Alberto Alesina and Oliver Williamson: Taking Political and Economic Frictions Seriously

Very sad news this week for the economics community: both Oliver Williamson and Alberto Alesina have passed away. Williamson has been in poor health for some time, but Alesina’s death is a greater shock: he apparently had a heart attack while on a hike with his wife, at the young age of 63. While one is most famous for the microeconomics of the firm, and the other for political economy, there is in fact a tight link between their research agendas. They have attempted to open “black boxes” in economic modeling – about why firms organize the way they do, and the nature of political constraints on economic activity – to clarify otherwise strange differences in how firms and governments behave.

First, let us discuss Oliver Williamson, the 2009 Nobel winner (alongside Elinor Ostrom), and student of Ken Arrow and later the Carnegie School. He grew up in Superior, Wisconsin, next to Duluth at the frigid tip of Lake Superior, as the son of two schoolteachers. Trained as an engineer before returning to graduate school, he had a strong technical background. However, he also possessed, in the words of Arrow, the more important trait of “asking good questions”.

Industrial organization in the 1960s was a field that needed a skeptical mind. To a first approximation, any activity that was unusual was presumed to be anti-competitive. Vertical integration as anticompetitive was high on this list. While Williamson was first thinking about the behavior of firms, the famous case of U.S. vs. Arnold, Schwinn reached the Supreme Court. Schwinn, the bicycle company, neither owned distributors nor retailers. However, it did contractually limit distributors from selling bikes to retailers that were not themselves partnered with Schwinn. In 1967, the Supreme Court ruled these contracts an antitrust violation.

Williamson was interested in why a firm might limit these distributors. Let’s start with the ideas of Mr. Coase. Coase argued that transactions in a market are not free: we need to find suppliers, evaluate quality, and so on. The organization of economic activity therefore attempts to economize on these “transaction costs”. In the Coasean world, transaction costs were nebulous, and attracted a great deal of critique. As Williamson, among many others, points out, both buying from a supplier and vertical integration require transaction costs: I need to haggle over the price of the component or else the price of the whole company! Therefore, in an unchanging world, it is not clear that integration does anything to reduce the transaction costs of evaluating what my partner – in procurement or in merger – is capable of. In the case of Schwinn, the transaction costs must be incurred whether we are debating how to split profits with a particular retailer for the upcoming year, or the price of a pallet of bicycles sold to that retailer.

Williamson’s model is richer. He takes change in the relationship as first order: the famous “unprogrammed adaptations”. The relationship between Schwinn and its retailers requires actions by both over time. Because we are not omniscient, no contract will cover every eventuality. When something unexpected happens, and we both want to renegotiate our contract, we are said to be facing an unprogrammed adaptation. For instance, if advertising is useful, and e-scooters unexpectedly become popular after Schwinn and their retailer sign their initial contract, then we will need to renegotiate who pays for those ads. Of course, we will only bother to negotiate at all if Schwinn and the retailer jointly profit from their relationship compared to their next best options, generating so-called “appropriable quasi-rents”.

We now have an explanation for Schwinn’s behavior. They expect frequent haggling with their retailer about which bicycles to advertise, service standards for repairs, employee training, and so on. If these negotiations fail, the next best option is pretty bad – many small towns might only have one full-service bicycle shop, the Schwinn bikes are more popular than alternatives, and Schwinn itself has neither the resources nor the knowledge to run its own full-service chain of retailers efficiently. Schwinn therefore uses exclusive retail contracts to limit the number of retailers it must negotiate with over service standards, advertising, and the like.

While we have focused on the application of transaction costs to antitrust, Williamson’s basic framework extends much further. He saw the problem as one of “choice” versus “contract”. The canonical topic of study in economics is choice: “Economics is the science which studies human behavior as a relationship between ends and scarce means which have alternative uses,” as Lionel Robbins famously puts it. However, constraints also matter. Agents can act only within the bounds of the law, as a function of what other firms are capable of, and so on. Some of these constraints are public – e.g., what tariff rate do we face, are we allowed to put a price on kidneys for exchange, and so on. Williamson focused our attention on private constraints: the contracts, governance structures, and tools to align incentives which help us reach efficiency when information is asymmetric and contracts are incomplete. The timing was perfect: both Williamson and his professor Ken Arrow, along with Alchian, Demsetz, Klein and others, saw how important this “private ordering” was in their work in the 1960s, but that work was largely qualitative. The formal advancements in game theory in the 1970s gave us the tools that permitted formal analyses of contracting let us transform these ideas into a modern field of industrial organization.

Williamson was in no way an ideologue who ignored the possibility of anticompetitive behavior. Indeed, many canonical anticompetitive strategies, such as “raising rivals’ costs” whereby a firm encourages legal restrictions which raise its own cost but raise rival costs to an even greater degree, originate with Williamson. I also particularly like that Williamson both wrote serious economics, but also frequently translated those results for law journals in order to reach a wider audience. Erik Hovenkamp and I tried to follow this legacy recently in our work on the antitrust of startup acquisitions, where we wrote both a theoretical version and a law review article on the implications of this theory for existing legal practice.

Transaction cost economics is now huge and the both the benefits and critiques of this approach are serious (for more, see my course notes on the theory of the firm). Every economist, when looking at “unusual” contracts or mergers, now follows Williamson in simultaneously looking for the strategic anticompetitive explanation and the cost-saving explanation. The name of this balance? Literally, the Williamson tradeoff!

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If Williamson was interested in “private ordering”, Alesina was focused on the public constraints on behavior. He was without question at the head of the table when it came to winning a Nobel for political economy. Economists, by and large, are technocrats. We have models of growth, of R&D, of fiscal policy, of interstate coordination, and so on. These models imply useful policies. The “public choice” critique, that the politicians and bureaucrats implementing these policies, may muck things up, is well known. The “political business cycle” approach of Nordhaus has politicians taking advantage of myopic voters by, for instance, running expansionary, inflation-inducing policy right before an election, generating lower unemployment today but higher inflation tomorrow.

Alesina’s research goes further than either of these approaches. Entering the field after the rational expectations revolution arrived, Alesina saw how skeptical economists were of the idea that politicians could, each election cycle, take advantage of voters in the same way. I like to explain rational expectations to students as the Bob Marley rule: “You can fool some people sometimes, but you can’t fool all the people all the time.” Rather than myopic voters, we have voters who do not perfectly observe the government’s actions or information. Politicians wish to push their preferences (“ideology”) and also to get re-elected (“career concerns”). Voters have differing preferences. We then want to ask: to what extent can politicians use their private information to push preferences that “society” does not necessarily want, and how does that affect the feasibility of political unions, monetary policy, fiscal policy, and so on?

One important uncertainty is that voters are uncertain about who will win an election. Consider a government which can spend on the military or on education (“guns” or “butter”), and can finance this through debt if they like. A benevolent social planner uses debt to finance investment such that the tax burden is distributed over time. In a political macro model, however, Alesina and Tabellini (RESTUD 1990) show that there will be too much debt, especially when elections are close. If I favor military spending more than education, I can jack up the debt when I am in power with military spending. This not only gets me more military today, but also constrains the other party from spending so much on education tomorrow since society’s debt load will be too high. In equilibrium, both parties try to constrain their rival’s action in the future by using debt spending today. The model makes clear predictions about how debt relates to fundamentals of society – political polarization, and so on – without requiring irrationality on the part of any actor, whether voter or politician.

It is not hard to see how the interests of economists are so heavily linked to their country of origin. Many of our best macroeconomists come from Argentina, home of a great deal of macroeconomic instability. Americans are overrepresented in applied micro, no surprise given the salience of health, education, and labor issues in U.S. political debates. The French, with their high level of technical training in schools and universities, have many great theorists. And no surprise, the Italians are often interested in how political incentives affect and limit economic behavior. Once you start applying Alesina’s ideas, the behavior of politicians and implications for society become clear. Why do politicians delegate some tasks to bureaucrats and not others? The hard ones the politicians might be blamed for if they fail get delegated, and the ones that allow control of distribution do not ((Alesina and Tabellini 2007 AER). Why doesn’t the US have a strong welfare state compared to Europe? The distortions from taxation, relative income mobility, or political power of the poor are relatively unimportant to the racial fractionalization which also explains changes in European preferences over time (Alesina, Glaeser and Sacerdote, Brookings 2001 and Alesina, Miano and Stantcheva 2018).

Perhaps the most salient of Alesina’s questions is one of his oldest (Alesina and Spoloare, QJE 1997): why are there so many countries? Are there “too many”, and what could this mean? In a crisis like Covid, would we be better off with a European fiscal union rather than a bunch of independent countries? Big countries can raise funds with less distortion, public goods often economies of scale, and transfers within countries can handle idiosyncratic regional shocks – these are both assumptions and empirical facts. On the other hand, the bigger the country, the less agreement on how to value public goods. Consider a region on the outskirts of an existing country – say, Sudtirol in Italy. If they secede, they pay higher taxes for their public goods, but the public goods provided are much closer to their preferences. In a democratic secession, these Sudtirol voters do not account for how their secession causes the cost of government in the remaining rump of Italy to rise. Hence they are too likely to secede, versus what a social planner prefers.

We can see this effect in the EU right now. An EU fiscal union would reduce the cost of providing some public goods, insurance to shocks among them. However, the Germans and Dutch have very different public goods preferences from the Italians and Greeks. A planner would balance the marginal cost of lower alignment for the average EU citizen against the marginal benefit of lower public goods costs. A German elected leader will weigh the marginal cost of lower alignment for the average German citizen (worse than that of the EU median citizen!) against the marginal benefit of lower public goods costs (less important, because it doesn’t account for cheaper public goods for Greeks and Italians when Germany joins them to borrow funds jointly). We therefore get too little coordinated fiscal action. This lack of action of public goods makes some Europeans skeptical of other aspects of the EU project: one of Alesina’s final op-eds was on was on the disastrously nationalistic EU response to Covid. Luis Garicano, the well-known Spanish economist and current MEP, has a very interesting discussion with Luigi Zingales on precisely this point.

It’s positive enough that Alesina’s work was well-respected in political science and not just economics. What I especially like about Alesina, though, is how ideologically confusing his policy advice is, especially for an American. He simultaneously supports a lower tax rate for women on the basis on intrafamily dynamics, and was the leading proponent of expansionary austerity, or spending cuts during recessions! The tax rate idea is based on the greater elasticity of labor supply of women, hence is a direct application of the Ramsey rule. Expansionary austerity is based on a serious review of austerity policies over many decades. He pushed these ideas and many others in at least 10 books and dozens of op-eds (including more than 30 for VoxEU). Agree with these ideas or not – and I object to both! – Alesina nonetheless argued for these positions from a base of serious theory and empirics, rather than from ideology. What worthier legacy could there be for an academic?

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Nobel Prize 2016 Part II: Oliver Hart

The Nobel Prize in Economics was given yesterday to two wonderful theorists, Bengt Holmstrom and Oliver Hart. I wrote a day ago about Holmstrom’s contributions, many of which are simply foundational to modern mechanism design and its applications. Oliver Hart’s contribution is more subtle and hence more of a challenge to describe to a nonspecialist; I am sure of this because no concept gives my undergraduate students more headaches than Hart’s “residual control right” theory of the firm. Even stranger, much of Hart’s recent work repudiates the importance of his most famous articles, a point that appears to have been entirely lost on every newspaper discussion of Hart that I’ve seen (including otherwise very nice discussions like Applebaum’s in the New York Times). A major reason he has changed his beliefs, and his research agenda, so radically is not simply the whims of age or the pressures of politics, but rather the impact of a devastatingly clever, and devastatingly esoteric, argument made by the Nobel winners Eric Maskin and Jean Tirole. To see exactly what’s going on in Hart’s work, and why there remains many very important unsolved questions in this area, let’s quickly survey what economists mean by “theory of the firm”.

The fundamental strangeness of firms goes back to Coase. Markets are amazing. We have wonderful theorems going back to Hurwicz about how competitive market prices coordinate activity efficiently even when individuals only have very limited information about how various things can be produced by an economy. A pencil somehow involves graphite being mined, forests being explored and exploited, rubber being harvested and produced, the raw materials brought to a factory where a machine puts the pencil together, ships and trains bringing the pencil to retail stores, and yet this decentralized activity produces a pencil costing ten cents. This is the case even though not a single individual anywhere in the world knows how all of those processes up the supply chain operate! Yet, as Coase pointed out, a huge amount of economic activity (including the majority of international trade) is not coordinated via the market, but rather through top-down Communist-style bureaucracies called firms. Why on Earth do these persistent organizations exist at all? When should firms merge and when should they divest themselves of their parts? These questions make up the theory of the firm.

Coase’s early answer is that something called transaction costs exist, and that they are particularly high outside the firm. That is, market transactions are not free. Firm size is determined at the point where the problems of bureaucracy within the firm overwhelm the benefits of reducing transaction costs from regular transactions. There are two major problems here. First, who knows what a “transaction cost” or a “bureaucratic cost” is, and why they differ across organizational forms: the explanation borders on tautology. Second, as the wonderful paper by Alchian and Demsetz in 1972 points out, there is no reason we should assume firms have some special ability to direct or punish their workers. If your supplier does something you don’t like, you can keep them on, or fire them, or renegotiate. If your in-house department does something you don’t like, you can keep them on, or fire them, or renegotiate. The problem of providing suitable incentives – the contracting problem – does not simply disappear because some activity is brought within the boundary of the firm.

Oliver Williamson, a recent Nobel winner joint with Elinor Ostrom, has a more formal transaction cost theory: some relationships generate joint rents higher than could be generated if we split ways, unforeseen things occur that make us want to renegotiate our contract, and the cost of that renegotiation may be lower if workers or suppliers are internal to a firm. “Unforeseen things” may include anything which cannot be measured ex-post by a court or other mediator, since that is ultimately who would enforce any contract. It is not that everyday activities have different transaction costs, but that the negotiations which produce contracts themselves are easier to handle in a more persistent relationship. As in Coase, the question of why firms do not simply grow to an enormous size is largely dealt with by off-hand references to “bureaucratic costs” whose nature was largely informal. Though informal, the idea that something like transaction costs might matter seemed intuitive and had some empirical support – firms are larger in the developing world because weaker legal systems means more “unforeseen things” will occur outside the scope of a contract, hence the differential costs of holdup or renegotiation inside and outside the firm are first order when deciding on firm size. That said, the Alchian-Demsetz critique, and the question of what a “bureaucratic cost” is, are worrying. And as Eric van den Steen points out in a 2010 AER, can anyone who has tried to order paper through their procurement office versus just popping in to Staples really believe that the reason firms exist is to lessen the cost of intrafirm activities?

Grossman and Hart (1986) argue that the distinction that really makes a firm a firm is that it owns assets. They retain the idea that contracts may be incomplete – at some point, I will disagree with my suppliers, or my workers, or my branch manager, about what should be done, either because a state of the world has arrived not covered by our contract, or because it is in our first-best mutual interest to renegotiate that contract. They retain the idea that there are relationship-specific rents, so I care about maintaining this particular relationship. But rather than rely on transaction costs, they simply point out that the owner of the asset is in a much better bargaining position when this disagreement occurs. Therefore, the owner of the asset will get a bigger percentage of rents after renegotiation. Hence the person who owns an asset should be the one whose incentive to improve the value of the asset is most sensitive to that future split of rents.

Baker and Hubbard (2004) provide a nice empirical example: when on-board computers to monitor how long-haul trucks were driven began to diffuse, ownership of those trucks shifted from owner-operators to trucking firms. Before the computer, if the trucking firm owns the truck, it is hard to contract on how hard the truck will be driven or how poorly it will be treated by the driver. If the driver owns the truck, it is hard to contract on how much effort the trucking firm dispatcher will exert ensuring the truck isn’t sitting empty for days, or following a particularly efficient route. The computer solves the first problem, meaning that only the trucking firm is taking actions relevant to the joint relationship which are highly likely to be affected by whether they own the truck or not. In Grossman and Hart’s “residual control rights” theory, then, the introduction of the computer should mean the truck ought, post-computer, be owned by the trucking firm. If these residual control rights are unimportant – there is no relationship-specific rent and no incompleteness in contracting – then the ability to shop around for the best relationship is more valuable than the control rights asset ownership provides. Hart and Moore (1990) extends this basic model to the case where there are many assets and many firms, suggesting critically that sole ownership of assets which are highly complementary in production is optimal. Asset ownership affects outside options when the contract is incomplete by changing bargaining power, and splitting ownership of complementary assets gives multiple agents weak bargaining power and hence little incentive to invest in maintaining the quality of, or improving, the assets. Hart, Schleifer and Vishny (1997) provide a great example of residual control rights applied to the question of why governments should run prisons but not garbage collection. (A brief aside: note the role that bargaining power plays in all of Hart’s theories. We do not have a “perfect” – in a sense that can be made formal – model of bargaining, and Hart tends to use bargaining solutions from cooperative game theory like the Shapley value. After Shapley’s prize alongside Roth a few years ago, this makes multiple prizes heavily influenced by cooperative games applied to unexpected problems. Perhaps the theory of cooperative games ought still be taught with vigor in PhD programs!)

There are, of course, many other theories of the firm. The idea that firms in some industries are big because there are large fixed costs to enter at the minimum efficient scale goes back to Marshall. The agency theory of the firm going back at least to Jensen and Meckling focuses on the problem of providing incentives for workers within a firm to actually profit maximize; as I noted yesterday, Holmstrom and Milgrom’s multitasking is a great example of this, with tasks being split across firms so as to allow some types of workers to be given high powered incentives and others flat salaries. More recent work by Bob Gibbons, Rebecca Henderson, Jon Levin and others on relational contracting discusses how the nexus of self-enforcing beliefs about how hard work today translates into rewards tomorrow can substitute for formal contracts, and how the credibility of these “relational contracts” can vary across firms and depend on their history.

Here’s the kicker, though. A striking blow was dealt to all theories which rely on the incompleteness or nonverifiability of contracts by a brilliant paper of Maskin and Tirole (1999) in the Review of Economic Studies. Theories relying on incomplete contracts generally just hand-waved that there are always events which are unforeseeable ex-ante or impossible to verify in court ex-post, and hence there will always scope for disagreement about what to do when those events occur. But, as Maskin and Tirole correctly point out, agent don’t care about anything in these unforeseeable/unverifiable states except for what the states imply about our mutual valuations from carrying on with a relationship. Therefore, every “incomplete contract” should just involve the parties deciding in advance that if a state of the world arrives where you value keeping our relationship in that state at 12 and I value it at 10, then we should split that joint value of 22 at whatever level induces optimal actions today. Do this same ex-ante contracting for all future profit levels, and we are done. Of course, there is still the problem of ensuring incentive compatibility – why would the agents tell the truth about their valuations when that unforeseen event occurs? I will omit the details here, but you should read the original paper where Maskin and Tirole show a (somewhat convoluted but still working) mechanism that induces truthful revelation of private value by each agent. Taking the model’s insight seriously but the exact mechanism less seriously, the paper basically suggests that incomplete contracts don’t matter if we can truthfully figure out ex-post who values our relationship at what amount, and there are many real-world institutions like mediators who do precisely that. If, as Maskin and Tirole prove (and Maskin described more simply in a short note), incomplete contracts aren’t a real problem, we are back to square one – why have persistent organizations called firms?

What should we do? Some theorists have tried to fight off Maskin and Tirole by suggesting that their precise mechanism is not terribly robust to, for instance, assumptions about higher-order beliefs (e.g., Aghion et al (2012) in the QJE). But these quibbles do not contradict the far more basic insight of Maskin and Tirole, that situations we think of empirically as “hard to describe” or “unlikely to occur or be foreseen”, are not sufficient to justify the relevance of incomplete contracts unless we also have some reason to think that all mechanisms which split rent on the basis of future profit, like a mediator, are unavailable. Note that real world contracts regularly include provisions that ex-ante describe how contractual disagreement ex-post should be handled.

Hart’s response, and this is both clear from his CV and from his recent papers and presentations, is to ditch incompleteness as the fundamental reason firms exist. Hart and Moore’s 2007 AER P&P and 2006 QJE are very clear:

Although the incomplete contracts literature has generated some useful insights about firm boundaries, it has some shortcomings. Three that seem particularly important to us are the following. First, the emphasis on noncontractible ex ante investments seems overplayed: although such investments are surely important, it is hard to believe that they are the sole drivers of organizational form. Second, and related, the approach is ill suited to studying the internal organization of firms, a topic of great interest and importance. The reason is that the Coasian renegotiation perspective suggests that the relevant parties will sit down together ex post and bargain to an efficient outcome using side payments: given this, it is hard to see why authority, hierarchy, delegation, or indeed anything apart from asset ownership matters. Finally, the approach has some foundational weaknesses [pointed out by Maskin and Tirole (1999)].

To my knowledge, Oliver Hart has written zero papers since Maskin-Tirole was published which attempt to explain any policy or empirical fact on the basis of residual control rights and their necessary incomplete contracts. Instead, he has been primarily working on theories which depend on reference points, a behavioral idea that when disagreements occur between parties, the ex-ante contracts are useful because they suggest “fair” divisions of rent, and induce shading and other destructive actions when those divisions are not given. These behavioral agents may very well disagree about what the ex-ante contract means for “fairness” ex-post. The primary result is that flexible contracts (e.g., contracts which deliberately leave lots of incompleteness) can adjust easily to changes in the world but will induce spiteful shading by at least one agent, while rigid contracts do not permit this shading but do cause parties to pursue suboptimal actions in some states of the world. This perspective has been applied by Hart to many questions over the past decade, such as why it can be credible to delegate decision making authority to agents; if you try to seize it back, the agent will feel aggrieved and will shade effort. These responses are hard, or perhaps impossible, to justify when agents are perfectly rational, and of course the Maskin-Tirole critique would apply if agents were purely rational.

So where does all this leave us concerning the initial problem of why firms exist in a sea of decentralized markets? In my view, we have many clever ideas, but still do not have the perfect theory. A perfect theory of the firm would need to be able to explain why firms are the size they are, why they own what they do, why they are organized as they are, why they persist over time, and why interfirm incentives look the way they do. It almost certainly would need its mechanisms to work if we assumed all agents were highly, or perfectly, rational. Since patterns of asset ownership are fundamental, it needs to go well beyond the type of hand-waving that makes up many “resource” type theories. (Firms exist because they create a corporate culture! Firms exist because some firms just are better at doing X and can’t be replicated! These are outcomes, not explanations.) I believe that there are reasons why the costs of maintaining relationships – transaction costs – endogenously differ within and outside firms, and that Hart is correct is focusing our attention on how asset ownership and decision making authority affects incentives to invest, but these theories even in their most endogenous form cannot do everything we wanted a theory of the firm to accomplish. I think that somehow reputation – and hence relational contracts – must play a fundamental role, and that the nexus of conflicting incentives among agents within an organization, as described by Holmstrom, must as well. But we still lack the precise insight to clear up this muddle, and give us a straightforward explanation for why we seem to need “little Communist bureaucracies” to assist our otherwise decentralized and almost magical market system.

Reinhard Selten and the making of modern game theory

Reinhard Selten, it is no exaggeration, is a founding father of two massive branches of modern economics: experiments and industrial organization. He passed away last week after a long and idiosyncratic life. Game theory as developed by the three co-Nobel laureates Selten, Nash, and Harsanyi is so embedded in economic reasoning today that, to a great extent, it has replaced price theory as the core organizing principle of our field. That this would happen was not always so clear, however.

Take a look at some canonical papers before 1980. Arrow’s Possibility Theorem simply assumed true preferences can be elicited; not until Gibbard and Satterthwaite do we answer the question of whether there is even a social choice rule that can elicit those preferences truthfully! Rothschild and Stiglitz’s celebrated 1976 essay on imperfect information in insurance markets defines equilibria in terms of a individual rationality, best responses in the Cournot sense, and free entry. How odd this seems today – surely the natural equilibrium in an insurance market depends on beliefs about the knowledge held by others, and beliefs about those beliefs! Analyses of bargaining before Rubinstein’s 1982 breakthrough nearly always rely on axioms of psychology rather than strategic reasoning. Discussions of predatory pricing until the 1970s, at the very earliest, relied on arguments that we now find unacceptably loose in their treatment of beliefs.

What happened? Why didn’t modern game-theoretic treatment of strategic situations – principally those involve more than one agent but less than an infinite number, although even situations of perfect competition now often are motivated game theoretically – arrive soon after the proofs of von Neumann, Morganstern, and Nash? Why wasn’t the Nash program, of finding justification in self-interested noncooperative reasoning for cooperative or axiom-driven behavior, immediately taken up? The problem was that the core concept of the Nash equilibrium simply permits too great a multiplicity of outcomes, some of which feel natural and others of which are less so. As such, a long search, driven essentially by a small community of mathematicians and economists, attempted to find the “right” refinements of Nash. And a small community it was: I recall Drew Fudenberg telling a story about a harrowing bus ride at an early game theory conference, where a fellow rider mentioned offhand that should they crash, the vast majority of game theorists in the world would be wiped out in one go!

Selten’s most renowned contribution came in the idea of perfection. The concept of subgame perfection was first proposed in a German-language journal in 1965 (making it one of the rare modern economic classics inaccessible to English speakers in the original, alongside Maurice Allais’ 1953 French-language paper in Econometrica which introduces the Allais paradox). Selten’s background up to 1965 is quite unusual. A young man during World War II, raised Protestant but with one Jewish parent, Selten fled Germany to work on farms, and only finished high school at 20 and college at 26. His two interests were mathematics, for which he worked on the then-unusual extensive form game for his doctoral degree, and experimentation, inspired by the small team of young professors at Frankfurt trying to pin down behavior in oligopoly through small lab studies.

In the 1965 paper, on demand inertia (paper is gated), Selten wrote a small game theoretic model to accompany the experiment, but realized there were many equilibria. The term “subgame perfect” was not introduced until 1974, also by Selten, but the idea itself is clear in the ’65 paper. He proposed that attention should focus on equilibria where, after every action, each player continues to act rationally from that point forward; that is, he proposed that in every “subgame”, or every game that could conceivably occur after some actions have been taken, equilibrium actions must remain an equilibrium. Consider predatory pricing: a firm considers lowering price below cost today to deter entry. It is a Nash equilibrium for entrants to believe the price would continue to stay low should they enter, and hence to not enter. But it is not subgame perfect: the entrant should reason that after entering, it is not worthwhile for the incumbent to continue to lose money once the entry has already occurred.

Complicated strings of deductions which rule out some actions based on faraway subgames can seem paradoxical, of course, and did even to Selten. In his famous Chain Store paradox, he considers a firm with stores in many locations choosing whether to price aggressively to deter entry, with one potential entrant in each town choosing one at a time whether to enter. Entrants prefer to enter if pricing is not aggressive, but prefer to remain out otherwise; incumbents prefer to price nonaggressively either if entry occurs or not. Reasoning backward, in the final town we have the simple one-shot predatory pricing case analyzed above, where we saw that entry is the only subgame perfect equilibria. Therefore, the entrant in the second-to-last town knows that the incumbent will not fight entry aggressively in the final town, hence there is no benefit to doing so in the second-to-last town, hence entry occurs again. Reasoning similarly, entry occurs everywhere. But if the incumbent could commit in advance to pricing aggressively in, say, the first 10 towns, it would deter entry in those towns and hence its profits would improve. Such commitment may not possible, but what if the incumbent’s reasoning ability is limited, and it doesn’t completely understand why aggressive pricing in early stages won’t deter the entrant in the 16th town? And what if entrants reason that the incumbent’s reasoning ability is not perfectly rational? Then aggressive pricing to deter entry can occur.

That behavior may not be perfectly rational but rather bounded had been an idea of Selten’s since he read Herbert Simon as a young professor, but in his Nobel Prize biography, he argues that progress on a suitable general theory of bounded rationality has been hard to come by. The closest Selten comes to formalizing the idea is in his paper on trembling hand perfection in 1974, inspired by conversations with John Harsanyi. The problem with subgame perfection had been noted: if an opponent takes an action off the equilibrium path, it is “irrational”, so why should rationality of the opponent be assumed in the subgame that follows? Harsanyi assumes that tiny mistakes can happen, putting even rational players into subgames. Taking the limit as mistakes become infinitesimally rare produces the idea of trembling-hand perfection. The idea of trembles implicitly introduces the idea that players have beliefs at various information sets about what has happened in the game. Kreps and Wilson’s sequential equilibrium recasts trembles as beliefs under uncertainty, and showed that a slight modification of the trembling hand leads to an easier decision-theoretic interpretation of trembles, an easier computation of equilibria, and an outcome that is nearly identical to Selten’s original idea. Sequential equilibria, of course, goes on to become to workhorse solution concept in dynamic economics, a concept which underscores essentially all of modern industrial organization.

That Harsanyi, inventor of the Bayesian game, is credited by Selten for inspiring the trembling hand paper is no surprise. The two had met at a conference in Jerusalem in the mid-1960s, and they’d worked together both on applied projects for the US military, and on pure theory research while Selten visiting Berkeley. A classic 1972 paper of theirs on Nash bargaining with incomplete information (article is gated) begins the field of cooperative games with incomplete information. And this was no minor field: Roger Myerson, in his paper introducing mechanism design under incomplete information – the famous Bayesian revelation principle paper – shows that there exists a unique Selten-Harsanyi bargaining solution under incomplete information which is incentive compatible.

Myerson’s example is amazing. Consider building a bridge which costs $100. Two people will use the bridge. One values the bridge at $90. The other values the bridge at $90 with probability .9, and $30 with probability p=.1, where that valuation is the private knowledge of the second person. Note that in either case, the bridge is worth building. But who should pay? If you propose a 50/50 split, the bridge will simply not be built 10% of the time. If you propose an 80/20 split, where even in their worst case situation each person gets a surplus value of ten dollars, the outcome is unfair to player one 90% of the time (where “unfair” will mean, violates certain principles of fairness that Nash, and later Selten and Harsanyi, set out axiomatically). What of the 53/47 split that gives each party, on average, the same split? Again, this is not “interim incentive compatible”, in that player two will refuse to pay in the case he is the type that values the bridge only at $30. Myerson shows mathematically that both players will agree once they know their private valuations to the following deal, and that the deal satisfies the Selten-Nash fairness axioms: when player 2 claims to value at $90, the payment split is 49.5/50.5 and the bridge is always built, but when player 2 claims to value at $30, the entire cost is paid by player 1 but the bridge is built with only probability .439. Under this split, there are correct incentives for player 2 to always reveal his true willingness to pay. The mechanism means that there is a 5.61 percent chance the bridge isn’t built, but the split of surplus from the bridge nonetheless does better than any other split which satisfies all of Harsanyi and Selten’s fairness axioms.

Selten’s later work is, it appears to me, more scattered. His attempt with Harsanyi to formalize “the” equilibrium refinement, in a 1988 book, was a valiant but in the end misguided attempt. His papers on theoretical biology, inspired by his interest in long walks among the wildflowers, are rather tangential to his economics. And what of his experimental work? To understand Selten’s thinking, read this fascinating dialogue with himself that Selten gave as a Schwartz Lecture at Northwestern MEDS. In this dialogue, he imagines a debate between a Bayesian economist, experimentalist, and an evolutionary biologist. The economist argues that “theory without theorems” is doomed to fail, that Bayesianism is normatively “correct”, and the Bayesian reasoning can easily be extended to include costs of reasoning or reasoning mistakes. The experimentalist argues that ad hoc assumptions are better than incorrect ones: just as human anatomy is complex and cannot be reduced to a few axioms, neither can social behavior. The biologist argues that learning a la Nelson and Winter is descriptively accurate as far as how humans behave, whereas high level reasoning is not. The “chairman”, perhaps representing Selten himself, sums up the argument as saying that experiments which simply contradict Bayesianism are a waste of time, but that human social behavior surely depends on bounded rationality and hence empirical work ought be devoted to constructing a foundation for such a theory (shall we call this the “Selten program”?). And yet, this essay was from 1990, and we seem no closer to having such a theory, nor does it seem to me that behavioral research has fundamentally contradicted most of our core empirical understanding derived from theories with pure rationality. Selten’s program, it seems, remains not only incomplete, but perhaps not even first order; the same cannot be said of his theoretical constructs, as without perfection a great part of modern economics simply could not exist.

The Economics of John Nash

I’m in the midst of a four week string of conferences and travel, and terribly backed up with posts on some great new papers, but I can’t let the tragic passing today of John Nash go by without comment. When nonacademics ask what I do, I often say that I work in a branch of applied math called game theory; if you say you are economist, the man on the street expects you to know when unemployment will go down, or which stocks they should buy, or whether monetary expansion will lead to inflation, questions which the applied theorist has little ability to answer in a satisfying way. But then, if you mention game theory, without question the most common way your interlocutor knows the field is via Russell Crowe’s John Nash character in A Beautiful Mind, so surely, and rightfully, no game theorist has greater popular name recognition.

Now Nash’s contributions to economics are very small, though enormously influential. He was a pure mathematician who took only one course in economics in his studies; more on this fortuitous course shortly. The contributions are simple to state: Nash founded the theory of non-cooperative games, and he instigated an important, though ultimately unsuccessful, literature on bargaining. Nash essentially only has two short papers on each topic, each of which is easy to follow for a modern reader, so I will generally discuss some background on the work rather than the well-known results directly.

First, non-cooperative games. Robert Leonard has a very interesting intellectual history of the early days of game theory, the formal study of strategic interaction, which begins well before Nash. Many like to cite von Neumann’s “Zur Theorie der Gesellschaftsspiele” (“A Theory of Parlor Games”), from whence we have the minimax theorem, but Emile Borel in the early 1920’s, and Ernst Zermelo with his eponymous theorem a decade earlier, surely form relevant prehistory as well. These earlier attempts, including von Neumann’s book with Morganstern, did not allow general investigation of what we now call noncooperative games, or strategic situations where players do not attempt to collude. The most famous situation of this type is the Prisoner’s Dilemma, a simple example, yet a shocking one: competing agents, be they individuals, firms or countries, may (in a sense) rationally find themselves taking actions which both parties think is worse than some alternative. Given the U.S. government interest in how a joint nuclear world with the Soviets would play out, analyzing situations of that type was not simply a “Gesellschaftsspiele” in the late 1940s; Nash himself was funded by the Atomic Energy Commission, and RAND, site of a huge amount of important early game theory research, was linked to the military.

Nash’s insight was, in retrospect, very simple. Consider a soccer penalty kick, where the only options are to kick left and right for the shooter, and to simultaneously dive left or right for the goalie. Now at first glance, it seems like there can be no equilibrium: if the shooter will kick left, then the goalie will jump to that side, in which case the shooter would prefer to shoot right, in which case the goalie would prefer to switch as well, and so on. In real life, then, what do we expect to happen? Well, surely we expect that the shooter will sometimes shoot left and sometimes right, and likewise the goalie will mix which way she dives. That is, instead of two strategies for each player, we have a continuum of mixed strategies, where a mixed strategy is simply a probability distribution over the strategies “Left, Right”. This idea of mixed strategies “convexifies” the strategy space so that we can use fixed point strategies to guarantee that an equilibrium exists in every finite-strategy noncooperative game under expected utility (Kakutani’s Fixed Point in the initial one-page paper in PNAS which Nash wrote his very first year of graduate school, and Brouwer’s Fixed Point in the Annals of Math article which more rigorously lays out Nash’s noncooperative theory). Because of Nash, we are able to analyze essentially whatever nonstrategic situation we want under what seems to be a reasonable solution concept (I optimize given my beliefs about what others will do, and my beliefs are in the end correct). More importantly, the fixed point theorems Nash used to generate his equilibria are now so broadly applied that no respectable economist should now get a PhD without understanding how they work.

(A quick aside: it is quite interesting to me that game theory, as opposed to Walrasian/Marshallian economics, does not derive from physics or other natural sciences, but rather from a program at the intersection of formal logic and mathematics, primarily in Germany, primarily in the early 20th century. I still have a mind to write a proper paper on this intellectual history at some point, but there is a very real sense in which economics post-Samuelson, von Neumann and Nash forms a rather continuous methodology with earlier social science in the sense of qualitative deduction, whereas it is our sister social sciences which, for a variety of reasons, go on writing papers without the powerful tools of modern logic and the mathematics which followed Hilbert. When Nash makes claims about the existence of equilibria due to Brouwer, the mathematics is merely the structure holding up and extending ideas concerning the interaction of agents in noncooperative systems that would have been totally familiar to earlier generations of economists who simply didn’t have access to tools like the fixed point theorems, in the same way that Samuelson and Houthakker’s ideas on utility are no great break from earlier work aside from their explicit incorporation of deduction on the basis of relational logic, a tool unknown to economists in the 19th century. That is, I claim the mathematization of economics in the mid 20th century represents no major methodological break, nor an attempt to ape the natural sciences. Back to Nash’s work in the direct sense.)

Nash only applies his theory to one game: a simplified version of poker due to his advisor called Kuhn Poker. It turned out that the noncooperative solution was not immediately applicable, at least to the types of applied situations where it is now commonplace, without a handful of modifications. In my read of the intellectual history, noncooperative games was a bit of a failure outside the realm of pure math in its first 25 years because we still needed Harsanyi’s purification theorem and Bayesian equilibria to understand what exactly was going on with mixed strategies, Reinhard Selten’s idea of subgame perfection to reasonably analyze games with multiple stages, and the idea of mechanism design of Gibbard, Vickers, Myerson, Maskin, and Satterthwaite (among others) to make it possible to discuss how institutions affect outcomes which are determined in equilibrium. It is not simply economists that Nash influenced; among many others, his work directly leads to the evolutionary games of Maynard Smith and Price in biology and linguistics, the upper and lower values of his 1953 results have been used to prove other mathematical results and to discuss what is meant as truth in philosophy, and Nash is widespread in the analysis of voting behavior in political science and international relations.

The bargaining solution is a trickier legacy. Recall Nash’s sole economics course, which he took as an undergraduate. In that course, he wrote a term paper, eventually to appear in Econometrica, where he attempted to axiomatize what will happen when two parties bargain over some outcome. The idea is simple. Whatever the bargaining outcome is, we want it to satisfy a handful of reasonable assumptions. First, since ordinal utility is invariant to affine transformations of a utility function, the bargaining outcome should not be affected by these types of transformations: only ordinal preferences should matter. Second, the outcome should be Pareto optimal: the players would have to mighty spiteful to throw away part of the pie rather than give it to at least one of them. Third, given their utility functions players should be treated symmetrically. Fourth (and a bit controversially, as we will see), Nash insisted on Independence of Irrelevant Alternatives, meaning that if f(T) is the set of “fair bargains” when T is the set of all potential bargains, then if the potential set of bargains is smaller yet still contains f(T), say S strictly contained by T where f(T) is in S, then f(T) must remain the barganing outcome. It turns out that under these assumptions, there is a unique outcome which maximizes (u(x)-u(d))*(v(x)-v(d)), where u and v are each player’s utility functions, x is the vector of payoffs under the eventual bargain, and d the “status-quo” payoff if no bargain is made. This is natural in many cases. For instance, if two identical agents are splitting a dollar, then 50-50 is the only Nash outcome. Uniqueness is not at all obvious: recall the Edgeworth box and you will see that individual rationality and Pareto optimality alone leave many potential equilibria. Nash’s result is elegant and surprising, and it is no surprise that Nash’s grad school recommendation letter famously was only one sentence long: “This man is a genius.”

One problem with Nash bargaining, however. Nash was famously bipolar in real life, but there is an analogous bipolar feel to the idea of Nash equilibrium and the idea of Nash bargaining: where exactly are threats in Nash’s bargain theory? That is, Nash bargaining as an idea completely follows from the cooperative theory of von Neumann and Morganstern. Consider two identical agents splitting a dollar once more. Imagine that one of the agents already has 30 cents, so that only 70 of the cents are actually in the middle of the table. The Nash solution is that the person who starts with the thirty cents eventually winds up with 65 cents, and the other person with 35. But play this out in your head.

Player 1: “I, already having the 30 cents, should get half of what remains. It is only fair, and if you don’t give me 65 I will walk away from this table and we will each get nothing more.”

Player 2: “What does that have to do with it? The fair outcome is 50 cents each, which leaves you with more than your originally thirty, so you can take your threat and go jump off a bridge.”

That is, 50/50 might be a reasonable solution here, right? This might make even more sense if we take a more concrete example: bargaining over wages. Imagine the prevailing wage for CEOs in your industry is $250,000. Two identical CEOs will generate $500,000 in value for the firm if hired. CEO Candidate One has no other job offer. CEO Candidate Two has an offer from a job with similar prestige and benefits, paying $175,000. Surely we can’t believe that the second CEO will wind up with higher pay, right? It is a completely noncredible threat to take the $175,000 offer, hence it shouldn’t affect the bargaining outcome. A pet peeve of mine is that many applied economists are still using Nash bargaining – often in the context of the labor market! – despite this well-known problem.

Nash was quite aware of this, as can be seen by his 1953 Econometrica, where he attempts to give a noncooperative bargaining game that reaches the earlier axiomatic outcome. Indeed, this paper inspired an enormous research agenda called the Nash Program devoted to finding noncooperative games which generate well-known or reasonable-sounding cooperative solution outcomes. In some sense, the idea of “implementation” in mechanism design, where we investigate whether there exists a game which can generate socially or coalitionally preferred outcomes noncooperatively, can be thought of as a successful modern branch of the Nash program. Nash’s ’53 noncooperative game simply involves adding a bit of noise into the set of possible outcomes. Consider splitting a dollar again. Let a third party tell each player to name how many cents they want. If the joint requests are feasible, then the dollar is split (with any remainder thrown away), else each player gets nothing. Clearly every split of the dollar on the Pareto frontier is a Nash equilibrium, as is each player requesting the full dollar and getting nothing. However, if there is a tiny bit of noise about whether there is exactly one dollar, or .99 cents, or 1.01 cents, etc., when deciding whether to ask for more money, I will have to weigh the higher payoff if the joint demand is feasible against the payoff zero if my increased demand makes the split impossible and hence neither of us earn anything. In a rough sense, Nash shows that as the distribution of noise becomes degenerate around the true bargaining frontier, players will demand exactly their Nash bargaining outcome. Of course it is interesting that there exists some bargaining game that generates the Nash solution, and the idea that we should study noncooperative games which implement cooperate solution concepts is without a doubt seminal, but this particular game seems very strange to me, as I don’t understand what the source of the noise is, why it becomes degenerate, etc.

On the shoulders of Nash, however, bargaining progressed a huge amount. Three papers in particular are worth your time, although hopefully you have seen these before: Kalai and Smorodinsky 1975 who retaining the axiomatic approach but drop IIA, Rubinstein’s famous 1982 Econometrica on noncooperative bargaining with alternative offers, and Binmore, Rubinstein and Wolinsky on implementation of bargaining solutions which deals with the idea of threats as I did above.

You can read all four Nash papers in the original literally during your lunch hour; this seems to me a worthy way to tip your cap toward a man who literally helped make modern economics possible.

“The Efficiency of Dynamic Post-Auction Bargaining: Evidence from Wholesale Used-Auto Auctions,” B. Larsen (2013)

Another job market season is in the books, as Brad Larsen was the last job talk I made it to this year. Here’s something you may not have known: there is an industry which sells lots of used cars at auctions. Each year, they sell eighty billion dollars worth of cars at these auctions! I’ve written auction theory papers before, and yet have never even heard of this industry. The complexity of economics never fails to impress, but this is good; it means there is always something interesting for us economists to study.

Now when you hear “inefficient bargaining” and “autos”, you probably immediately think of Stiglitz’ lemons model. But selection really isn’t a big issue in these used-auto auctions. Car rental agencies that participate, for instance, sell off an entire season of cars all at once. The real inefficiency is of the Myerson-Satterthwaite type. In that classic result, your private value for a good and my private value for a good are drawn from overlapping distributions – and “draw” and “distribution” may be over the set of all possible buyers or sellers as in Harsanyi purification – then there is no price at which we would agree to a transaction. (You must know Myerson-Satterthwaite! Among other things, it absolutely destroys the insight behind the Coase theorem…) Myerson and Satterthwaite, as well as a handful of other others, later fully described the second-best mechanism when first-best trade is impossible. This second-best mechanism turns out to be quite complicated. Almost all of the auto auction houses use a seemingly strange mechanism instead. First, sellers set a secret reserve which is told to the auctioneer. Then the car is sold in an English auction. If the auction ends below the reserve price, then sellers and potential buyers can opt to bargain individually over the phone, perhaps asynchronously. At the end of these bargains, there are still many cars that go unsold.

This brings up the obvious question: how close to the second-best optimum is this strange selling mechanism? Larsen got access to some amazing data, which included outcomes of the auction, all of the sequential offers made over the phone, seller secret reserve prices, and tons of data at the level of the car and the buyer. The problem, of course, is that we don’t have access to the seller and buyer types (i.e., their private valuations of the car). Indeed, we don’t even have knowledge of the distribution of their types. If you are a regular reader of this blog, you know what is coming next – we can perhaps back out those distributions, but only if theory is applied in a clever way. (And, wow, how are job market speakers not permanently nervous? It’s one thing to stretch the Myerson-Satterthwaite framework to its limits, but it’s another thing to do so when Mark is sitting in the front row of the seminar room, as was the case here at Kellogg. Luckily, he’s a nice guy!)

The high bid in the auction helps us get buyer valuations. This high bid is, if bidders bid truthfully, equivalent to the second-order statistic of bidder values. Order theory turns out to give us a precise relationship between the underlying distribution and distribution of draws of its second-order statistic (when the second order is from a set of N draws from the distribution). Larsen knows exactly how many people were at each auction house, and can use this to roughly estimate how many bidders could potentially have bid on each car. Homogenizing each car using observable characteristics, therefore, the order statistic method can be used to gather the underlying distribution of buyer values for each car.

On the seller side, it is the secret reserve price that really helps us estimate the bargaining game. If the post-auction bargaining never results in a price lower than the last bid, then bidders have a dominant strategy to bid truthfully. Costly bargaining in addition to truthful bidding by buyers means that the optimal seller reserve price must be strictly increasing in the seller’s type. And what does strict monotonicity give us? Invertibility. We now know there is a link between the seller reserve price and the seller type. The structure of post-auction bargaining helps us to bound the relationship between seller type and the reserve. Finally, multiple rounds of bargaining let us bound the disutility costs of bargaining, which turn out to be quite small.

So how does the auto auction bargaining mechanism do? In this market, given the estimated type distributions, the Myerson-Satterthwaite second-best gives you 98% of the surplus of a first-best (informationally impossible) mechanism. Real-world dynamic bargaining captures 88-96% of that second-best surplus, with the most inefficiency coming from small sellers where, perhaps, screening problems result. That’s still leaving money on the table, though. Larsen, among others, suggests that these types of strange dynamic mechanisms may persist because in two-sided markets, they roughly are equivalent to committing to giving buyers a large chunk of the gains from trade, and we know that attracting additional potential buyers is the most important part of successful auctions.

January 2013 working paper (No IDEAS version).

“Long Cheap Talk,” R. Aumann & S. Hart (2003)

I wonder if Crawford and Sobel knew just what they were starting when they wrote their canonical cheap talk paper – it is incredible how much more we know about the value of cheap communication even when agents are biased. Most importantly, it is not true that bias or self-interest means we must always require people to “put skin in the game” or perform some costly action in order to prove the true state of their private information. A colleague passed along this paper by Aumann and Hart which addresses a question that has long bedeviled students of repeated games: why don’t they end right away? (And fair notice: we once had a full office shrine, complete with votive candles, to Aumann, he of the antediluvian beard and two volume tome, so you could say we’re fans!)

Take a really simple cheap talk game, where only one agent has any useful information. Row knows what game we are playing, and Column only knows the probability distribution of such games. In the absence of conflict (say, where there are two symmetric games, each of which has one Pareto optimal equilibrium), Row first tells Column that which game is the true one, this is credible, and so Column plays the Pareto optimal action. In other cases, we know from Crawford-Sobel logic that partial revelation may be useful even when there are conflicts of interest: Row tells Column with some probability what the true game is. We can also create new equilibria by using talk to reach “compromise”. Take a Battle of the Sexes, with LL payoff (6,2), RR (2,6) and LR=RL=(0,0). The equilibria of the simultaneous game without cheap talk are LL,RR, or randomize 3/4 on your preferred location and 1/4 of the opponent’s preferred location. But a new equilibria is possible if we can use talk to create a public randomization device. We both write down 1 or 2 on a piece of paper, then show the papers to each other. If the sum is even, we both go LL. If the sum is odd, we both then go RR. This gives ex-ante payoff (4,4), which is not an equilibrium payoff without the cheap talk.

So how do multiple rounds help us? They allow us to combine these motives for cheap talk. Take an extended Battle of the Sexes, with a third action A available to Column. LL still pays off (6,2), RR still (2,6) and LR=RL=(0,0). RA or LA pays off (3,0). Before we begin play, we may be playing extended Battle of the Sexes, or we may be playing a game Last Option that pays off 0 to both players unless Column plays A, in which case both players get 4; both games are equally probable ex-ante, and only Row learns which game we actually in. Here, we can enforce a payoff of (4,4) if, when the game is actually extended Battle of the Sexes, we randomize between L and R as in the previous paragraph, but if the game is Last Option, Column always plays A. But the order in which we publicly randomize and reveal information matters! If we first randomize, then reveal which game we are playing, then whenever the public randomization causes us to play RR (giving row player a payoff of 2 in Battle of the Sexes), Row will afterwards have the incentive to claim we are actually playing Last Resort. But if Row first reveals which game we are playing, and then we randomize if we are playing extended Battle of the Sexes, we indeed enforce ex-ante expected payoff (4,4).

Aumann and Hart show precisely what can be achieved with arbitrarily long strings of cheap talk, using a clever geometric proof which is far too complex to even summarize here. But a nice example of how really long cheap talk of this fashion can be used is in a paper by Krishna and Morgan called The Art of Conversation. Take a standard Crawford-Sobel model. The true state of the world is drawn uniformly from [0,1]. I know the true state, and get utility which is maximized when you take action on [0,1] as close as possible to the true state of the world plus .1. Your utility is maximized when you take action as close as possible to the true state of the world. With this “bias”, there is a partially informative one-shot cheap talk equilibrium: I tell you whether we are in [0,.3] or [.3,1] and you in turn take action either .15 or .65. How might we do better with a string of cheap talk? Try the following: first I tell you whether we are in [0,.2] or [.2,1]. If I say we are in the low interval, you take action .1. If I say we are in the high interval, we perform a public randomization which ends the game (with you taking action .6) with probability 4/9 and continues the game with probability 5/9; for example, to publicly randomize we might both shout out numbers between 1 and 9, and if the difference is 4 or less, we continue. If we continue, I tell you whether we are in [.2,.4] or [.4,1]. If I say [.2,.4], you take action .3, else you take action .7. It is easy to calculate that both players are better off ex-ante that in the one-shot cheap talk game. The probabilities 4/9 and 5/9 were chosen so as to make each player indifferent from following the proposed equilibrium after the randomization or not.

The usefulness of the lotteries interspersed with the partial revelation are to let the sender credibly reveal more information. If there were no lottery, but instead we always continued with probability 1, look at what happens when the true state of nature is .19. The sender knows he can say in the first revelation that, actually, we are on [.2,1], then in the second revelation that, actually, we are on [.2,4], in which case the receiver plays .3 (which is almost exactly sender’s ideal point .29). Hence without the lotteries, the sender has an incentive to lie at the first revelation stage. That is, cheap talk can serve to give us jointly controlled lotteries in between successive revelation of information, and in so doing, improve our payoffs.

Final published Econometrica 2003 copy (IDEAS). Sequential cheap talk has had many interesting uses. I particularly enjoyed this 2008 AER by Alonso, Dessein and Matouschek. The gist is the following: it is often thought that the tradeoff between decentralized firms and centralized firms is more local control in exchange for more difficult coordination. But think hard about what information will be transmitted by regional managers who only care about their own division’s profits. As coordination becomes more important, the optimal strategy in my division is more closely linked to the optimal decision in other divisions. Hence I, the regional manager, have a greater incentive to freely share information with other regional managers than in the situation where coordination is less important. You may prefer centralized decision-making when cooperation is least important because this is when individual managers are least likely to freely share useful information with each other.

“The Nash Bargaining Solution in Economic Modeling,” K. Binmore, A. Rubinsten & A. Wolinsky (1986)

If we form a joint venture, our two firms will jointly earn a profit of N dollars. If our two countries agree to this costly treaty, total world welfare will increase by the equivalent of N dollars. How should we split the profit in the joint venture case, or the costs in the case of the treaty? There are two main ways of thinking about this problem: the static bargaining approach developed first by John Nash, and bargaining outcomes that form the perfect outcome of a strategic game, for which Rubinstein (1982) really opened the field.

The Nash solution says the following. Let us have some pie of size 1 to divide. Let each of us have a threat point, S1 and S2. Then if certain axioms are followed (symmetry, invariance to unimportant transformations of the utility function, Pareto optimality and something called the IIA condition), the bargain is the one that maximizes (u1(p)-u1(S1))*(u2(1-p)-u2(S2)), where p is the share of the pie of size 1 that accrues to player 1. So if we both have linear utility, player 1 can leave and collect .3, and player 2 can leave and collect 0, but a total of 1 is earned by our joint venture, the Nash bargaining solution is the p that maximizes (p-.3)*(1-p-0); that is, p=.65. This is pretty intuitive: 1-.3-0=.7 of surplus is generated by the joint venture, and we each get our outside option plus half of that surplus.

The static outcome is not very compelling, however, as Tom Schelling long ago pointed out. In particular, the outside option looks like a noncredible threat: If player 2 refused to offer player 1 more than .31, then Player 1 would accept given his outside option is only .3. That is, in a one-shot bargaining game, any p between .3 and 1 looks like an equilibrium. It is also not totally clear how we should interpret the utility functions u1 and u2, and the threat points S1 and S2.

Rubinstein bargaining began to fix this. Let players make offers back and forth, and let there be a time period D between each offer. If no agreement is reached after T periods, we both get our outside options. Under some pretty compelling axioms, there is a unique perfect equilibrium whereby player 1 gets p* if he makes the first offer, and p** if player 2 makes the first offer. Roughly, if the time between offers is D, player 1 must offer player 2 a high enough share that player 2 is indifferent between that share today and the amount he could earn when he makes an offer in the next period. Note that the outside options do not come into play unless, say, player 1’s outside option is higher than min{p*,p**}. Note also that as D goes to 0, all of the difference in bargaining power has to do with who is more patient. Binmore et al modify this game so that, instead of discounting the future, rather there is a small chance that the gains from negotiation will disappear (“breakdown”) in between every period; for instance, we may want to form a joint venture to invent some product, but while we negotiate, another firm may swoop in and invent it. It turns out that this model, with von Neumann-Morganstern utility functions for each player (though perhaps differing levels of risk aversion) is a special case of Rubinstein bargaining.

Binmore et al prove that as D goes to zero, both strategic cases above have unique perfect equilibria equal to a Nash bargaining solution. But a Nash solution for what utility functions and threat points? The Rubinstein game limits to Nash bargaining where the difference in utilities has to do with time preference, and the threat points S1 and S2 are equal to zero. The breakdown game limits to Nash bargaining where the difference in utilities has to do with risk aversion, and the threat points S1 and S2 are equal to whatever utility we would get from the world after breakdown.

Two important points: first, it was well known that a concave transformation of a utility function leads to a worse outcome in Nash bargaining for that player. But we know from the previous paragraph that this concave transformation is equivalent to a more impatient Rubinstein bargainer: a concave transformation of the utilities in the Nash outcome has to do with changing the patience, not the risk aversion, of players. Second, Schelling was right when he argued that the Nash threat points involve noncredible threats. As long as players prefer their Rubinstein equilibrium outcome to their outside option, the outside option does not matter for the bargaining outcome. Take the example above where one player could leave the joint venture and still earn .3. The limit of Rubinstein bargaining is for each player to earn .5 from the joint venture, not .65 and .35. The fact that one player could leave the joint venture and still earn .3 is totally inconsequential to the negotiation, since the other player knows that this threat is not credible whenever the first player could earn at least .31 by staying. This point is often wildly misunderstood when people apply Nash bargaining solutions: properly defining the threat point matters!

Final RAND version (IDEAS). There has been substantial work since the 80s on the problem of bargaining, particularly in trying to construct models where delay is generated, since Rubinstein guarantees agreement immediately and real-world bargaining rarely ends in one step; unsurprisingly, these newer papers tend to rely on difficult manipulation of theorems using asymmetric information.