Knowledge that Transforms

The paper shows that an increase in competition has two effects on managerial incentives: It increases the probability of liquidation, which has a positive effect on managerial effort, but it also reduces the firm's profits, which may make it less attractive to induce high effort. Thus, the total effect is ambiguous. I identify natural circumstances where increasing competition unambiguously reduces managerial slack. In general, however, this relation need not be monotonic. A simple example demonstrates that—starting from a monopoly—managerial effort may increase as additional competitors enter the market, but will eventually decrease when competition becomes too intense.

We develop a model of search and unemployment in an economy consisting of a large number of spatially separated local competitive labour markets and aggregate uncertainty. If aggregate shocks are positively autocorrelated, the implied cyclical behaviour of the aggregate variables match those of empirical studies: worker movement and job creation are procyclical while total unemployment, job destruction and job reallocation are countercyclical.

We study the dual issues of allocation and coalition formation in a model of social learning. For a class of economies which can be expressed in terms of a real valued characteristic function, we first show that all self-perpetuating allocations realized from a simple bargaining game must be core allocations although players make simultaneous demands for surplus and only on their own behalf. Following this, we provide a sufficient condition under which the society eventually learns to divide the surplus according to some core allocation, regardless of the initial history.

We say that a player is certain of an event A if she assigns probability 1 to A. There is common certainty (CC) of A if the event A occurred, each player is certain of A, each player is certain that every other player is certain of A, and so forth. It is shown that in a generic perfect-information game the set of outcomes that are consistent with common certainty of rationality (CCR) at the beginning of the game coincides with the set of outcomes that survive one deletion of weakly dominated strategies and then iterative deletion of strongly dominated strategies. Thus, the backward induction outcome is not the only outcome that is consistent with CCR. In particular, cooperation in Rosenthal's (1981) centipede game, and fighting in Selten's (1978) chainstore game are consistent with CCR at the beginning of the game. Next, it is shown that, if in addition to CCR, there is CC that each player assigns a positive probability to the true strategies and beliefs of the other players, and if there is CC of the support of the beliefs of each player, then the outcome of the game is a Nash equilibrium outcome.

The author derives the limiting properties of the two-stage least squares estimator of an equation in a dynamic simultaneous model when variables are nonstationary and cointegrated. The implication on hypothesis testing is also discussed. It is shown that, in a structural equation approach, what one needs to worry about are the classical issues of identification and estimation, not nonstationarity and cointegration. Conventional formulae for computing the asymptotic covariance of the two-stage least squares estimator and the Wald-type test statistics remain good approximations despite the fact that variables may be integrated. Copyright 1997 by The Review of Economic Studies Limited.

This paper develops a model of repeated innovation with knowledge spillovers. The model's novel feature is that firms compete on two dimensions: (1) product quality, where one firm's innovation ultimately spills over to other firms; and (2) distribution costs, where there are no spillovers across firms and where learning-by-doing on the part of incumbent firms gives them a competitive advantage over would-be entrants. Such firm-specific learning-by-doing has two important consequences: (1) it can in some circumstances dramatically reduce the long-run average level of innovation; (2) it leads to endogeneous bunching, or waves, in innovative activity.

This paper reconsiders the Strotz-Pollak problem of consistent planning and argues that a solution to this problem requires a refinement of subgame-perfectness. Such a refinement is offered through an analysis based on Greenberg's “theory of social situations”. The properties of this refinement are investigated and illustrated. A unifying framework is presented whereby consistent one-person planning as a problem of individual time-consistency and renegotiation-proofness as a problem of collective time-consistency are captured through the same general concept.

In this paper a competitive distribution of auctions is described for an economy consisting of an infinite number of buyers and sellers, all of whom differ according to their valuation for the single indivisible object being traded. A competitive distribution of auctions is such that no seller can improve his profits by deviating to any alternative direct mechanism. It is shown that the competitive distribution of auctions will have the property that each buyer and seller's best reply is independent of his beliefs about the tastes of other buyers and sellers on the market.

This paper shows that in a frictional labour market part of the productivity gains from general training will be captured by future employers. As a result, investments in general skills will be suboptimally low, and contrary to the standard theory, part of the costs may be borne by the employers. The paper also demonstrates that the interaction between innovation and training leads to an amplification of this inefficiency and to a multiplicity of equilibria. Workers are more willing to invest in their skills by accepting lower wages today if they expect more firms to innovate and pay them higher wages in the future. Similarly, firms are more willing to innovate when they expect the quality of the future workforce to be higher, thus when workers invest more in their skills.

In this paper I discuss alternatives to the GMM estimators proposed by Hansen (1982) and others. These estimators are shown to have a number of advantages. First of all, there is no need to estimate in an initial step a weight matrix as required in the conventional estimation procedure. Second, it is straightforward to derive the distribution of the estimator under general misspecification. Third, some of the alternative estimators have appealing information-theoretic interpretations. In particular, one of the estimators is an empirical likelihood estimator with an interpretation as a discrete support maximum likelihood estimator. Fourth, in an empirical example one of the new estimators is shown to perform better than the conventional estimators. Finally, the new estimators make it easier for the researcher to get better approximations to their distributions using saddlepoint approximations. The main cost is computational: the system of equations that has to be solved is of greater dimension than the number of parameters of interest. In practice this may or may not be a problem in particular applications.