John Conlisk

Cyclic Pricing by a Durable Goods Monopolist

In the model of this paper a monopoly seller of a durable good holds periodic sales as a means of price discrimination. A new cohort of consumers enters the market in each period, interested in purchasing the good either immediately or after a delay. Within each cohort, consumers vary in their tastes for the good. Under broad conditions, the seller will vary the price over time. In most periods, he will charge a price just low enough to sell immediately to consumers with a high willingness to pay. Periodically, however, he will drop the price far enough to sell to an accumulated group of consumers with a low willingness to pay.

Product Quality in Markets Where Consumers are Imperfectly Informed

I. Introduction, 1.—II. Context of the model, 3.—III. Consumer specifications and market equilibrium in the case of fixed breakdown probabilities, 5.—IV. Breakdown probabilities set by profit considerations, 11.—V. Conclusion, 19.—Appendix, 20.

The Utility of Gambling

A tiny utility of gambling is appended to an expected utility model for a risk-averse individual. It is shown that the model can explain small payoff gambles, large prize lotteries, and patterns of risk-seeking in the experimental evidence that are puzzling from the viewpoint of standard theory. At the same time, the model maintains expected utility theorys ability to explain insurance purchase, portfolio diversification, and other risk-averting behavior. The tiny utility of gambling could equally well be appended to models of risky choice other than the expected utility model.

Costly optimizers versus cheap imitators

Abstract A dynamic model is constructed with two types of agents, optimizers and imitators. The mix between the two types evolves according to the relative average performances of the two groups. The main conclusion is that imitators may have as high a long-run ‘fitness’ as optimizers. The model is used to sort issues concerning the conventional hypothesis that everyone acts as if unboundedly rational.

Interactive markov chains

Markov chains, and various generalizations of them, almost universally assume that the transition probabilities applying to a single individual are independent of the behavior of other individuals in the population. That is, there is no interaction among individuals. This is an extremely limiting assumption in modelling social processes. This paper concerns interactive Markov chains, defined as Markov chains in which transition probabilities are functions of population frequencies in the states.

Eigenvalue immobility measures for Markov chains 1

Two eigenvalue measures of immobility are proposed for social processes described by a Markov chain. One is the second largest eigenvalue modulus of the chains transition matrix. The other is the second largest eigenvalue modulus of a closely related transition matrix. The two eigenvalue measures are compared to each other and to correlation and regression‐to‐the‐mean measures. In illustrative applications to intergenerational occupational mobility, the eigenvectors corresponding to the eigenvalue measures are found to be good proxies for occupational status rankings for a number of countries, thus reinforcing a pattern noted by Klatsky and Hodge and by Duncan‐Jones.

Monotone mobility matrices

The transition matrix of a discrete Markov chain is called monotone if each row stochastically dominates the row above it. Monotonicity is an ideal assumption to impose on a Markov chain model of mobility. Monotonicity is behaviorally weak yet mathematically strong. It is behaviorally weak in the sense that it is theoretically plausible and is empirically supported. It is mathematically strong in the sense that monotone Markov chains have a number of convenient mathematical properties. This paper reviews the convenient properties and applies the monotonicity concept to immobility measurement.

An Aggregate Model of Technical Change

A simple aggregate growth model is presented in which technology is described by a probability distribution from which new plants are drawn. Especially good draws are viewed as technological innovations that shift the mean of the following periods plant distribution function. The resulting technical change is endogenous, random, and cumulative. In contrast to conventional growth models, the models growth path displays nonstationary drift rather than deterministic trend, and the long-run per capita growth rate has positive rather than zero sensitivity to the models saving parameter.

Bounded rationality and market fluctuations

Abstract In a model of a competitive market, each firm in each period faces a planning problem caused by random changes in circumstances. Due to bounded rationality, a firm is unable to compute, costlessly and exactly, its optimal output. Instead the firm approximates optimal output through a decision-making process called a ‘deliberation technology’. This technology involves a rule of thumb, a costly deliberation mechanism, and a random deliberation error. The issue addressed by the model is how bounded rationality affects market fluctuations. The first glance intuition is that fluctuations will increase since deliberation error is an added disturbance to the market. However, the actual effect is much more complicated and might go either way.

A NEW CLASS OF MODELS OF SPATIAL DISTRIBUTION

We analyze a new class of models of spatial distribution, developing mathematical properties and performing empirical tests. The models are based on a simple colonization rule operating on a rectangular grid. Two special cases within the class are traditional random placement and negative binomial models. Over three large data sets, these two cases are strongly outperformed by more flexible models within the class, in particular, models that allow more general patterns of aggregation. The models are simple and broadly applicable, with only one adjustable parameter, representing aggregation. Shortcomings of the colonization rule are studied, and extensions and applications of the models are discussed.