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The following monograph deals with the approximate stochastic behavior of a system consisting of a sequence of servers in series with finite storage between consecutive servers. The methods employ deterministic queueing and diffusion approximations which are valid under conditions in which the storages and the queue lengths are typically large compared with 1. One can disregard the fact that the customer counts must be integer valued and treat the queue as if it were a (stochastic) continuous fluid. In these approximations, it is not necessary to describe the detailed probability distribution of service times; it suffices simply to specify the rate of service and the variance rate (the variance of the number served per unit time). Specifically, customers are considered to originate from an infinite reservoir. They first pass through a server with service rate ~O' vari ance rate ~O' into a storage of finite capacity c . They then pass l through a server with service rate ~l' variance rate ~l' into a storage of capacity c ' etc., until finally, after passing through an nth server, 2 they go into an infinite reservoir (disappear). If any jth storage become , n , the service at the j-lth server is interrupted full j = 1, 2, and, of course, if a jth storage becomes empty the jth server is inter rupted; otherwise, services work at their maximum rate.
The present 'Introductory Lectures on Arbitrage-based Financial Asset Pricing' are a first attempt to give a comprehensive presentation of Arbitrage Theory in a discrete time framework (by the way: all the re sults given in these lectures apply to a continuous time framework but, probably, in continuous time we could achieve stronger results - of course at the price of stronger assumptions). It has been turned out in the last few years that capital market theory as derived and evolved from the capital asset pricing model (CAPM) in the middle sixties, can, to an astonishing extent, be based on arbitrage arguments only, rather than on mean-variance preferences of investors. On the other hand, ar bitrage arguments provided access to a wider range of results which could not be obtained by standard CAPM-methods, e. g. the valuation of contingent claims (derivative assets) Dr the_ investigation of futures prices. To some extent the presentation will loosely follow historical lines. A selected set of capital asset pricing models will be derived according to their historical progress and their increasing complexity as well. It will be seen that they all share common structural properties. After having made this observation the presentation will become an axiomatical one: it will be stated in precise terms what arbitrage is about and what the consequences are if markets do not allow for risk-free arbitrage opportunities. The presentation will partly be accompanied by an illus trating example: two-state option pricing.
This book is a treatise on empirical microeconomics: it describes the econometric theory of qualitative choice models and the empirical practice of modeling consumer demand for a heterogeneous commodity, housing. Accordingly, the book has two parts. The first part gives a self-contained survey of discrete choice models with emphasis on nested and related multinomial logit models. The second part concentrates on three sUbstantive questions about housing demand and how they can be answered using discrete choice models. Why combine these two distinct parts in one book? It is the interaction between theory and application in empirical microeconomics on which we focus in this book. Hence, emphasis in the methodological part is on practicability, and emphasis in the applied part is on the usage of the proper econometric specifications. Econometrics means measuring economic phenomena. Because nature (ironically, in the case of economics, this is most often the government) rarely provides us with well-defined economic experiments, measurement of economic phenomena usually requires an elaborate statistical apparatus that is able to separate concurrent and confounding phenomena. Discrete choice models have proved to be a very convenient apparatus to study the complex issues in housing demand. We present models, techniques, and statistical problems of discrete choice in the first and methodological part of the book, written in conventional textbook style.
This book contains a collection of the most significant contributions to some of R.M. Goodwin's ideas, which were presented on the occasion of the outstanding economist's 73rd birthday celebrations held in Modena on February 24th, 1986. The most important feature of this book is the unique combination of papers by economists, econometricians and mathematicians. Their papers deal with the different aspects of Goodwin's celebrated models. The book is divided into three parts. The first part contains five papers which describe Goodwin's scientific life. The second part is more quantitative and contains extensions and modifications to the nonlinear model of growth cycles. The third part is an economic reflection linked to Goodwin's themes. The book presents a combination of both qualitative and quantitative contributions to Goodwin's pioneering works.
This volume contains eleven articles which deal with different aspects of dynaoic and differential game theory and its applications in economic modeling and decision making. All but one of these were presented as invited papers in special sessions I organized at the 7th Annual Conference on Economic Dynamics and Control in London, England, during the period June 26-28, 1985. The first article, which comprises Chapter 1, provides a general introduction to the topic of dynamic and differential game theory, discusses various noncooperative equilibrium solution concepts, includ ing Nash, Stackelberg, and Consistent Conjectural Variations equilibria, and a number of issues such as feedback and time-consistency. The second chapter deals with the role of information in Nash equilibria and the role of leadership in Stackelberg problems. A special type of a Stackelberg problem is the one in which one dominant player (leader) acquires dynamic information involving the actions of the others (followers), and constructs policies (so-called incentives) which enforce a certain type of behavior on the followers; Chapter 3 deals with such a class of problems and presents some new theoretical results on the existence of affine incentive policies. The topic of Chapter 4 is the computation of equilibria in discounted stochastic dynamic games. Here, for problems with finite state and decision spaces, existing algorithms are reviewed, with a comparative study of their speeds of convergence, and a new algorithm for the computation of nonzero-sum game equilibria is presented.