between authors who did, and did not, undergo an ideological reversal, between the time before, and after, the reversal occurred. In other words, they look at whether citation counts rise more for economists who have an ideological reversal than for otherwise similar economists who do not. The results are striking, with:

...a sharp clear increase in citation count following an ideological reversal with essentially no evidence of pre-trends... The citation boost accumulates to approximately 9 over a one-decade period and 30 over a two-decade period.

The results remain consistent when Knepper and Wheaton limit the analysis to papers published before the ideological reversal, and when they limit the analysis to papers in the meta-analysis only (showing that the machine learning approach doesn't drive the results). Knepper and Wheaton also find evidence consistent with no change in the quality of papers before and after the ideological reversal, and that:

Both left-to-right and right-to-left reversals are rewarded by increased citations of roughly the same magnitude. The boost in citations received subsequent to a left-to-right reversal is mostly driven by citations from right-wing authors, and the boost in citations received subsequent to a right-to-left reversal is mostly driven by citations from left-wing authors. Encouragingly, however, the new right-wing (left-wing) audience garnered by a left-to-right (right-to-left) reversal... also engages with and cites the author's previous left-wing (right-wing) papers. This dynamic suggests that ideological reversals help prevent the formation of echo chambers in economics academia and expose authors to opposite ideological findings.

This last result is particularly important, and I believe it allows us to conclude that economists need not fear ideological reversals. In doing so, they can attract a new audience from the other side of the ideological spectrum, bringing the two sides closer together. Hopefully through that, we end up with higher-quality research overall.

[HT: Marginal Revolution, last year]

Anticipating higher future petrol prices, consumers actually push up petrol prices now

In his 1984 book The Evolution of Cooperation, Robert Axelrod suggested that people cooperate in repeated games because of 'the shadow of the future'. They alter their behaviour by cooperating now, because they anticipate that will lead to greater gains for them in the future. I really like this analogy of the shadow of the future affecting our decisions now, and not just in the context of game theory and repeated games. In fact, we've seen it play out in a different context this past week, as reported by the New Zealand Herald:

Kiwis are rushing to fill up their cars across the country amid fears of price increases at the pump because of escalating conflict in the Middle East.

Video sent to the Herald of Waitomo Tinakori petrol station in Wellington today showed a queue of cars waiting for fuel, with vehicles spilling out on to the road.

Waitomo Group CEO Simon Parham said there has been a similar increase in demand at stations across the country, with sales increasing by 10-15% this week.

“People are filling up and filling their cars ahead of the price increase that will flow through the market over the coming weeks because of the Iran conflict,” he said.

To see what is going on here, let's consider the retail market for petrol, as shown in the diagram below. Before the current conflict in the Middle East, the equilibrium price of petrol was P0, and Q0 petrol was traded per week. Then the conflict begins. Consumers anticipate that the price of petrol will increase in the future, so they decide to fill up their vehicles now. That increases the demand for petrol from D0 to D1. The equilibrium price of petrol increases to P1, and there is Q1 petrol traded in the week. 

Notice that by trying to avoid the high petrol price in the future, the consumers cause the price to rise today, which is exactly the outcome they were trying to avoid! In effect, when consumers rush to fill up early, they bring some of the future price pressure forward into the present. Expectations about future prices can cause self-fulfilling prophecies like this, which is a point I will make in my ECONS101 class in several weeks, when we talk about financial markets (where self-fulfilling prophecies are a clear and present danger at all times). The shadow of the future matters - consumers' actions based on trying to avoid future price rises make those price rises happen now instead.

Tuition fees, incentives, and 'ghost students'

When the New Zealand government introduced 'first-year fees free' in 2018, the universities expected a big uptick in student numbers. It didn't happen (as I discussed in this 2023 post). As the figure below (source) shows, the mild downward trend in domestic student numbers (equivalent full-time students, or EFTS) continued for at least a couple of years past 2018:

My colleagues were worried that we would see an increase in the number of students who enrol, and then do nothing at all (what we call 'ghost students'). My impression was that this didn't happen, but until now I never looked intentionally at the numbers. However, the figure below shows the proportion of each of my A Trimester ECON100 classes (up to 2017) or ECONS101 classes (for 2018 onwards) that were ghost students (I didn't teach the class in 2022, which is why there is no observation for that year). Here, I define a 'ghost student' as any student who didn't attempt any of the tests or exams (although they may have attended some classes during the trimester). In each trimester, the class had between 250-350 enrolments in total. [*]

As the figure shows, there was a big jump in 'ghost students' in 2021, but that is attributable to the COVID pandemic and the weirdness of that whole time period, rather than anything to do with fees-free. In most years, somewhere between three and five percent of students are 'ghosts'. In 2025, the government shifted from first-year fees free to final-year fees free. There's no evidence that change affected the proportion of 'ghost students' either. Or it's too early to tell - the proportion in 2025 was lower than either of the previous two years.

Why might we expect the changes in fees to affect the number of 'ghost students'? It comes down to incentives. As my ECONS101 students will hear next week, when the cost of something decreases, we tend to do more of it. First-year fees free decreased the cost of being a 'ghost student', so ceteris paribus (holding all else constant), we would expect to see more 'ghost students'. Final-year fees free (with first-year fees reintroduced) increased the cost of being a 'ghost student', so ceteris paribus, we would expect to see fewer 'ghost students'. The fact that didn't happen is interesting, and we'll come back to that a bit later.

To see why the New Zealand effect might be negligible, it helps to compare with a setting where student status comes with larger immediate benefits. To do that, I want to discuss this recent article by Johannes Berens (RH Köln), Leandro Henao, and Kerstin Schneider (both University of Wuppertal), published in the journal Labour Economics (ungated earlier version here). They look at the impact of the removal of tuition fees in North Rhine-Westphalia in Germany in 2011. Tuition fees were a very modest EUR500 per year (for every year of study), and Berens et al. essentially compare students who were more or less affected by the policy (depending on how many years they didn't have to pay fees for), looking at a range of academic outcomes including exam registrations and withdrawals, credit points earned, grades, and dropout probabilities, as well as the number of 'ghost students'.

Their data come from a single university, with over 11,000 students who first enrolled between 2008 and 2011. The students in the 2008 cohort would have graduated before the fees were removed, while those in the 2011 cohort would not have faced any fees at all. The other cohorts would have had fees in their later year/s, but not earlier year/s. Applying a difference-in-differences approach, Berens et al. find that:

...abolishing tuition fees significantly affected student behavior and academic outcomes. Active students reduced their academic performance by 1.7 credit points per semester (12 % relative to baseline), despite maintaining similar exam registration patterns... Additionally, the reform increased the prevalence of ghost students by 10 percentage points...

So, removing fees in this context substantially increased the proportion of 'ghost students' by 10 percentage points, from a baseline that was already over 10 percent (Berens et al. present the data by study semester, and the 'ghost student' proportion varies between 10 percent and 20-25 percent, depending on year and study semester).

What explains the high impact of removing fees in Germany? Berens et al. highlight the role of incentives, and in particular the generous nature of public assistance available to students. Specifically:

...student status confers substantial benefits, generally independent of academic performance... These benefits include subsidized health insurance (until age 25), state-wide public transport access (worth EUR 2900 annually), and parental child allowance (EUR 2450 annually). About 16 % of students also receive need-based grants averaging EUR 6800 annually...

So, being classified as a student can be quite lucrative in Germany, even if the student is a 'ghost'. That might also explain the lack of effect of first-year fees free in New Zealand. While the fees are higher in New Zealand than in Germany, being a student in New Zealand is hardly a pathway to great riches (at least, not during the time spent as a student - see this post, and the links at the end of it). The student allowance is not very generous, and while there are some other perks to being a student, cheap movie tickets and public transport are not exactly worth a lot of money. So, it shouldn't be much surprise that the impact in Germany was much larger than for a similar policy change in New Zealand.

Another reason that the impact was not apparent in New Zealand could be that many students do not pay their tuition fees immediately. Instead, many (perhaps most) students' tuition fees are paid by student loans. 'Student Greg' is probably quite content to say that the student loan is 'Graduated Greg's' problem, and not worry about it today. So, from the perspective of 'Student Greg', first-year fees free doesn't really impact the decision to become a student or not. It doesn't change the costs of being a student for 'Student Greg', because they don't consider paying back the student loan as part of the costs of studying today. [**] And that might explain why there was no incentive effect of first-year fees free in New Zealand (also, fees-free papers are not free if students fail them, as I noted in this 2023 post).

The incentives in Germany and New Zealand, when the tuition fees were changes, resulted in quite different impacts. In Germany, where the benefits of being a student were higher, lower costs of being a 'ghost student' induced many people to enrol, whereas in New Zealand, where the benefits of being a student are lower, and the costs of tuition are typically deferred to the future, lower costs of being a 'ghost student' appear to have made no difference.

The nature of incentives, and the costs and benefits around the decision, definitely matter. The policy takeaway from this is that tinkering with fees alone may induce more (or less) 'ghost students', so the other immediate benefits and costs associated with student status also need to be considered. 

*****

[*] The data are for only one paper, but ECON100 and ECONS101 have been, for the most part, compulsory papers for business students. In a couple of years, some students could avoid the paper by taking all of the other first-year business papers. However, unless 'ghost student' status was more likely for students who did not take first-year economics, these results should be broadly representative.

[**] Essentially, 'Student Greg' is heavily discounting the future. In my ECONS102 class, we say that 'Student Greg' exhibits present bias, and is therefore only quasi-rational, not purely rational. Of course, not all students will have acted like 'Student Greg', but if enough of them did, that would explain the lack of incentive effects of the changes in first-year fees.

Distillers don't need tax relief in order to promote their goods internationally - they already have it

Earlier this week, the NBR reported (paywalled):

Kiwi distillers are calling on the Government to introduce an excise tax rebate scheme, arguing the current system is stifling an industry that could follow wine's path from obscurity to international recognition...

The proposal requests an excise duty remission of up to $350,000 annually for each distillery, which would free up funds that could be put towards employment, expansion, and export growth.

In order to be eligible for the DSA proposed scheme, distillers would need to hold a license to manufacture distilled beverages, produce at least 70% of its alcohol content (by volume) within New Zealand, be independent, and be a member of DSA.

The proposal is modelled on Australia's excise remission scheme, which allows domestic distilleries to claim up to A$400,000 ($469,600) a year...

On the outskirts of Auckland, Pōkeno Whisky's Johns estimates about 35% of his company's domestic revenue goes toward tax. He says he holds four roles at New Zealand's largest single malt distillery – running sales, marketing, operations, and general business – but doesn't pay himself. He has halved distillation over the past 18 months because times are tough, and is investing what he can into sales and marketing in an attempt to buck the trend.

"At the end of the day, we're not selling Pōkeno Whisky overseas. We're selling brand New Zealand."

Bluff Distillery's Nash says while a spirits tax made sense historically, the system was overweighted and out of date. He says a lot of distillers that could have explored international markets haven't been able to because the lion's share of returns go toward excise.

The first thing to note is that the excise tax paid by domestic distillers is not a big money-spinner for the government. The article reports that domestic distillers pay about $23 million in excise each year. That is small relative to the overall $800 million in total alcohol excise tax collected each year (see here). The purpose of an alcohol excise tax is to reduce the consumption of a good that has negative externalities - it is an example of a Pigovian tax. Reducing excise tax would lower the price that consumers pay for alcohol, increasing consumption, and increasing the negative externalities associated with alcohol consumption. That is not a proposal that should receive broad support.

Now, I was thinking about this and I had a better idea that would give some excise tax relief for distillers, without increasing alcohol-related harm in New Zealand: zero-rate the excise tax for exports. In other words, distillers would pay excise tax only on products that they sell domestically, and not on exports. If the argument by the distillers (as noted by Matt Johns of Pōkeno Whisky in the quote above, is that they want to explore international markets, then this proposal lets them do so, and on a more level playing field with distillers overseas. The distillers will pay tax on their profits. The government doesn't really need to tax them twice. And, since by definition exports are not sold domestically, there is no increase in negative externalities from removing the excise on those exports, and there may even be a decrease [*].

It turns out my proposal already happens - there is an 'excise duty drawback' that allows distillers to claim back the excise tax paid on any goods that they export. So, the distillers are already free to 'sell brand New Zealand' to their heart's content. They don't need to have their excise on New Zealand sales reduced in order to achieve that goal. Is there a real problem here? Or is this just another case of an industry with its hand out for government support?

*****

[*] Interestingly, the zero-rating of excise tax on exports may produce a further benefit in terms of reducing alcohol consumption (and negative externalities) in New Zealand. If it becomes more profitable to produce and export distilled products, then they may choose to sell less in New Zealand. That would actually increase prices in New Zealand, reducing alcohol sales and consumption.

To see how this works, consider a distiller who could sell overseas at a price P1, receiving the price P0 after paying an excise to the government on all of their production (sold overseas, or sold locally). Call the difference in those two prices T (the excise tax), so P1 - T = P0. It makes sense for the distiller to also sell its products at the price P1 in New Zealand (if they could receive a higher price overseas, they would sell there instead), also receiving P0 after paying the excise tax. Now, what happens when the excise tax is removed for exports? Instead of receiving P0 from exports, the distiller receives P1 (since they no longer have to pay the excise tax T). They won't want to sell their products in New Zealand and receive less than P1. That only happens if they raise the price from P1 to P1 + T (which leaves the distiller with P1 after they pay the excise tax T). So, we would expect the price on distilled products to increase in New Zealand, if the excise tax were removed from exports. In other words, the 'excise duty drawback' scheme likely increases prices on distilled products in New Zealand, although in reality the 'pass-through' of tax to retail prices is likely to be somewhat less than the full amount of T.

People's offsetting behaviour thwarts well-intentioned interventions in social media and smartphone use

People lead complicated lives. They have many competing goals, and have to trade off between those goals. Economists assume that they choose their actions with the overall aim of maximising their utility (satisfaction, or happiness). However, the many competing goals can sometimes thwart well-intentioned interventions. For example, when seatbelts were made compulsory, that made driving faster safer to do, and people responded by driving faster, and therefore less safely (for related examples, see here and here). Economists refer to that as offsetting behaviour.

Two recent examples of this arose in research papers I read this week. The first is this NBER Working Paper by Hunt Allcott (Stanford University) and a long list of co-authors, who investigated the impact of people temporarily deactivating Facebook or Instagram on their emotional state. Working with Meta (where some of the co-authors work), they:

...recruited 19,857 Facebook users and 15,585 Instagram users who spent at least 15 minutes per day on the respective platform. We randomly assigned 27 percent of participants to a treatment group that was offered payment for deactivating their accounts for the six weeks before the election. The remaining participants formed a control group that was paid to deactivate for just the first of those six weeks.

They then compare the difference in emotional state between before and after the deactivation for the treatment group (who deactivated for six weeks) and the control group (who deactivated for one week), and find that:

...users in the Facebook deactivation group reported a 0.060 standard deviation improvement in an index of happiness, anxiety, and depression, relative to control users...

...users in the Instagram deactivation group reported a 0.041 standard deviation improvement in the emotional state index relative to control.

Those effects are quite small in comparison to other interventions, and in comparison to changes in emotional state over time, and:

Under the approximation that emotional state index is normally distributed, the estimated effects of Facebook or Instagram deactivation would move the median user from the 50th percentile to the 52.4th or 51.6th percentile, respectively.

Why was the effect so small? Users who deactivated Facebook or Instagram spent more of their newly-freed-up time on other apps. Those who deactivate Facebook increased their use of Instagram, but also:

Facebook and Instagram deactivation both increased use of Twitter, Snapchat, TikTok, YouTube, web browsers, other social media apps, and other non-categorized apps by a few minutes per day.

It's little wonder that deactivating Facebook or Instagram had such small effects, given the offsetting behaviour of the users pivoting to using other apps, including other social media apps, instead. None of this is to say that the intervention made the users worse off, but it probably didn't make them better off overall either.

The second example is this NBER Working Paper by Billur Aksoy (Rensselaer Polytechnic Institute), Lester Lusher (University of Pittsburgh), and Scott Carrell (University of Texas at Austin), which looked at the effects of the app 'Pocket Points' at Texas A&M University. Specifically:

Pocket Points is marketed as a soft commitment device and provides incentives for students to stay off of their phones. In particular, Pocket Points rewards students with “points” for staying off their phones during class: Students open the app, lock their phone, and start accumulating points, all while the app verifies through GPS coordinates that the student is indeed in class. These points can then be used to get discounts at participating local and online businesses.

One thousand Texas A&M students were invited to participate in the experiment in 2017, and half were randomised to treatment, where they were instructed to download the Pocket Points App and create an account. Aksoy et al. then compare the treatment and control students. They also distinguish effects between those who used the app at least once, and those who used the app more than once a week (based on survey results). Importantly, first Aksoy et al. report that:

...treatment students were about 25 percentage points more likely to download the app... and over 31 percentage points more likely to use the app... than control students. Additionally, treatment students were 13 percentage points more likely to use the app more than once a week...

So, the treatment worked in encouraging students to use Pocket Points. But did it work? Aksoy et al. find some positive effects in the classroom, such as:

...Pocket Points usage is associated with a 0.42 standard deviation reduction in phone distraction rate in the classroom... we observe increases in student satisfaction with their academic performance for the semester: Students who used the app more than once a week experienced more than a one standard deviation increase in satisfaction...

That seems promising. However, when they look at student grades (from their official TAMU transcripts), Aksoy et al. find that:

...students who used the app more than once a week experienced a 0.50 unit increase in GPA. These estimates, however, are statistically insignificant...

So, even though the Pocket Points app reduced in-class distractions, it had no statistically significant effect on students' grades. That may be because there were also:

...significant decreases in time spent studying on campus... treated students spent approximately 18.2 hours/week studying, 12.0 of which were on campus, whereas control students spent 20.3 hours/week studying, 14.1 of which were on campus. Thus, it appears that the increased learning and attendance in the classroom came with a reduction in time spent studying.

It's little wonder that there was no effect on students' grades, given the offsetting behaviour of students spending less time studying, perhaps because they believed (perhaps rightly) that their in-class study time was more effective without phone distractions. None of this is to say that the app made the students worse off, but it probably didn't make them better off overall either.

When we implement an intervention that we hope will lead to better outcomes, such as improved emotional state due to less time spent on social media, or improved student performance due to more focused studying in class, we need to be prepared for the offsetting behaviour of the people affected by the intervention. Their lives are complicated, and they are trading off between competing goals. Just because we want to make one of their goals easier to achieve, that doesn't mean that they will focus extra energy on that goal. As we have seen from the two examples above, they may simply re-focus their energies elsewhere, leaving the outcome that we want to improve unchanged.

[HT: Marginal Revolution, last year]

Déjà vu: It's not a tax, it's a levy

In 2018, I mocked the government for their insistence that an increase in fuel tax was an excise, not a tax. Since I'm a firm believer in equal treatment of the government of the day when they display their economic illiteracy, I thought I needed to pick up on this story from earlier in the week:

Is it a tax? Is it a levy? An additional charge for a liquefied natural gas import terminal has turned into a communications nightmare for the Government...

Asked if this was a new tax on households, the prime minister was quick to intervene.

“This isn’t a tax, it’s a levy to fund a key piece of infrastructure,” he said.

So, it's a levy, and that is different from a tax? Not according to the OED, which defines a levy as:

Levy, n.

A duty, impost, tax.

Or, if you prefer the Merriam Webster Dictionary:

1 a : the imposition or collection of an assessment

Merriam Webster then defines an assessment as (emphasis is mine):

2 : the amount assessed : an amount that a person is officially required to pay especially as a tax

A levy is a tax. It has the same effects as a tax (for example, see this post for the details) - it raises the price that consumers pay, it lowers the effective price that sellers receive (after paying the levy to the government), it delivers revenue to the government, and it creates a deadweight loss (even if there may be offsetting benefits from how the revenue is spent). Whether the government uses that revenue for a liquefied natural gas import terminal, or for any other purpose, that doesn't change the fact that the levy is a tax.

I wrote back in that 2018 post that:

...this isn't the first (and it won't be the last) government to try their hardest not to refer to taxes as taxes.

It seems I was correct in that assessment.

Read more:

• It's not a tax, it's an excise