Let me begin with a thought experiment. Imagine you have a Platinum health plan, meaning that your insurance covers (almost) all the costs for a very large variety of treatments and diagnostic tests – in exchange, of course, for a high monthly premium. After years of paying the premium without ever needing to use medical insurance, eventually the day arrives when you are not feeling well and visit the hospital. After a consultation, the doctor explains to you that there are different treatments available for your condition, with varying degrees of costs. She also mentions the possibility of running some additional tests, which are not really necessary – but just to be on the safe side.

What would you do? Well, most likely, you would opt for the most extensive and most expensive treatments and tests: after all, the expenses are fully covered by your insurance. In economics, this phenomenon is called moral hazard: since you are not liable for paying for the treatments and tests yourself, you have no reason to make an effort to reduce costs.

Now let us consider the doctor’s incentives. Sure enough, her main concern is hopefully your well-being. But, since you are now in hospital, and since you are the proud owner of a Platinum health plan, perhaps she is tempted to order a couple of expensive additional tests, or even provide expensive and unnecessary treatments that she would not have performed for someone with very basic or no insurance.

Why? Because your insurance will pay for everything, and so she anticipates that you do not mind the higher costs – according to the premise of the moral hazard problem outlined just above. This kind of mechanism puts a strain on the finances of public healthcare and contributes to high government deficits and to high insurance premia.

This is the kind of story our study examines, using a controlled field experiment. But we did not conduct our study in the heath care sector. As a matter of fact, health services are just one example of a wide class of goods and services that most of us consume on a very regular basis, called credence goods. With credence goods, an uninformed consumer must put his faith in an expert who can perform a diagnosis and then recommend an appropriate quality of service.

Typical examples of credence goods (besides healthcare) include repair services (think of car or computer repairs), financial services, legal services, and many others. Taxi rides also belong on this list: taking a taxi ride in an unknown city means you have to rely on the driver to take the most appropriate route to your destination and to charge the appropriate price. Many of us have sometimes suspected that a driver took a detour in order to increase the fare, or even that he or she somehow cheated us on the price of the ride. As with doctors, the problem here is that the customer is unable to verify whether the service he received was the right one, and this creates opportunities for fraud.

In our experiment we sent four research assistants on 400 undercover rides in Athens, Greece. Every time they entered a taxi, they indirectly let the driver know that they were unfamiliar with the city, and hence signalled that the driver possessed superior information that he could potentially exploit by taking a longer route or inflating the expenses. In addition, in half of the rides, our undercover passengers also mentioned that they would need a receipt because they would have their expenses covered by their employer. Does this sound familiar? It is quite like the doctor’s example at the beginning of this text. The driver, anticipating that his passenger does not mind paying a higher price, may act in a way that increases expenditure.

This is precisely what we found in our data. Mentioning a fictitious employer who covers the costs of the ride increased the average price paid for a ride by 6.7 per cent. This increase did not result from longer detours, but rather from a higher likelihood of dishonest charging behaviour: the incidence of such cases (for instance, through fake additional charges or manipulated taximeters) was 37 per cent with cost reimbursement, compared to 20 per cent without. We should also mention that we observe gender differences in this context, with women paying 2.6 per cent more than men on average for the same ride.

What do our results mean for the economy and for practitioners? Well, for one, our story directly applies to the relationship between firms and their employees. Our data show that travel costs can be unnecessarily high for a sponsoring employer, while the same is likely to apply to expense accounts and in general to every situation where employees are not liable for paying for various goods and services themselves and have weak incentives to minimise costs.

Our results are also in line with the large body of anecdotal evidence indicating that a substantial share of the realised costs in the healthcare sector could be avoided. All of the above mean that there is an incentive for funders (like employers or insurance companies) to reduce their costs by means of some kind of fraud-restraining institutions or strategies. For instance, employers could buy their own fleet of cars and run a chauffeur service for their employees, with drivers paid with fixed wages. In the medical industry, managed care basically works in a similar way: health maintenance organisations (HMOs) hire their own doctors and pay them in a way as to contain costs. As for consumers, unless they don’t mind inflated bills, they are well-advised to keep this information in mind when interacting with experts.



  • This post post is based on the author’s paper Second-Degree Moral Hazard In A Real-World Credence Goods Market, co-authored by Rudolf Kerschbamer and Matthias Sutter, in The Economic Journal, Volume 127, Issue 599, February 2017, Pages 1–18
  • The post gives the views of its authors, not the position of LSE Business Review or the London School of Economics.
  • Featured image credit: Athens Syntagma Square, by Юкатан, own work, under a CC BY-SA 3.0 licence or GFDL, via Wikimedia Commons
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Loukas Balafoutas is Professor of Experimental Economics in the Department of Public Finance at the University of Innsbruck. He holds a Ph.D. in Economics from the University of Edinburgh, has taught at various universities and also worked at the OECD Development Centre. His research focuses on the behavioural underpinnings of economic activity and uses laboratory and field experiments to study behaviour in areas such as fraud in markets with asymmetric information, tournaments, public goods, property rights, and social norms. Prof. Balafoutas has published his work in several peer-reviewed academic journals. His work has also attracted substantial media attention in television, radio, and the press.