Fonterra, monopsony, and market power

This week in ECONS101, we will be discussing firms with market power. Market power refers to the ability of the seller (or sometimes the buyer) to have an influence over market prices. In our case, we will be focusing on firms who have market power over markets into which they are selling. In those cases, the firm will raise the price above the price that would arise in a more competitive market (and will consequently sell a lower quantity, but at a higher profit). At the extreme end of market power are monopolies, where there is just a single seller of the product and where there are no close substitutes.

Sometimes though, it is the buyers who have market power. Think about the case of a single employer in a small isolated town (like a company town, for instance). If people in the town want a job, they have to work for the single employer. This gives the employer market power, and they can react by lowering wages - after all, the employees aren't going to go work for some other firm, as there are no other employers in the town. This is an example of a monopsony.

That brings me to Fonterra. It isn't quite a monopsony (there are other dairy companies in New Zealand), but it does have a high degree of market power due to its dominant position as a buyer of milk from farmers. If Fonterra was to act on its market power, it could easily drive down the price of milk paid to farmers. Until relatively recently, this wouldn't have been worthwhile, because the farmers were also the shareholders of Fonterra, so any profit gains obtained from buying milk more cheaply from farmers would have simply been returned to the same farmers in the form of higher profits. However, Fonterra underwent a capital restructure in 2009-2010, so the concordance between farmers as sellers of milk and shareholders as receivers of dividends from Fonterra profits decreased.

Despite that, there are still a couple of things that keep Fonterra's monopsony market power in check. The first is the existence of smaller dairy companies. If Fonterra screwed its farmers over too badly, they could jump ship to the competition. However, those other dairy companies are small and their ability to absorb large numbers of new farmer suppliers is limited. So, Fonterra could get away with offering a slightly lower price than its local competitors offer.

The second restriction on Fonterra's market power is the legislated requirement that it must accept all milk that its farmer suppliers offer to it. That is why this proposal should be a worry:

Fonterra, a farmer-owned cooperative with listed units, has long pushed back against the DIRA requirement that it take all milk offered to it, which has resulted in the company having to spend hundreds of millions on new stainless steel processing capability as annual milk production climbed in recent years.

Fonterra argues this capital requirement erodes its strategy to move from processing commodities to value-add products, and is helping its internationally-backed competitors.

DIRA is the Dairy Industry Restructuring Act 2001, which was the legislation that enabled the creation of Fonterra, through the merger of New Zealand Dairy Group and Kiwi Co-operative Dairies, the two largest farmer cooperatives at the time, and the New Zealand Dairy Board, which was the exporting agent for all of the country's dairy cooperatives. DIRA is currently under review, and unsurprisingly Fonterra wants the shackles removed. They are arguing that:

The industry had become "highly competitive" particularly with the relatively large number of new entrants in the past five years.

"These international new entrants are often backed by deep capital and global businesses. They do not need an extra leg-up via milk from New Zealand farmers. Given this new competitive environment, the issue of open entry – which means having to accept all milk from new suppliers – is a critical part of the review," it said.

"Open entry limits our farmer-shareholders and the industry's ability to maximise value for New Zealand. It distorts investment decisions and leaves Fonterra's farmers underwriting risk for competitors who cherry-pick their suppliers."

Fonterra still collects over 80 percent of the milk production in New Zealand. Its competitors are much smaller. If the Government removes the requirement for Fonterra to accept all milk offered to it, then its market power naturally increases. If a farmer wants Fonterra to accept milk, and Fonterra doesn't have to accept it, then Fonterra can say, "We'll take your milk, but only at a discount of X%". How large X% is will depend on whether the competition could feasibly take the milk. In areas where there isn't local collection by Synlait, Westland, Tatua, etc., those farmers are at very real risk of being seriously screwed over by such a change.

There may well be benefits to Fonterra's shareholders from freeing Fonterra up from the requirement to accept all milk offered to it. But that doesn't mean that the proposal won't also come with real costs to farmers attached to it.

How does New Zealand's alcohol control policy regime rate?

Given the fairly constant flow of news stories about New Zealand's drinking environment, you'd be forgiven for thinking that New Zealand is very permissive in terms of alcohol. Take, for instance, this recent New Zealand Herald story:

New Zealand's drinking culture has come under fire following a new study which shows a link between alcohol consumption and trips to the emergency department.

Experts are linking the result to New Zealand's binge drinking culture and easy access to cheap booze.

The study, recently published in Addiction, shows data from 62 emergency departments in the 28 countries, and includes more than 14,000 patients.

It ranks New Zealand second out of 28 countries for the proportion of injury cases presenting to emergency departments where the person had consumed alcohol in the preceding six hours...

[Alcohol Healthwatch director Nicki] Jackson said such injuries were costing New Zealand billions of dollars.

If we want to improve mental health, reduce suicides and shorten hospital waiting lists, government needed to start making changes around accessibility to alcohol, she said.

"We haven't taken any strong measures against the most harmful drug in our society. We will keep paying this cost until we take strong action."

There were issues around easy access to alcohol, increasing affordability, and marketing.

"We need to raise excise tax on alcohol," she said, adding taxes were "nowhere near the level they should be" when it comes to drinking.

I tracked down the research paper mentioned in the article (sorry I don't see an ungated version). It was written by Cheryl Cherpitel (Alcohol Research Group in the U.S.) and others (including Bridget Kool of the University of Auckland). [*]

In the paper, they use a measure called the International Alcohol Policy and Injury Index (IAPII) as an omnibus measure of the policy environment with a range from zero to 100. Higher values of this measure represent a stricter policy environment, and lower values represent a more permissive environment. Based on the 33 studies included in Table 1 of the paper (and treating them all as independent observations [**]), the average value of the IAPII is 59.8. New Zealand's IAPII was 76 in 2000, and 78 in 2015-16. In fact, only Sweden (91 for two observations), Canada (80 for three observations), and Ireland (79 for one observation) have stricter alcohol policy environments than New Zealand. Australia's IAPII in 1997 was also 78.

That doesn't strike me as particularly bad. But equally, I'm not sure that we want a permissive alcohol policy environment, so I would want to know how the policy environment relates to harm. There's another measure in the paper that will help with that question: the detrimental drinking patterns (DDP) measure. DDP is "an indicator of the ‘detrimental impact’ on health and other drinking-related harms at a given level of alcohol consumption", and is measured on a 1-4 scale, "from 1 (the least detrimental pattern of drinking) to 4 (the most detrimental)." New Zealand rates as a 2 on the DDP score, equal with Canada, but better than Sweden or Ireland (both have DDP scores of 3). Only Australia and Switzerland rate a 1 on the DDP measure.

I graphed the relationship between DDP and IAPII for the observations from the Cherpitel et al. paper, and that graph is shown below. The IAPII is on the vertical axis, and the DDP is on the horizontal axis (there are only four values of the DDP). Each blue dot represents on study site from Table 1 of the paper. The two red dots are the observations for New Zealand (the lower dot is the observation for 2000, and the higher dot is the observation for 2015-16). The dotted green line is a linear regression line showing the relationship between the two variables. As you might expect, the relationship is negative, meaning that countries with more permissive alcohol control policies (lower IAPII) have worse detrimental drinking patterns (higher DDP).

One thing to note from this diagram is that the dotted line essentially shows the 'average' IAPII for sites at that level of DDP. Observations above the line are under-achieving - their DDP is higher than would be expected, given the strictness of their alcohol control policies. New Zealand fits into that category.

All of that suggests to me that the problem isn't our alcohol control policies. If we have high alcohol-related emergency department admissions, as the Cherpitel et al. paper contends, then the solution is unlikely to be found in stricter alcohol control policies. At least, based on the comparison with other sites in this study. Our policies are already one of the strictest, and are stricter than would be expected given our level of detrimental drinking patterns.

One notable aspect that isn't covered in the IAPII measure is pricing, and that could be a fruitful policy avenue to explore. If we want to reduce alcohol-related harm, we might get more value out of pricing interventions (e.g. minimum pricing, higher excise taxes) than stricter policy controls.

*****

[*] I haven't written too much about the Cherpitel et al. paper itself in this post, because that wasn't my focus. They show that IAPII and DDP have independent and statistically significant relationships with the chance of a person presenting at ED for an injury having consumed alcohol in the previous six hours. In other words, higher IAPII is associated with a lower proportion of injuries that are alcohol-related, and higher DDP is associated with a higher proportion of injuries that are alcohol-related. That isn't unexpected. However, when they include both variables in the same model, only IAPII is statistically significant. This is because of multicollinearity - two of their explanatory variables are closely correlated, so that reduces the chance that either of them show up as statistically significant when they are both included in the same model, because they are trying to explain the same part of the variation in the outcome variable. Notice the close relationship between IAPII and DDP in the diagram above.

[**] Strictly speaking, we should down-weight multiple observations from the same country (e.g. two observations from New Zealand, and three from Canada). However, I don't think it would make much difference in this case.

Radiation and house prices after the Fukushima nuclear disaster

How much less would you be willing to pay for a house in an area affected by radiation significantly above background levels, compared with an otherwise-identical house that is unaffected by radiation? It's not a crazy question. In the U.S., hundreds of millions of people (including the populations of 26 of the 100 most populous cities) live within 50 miles of a nuclear reactor. Worldwide, there are 21 nuclear plants that each have more than one million people living within 30 kilometres of them.

Of course, nuclear accidents are thankfully rare. But the risk is not zero, and when an accident does occur, as happened in Fukushima in 2011, people can be understandably reluctant to live in the affected areas due to the risks to their health and wellbeing. Obviously, that has a flow-on impact on house prices, even outside the most heavily affected areas.

Hedonic demand theory (or hedonic pricing), which we discussed in my ECONS102 class last week, recognises that when you buy some (or most?) goods you aren't so much buying a single item but really a bundle of characteristics, and each of those characteristics has value. The value of the whole product is the sum of the value of the characteristics that make it up. For example, when you buy a house, you are buying its characteristics (number of bedrooms, number of bathrooms, floor area, land area, location, etc.). When you buy land, you are buying land area, soil quality, slope, location and access to amenities, etc. You are also buying the exposure to current levels of radiation, as well as the risk of future exposures to radiation in the event of a nuclear accident. If each of those characteristics can be separately valued, then you can place a value on how much people are willing to pay to avoid radiation (or alternatively, how much they are willing to accept to live in a radiation-affected area).

In a new paper in the Journal of Regional Science (sorry I don't see an ungated version anywhere online), Alistair Munro (National Graduate Institute for Policy Studies, Japan) looks at the impact of the Fukushima disaster on house prices in Fukushima and Miyagi prefectures, using data from 2009 to 2017. Fukushima prefecture was most affected by radiation as well as the tsunami that led to the nuclear disaster, while neighbouring Miyagi prefecture was only affected by the tsunami. So, differences between the two in terms of changes in house prices can be attributed to differences in radiation levels (once you control for other characteristics of the properties, of course). He finds that:

...across the subsample of noncondominium residence types a 1 percent rise in radiation leads to a 0.051 percent drop in values, while for condominiums treated separately the elasticity is also 0.051. For housing land the elasticity is 0.044, and 0.032 for land with existing buildings if the age of the building is controlled for.

In other words, areas more affected by radiation have lower house prices. How much lower? Munro reports that:

...using a variety of methods... the impact of radiation translates into a one to two million Yen (US$10,000–20,000)... reduction in housing prices for average residential properties.

That is quite substantial, but is not terribly surprising. However, the next part of the paper is very cool. Having established how much less people are willing to pay for living in an area with more radiation, Munro then uses that information plus information on the risk of cancer arising from environmental radiation, to estimate the value of a statistical life (or VSL).

As I will discuss with my ECONS102 class later this semester, the VSL can be estimated by taking the willingness-to-pay for a small reduction in risk of death, and extrapolating that to estimate the willingness-to-pay for a 100% reduction in the risk of death, which can be interpreted as the implicit value of a life. Munro estimates VSL to be in the region of US$4.5-6.4 million, which is similar to VSL estimated in other studies (and other risk contexts). An additional take-away from that analysis is that there isn't a particularly high element of dread associated with avoiding death from radiation (otherwise, people would be willing to pay more to avoid it, and the estimated VSL would be much higher).

Next we really need to know whether the Fukushima disaster affected people's perceptions of nuclear risk in other areas that are near nuclear plants but which weren't affected by the disaster. That would be much more difficult to establish, but potentially much more interesting.

Evergreening viagra, revisited

Back in April, I wrote:

Of course, if it turns out that Viagra (or sildenafil) is an effective treatment for babies suffering from stunted growth, then that is a great thing. And not just for the babies. Pfizer (the patent-holder for Viagra) would have protection from generic versions of sildenafil for another twenty years, meaning another twenty years of market power - not just for Viagra used for treating babies, but Viagra used for all treatments (including the highly profitable market for treating erectile dysfunction). A really cynical person would probably recognise that the sudden interest in new uses of Viagra now (the four trials mentioned in the article are not the only trials trying to find new uses for Viagra - see here for another example) is because Viagra comes off patent in April 2020. The clock is ticking for Pfizer, if they want to keep milking their Viagra cash cow.

The context was a drug trial for the use of Viagra to treat babies at risk of stunting. If Pfizer can find a new use for Viagra before it comes off patent in 2020, they can re-start the patent clock and retain their market power and high profits from the drug.

In today's news though:

Overseas deaths of babies involved in a clinical trial has prompted a review from researchers who have been running an aligned study here in New Zealand.

The international research STRIDER consortium has involved four trials - one of them carried out here and in Australia - investigating a possible use for the drug sildenafil in treating fetal growth restriction.

Sildenafil is better known as the drug behind Viagra, which is used to treat male erectile dysfunction by dilating blood vessels in the pelvis.

The researchers drew on a generic version of sildenafil, not manufactured by Viagra's makers Pfizer, to investigate whether it might work the same way in pregnant women by increasing blood supply to the placenta.

But last week, one of the trials, which was being carried out in the Netherlands, was terminated early due to safety concerns.

Results from a planned interim analysis showed more babies in the sildenafil group suffered a serious lung condition, called persistent pulmonary hypertension, which may have led to 11 more liveborn babies dying before hospital discharge.

Are we now seeing the real cost of attempts to evergreen the patent for Viagra? It's hard to say. As Thomas Lumley noted on StatsChat this morning:

It looks as though something might have been different about the Amsterdam study — although it’s also possible they were extremely unlucky.

In other words, it's too early to say, and the other drug trials (in the UK, Canada, and New Zealand/Australia) haven't shown such negative effects (but apart from the New Zealand/Australia study, they also haven't shown positive effects). However, eleven additional deaths as a result of a drug trial is far too many, and it's appropriate that the Dutch researchers have called it off. As Lumley notes, a trial that shows a negative effect is still a positive outcome, if it prevents future deaths from inappropriate treatment.

However, would this trial have gone ahead if Pfizer weren't intent on evergreening their Viagra patent? If I extend my cynicism from my April post on evergreening Viagra though, this episode demonstrates that the ability to evergreen patents might not only have costs in terms of lost economic welfare (due to the ongoing market power of the patent-holder), but might have real human costs.