A Theory of Endogenous Institutional Change

ABSTRACT: This paper asks (a) why and how institutions change; (b) how does an institution persist in a changing environment and (c) how do processes that it unleashes lead to its own demise. The paper shows that the game theoretic notion of self-enforcing equilibrium and the historical institutionalist focus on process are both inadequate to answer these questions. Building on a game theoretic foundation, but responding to the critique of it by historical institutionalists, the paper introduces the concepts of quasi-parameters and self–reinforcement. With these concepts, and building on repeated game theory, a dynamic approach to institutions is offered, one that can account for endogenous change (and stability) of institutions. Contextual accounts of formal governing institutions in early modern Europe and the informal institution of cleavage structure in the contemporary world provide illustrations of the approach.

Deciding Between Competition and Collusion

ABSTRACT: In many studies in empirical industrial organization, the economist needs to decide between several non-nested models of industry equilibrium. In this paper, we develop a new approach to the model selection problem that can be used when the economist must decide between models with bid-rigging and models without bid-rigging. We elicit from industry experts a prior distribution over markups across auctions. This induces a prior distribution over structural cost parameters. We then use Bayes Theorem to compute posterior probabilities for several non-nested models of industry equilibrium. In many settings, we believe that it is useful to formally incorporate the a prior beliefs of industry experts into estimation, especially in small samples where asymptotic approximations may be unreliable. We apply our methodology to a data set of bidding by construction firms in the Midwest. The techniques we propose are not computationally demanding, use flexible functional forms and can be programmed using most standard statistical packages.

Monte Carlo Simulation of Macroeconomic Risk with a Continuum of Agents: The Symmetric Case

Suppose a large economy with individual risk is modeled by a continuum of pairwise exchangeable random variables (i.i.d., in particular). Then the relevant stochastic process is jointly measurable only in degenerate cases. Yet in Monte Carlo simulation, the average of a large finite draw of the random variables converges almost surely. Several necessary and sufficient conditions for such “Monte Carlo convergence” are given. Also, conditioned on the associated Monte Carlo sigma-algebra, which represents macroeconomic risk, individual agents’ random shocks are independent. Furthermore, a converse to one version of the classical law of large numbers is proved.

Order Without Law? Property Rights During the California Gold Rush

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