Economic Governance

Institutions are sets of rules that govern human interaction. The main purpose of many institutions
is to facilitate production and exchange. Examples of institutions that affect human prosperity
by enabling production and exchange include laws, business organizations and political
government. Economic governance research seeks to understand the nature of such institutions
in light of the underlying economic problems they handle.

One important class of institutions is the legal rules and enforcement mechanisms that protect
property rights and enable the trade of property, that is, the rules of the market. Another class of
institutions supports production and exchange outside markets. For example, many transactions
take place inside business firms. Likewise, governments frequently play a major role in funding
pure public goods, such as national defense and maintenance of public spaces. Key questions
are therefore: which mode of governance is best suited for what type of transaction, and to what
extent can the modes of governance that we observe be explained by their relative efficiency?

This year’s prize is awarded to two scholars who have made major contributions to our understanding
of economic governance, Elinor Ostrom and Oliver Williamson.

More...

NB: this post does not imply that I subscribe to the notion of "pure public goods" :)

Iterative Combinatorial Auctions: Achieving Economic and Computational Efficiency

Iterative Combinatorial Auctions: Achieving Economic and Computational Efficiency

A fundamental problem in building open distributed systems is to design mechanisms that compute optimal system-wide solutions despite the self-interest of individual users and computational agents. Classic game-theoretic solutions are often prohibitively expensive computationally. For example, the Generalized Vickrey Auction (GVA) is an efficient and strategy-proof solution to the combinatorial allocation problem (CAP), in which agents demand bundles of items, but every agent must reveal its value for all possible bundles and the auctioneer must solve a sequence of NP-hard optimization problems to compute the outcome. I propose iBundle, an iterative combinatorial auction in which agents can bid for combinations of items and adjust their bids in response to bids from other agents. iBundle computes the efficient allocation in the CAP when agents follow myopic best-response bidding strategies, bidding for the bundle(s) that maximize their surplus taking the current prices as fixed. iBundle solves problems without complete information revelation from agents and terminates in competitive equilibrium. Moreover, an agent can follow a myopic best-response strategy with approximate values on bundles, for example with lower- and upper- bounds. My approach to iterative mechanism design decomposes the problem into two parts. First, I use linear programming theory to develop an efficient iterative auction under the assumption that agents will follow a myopic best-response bidding strategy. Second, I extend the approach to also compute Vickrey payments at the end of the auction. This makes myopic best-response a sequentially-rational strategy for agents in equilibrium, inheriting many of the useful game-theoretic properties of the GVA. iBundle implements a primal-dual algorithm, CombAuction, for the CAP, computing a feasible primal (the provisional allocation) and a feasible dual (the ask prices) that satisfy complementary slackness conditions. An extended auction, iBundle Extend & Adjust, interprets a primal-dual algorithm, VickAuction, as an iterative auction. VickAuction computes the efficient allocation and Vickrey payments with only best-response information from agents. Experimental results demonstrate that iBundle Extend & Adjust, which keeps iBundle open for a second phase before adjusting prices towards Vickrey payments, computes Vickrey payments across a suite of problems.

SUBJECTIVE PERFORMANCE MEASURES IN OPTIMAL INCENTIVE CONTRACTS

SUBJECTIVE PERFORMANCE MEASURES IN OPTIMAL INCENTIVE CONTRACTS

Incentive contracts often include important subjective components that mitigate
incentive distortions caused by imperfect objective measures. This paper explores the
combined use of subjective and objective performance measures in (respectively)
implicit and explicit incentive contracts. We show that the presence of sufficiently
effective explicit contracts can render all implicit contracts infeasible, even those that
would otherwise yield the first-best. We also show, however, that in some
circumstances objective and subjective measures are complements: neither an explicit
nor an implicit contract alone yields positive profit, but an appropriate combination of
the two does. Finally, we consider subjective weights on objective measures.

The Theory of the Firm

The Theory of the Firm

Smart Contracts: Building Blocks for Digital Markets

Smart Contracts: Building Blocks for Digital Markets

The contract, a set of promises agreed to in a "meeting of the minds", is the traditional way to formalize a relationship. While contracts are primarily used in business relationships (the focus of this article), they can also involve personal relationships such as marraiges. Contracts are also important in politics, not only because of "social contract" theories but also because contract enforcement has traditionally been considered a basic function of capitalist governments.

Whether enforced by a government, or otherwise, the contract is the basic building block of a free market economy. Over many centuries of cultural evolution has emerged both the concept of contract and principles related to it, encoded into common law. Algorithmic information theory suggests that such evolved structures are often prohibitively costly to recompute. If we started from scratch, using reason and experience, it could take many centuries to redevelop sophisticated ideas like property rights that make the modern free market work [Hayek].

The success of the common law of contracts, combined with the high cost of replacing it, makes it worthwhile to both preserve and to make use of these principles where appropriate. Yet, the digital revolution is radically changing the kinds of relationships we can have. What parts of our hard-won legal tradition will still be valuable in the cyberspace era? What is the best way to apply these common law principles to the design of our on-line relationships?

Computers make possible the running of algorithms heretofore prohibitively costly, and networks the quicker transmission of larger and more sophsiticated messages. Furthermore, computer scientists and cryptographers have recently discovered many new and quite interesting algorithms. Combining these messages and algorithms makes possible a wide variety of new protocols.

New institutions, and new ways to formalize the relationships that make up these institutions, are now made possible by the digital revolution. I call these new contracts "smart", because they are far more functional than their inanimate paper-based ancestors. No use of artificial intelligence is implied. A smart contract is a set of promises, specified in digital form, including protocols within which the parties perform on these promises.

From Capabilities To Financial Instruments

From Capabilities To Financial Instruments

A major aspect of the emergence of capitalism from feudalism was the rise of contract. By creating a contract, you could define and transfer an arbitrary bundle of rights. The complexity of trade could now bloom, unrestrained by the simple limits of physical matter. During the twentieth century, a great variety of financial instruments were invented. These instruments represent the discovery of many new kinds of rights, and ways of deriving these rights from more primitive rights. We should hope the growth of financial cryptography will only accelerate this trend. For this hope to be realized, we should seek not just the secure computational expression of the contracts representing existing instruments, but the creation of secure material from which similar new contracts can easily be built. Following Nick Szabo [Szabo97], we refer to a partially self-enforcing computational embodiment of a contract as a smart contract.

A Formal Language for Analyzing Contracts

A Formal Language for Analyzing Contracts

The author presents a mini-language for professionals and researchers interested in drafting and analyzing contracts. It is intended for computers to read, too. The main purpose of this language is to, as unambiguously and completely and succinctly as possible, specify common contracts or contractual terms. These include financial contracts, liens and other kinds of security, transfer of ownership, performance of online services, and supply chain workflow.

RELATIONAL CONTRACTS AND THE THEORY OF THE FIRM

RELATIONAL CONTRACTS AND THE THEORY OF THE FIRM

Relational contracts—informal agreements sustained by the value of future
relationships—are prevalent within and between firms. We develop repeated-game
models showing why and how relational contracts within firms (vertical integration)
differ from those between (non-integration). We show that integration affects the
parties’ temptations to renege on a given relational contract, and hence affects the best
relational contract the parties can sustain. In this sense, the integration decision can be
an instrument in the service of the parties’ relationship. Our approach also has
implications for joint ventures, alliances, and networks, and for the role of
management within and between firms.