When is more competition bad?

Contrary to popular belief, standard economic theory does not provide a theoretical foundation for the notion that "competition is everywhere and always good." It turns out that legislation that promotes competition among producers may improve consumer welfare. Or it may not. As so many things in economics (and in life), it all depends.

I recently came across an interesting paper demonstrating this idea by Ben Lester, Ali Shourideh, Venky Venkateswaran, and Ariel Zetlin-Jones with the title "Screening and Adverse Selection in Frictional Markets," forthcoming in the Journal of Political Economy.The paper is written in the standard trade language. Like any trade language, it's difficult to understand if you're not in the trade! But I thought the idea sufficiently important that I asked Ben to translate the basic results and findings for a lay audience. I'm glad to say he was very happy to oblige.

And so, without further ado, today's guest post by Ben Lester, my colleague at the Philadelphia Fed.
You can follow Ben on Twitter :  @benjamminlester 

Competition in Markets with Asymmetric Information

By Benjamin Lester

Background

In many basic economic models, competition is good – it increases welfare.  As a result, policy makers often introduce reforms that they hope will reduce barriers or “frictions” in order to increase competition.  For example, the Dodd-Frank Act contains regulations aimed at promoting more competition in certain financial markets, such as derivatives and swaps, while the Affordable Care Act contained provisions that were intended to promote competition across health insurance providers.

In a recent paper with Ali Shourideh, Venky Venkateswaran, and Ariel Zetlin-Jones, we re-examine the question of whether more competition is welfare-improving in markets with a particular feature – what economists call “asymmetric information.”  These are markets where one side has information that is relevant for a potential trade, but the other side can’t see it. Classic examples include insurance markets, where an individual knows more about his own health than an insurer; loan markets, where a borrower knows more about her ability to repay than a lender; and financial markets, where the owner of an asset (like a mortgage-backed security) may know more about the value of the underlying assets than a potential buyer.

Unfortunately, understanding the effects of more or less competition in markets with asymmetric information has been constrained by a shortage of appropriate theoretical frameworks.  As Chiappori et al. (2006) put it, there is a “crying need for [a model] devoted to the interaction between imperfect competition and adverse selection.”

What we do

We develop a mathematical model of a market – to fix ideas, let’s call it an insurance market – that has three key ingredients.  The first ingredient is adverse selection: one side of the market (consumers) know more about their health than the other side of the market (insurers).  Second, we allow the two sides of the market to trade sophisticated contracts: as in the real world, insurers can offer consumers a rich set of options to choose from, consisting of different levels of coverage that can be purchased at different prices.  Last, we introduce imperfect competition by assuming that consumers don’t always have access to multiple insurers: in particular, each consumer will get offers from multiple insurers with some probability, but there is also a chance of receiving only one offer.[1]  Hence, our model allows us to capture the case of perfect competition (where all consumers get multiple offers), monopoly (where all consumers get only one offer), and everything in between.

What we find

One of our main results is that increasing competition can actually make people worse off.[2]  To understand why, it’s important to understand the types of contracts that our model predicts will be offered by insurers.  Let’s say that there are two types of consumers: those who are likely to require large medical expenses (“sick” consumers), and those who are not (“healthy” consumers).  Then insurers will often find it optimal to offer two different plans: one that is expensive but provides more coverage, and one that is cheaper but provides less coverage.[3]  Designed correctly, these two options will induce consumers to self-select into the plan intended for them, so that sick consumers will pay a higher price for more coverage and healthy consumers will pay a lower price for less coverage.

An important property of these contracts is that they fully insure sick consumers, but they under-insure healthy consumers.  Ideally, insurers would like to offer healthy patients more coverage, but they can’t: given the lower price, sick consumers would choose this new plan, making it no longer profitable for insurers to offer it.  This theoretical result – that separating the sick from the healthy requires under-insuring healthy consumers – is a fundamental result in markets where asymmetric information is present.  The relevant question for us is: how does the amount of competition determine the extent to which healthy consumers are under-insured? The answer we find is that some competition can induce insurers to provide healthy consumers with more insurance, but too much competition can have the opposite effect. 

The intuition is as follows.  When consumers are more likely to receive multiple offers, insurers respond by making more attractive offers to consumers, as they try to retain market share.  The key question turns out to be: does increasing competition make them sweeten the deal more for sick consumers, or for healthy consumers? On the one hand, as the offer intended for sick consumers gets better, they have less incentive to take the offer intended for healthy consumers – in the parlance of economics, their “incentive constraint” loosens.  Hence, as insurers sweeten the offer intended for sick consumers, they are able to offer healthy consumers more coverage, and welfare rises.[4]  On the other hand, however, as the offer intended for healthy consumers become more attractive, sick consumers are more tempted to take it – their incentive constraint tightens – and the only way to keep the two separate is to reduce the amount of coverage being offered to healthy consumers, causing welfare to decline.

In the paper, we show that the former, positive effect dominates in markets where insurers have a lot of market power, while the latter, negative effect dominates when the market is relatively competitive. Hence, in markets with asymmetric information, welfare is maximized at some interior point, where there is some competition, but not too much!

Other results and future research

In the paper, we also show that increasing transparency has ambiguous effects on welfare.  In particular, we study the effects of a noisy signal about a consumer’s type – in the insurance example, this could be a blood test or information about an individual’s pre-existing conditions.  We show that increasing transparency is typically beneficial when insurers have a lot of market power, but it can be detrimental to welfare in highly competitive environments.

More generally, our model provides a tractable framework to confront a variety of theoretical questions regarding markets that suffer from asymmetric information, and offers a number of insights into existing empirical studies, too.[5]  For example, there is a large literature that tests for the presence of asymmetric information by studying the quantitative relationship between, e.g., the amount of insurance that consumers buy and their tendency to get sick.[6]  However, according to our analysis, insurers find it optimal to offer menus that separate consumers only when markets are sufficiently competitive, and when there is a sufficiently large number of sick consumers in the population.  Otherwise, they find it best to offer a single insurance plan.  This finding implies that, when insurers have sufficient market power, there will be no relationship between the quantity of insurance a consumer buys and his health status.  In other words, one can’t empirically test for asymmetric information without controlling for the market structure.  This is just one of many positive predictions of our model that we plan to test in the data.

References:

Burdett, K., and K. L. Judd (1983) “Equilibrium Price Dispersion,” Econometrica, 51, pages 955–69.

Chiappori, P.-A., B. Jullien, B. Salanié, and F. Salanié (2006) “Asymmetric Information in Insurance: General Testable Implications,” RAND Journal of Economics, 37, pages 783–98.

Chiappori, P.-A., and B. Salanié  (2000) “Testing for Asymmetric Information in Insurance Markets” Journal of Political Economy,  108, pages 56–78.

Lester, B., A. Shourideh, V. Venkateswaran, and A. Zetlin-Jones (2018) “Screening and Adverse Selection in Frictional Markets,” Journal of Political Economy, forthcoming.

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[1] We borrow this modeling device from the paper by Burdett and Judd (1983).

[2] At a high level, the idea that reducing frictions can sometimes make people worse off is not unique to our paper; these types of results are known from the theory of the second best. What distinguishes our result is the context in which it arises, and our ability to characterize precisely when and why reducing frictions (or increasing competition) is harmful.

[3] The negative relationship between price and coverage should be familiar to most readers; see, e.g., the metal tiers (platinum, gold, silver, bronze) offered at https://www.healthcare.gov/choose-a-plan/plans-categories/.

[4] Since sick consumers are always fully insured, consumers’ welfare always rises when healthy consumers are offered more insurance.  On a more technical level, all of our statements about welfare are based on a measure of ex ante, utilitarian welfare.
[5] As a technical aside, unlike many models of asymmetric information and screening, we find that an equilibrium always exists in our environment, that the equilibrium is unique, and that the equilibrium does not rely on any assumptions regarding “off-path beliefs.”

[6] See the seminal paper by Chiappori and Selanie (2000).

Disclaimer

The views expressed here are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System.