Principal-agent and adverse selection problems among Senegalese taxi drivers

A principal-agent problem (or agency problem) may arise in interaction that involve a person or group (the agent) being given the power to decide how to use resources that ‘belong’ to someone else (the principal). The problem that may arise is when the principal wants the agent to use the resources in a particular way that is contrary to the interests of the agent (who has their own goals and motivations), but the agent uses the resources in some other way that is detrimental to the principal. This principal-agent problem is an example of moral hazard. The market failure here is that the principal becomes unwilling to engage an agent, if they can't be sure that the agent will act in the principal's best interests.

An interesting example is described in this post from the Development Impact blog late last year, which was based on the job market paper of Deivy Houeix (MIT). They describe the problem as follows:

The Senegalese taxi industry exemplifies common principal-agent challenges faced by small firms in lower-income countries. The typical arrangement involves a car owner (employer) and a single driver (employee) linked by a relational contract. The driver keeps any revenue exceeding a rental fee paid weekly and sometimes receives an upfront payment from the owner. Due to limited liability, drivers can default on the rent by claiming low earnings for the week. Importantly, the owner has no way to observe whether this is due to bad luck, lack of effort from the driver, or whether the driver misreports revenue. This creates scope for moral hazard in both driver's effort and reported output and allows drivers to capture informational rents, contributing to inefficiencies common in informal arrangements. Default may lead to the (costly) termination of the relationship to mitigate moral hazard.

Notice that this has all the features described above. The car owners are the principals. The drivers are the agents. The resources belonging to the principal, that the agent has the power to decide how to use, are the taxis. The car owner wants the taxi drivers to pay the full rent for the car. However, the drivers have an incentive to claim low earnings and default on paying the rent. The market could fail, because the car owners choose to terminate the agreement with the drivers.

Houeix's post was about how to solve the principal-agent problem, and describes the results of two field experiments that were conducted to test whether adopting digital payment technology could reduce the principal-agent problem. Since closer monitoring of the agent by the principal is one solution to principal-agent problems, using digital payment technology to facilitate this monitoring seems like it could be beneficial.

I recommend reading the entire post (and following up with the job market paper itself, for further detail), but in short the results show limited success. On the one hand, the digital payment technology:

...significantly cuts drivers' cash-related costs (e.g., small-change shortages) by half and serves as effective monitoring tools even with partial digitalization of transactions (about 13% of revenue).

The digital payment technology made it easier for drivers to accept payment, and easier for car owners to monitor what drivers were doing. However, drivers had the option not to adopt the digital payment technology, by simply not providing the car owner's details:

I find that observability is an important barrier to technology adoption, especially for the worst-performing and poorest workers. Initially, 50% of drivers did not want to adopt the technology, citing various privacy concerns for not sharing owners' information.

This should be no surprise. The lowest-productivity workers are likely to be the ones hurt the most by closer monitoring, so of course they wouldn't want to adopt the digital payment technology.

However, there may be an upside. Since car owners don't know who the high-productivity drivers are (productivity is private information), there is also an adverse selection problem here. That problem is that, because the car owners can't tell high-productivity and low-productivity drivers apart, they must assume that all drivers are low-productivity drivers, and will treat them accordingly. This is a pooling equilibrium (because all drivers are pooled together and treated the same). The high-productivity drivers don't want to be treated as if they are low-productivity, so they will be more likely to leave the market. If this continues, eventually only low-productivity drivers are left. The market fails.

This adverse selection problem could be solved by the car owners asking drivers to adopt the digital payment technology (this is a type of screening, since it involves the uninformed party (the car owners) attempting to credibly reveal the private information). The answer to the question about whether they will agree to install the digital payment technology reveals the productivity of the drivers. The drivers who don't agree are likely to be the low-productivity drivers, and so the car owners should choose not to rent their car to those drivers. Instead, the drivers who accept the digital payment technology will be the high-productivity drivers, and the car owners should be happy with them. That creates a separating equilibrium (since the low-productivity and high-productivity drivers can now be separated), and solves the adverse selection problem for the car owners.

Houeix didn't note the potential solution to the adverse selection problem in the post, nor in their job market paper. That was a missed opportunity, and may be the real benefit of the digital payment technology that they investigated.

The moral hazard of bailing out scam victims

Earlier this year, bowing to pressure from media and advocacy groups, banks acted to help out victims of financial scams. As the New Zealand Herald reported in April:

Banks will be required to reimburse fraud victims up to $500,000 and introduce new rules to crack down on scammers in a suite of measures unveiled today.

The changes include new technology to identify risky or unusual transactions based on a customer’s banking history and the ability to freeze payments and suspect accounts.

The moves are in response to Government demands to improve customer protections or be regulated in the face of Kiwi victims losing hundreds of millions of dollars to scammers each year...

The New Zealand Banking Association says it is rolling out a package of new protections in line with international best practice, which will be in place by November.

However, by itself the reimbursement of fraud victims creates a problem that might actually result in there being more victims of fraud overall. That is because of what economists call moral hazard. Moral hazard arises when one of the parties to an agreement has an incentive, after the agreement is made, to act differently than they would have acted without the agreement. Importantly, the agreement doesn't have to be a formal contract. It can be an implicit understanding or expectation.

In this case, there is an implicit agreement between banks and their clients, that makes it clear that the bank will reimburse the client when the client is impacted by a financial scam. Without that implicit agreement, bank clients have a strong financial incentive to avoid being scammed. If they are scammed, they lose a lot of money. However, now that banks will bail them out, bank clients have less incentive to act carefully and avoid financial scams. Scammers may be more successful as a result, leading to more scam victims.

This is not to say that bank clients will be flagrantly imprudent with their money, only that at the margin, clients will act a little less cautiously. The moral hazard problem here is that the risky actions of the bank clients end up costing the banks money, in the case when the bank client is scammed and the bank needs to reimburse them. If banks couldn't do anything about the risk, they would be less inclined to take on depositors. If the risk turned out to be extreme, the market for bank deposits could fail entirely.

Fortunately, banks can respond to this increased moral hazard in various ways. The first way is through increased monitoring of their clients. Notice in the quote from the article above that banks will employ "new technology to identify risky or unusual transactions based on a customer’s banking history". By monitoring clients' transactions, banks can hopefully head off any scam activity. Banks could also use incentives to reward their clients for not being scammed. Perhaps they could pay slightly higher interest rates to those that pass occasional bank-delivered 'scam checks' (where the bank employs someone to test whether the client will fall for a scam). None of the banks are proposing this yet, but it is a solution that is open to them.

Overall, this change is likely to be positive for bank clients. However, with these new scam protections in place, people will be less careful. Banks will need to remain very vigilant, or the number of scam victims will increase.

Moral hazard, and bailing out failing banks

At the time of the Global Financial Crisis, in 2008-09, I was fresh out of completing my PhD and still fairly idealistic in terms of what it was possible to do with policy. At that time, it struck me as a bad move to be bailing out the banks that had created such a fragile system. My views have softened significantly since then (although, as noted in my previous post on windfall taxes, I think there is an asymmetry to the relationship between business and government), especially as we've seen the global financial system recover (albeit with a significant increase in central bank balance sheets that is proving difficult to unwind). And now we seem to be at it again, with the US stepping in to save uninsured depositors at Silicon Valley Bank and Signature Bank earlier this week.

Why would saving bank depositors be a bad thing? Moral hazard arises when one of the parties to an agreement has an incentive, after the agreement is made, to act differently than they would have acted without the agreement. Importantly, the agreement doesn't have to be a formal contract. It can be an implicit understanding or expectation.

In this case, if large depositors [*] at failed banks lose all of their deposits, then there is a strong incentive for the depositors to undertake due diligence on their bank. They will want to be sure that their money is safe, and if not, they will bank elsewhere. Or, at least, large depositors will spread their risk by having deposits at multiple banks, rather than banking at a single bank. Because banks know that large depositors are being careful, they will do everything they can to convince depositors that they are safe institutions (and at least some of those actions will actually make the banks less risky). However, when the government develops a reputation for bailing out large depositors, this reduces the incentives for large depositors to undertake due diligence, which in turn reduces the incentives for banks to be safe institutions. This is not to say that banks will be flagrantly risky, only that at the margin, banks will act a little more risky. The moral hazard problem here is that the risky actions of the banks end up costing the large depositors, in the case when the bank fails and if the government doesn't reimburse the large depositors. This would be less likely to happen if the government hadn't created an expectation that they would bail out the large depositors in the first place.

In the current situation in the US, bailing out the large depositors at Silicon Valley Bank and Signature Bank reinforces an expectation at all other banks that the US will bail out large depositors if the bank fails. We can expect riskier behaviour from the banks in the future.

So, should we be against these bailouts? On the Marginal Revolution blog, Tyler Cowen has the most clear-headed explanation of why, in spite of any moral hazard problems, bailing out large depositors was probably the right move. One argument that Cowen makes is that:

An unwillingness to guarantee all the deposits would satisfy the desire to penalize businesses and banks for their mistakes, limit moral hazard, and limit the fiscal liabilities of the public sector. Those are common goals in these debates. Nonetheless unintended secondary consequences kick in, and the final results of that policy may not be as intended.

Once depositors are allowed to take losses, both individuals and institutions will adjust their deposit behavior, and they probably would do so relatively quickly. Smaller banks would receive many fewer deposits, and the giant “too big to fail” banks, such as JP Morgan, would receive many more deposits. Many people know that if depositors at an institution such as JP Morgan were allowed to take losses above 250k, the economy would come crashing down. The federal government would in some manner intervene – whether we like it or not – and depositors at the biggest banks would be protected.

In essence, we would end up centralizing much of our American and foreign capital in our “too big to fail” banks. That would make them all the more too big to fail. It also might boost financial sector concentration in undesirable ways.

To see the perversity of the actual result, we started off wanting to punish banks and depositors for their mistakes. We end up in a world where it is much harder to punish banks and depositors for their mistakes.

Cowen makes additional points (and I encourage you to read his entire post), but the one quoted above is the kicker. If large depositors do not expect to be bailed out, they will only bank at large and safe banks. That will make smaller banks, and probably financial start-ups, less viable. This increases the risks to the financial system if one of the (fewer, larger) remaining banks was to fail. So, policymakers are left with a difficult trade-off: bail out the large depositors and create a moral hazard problem, or not bail out large depositors, and be left with a financial system that is more concentrated, and more vulnerable to future failures. An idealist, like my 2008-09 self, might prefer the second option. However, I'm much more comfortable with where this has gone this time.

One last important point to make is that it appears that the US actions are not bailing out the bankers themselves, only the large depositors. That marks a significant difference between now and the Global Financial Crisis, where it appeared that the bankers mostly got off scot-free. I'm sure that some will argue that the banks found themselves in an unfortunate situation that was unforeseeable and therefore the bankers themselves are not responsible for this outcome. We should reject those arguments, as higher interest rates are not unforeseeable, although they may be unanticipated. Bankers should be better at stress testing for a wide range of future interest rate costs. After all, if it results in higher costs, those costs simply get passed onto their customers. Although that's probably the problem here - passing on higher costs because your bank is stress testing at a more rigorous level than other banks simply makes you less competitive. I guess we will find out in the fullness of time whether there were any consequences for the bankers, and whether there are regulatory changes in relation to banks' testing their vulnerability to future interest rate changes.

*****

[*] Notice that I restrict the argument here to large depositors. It is unreasonable to expect small depositors to have the time or resources to undertake due diligence on their bank. Also, small depositors can't as easily spread their risk by having deposits at multiple banks. Small depositors are therefore at risk, and have limited means to reduce that risk. So, it is reasonable that small depositors are protected by the government (through deposit insurance, for example).

More on climate risk, insurance, and moral hazard

Nearly two years ago, I posted about climate risk and disaster insurance, noting that insurance premiums for the homes most at risk as a result of climate change, including coastal properties, were likely to face increasing insurance premiums. The most surprising thing is that, nearly two years on, there hasn't yet been a major shift by the insurers. Until now, as the New Zealand Herald reported last month:

A major insurer is eyeing risk-based pricing for coastal erosion, in what's being described as another landmark step by the industry to confront climate threats.

Last year, Tower became New Zealand's first insurer to introduce a new pricing model based on individual homes' risk of flooding from rainfall and rivers – and to make such ratings public.

It meant about 100,000 customers received either a low, medium or high rating for their home, reflecting the potential risk of a flood and the estimated cost of replacing or repairing.

About one in 10 customers received a small hike in the flood risk portion of their premiums – while a few hundred that received a high or very high ratings saw increases of more than $500 a year.

In some cases, the company needed to find customers alternative insurance cover, chief executive Blair Turnbull told the Herald.

 That story came hot on the heels of this one the day before, also from the New Zealand Herald:

Properties worth $1 million on Wellington's Petone foreshore could cost $100,000 a year to insure in 20 years, a climate risk expert says.

The warning came as the Government grappled with whether to set up its own flood insurance scheme to cover people as private insurers become less willing to.

Climate change is driving increasingly common and damaging storms, and it, coupled with sea level rise, means thousands of homeowners in harm's way face spiralling premiums or having cover pulled altogether.

The scary thing about that story is the mere suggestion that the government might get involved in offering insurance to high-risk properties. That is exactly the problem I was concerned about in my post from two years ago. The government offering insurance to coastal properties, or properties on flood plains, or those at risk of severe erosion, or whatever, leads to a problem of moral hazard.

Moral hazard arises when one of the parties to an agreement has an incentive, after the agreement is made, to act differently than they would have acted without the agreement. In this case, the agreement is between the government, and homeowners (or potential homeowners) of high-risk properties. After the government creates an insurance scheme for high-risk properties (or agrees to subsidise insurance premiums in some way), that reduces the costs of owning an at-risk property. When the cost of something decreases, we tend to do more of it than we would otherwise. At the margin, people will be a little more likely to buy or live in at-risk properties, or to construct more at-risk properties. It likely makes the problem of the amount of assets (and people) at risk of sea level rise, coastal inundation, erosion, etc. even worse.

This is not just an issue that New Zealand is grappling with. As this July article in The Conversation, by Brian Cook and Tim Werner (both University of Melbourne) notes in relation to the Sydney floods that month:

In flood risk management, there’s a well-known idea called the “levee effect.” Floodplain expert Gilbert White popularised it in 1945 by demonstrating how building flood control measures in the Mississippi catchment contributed to increased flood damage. People felt more secure knowing a levee was nearby, and developers built further into the flood plains. When levees broke or were overtopped, much more development was exposed and the damages were magnified. “Dealing with floods in all their capricious and violent aspects is a problem in part of adjusting human occupance,” White wrote.

Cook and Werner note that:

To tackle flood risk, we have to respond to the social, political, economic, and environmental factors that drive development and occupation of floodplains.

Surprisingly, Cook and Werner don't note the additional problems that providing additional insurance to at-risk property owners would create. They are right that there are a range of inter-related factors that lead to development in at-risk and largely inappropriate locations. Their solution is to prohibit development in those areas. Prohibition is a very blunt instrument, but at the very least government shouldn't be considering policies that would incentivise more at-risk development. We need to ensure that homeowners and developers adequately take into account the actual climate risks that their properties face. There is evidence that coastal properties are not sufficiently risk-priced (see this post). Only then will we see a reduction in at-risk developments, as well as saving the taxpayer from covering the costs of coastal property owners' and developers' decisions.

*****

Read more:

• Climate change risk, disaster insurance, and moral hazard

'All you can fly' tickets will crash and burn

The New Zealand Herald reported last month:

A New Zealand airline is releasing $799 all-you-can-fly tickets, giving purchasers three months to travel as often as they like with the airline.

Regional carrier Sounds Air has 1000 tickets available and flies to nine destinations from Blenheim, Christchurch, Nelson, Paraparaumu, Picton, Taupō, Wānaka, Wellington and Westport.

Sounds Air general manager Andrew Crawford said the country was past Omicron and Covid-19, and while people wanted to get "out there" again, they had been slow coming back to air travel.

This could go really wrong for Sounds Air. The reason is moral hazard, which I covered with my ECONS102 class this week. Moral hazard arises when one of the parties to an agreement has an incentive, after the agreement is made, to act differently than they would have acted without the agreement. In this case, the agreement is between Sounds Air and the customers who buy the 'all-you-can-fly' tickets.

After the ticket is purchased, the marginal cost of flying decreases to zero for the ticket-holder. When the cost of something (like flying) decreases, we tend to do more of it than we would otherwise. The ticket-holders will fly more. Sounds Air might argue that that was their intention. From the article:

"We've got spare capacity, let's get people buying a season pass and try to get them on flights that are not full anyway.

Clearly, Sounds Air wants people to fly more. However, the important question is how much more will people fly? The monetary cost of each additional flight is now zero for the 'all-you-can-fly' ticket holders, so unless there is some fine print in the ticket, I'd expect some of them to fly a whole lot more. And probably they will fly far more than Sounds Air is expecting. What will Sounds Air do if their season ticket-holders start to take up all the seats on their flights? How sustainable is a business going to be that gives away its product for free? I predict that this experiment will crash and burn, and after this initial run, we won't hear of it again, just like the Minnesota pub that offered free beer for life.

The economics of the government's plan for 'social unemployment insurance'

One of the big (and surprising) announcements in the Budget earlier this year was that the government was developing a 'social unemployment insurance' scheme. This would presumably sit alongside the current unemployment benefit system, but would work in a similar way to accident compensation, paying each person who is made unemployed (and meeting certain conditions) 80 percent of their prior wage up to a certain cap.

This would represent a significant shift in the style of social security system that New Zealand operates. In my ECONS102 class, we distinguish three types (or models) of social security system:

1. A social assistance model - where there is an emphasis on self-reliance and responsibility, and the government provides support (often means tested) where a person would otherwise face hardship;
2. A social insurance model - where social assistance is available and based on previous contributions to a fund (which might be an individual account, or a general account for all insured people); and
3. A social citizenship model - where all citizens have a right to assistance for any contingencies they face (and the assistance is often not means tested).

In reality, most social security systems have features in common with all three types, but New Zealand's system up until now has mostly been a social assistance model, with the exception of accident compensation, which is clearly a social insurance scheme. This proposed introduction of social unemployment insurance would move unemployment assistance into the social insurance model (it would be interesting to see what the government would do with sickness and invalids benefits, or whether they would remain under the old system, along with sole parents and student allowances).

Anyway, there was a great article in The Conversation today by Simon Chapple and Michael Fletcher (both Victoria University of Waikato) that outlines some of the economic issues with a social insurance scheme:

However, there are two problems with the private insurance market, meaning they under-provide relative to people’s real need.

The first problem is called “adverse selection”, meaning people choosing to buy insurance have better information about the risks facing them than insurance businesses do, and no good reason to disclose that information.

To protect themselves from this, insurance companies set premiums higher. In turn, due to the costs, this leads to people being under-insured. Ultimately, society’s best interests aren’t met.

There’s also the problem of “moral hazard” – if a person has insurance they may take on more risk, without the insurer knowing exactly which customers are adopting riskier behaviour.

Again, insurance companies set higher premiums and people are generally under-insured. And again, this isn’t in society’s best interests...

These market failures mean there is potential for well-designed government interventions to meet the social interest. In particular, making everyone join a social insurance scheme would fix the adverse selection problem.

But a compulsory social insurance system also expands the scope for moral hazard. People might change their behaviour to increase their eligibility for an insurance payout. They might take on jobs with higher redundancy risks, or be less motivated to look for work, because the consequences are now less severe.

The problems of information asymmetry (including adverse selection and moral hazard) is among my favourite topics to teach in my ECONS102 class. Chapple and Fletcher are right that the unemployment social insurance scheme would not have an adverse selection problem (provided it is compulsory, in the same way that accident compensation currently is), and the key problems would be moral hazard.

To expand on the moral hazard problems a little bit, workers would be less fearful of losing their jobs, because they would receive a higher unemployment payment than previously. So, at the margin, workers would not work as hard, and productivity might decrease. Similarly, absenteeism might increase, which also reduces productivity. 

On the other hand, wages might increase. To see why, consider a search model of the labour market. This model recognises that each matching of a worker and a job creates a surplus that is shared between the worker and the employer, based on their relative bargaining power. A higher unemployment payment increases the worker's bargaining power, since they can afford to hold out for a better deal. Employers will have to offer slightly higher wages than before, in order to attract workers to leave the unemployment payment and accept the job offer. So, wages will increase, and employers will find that vacancies take a little longer to fill.

Workers may also benefit from better job matches. Since they can afford to stay on the higher unemployment insurance payment for longer, they can afford to wait and find a job they really want, rather than accept the first half-decent offer they receive. The number of unemployed will likely increase, and the average length of unemployment spells will also increase.

Clearly, there is a lot for the government to balance here. Chapple and Fletcher also note that:

If it turns out there are gaps in the current system, advocates of social insurance must also consider:

• such a scheme may simply be substituting for one or several of the existing solutions, which would then reduce if the scheme were introduced

• reforming and improving what already exists may be preferable in terms of cost, effectiveness and equity than introducing an entirely new system

• there may be implications for both equity and erosion of the core welfare system of creating a separate, higher tier of assistance for some.

At this stage, all we have had from the government is an announcement, and a promise of "public consultation later in 2021". Presumably that consultation has been delayed until next year, due to the pandemic. It will be interesting to see what comes out of this.

Climate change risk, disaster insurance, and moral hazard

One problem that insurance companies face is moral hazard - where one of the parties to an agreement has an incentive, after the agreement is made, to act differently than they would have acted without the agreement and bring additional benefits to themselves, and to the expense of the other party. Moral hazard is a problem of 'post-contractual opportunism'. The moral hazard problem in insurance occurs because the insured party passes some of the risk of their actions onto the insurance company, so the insured party has less incentive to act carefully. For example, a car owner won't be as concerned about keeping their car secure if they face no risk of loss in the case of the car being stolen.

Similar effects are at play in home insurance. A person without home insurance will be very careful about keeping their house safe, including where possible, lowering disaster risk. They will avoid building a house on an active fault line, or on an erosion-prone clifftop, for example. In contrast, a person with home insurance has less incentive to avoid these risks [*], because much of the cost of a disaster would be borne by the insurance company.

Unfortunately, there are limited options available to deal with moral hazard in insurance. Of the four main ways of dealing with moral hazard generally (better monitoring, efficiency wages, performance-based pay, and delayed payment), only better monitoring is really applicable in the case of home insurance. That would mean the insurance company closely monitoring homeowners to make sure they aren't acting in a risky way. However, that isn't going to work in the case of disaster insurance. Instead, insurance companies tend to try to shift some of the risk back onto the insured party through insurance excesses (the amount that the loss must exceed before the insurance company is liable to pay anything to the insured - this is essentially the amount that the insured party must contribute towards any insurance claim).

And that brings me to this article from the New Zealand Herald from a couple of weeks ago:

Thousands of seaside homes around New Zealand could face soaring insurance premiums - or even have some cover pulled altogether - within 15 years.

That's the stark warning from a major new report assessing how insurers might be forced to confront the nation's increasing exposure to rising seas - sparking pleas for urgent Government action.

Nationally, about 450,000 homes that currently sit within a kilometre of the coast are likely to be hit by a combination of sea level rise and more frequent and intense storms under climate change...

The report, published through the Government-funded Deep South Challenge, looked at the risk for around 10,000 homes in Auckland, Wellington, Christchurch and Dunedin that lie in one-in-100-year coastal flood zones.

That risk is expected to increase quickly.

In Wellington, only another 10cm of sea level rise - expected by 2040 - could push up the probability of a flood five-fold - making it a one-in-20-year event.

International experience and indications from New Zealand's insurance industry suggest companies start pulling out of insuring properties when disasters like floods become one-in-50-year events.

By the time that exposure has risen to one-in-20-year occurrences, the cost of insurance premiums and excesses will have climbed sharply - if insurance could be renewed at all.

Because insurance companies have few options for dealing with moral hazard associated with disaster risk, their only feasible option is to increase insurance excesses, and pass more of the risk back onto the insured. Increasing the insurance premium also reflects the higher risk nature of the insurance contract. Even then, in some cases it is better for the insurance company to withdraw cover entirely from houses with the highest disaster risk.

I'm very glad that the Deep South report and the New Zealand Herald article avoided the trap of recommending that the government step in to provide affordable insurance, or subsidise insurance premiums for high-risk properties. That would simply make the moral hazard problem worse. Homeowners (and builders/developers) need the appropriate incentives related to building homes in the highest risk areas. Reducing the risk to homeowners (and buyers) by subsidising their insurance creates an incentive for more houses to be built in high-risk locations. However, as the New Zealand Herald article notes:

Meanwhile, homeowners were still choosing to buy, develop and renovate coastal property, and new houses were being built in climate-risky locations, said the report's lead author, Dr Belinda Storey of Climate Sigma.

"People tend to be very good at ignoring low-probability events.

"This has been noticed internationally, even when there is significant risk facing a property.

"Although these events, such as flooding, are devastating, the low probability makes people think they're a long way off."

Storey felt that market signals weren't enough to effect change - and the Government could play a bigger role informing homeowners of risk.

Being unable to insure one of these properties creates a pretty strong disincentive to buying or building them. Perhaps withdrawal of insurance cover isn't a problem, it's the solution to a problem? 

*****

[*] Importantly, the homeowner with insurance doesn't face no incentive to avoid disaster risk, because while the loss of the home and contents may be covered by insurance, there is still a risk of loss of life, injury, etc. in the case of a disaster, and they will want to reduce that risk.

Gaming the Lambda School system and avoiding the tax

The New York Times reported last week:

Now, Silicon Valley is backing a novel idea that proposes to rewrite the economics of getting an education.

The concept is deceptively simple: Instead of charging students tuition — which often requires them to take out thousands of dollars in loans — students go to school for free and are required to pay back a percentage of their income after graduation, but only if they get a job with a good salary.

The idea, known as an Income Share Agreement, or I.S.A., has been experimented with and talked about for years. But what’s happening at Lambda School, an online learning start-up founded in 2017 with the backing of Y Combinator, has captivated venture capitalists...

At Lambda, students pay nothing upfront. But they are required to pay 17 percent of their salary to Lambda for two years if they get a job that pays more than $50,000. (Lambda says 83 percent of its students get a job with a median salary of $70,000 within six months of graduating.) If they don’t get a job, or their salary is lower, they pay nothing. Payments are capped at $30,000, so a highly paid student isn’t penalized for success, and if a student loses a job, the payments pause.

It is a model that so far has been aimed at vocational education but has the potential to end the crushing cycle of student debt and change the way schools think about students.

“It aligns the incentives fully,” said Mr. Lewis, the venture capitalist.

I'm not sure whose incentives are aligned here, but I doubt they are aligned fully in the way Mr Lewis thinks they are. Sure, the Lambda School has a strong incentive to make their graduates employable, and employable at a high salary, in order to maximise their return in the two years that the graduate is paying the 17 percent Lambda tax.

However, the student's incentives are not necessarily aligned with those of Lambda. They'd rather avoid paying that Lambda tax, and the more income they earn, they more they have to pay to Lambda. On the surface, the student still maximises their income by finding the highest paying job after graduation.

However, I'd say this system also creates some strong incentives for students in the opposite direction to what Lambda wants. There is an incentive for the student to engage in moral hazard. Moral hazard the tendency for someone who is imperfectly monitored to take advantage of the terms of a contract (a problem of post-contractual opportunism). In this case, the student takes advantage of their free tuition, but then tries to avoid paying the 17 percent Lambda tax.

There are several ways students could game the Lambda system, by their actions after completing their education. For instance, the student could choose to take the first two years off after graduating, thereby paying Lambda back nothing. Of course, the student also gives up two years of earnings, so that isn't very attractive. And in any case, surely Lambda has thought of that already and there is a contract clause preventing it (say, the students have to pay 17 percent of their first two years' working after graduation).

So, maybe the student could work as a volunteer, or in the Peace Corps? Or go on a Mormon mission? The student is still giving up their salary for two years, but they are adding to their CV and might earn more once they start working, and they don't have to pay anything to Lambda. Of course, Lambda could no doubt contract around those situations as well (e.g. 17 percent of the student's first two years of paid work after graduation).

So, what if the student joins a start-up and is paid a nominal salary in cash, which is less than the $50,000 threshold, and receives the rest of their salary as stock options? Again, Lambda could contract for that eventuality. So, the smart student play here might be to find an employer who would agree to some form of deferred salary payment, payable after more than two years and thereby not subject to the 17 percent Lambda tax. Or they go into self-employment and pay themselves the $50,000 salary, but the remainder in dividends. Or... you can probably see by now there are lots of alternatives to get around the Lambda tax.

Of course, not all students would engage in this opportunistic behaviour. But it's clear to me that Lamba's system is too easily exploited. One solution for Lambda (if they don't want to move to a formal student loan system) would be to have some minimum required payment, which would be paid back regardless of how many years it takes, and 17 percent for two years otherwise. That makes it less attractive for students to engage in moral hazard to avoid the Lambda tax.

[HT: Marginal Revolution]

Book review: Foolproof

One good thing about the Christmas break is that I have a lot of time for catching up on reading. So, it only took a couple of days for me to read Greg Ip's Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe.

I quite enjoyed the book, as at its heart it is about moral hazard and especially about unintended consequences, which regular readers of this blog will recognise is one of my favourite topics. However, Ip continually returns to financial crises, which nicely knits the book together into a coherent narrative. If you've already read books about the Global Financial Crisis, then I doubt you would gain much from reading this one, but Ip writes it in a very accessible way, and the links to moral hazard and unintended consequences mean that almost any student of economics will learn a lot, along with the general reader. The overall message is that because our economic institutions (like central banks) work hard to reduce risks to the economy, we end up taking more risks, so that when the system fails, it does so catastrophically.

Although the book has financial crises as an underlying theme, I generally enjoyed some of the other examples more (although I must admit, a lot of the stuff about the Volcker years in the U.S. was new to me). For example, this bit on floods:

Gilbert White, an obscure government geographer who had been pursuing graduate studies part-time at the University of Chicago, noticed that the frenzy of levee and dam building in the 1930s had not solved flooding; instead it had created a new problem: more homes, factories, and farms had sprung up on the floodplain, so more destruction ensued when floods overtopped the levees.

And this bit on helmets in the National Hockey League (NHL):

Helmets became mandatory for new National Hockey League players in 1979. Thereafter the number of head fractures went down, while the number of spinal injuries went up. The conclusion of several specialists was that a more aggressive style of play, perhaps encouraged by the wearing of helmets and full face masks, was causing players to hit one another harder in ways that made spinal injuries more likely.

The lessons from these other examples though, are targeted towards finance, such as this on the 1987 stockmarket crash:

Nonetheless, the crash taught an important lesson about insurance against financial catastrophes. It works when only a few people buy it; when everyone does, it not only makes the catastrophe more likely, it threatens the survival of the system...

Just as flood and earthquake insurance enable more people to live in flood- or earthquake-prone regions, insurance against market disruptions enables more investors to pile into those markets and perversely make the event more likely and more severe. Portfolio insurance had enabled this with stocks in 1987, and now CDSs [Credit Default Swaps] did the same with mortgages.

Ip doesn't get everything right though, at least from my perspective. In one section, he does a poor job of explaining Prospect Theory, and consequently the book stumbles over the distinction between loss aversion and risk aversion. Similarly, most economists would disagree with Ip that risk aversion is characteristic of behavioural economics, and not traditional economics. However, the general reader will not notice these errors.

As you might expect of a book about financial crises, Ip does come up with solutions. He concludes that:

Our goal should be to eliminate big disasters, not small ones, to accept a bit more risk and instability today in return for more reward and stability in the long run.

An analogy here (surprisingly not used in the book) is allowing children to take risks and hurt themselves a little, so that they can learn about their own limits and avoid catastrophe in the future. A few small boo-boos in the financial system should help us to reduce the chance of serious life-threatening events in the future. Overall, this is a good book for those interested in financial crises, but who don't want to do a deep dive into a book heavy on theory.

The economics of corporate lobbying

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

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

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

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

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

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

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

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

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

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

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

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

[HT: Marginal Revolution, back in January]

Principal-agent problems among Sicilian firefighters

In the first week of ECON110, we talk about unintended consequences. One of the examples I ask students to consider in class is what would happen if firefighters were paid for each fire they start, rather than bulk funded. Inevitably, someone always suggests that the firefighters might start fires themselves, in order to increase their funding. I always point out that seems unlikely, and that firefighters would more likely simply spend less effort on prevention activities. It turns out though, maybe those students were right. The Guardian reported back in August:

Fifteen volunteer firefighters have been arrested in Sicily on suspicion of starting wildfires and reporting non-existent blazes so they could earn €10 (£9) an hour for putting them out.

Police in Ragusa province, in the south of the Mediterranean island, said the fire department became suspicious when it emerged that the auxiliary brigade had responded to 120 incidents compared with just 40 tackled by other volunteer teams over the same period...

Most of the team were under investigation for fraud, with several also suspected of arson, Ansa said. The island is plagued by fires in summer and auxiliary firefighters are paid €10 an hour by the state to help extinguish them.

This is also a good example of a principal-agent problem (a type of moral hazard). In this case, the fire department is the principal, and it engages the volunteers (its' agents) to fight fires. However, the fire department probably doesn't want more fires, so the incentives of the fire department (less fires) and the volunteers (more fires, so that they get paid more) are in conflict. The agents will take advantage of the fact that they are not being closely monitored by the principal, in this case by lighting fires themselves.

There are four main ways to deal with moral hazard problems (including principal-agent problems):

1. Better monitoring of the agent (just keeping an eye on the volunteers to make sure they aren't up to no good, I guess - this appears to be what has happened in this case)
2. Efficiency wages (paying a wage that is higher than the equilibrium wage, so that if the agent is up to no good, then have an incentive to behave themselves or else they lose the higher-paying job and have to work somewhere else for a much lower wage)
3. Performance-based pay (paying based on some metric of output - probably this is where things went wrong in this case, since the volunteers were paid for each fire they fought!)
4. Delayed payment (holding back some part of the agent's wages until it is clear whether they did a good job - this works for contractors, but it might not be appropriate in this case).

Performance-based pay is not always the right solution to every moral hazard problem. In this case, it might well have been the cause of the problem in the first place!

[HT: Marginal Revolution]

Rockonomics: The economics of popular music

I really enjoyed my time in Seattle, and especially the Museum of Pop Culture. The plane trip from Seattle to Portland (which we also visited before returning to New Zealand) seemed an opportune time then to read this 2006 chapter (with the same title as this post) from the Handbook of the Economics of Art and Culture (ungated earlier versions here and here), by Marie Connolly and Alan Krueger (both Princeton).

That chapter had been sitting in my must-read pile for about ten years (!), but for whatever reason consistently kept getting bumped a little lower down the pile. It is important to me because the economics of popular music provides a lot of good illustrations of the things we teach in first year microeconomics. So given that ECON100 and ECON110 both start B Semester lectures next week, in this post I'm going to take some brief quotes (taken from the NBER working paper version of the chapter) from the chapter to illustrate some of the things we will cover in those papers.

Besides that, the chapter includes a lot of interesting detail on the structure of the music economy. Consider these bits, which relate to the ECON110 topic on media economics:

...it is clear that concerts provide a larger source of income for performers than record sales or publishing royalties. Only four of the top 35 income-earners made more money from recordings than from live concerts, and much of the record revenue for these artists probably represented an advance on a new album, not on-going royalties from CD sales... 

If a band composed its own music, it will also contract with a publisher to copyright the music... The publisher usually takes half the royalties, and the composer receives the other half (some of which goes to the manager).

...bands receive relatively little of their income from recording companies. Indeed, only the very top bands are likely to receive any income other than the advance they receive from the company, because expenses – and there are many – are charged against the bands advance before royalties are paid out...

Record companies tend to sign long-term agreements with bands that specify an advance on royalties and a royalty rate. The typical new band has very little negotiating power with record labels, and the advance rarely covers the recording and promotion costs, which are usually charged to the band. Because fixed recording costs vary little with band quality, only the most popular artists earn substantial revenue from record sales...

[Quoting Jacob Slichter, the drummer for Semisonic]: If our CD was sold in stores for fifteen dollars, the band’s share of the revenue might be something between fifty cents and a dollar per CD.

We cover moral hazard in both ECON100 and ECON110. Moral hazard occurs when one of the parties to an agreement has an incentive, after the agreement is made, to act in a way that brings additional benefits to themselves at the expense of the other party. In relation to that Connolly and Krueger write:

Caves prosaically notes that, “From the artist’s viewpoint, a problem of moral hazard arises because the label keeps the books that determine the earnings remitted to the artist.”

So, the recording label engages in moral hazard because it provides additional benefits to the label, and because the artists cannot easily monitor what the label is doing when it estimates earnings and costs and what should be paid to the artist. There are also a number of points that Connolly and Krueger write in relation to pricing (which we cover in ECON100), including:

As an economic good, concerts are distinguished by five important characteristics: (1) although not as extreme as movies or records, from a production standpoint concerts have high fixed costs and low marginal costs; (2) concerts are an experience good, whose quality is only known after it is consumed; (3) the value of a concert ticket is zero after the concert is performed; (4) concert seats vary in quality; (5) bands sell complementary products, such as merchandise and records...

The price of a concert ticket is set lower than it would be in the absence of complementary goods, because a larger audience increases sales of complements and raises revenue.

Firms that sell complementary products need not necessarily profit maximise for any of those products individually, if they can profit maximise across the whole range of their products. And in terms of price elasticity (covered in ECON100):

...despite flat or declining tickets sales, total revenues (in 2003 dollars) trended upwards until 2000 because of price increases. Other things equal, these trends suggest the elasticity of demand was less than 1 before 2000. Since 2000, however, there has been a 10 percent drop in ticket revenue for these artists, suggesting that prices increases have been offset by a larger than proportional demand response.

When demand is relatively inelastic, a given percentage increase in price is associated with a smaller percentage decrease in quantity demanded, so total revenues (price x quantity) increases. This is what happened prior to 2000, but after 2000 demand appears to have been elastic, so that the percentage increase in price was more than offset by a larger percentage decrease in quantity demanded, meaning that total revenues (price x quantity) decreased.

Connolly and Krueger cover inequality as well (as we will in ECON110):

...concert revenues became markedly more skewed in the 1980s and 1990s. In 1982, the top 1% of artists took in 26% of concert revenue; in 2003 that figure was 56%. By contrast, the top 1% of income tax filers in the U.S. garnered “just” 14.6% of adjusted gross income in 1998 (see Piketty and Saez, 2003). The top 5% of revenue generators took in 62% of concert revenue in 1982 and 84% in 2003.

And on intellectual property rights (which we cover in ECON110):

How far does intellectual protection go? Are rights strong enough to encourage the optimal amount of innovation? The problem stems from the fact that musical compositions are nonrival goods, whose property rights, as laid out by Nordhaus (1969), generate a trade-off between under-provision of the nonrival good (with weak rights) on the one hand and monopoly distortions (when the property rights are strong) on the other. 

Nordhaus's characterisation of the trade-offs inherent in intellectual property is one of the key pillars of the ECON110 topic on intellectual property rights. There are other bits of interest, including ticket scalping (which we cover in both ECON100 and ECON110), signalling (also both ECON100 and ECON110), and superstar effects (which we discuss in ECON110). A few parts of the chapter are a little technical, but all of it is interesting, and there are lots of gems to take away. Some parts of the chapter are getting a little dated, but mostly it has aged well and if you like to see economics in action, I encourage you to read it.

Beware bogus taxi surcharges when travelling on an expense account

In my ECON100 and ECON110 classes, we discuss moral hazard. In ECON110, we also discuss supplier-induced demand. So, I was interested to read this new paper (ungated earlier version here) by Loukas Balafoutas (University of Innsbruck), Rudolf Kerschbamer (University of Innsbruck), and Matthias Sutter (European University Institute), published in the journal The Economic Record.

In the paper, Balafoutas et al. look at moral hazard among taxi drivers. Recall that moral hazard is the tendency for a person who is imperfectly monitored to engage in dishonest or otherwise undesirable behaviour. That is, moral hazard is a problem of post-contractual opportunism, where people have the incentive to change their behaviour to take advantage of the terms of the agreement (or contract) to extract additional benefits for themselves, at the expense of the other party.

However, what the authors are looking at in this paper isn't your run-of-the-mill moral hazard. They distinguish it as what they call second-degree moral hazard:

As an illustration consider the market for health care services and assume that the consumer of the service – in this case, a patient – is fully insured and interacts with a seller of the service – in this case, a physician. Moral hazard implies that the patient may have incentives to demand more of the service than required (by asking for more numerous or more extensive tests or treatments), since he will not bear its costs. However, the behaviour of the physician may also be affected by the extent of the coverage: if the physician expects that the patient is not concerned about minimising costs, he may be more inclined to suggest or prescribe more expensive treatments. Notice that the two stories – which we will call first-degree moral hazard and second-degree moral hazard – are observationally equivalent in terms of final outcomes, in the sense that more extensive insurance coverage leads to higher expenditure, but the mechanisms are different. While first-degree moral hazard operates through the demand side, second-degree moral hazard increases expenditure through supplier-induced demand – the artificial increase in demand induced by the actions of the seller.

Supplier-induced demand occurs when there is asymmetric information about the necessity for services. In a city that is unfamiliar to the taxi passenger, they may not know the shortest route to get to their destination, whereas the taxi driver does. So, the taxi driver has an incentive to take the passenger on a longer (and more expensive route). Balafoutas et al. note:

In the case of taxi rides in an unknown city, the service traded on the market is a credence good... meaning that an expert seller possesses superior information about the needs of the consumer. In particular, the driver knows the correct route to a destination while the consumer does not. This property of credence goods opens the door to different types of fraud: overtreatment occurs when the consumer receives more extensive treatment than what is necessary to meet his needs (with taxi rides, this amounts to a time-consuming detour); in the opposite case of undertreatment, the service provided is not enough to satisfy the consumer (i.e. he does not reach his destination); finally, in credence goods markets where the consumer is unable to observe the quality she has received, there might also be an overcharging incentive, meaning that the price charged by the seller is too high, given the service that has been provided.

The paper uses an interesting field experiment to tease out how (and by how much) taxi drivers engage in second-degree moral hazard behaviour. They used four research assistants (two male, two female), who each took 100 trips across Athens. All four of them went on each trip within a few minutes of each other (to ensure they faced similar traffic situations, etc.), and two of them (one male, one female) made it clear to the driver that their (the passenger's) employer was paying for the ride (which I guess was true - the researchers no doubt paid for these rides). The research assistants then recorded the price paid for the journey, plus measured the distance travelled using a portable GPS. This allowed the authors to compare rides between male and female passengers, as well as between the 'moral hazard treatment' and control. They found that:

our moral hazard manipulation has an economically pronounced and statistically significant positive effect on the likelihood and the amount of overcharging, with passengers in that treatment being about 17% more likely to pay higher-than-justified prices for a given ride. This also leads to significantly higher consumer expenditures in this treatment on average. At the same time, the rate of overtreatment (by taking time-consuming detours) does not differ across treatments. Hence, second-degree moral hazard does not increase the extent of overtreatment compared to the control, while it does increase the likelihood and the extent of overcharging.

The actual mechanism of the overcharging was interesting:

In the large majority of these cases (86 out of 112, or 76.8%) bogus surcharges were applied, namely higher-than-justified extras from and to the airport, the port, the railway station and the bus station. The second most frequent source of overcharging (14 cases) were manipulated taximeters or the use of the night tariff during daytime, while rounding-up (not tipping!) of the price (by more than 5%) accounted for the remaining twelve cases of overcharging.

I also found it interesting that in the control, female passengers were more likely to pay a higher fare than male passengers. However, in the moral hazard treatment (i.e. when passengers told the drivers their employer was paying) there was no gender difference in overcharging.

Overall, this is a really interesting use of a field experiment to tease out results that would not be easily possible in other ways. The only part of the paper that made me a little concerned was buried in a footnote:

We note that the sample initially consisted of 256 observations collected in 2013. The remaining 144 observations were collected in 2014 at the advice of the editor and referees and resulted in stronger statistical significance. Based on the initial sample alone, some of the results outlined in subsection 2.2 were only marginally significant.

This trick of boosting the sample size in order to generate effects that are statistically significant is a trick that experimental psychologists use, and shouldn't really be condoned. It's been implicated in the replication crisis that psychology is facing. At least they were up-front about it, and the results were published. But imagine, if the results became less statistically significant, then what do they do? Not publish? Or continue to collect additional data, until eventually they attain some statistical significance?

Anyway, that little gripe aside, I found this paper a good read, with important implications. One of which is that I will certainly be looking out for bogus taxi surcharges the next time I take a taxi from the airport in a strange city.

[HT: The Economist]

The economics of kidnapping and ransom insurance

Anja Shortland (King's College London) recently wrote a piece for the Washington Post's Monkey Cage, on the economics of kidnapping and ransom insurance, based on her forthcoming article in the journal Governance (sorry I don't see an ungated version online). I was intrigued, so I read the journal article, and it has lots of bits of interest, such as:

The market for kidnap insurance is characterized by externalities: Cash-rich victim stakeholders can increase kidnappers’ ransom expectations and encourage new kidnappings. Insurers need to prevent quick payments of premium ransoms, but can only do so at a cost...

For the market to be stable and risks to be calculable, this externality needs to be managed. Given the impossibility of enforcing “proper” ransom negotiations through contracts due to high transaction costs, the Coasean prediction would be a single supplier of kidnap insurance...

The Lloyd’s solution is, therefore, an ingenious answer to the problems presented by kidnap insurance. All kidnap insurance is underwritten or reinsured at Lloyd’s...

Kidnap insurance at Lloyd’s is, therefore, a perfect example of the way in which externalities and transactions costs shape the institutions, which make up the economic system...

In ECON100 and ECON110, we talk about the private solutions to an externality problem, one of which is integration - the party creating the externality and the party suffering from the externality combine into a single entity (the classic example is a beekeeper and an orchard, who combine into a single firm - an example which I've written about before). Shortland argues that this is also the case for kidnapping and ransom insurance. If victims' families pay too much ransom, then they impose additional costs on future kidnap victims' families, because kidnappers will expect larger ransoms to be paid. Because all kidnap insurance is underwritten or reinsured at Lloyd’s, this is like integration (though not exactly, since this is integration into a single market space and not into a single firm). It allows easy sharing of information about kidnappings and ransoms paid, and ensures that all insurers follow the 'rules' that reduce any externality problems. Because Lloyd's has complete control over who can be part of this market, it is relatively easy to enforce standards of behaviour for the insurers.

It also explains why these insurers offer pro bono advice to the uninsured. By controlling negotiations between the uninsured victims' families (or employers) and kidnappers, the insurers (or rather, their agents) can reduce any spillover externalities. That is, they ensure that future ransoms will not escalate because of excessive ransom payments by uninsured victims' families or employers.

Now, we know insurance leads to moral hazard problems. Moral hazard arises when, after an agreement is made, one of the parties has an incentive to change their behaviour (usually to take advantage of the terms of the agreement) in a way that harms the other party. In the case of kidnapping and ransom insurance, once a person has insurance their incentives change slightly - they may engage in riskier behaviour safe in the knowledge that any future ransom will be paid by the insurer. So, we might expect to see people take fewer precautions to avoid being kidnapped. So, I found this bit from the article interesting:

The maximum cover is limited to the ransom the client (corporate or family) can raise themselves. The ransom is reimbursed after payment and the insurance contract cannot be used as collateral—meaning the victim stakeholders actually have to raise the ransom themselves initially. Employers are not allowed to discuss the insurance with their employees—doing so invalidates the insurance cover... All these stipulations serve to reduce moral hazard among the insured.

So, because the victim doesn't fully avoid the costs of being kidnapped (and probably does not even know they are insured!), the moral hazard problems are reduced.

Finally, back to externalities, Shortland identifies a real problem with governments negotiating directly with kidnappers on behalf of victims' families:

Governments that intervene on behalf of kidnapped citizens regularly pay premium ransoms... Unlike the participants in the private governance regime, governments often act myopically and under media pressure. They have neither binding budget constraints nor a profit motive to contain ransoms. There is no mechanism to internalize the spillovers of one government’s settlements on other negotiations. Paying multimillion dollar ransoms solves political problems in the short term but confers significant externalities on concurrent and future victims, their governments, and the insurance sector.

I'd suggest that there is a case for governments to also rely on the services of the insurers' agents, rather than handling these negotiations themselves. If they can do so anonymously (as the insurers do), then the outcome would be better, in terms of lower future ransoms and lower incentives for kidnappers.

[HT: Marginal Revolution]

Wage segregation, asymmetric information and inequality

Samuel Hammond wrote a post for the Niskanen Center blog that might be one of the clearest and most insightful blog posts I've ever read. Hammond writes about increasing wage segregation in the U.S. labour market, but the insightful bit is to link it to reductions in information asymmetry between employers and workers. I'll refrain from wholesale copying-and-pasting most of the post, which you should read! Here is the most important bit:

How does this apply to technological change, wages, and inequality?

Think back to the naive insurer attempting to “pool” high and low risk types under one premium. Now substitute insurer with employer, and high and low risk types with low and high productivity workers, and the flat premium with a relatively flat wage structure.

Our nostalgic vision of the mid-20th century’s strong middle class is a memory of a wage pooling equilibrium that eventually unraveled. Behemoth corporate employers priced labor in a relatively naive way, given an inability to observe the heterogeneity of individual productivity moment by moment, and the role of labor unions in negotiating wages as a collective. While there was still a premium on things like seniority and higher education, wages were nevertheless fairly compressed.

For workers who contributed substantially more value to the company than they were being paid for, this was a raw deal. Conversely, it was great deal for workers whose productivity lagged. In other words, high productivity workers bore a negative externality by having to partially subsidize low productivity workers due to the inherent opacity of who-contributes-what within team production.

That has changed with information technology that makes it easier than ever to observe and measure individual worker productivity and screen for it accordingly (which may be why the premium from working at larger firms has also diminished).

Wage segregation is of course important because it is one of the causes of the recent increase in inequality observed in the U.S. The previous pooling equilibrium led both high and low productivity workers to have roughly the same wages, because it was difficult for employers to tell them apart. With the (technological) ability to more closely monitor and measure worker performance, the high and low productivity workers can be separated, allowing firms to reward the high productivity workers with higher wages (and not reward low productivity workers).

Now, having said all that it makes me wonder - why isn't inequality increasing in New Zealand for the same reason? As Eric Crampton has noted many times, inequality has barely changed in New Zealand since the mid-1990s. Surely we must have wage segregation here as well? What gives?

Should landlords offer efficiency rents?

Last week, Ron Goodwin wrote in the New Zealand Herald about the problems of being a landlord:

You think it's easy being a landlord? All we do is sit around and randomly put up rents when our Jags need servicing. Capitalist pigs, feeding from the trough of tenants' misery. Apparently we bunch people's undies too...

Last week, my hired rental inspector and I went to my worst tenants' house. The whole place was a trashed pigsty. Broken windows, the kitchen vinyl torn to bits beyond recognition, the lounge carpet covered in big black stains and torn, rubbish piled up around the place, torn and missing curtains, the deck gate smashed, the main steel driveway gate bent beyond repair.

These are tenants who wrecked an outside tap and then left it running, and who throw much of their rubbish out the windows, over the deck and out the doors into the yards and landscaped gardens...

Anyone want this lot living in their house?

This got me thinking. There are good tenants and bad tenants, and it is difficult for landlords to regulate tenants' behaviour after they have signed the rental agreement. Given this is moral hazard and efficiency wages is one way to deal with moral hazard in labour markets, is there a rental market equivalent of efficiency wages?

First, some context. In ECON100 and ECON110, we discuss moral hazard and agency problems. One such problem is where employees' incentives (after they have signed their employment agreement) are not aligned with those of the employer. The employer wants their employees to work hard, but working hard is costly for the employee so they prefer to shirk. One potential solution to this is efficiency wages (I've previously discussed efficiency wages here). With efficiency wages, employers offer wages that are higher than the equilibrium wage, knowing that this will encourage higher productivity and lower absenteeism from their workers. This is because if workers don't work hard (and avoid absenteeism), they may lose their jobs and have to find a job somewhere else at a much lower rate.

Which brings me to landlords and efficiency rents. As noted above, there is a moral hazard problem for landlords - tenants' incentives (to look after the property) are not aligned with the landlord's incentive (to keep the property in top condition). If the landlord instead offered an efficiency rent (a rent below the equilibrium market rent), then they would have many potential tenants applying for the property, allowing the landlord to pick the best (the least likely to damage the property). It also gives the tenants an incentive to look after the property after signing the tenancy agreement, because if they don't they get evicted and have to find another place to live at a much higher cost.

Maybe landlords offer efficiency rents already and we just don't realise it? There is certainly plenty of evidence for excess demand for rental properties (see here or here for example), so maybe rents are below equilibrium (though they are rising quickly so it's possible that the observed below-equilibrium rents are simply in transition to a higher equilibrium level). Excess demand by itself is pretty weak evidence for efficiency rents. I'd want to hear landlords telling us they offer lower rents to attract good tenants before I found it believable. There's not a lot of evidence in the academic literature on efficiency rent either (see this paper by Basu and Emerson as one example, ungated here).

So, why wouldn't landlords offer efficiency rents? If it is difficult to evict tenants due to tenant protection laws, then that lowers the incentives for tenants to look after the property (since the risk of eviction is lower, or they know it will take a long time before they are eventually evicted, as Ron Goodwin's article suggests). This in turn reduces the incentives for landlords to offer lower rents than the equilibrium rent - why take the risk?

Would efficiency rents be a good thing? Would they have some of the same effects as rent control (which I have discussed here and here, and which we cover in both ECON100 and ECON110)? Perhaps. There would certainly be excess demand at the level of the efficiency rent. However, if not all landlords are offering efficiency rent, there need not be excess demand overall - this might simply be a way of allocating low rent houses to low cost tenants (i.e. those who would look after the properties), with high cost tenants paying higher rents.

Why performance pay may underperform

Tim Harford wrote an interesting piece last month about performance pay. He wrote:

Here’s an age-old management conundrum: who should be rewarded for high performance, and how? As Diane Coyle, the economist and former adviser to the UK Treasury, recently observed in this newspaper, the answer to the question is usually self-serving. Simple and easily monitored jobs, such as flipping burgers, are natural candidates for performance incentives. Yet somehow it’s the inhabitants of the C-suite who tend to pick up bonuses, despite the fact that their complex, hard-to-measure jobs are poorly suited to the crude nature of performance-related pay.

Harford (as always) does a great job of summarising the state of research in this area. He correctly identifies that financial rewards don't work in all situations. I'm going to use this post to highlight the factors that must be in place for a performance pay scheme to work well - the absence of one or more of these factors will lead to a performance pay scheme that won't work so well.

First though, some background. Why have performance pay? Employers face a problem we refer to as the principal-agent problem (a specific type of moral hazard). The employer (the principal) engages an employee (the agent) to work on their behalf. However, the goals of the employee are rarely perfectly aligned with the goals of the employer. So, because the employer cannot easily monitor all of the employee's activities, the employee can engage in activities that are not necessarily in the best interests of the employer (like goofing off). Rewarding employees for meeting set targets (and performance pay more generally) is one way of re-aligning the interests of the employee with those of the employer (other options include closer monitoring of employees, and paying efficiency wages, which I have previously discussed here). However, for performance pay to work well a number of things factors need to be present.

First, employees must respond to incentives. This seems like a given, since one of the assumptions economists make is that people respond to incentives. However, it might not always be true. If employees are already highly paid, and the performance payment is small, it might not be enough incentive to encourage greater work effort. So, if you are selling farm machinery, for performance pay to work well your salespeople must be willing to try to earn more sales to capture the performance pay (e.g. commissions).

Second, employees' output must be sensitive to their effort. If employees work harder but the additional effort does not enable them to produce (or sell) more, then rewarding them with performance pay simply won't work well. Why waste your time working harder if it doesn't lead to more output (and higher pay)? So, for performance pay to work well your farm machinery salespeople must be able to sell more tractors if they work harder (at trade shows, visiting potential clients, etc.).

Third, employees' output must be measured easily. If you are going to reward employees for their performance, you must be able to objectively measure their performance. On top of that, employees must be able to believe that the measurement of their performance is accurate. Measurements that are not credible will not encourage employees to work harder. So, for performance pay to work you must be able to know how many tractors each salesperson is selling.

Fourth, employees must not be too risk averse. Risk averse people prefer a higher degree of certainty. Performance pay reduces the certainty of employees' incomes, so if they are highly risk averse they will prefer to work elsewhere (this may or may not be a good thing!). So, your farm machinery salespeople must be willing to accept some likely fluctuations in their salary (as their sales increase or decrease from month to month).

Finally, the level of risk that is beyond the employees' control must be low. If employees' performance depends on their own effort, but also on other factors that are beyond their control, then rewarding high performance may not necessarily increase work effort. This will be a greater problem the greater the share of employee performance that is driven by the external factors. So, if farm machinery sales are driven more by the weather and how farm profits are going, and less by the efforts of the individual salespeople themselves, it will not work so well.

On that last point though, one work-around is to reward employees for their relative performance, i.e. their performance relative to their peers, to industry benchmarks, or to agreed targets. However, it is possible to take performance pay too far - to the extent where competition between different employees is encouraged to an unhealthy extent. In any case, performance pay is one method of dealing with underperforming employees - but if the factors noted above are not present the performance pay scheme itself may well underperform.

Consumer technology and insurance fraud

This week is International Fraud Awareness Week. So, this story in the New Zealand Herald last week was a bit early. It notes:

Insurance fraud spikes whenever a new technology upgrade, such as the release of a new iPhone, occurs, says Dave Ashton, head of the Insurance Council's Insurance Claims Register...

Speaking at the council's annual conference this week, Ashton said when new technology was released, many people want to upgrade their model and therefore claimed their older models had been stolen, lost, or accidentally damaged. The ensuing insurance pay-out funded the new upgrade.

This type of insurance fraud is an example of what economists call moral hazard. Moral hazard is the tendency for someone who is imperfectly monitored to take advantage of the terms of a contract (a problem of post-contractual opportunism). Smartphone owners who are uninsured have a large financial incentive to look after their devices and avoid dropping them in the toilet (which I note one of our previous ECON100 tutors did, twice), because if they damage the device they must cover the full cost of repair ore replacement themselves (or use a damaged phone, etc.). Once their phone is insured, the driver has less financial incentive to look after their device because they have transferred part or all of the financial cost of any accident onto the insurer. The insurance contract creates a problem of moral hazard - the smartphone owner's behaviour could change after the contract is signed.

Things are worse in the case of the type of insurance fraud noted in the article. This goes beyond simply being less careful, and extends to deliberate misrepresentation to take advantage of the terms of the insurance contract.

If you want to understand why, you only need to consider the incentives. A rational (or quasi-rational) person makes decisions based on the costs and benefits, e.g. the costs and benefits of claiming that your old phone was stolen. The benefit is the added benefit from the new phone (compared with the old phone). The costs are the moral cost (from lying to the insurance company), as well as the expected cost associated with being caught (which depends on the probability of being caught, and the financial penalty you face if caught).

Most people don't engage in insurance fraud because the combined costs (moral plus potential financial punishment) are greater than the perceived benefits. However, when a new phone is released the benefits of fraud increase significantly (because the new phones provide a much increased benefit). Again, this doesn't mean that everyone will engage in insurance fraud, but at least some people will.

Insurance companies are not stupid though, and they are moving on this, according to the Herald article:

The council this week launched upgraded technology on the register which allows more 'big data' analysis, including hotspots such as the number of burglary claims in a particular neighbourhood. It can also provide predictive analysis around likely claims for things like weather events based on the collective claims history.

So you can probably expect your next claim for a damaged iPhone to come under a little more scrutiny, if you are claiming just after a new phone is released.

Read more:

• How to beat the fitness trackers (for cheaper health insurance)
• Why your Fitbit or Apple Watch could soon get you cheaper health insurance
• Could technology eliminate moral hazard in car insurance?