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1.1. Scope of the Book This book is a contribution to the area of "dynamic models of the firm". The motivation for this kind of research is the following: Empirical studies (e.g. Albach (1976)) have shown that the development of the firm over time can be divided into different stages. such as growth. stationarity and contraction. In order to understand and evaluate these stages in a proper way. it is important to develop a suitable theoretical framework. To that end. economists have applied dynamic mathematical techniques. such as optimal control theory. calculus of variations and dynamic programming to design and analyse dynamic models of the firm. In this way. the economic theory of the firm is extended to a dynamic context. Within the field of the dynamics of the firm this book - develops a general investment decision rule. based on the concept "net present value of marginal investment". which is applicable in deterministic dynamic models of the firm; - studies the influence of adjustment costs of investment on optimal dynamic firm behavior; - extends the stochastic dynamic theory of the firm by connecting it with a dynamic version of the Capital Asset Pricing Model. Before elaborating on "the dynamics of the firm". we first review the subject of net present value in the classical analysis.
The history of many sciences is characterized by an almost continuous emer gence of new theories. From a normative point of view, the survival of a new theory should mainly be determined by its ability to explain a new body of facts which the existing theories are unable to explain. If in addition the new theory is able to explain all the results obtained by the existing theories and if it can point out why these theories fail to explain certain facts, it should become the dominant theory. Otherwise, it might coexist with other theories for some time. Hence, a new theory ought to be judged not only by confronting it with existing facts, but also by confronting it with existing theories. The idea that a theory should be able to account for the results ob tained by other theories, although implicitly adhered to by many scientists, has rarely been formalized. The statistics literature on parametric hypoth esis testing, though, might be seen as an instance of such a formalization.
Bilateral bargaining situations are of great importance in reality. Traditional microeconomics, however, make cognitive and motivational assumptions of subjects` full rationality that are revealed as being unrealistic by a growing number of experimental investigations. The present book adds an important contribution to the understanding of principles of boundedly rational behavior by directly observing groups of subjects in a decision situation and videotaping their discussions. A very important result of the book is that the behavior of subjects is guided by aspirations regarding the final outcome. The levels of aspirations are influenced by prominence and different forms of the equity principle resulting in several fairness norms as to the allocation of the amount of money to be divided. Another important feature of the book stems from the analysis of break off discussions and enables a motivational explanation of the emergence of breakdowns in bargaining.
This book presents an econometric modeling approach for analysing macroeconomic disequilibria, focusing on the market for goods and labor and the spillovers between these markets transmitted through firms' decisions in the production sphere. The macroeconomic markets are treated as heterogeneous aggregates, consisting of a multitute of micro markets on which demand/supply ratios differ. Disequilibrium models have been under attack because they neglect that inventories enable firms to smooth production over the cycle, but the author argues that buffer stocks (output inventories, unfilled orders) should be accounted for within the disequilibrium framework, giving rise to a dynamic modification rather than a fundamental invalidation of rationing and spillover effects. The model developed in this book combines traditional Keynesian-type analysis with supply-side considerations and at the same time allows for micro-level imbalance. The resulting econometric structure is inherently nonlinear, reflecting that the response of economic activity to demand-side and supply-side factors varies over the cycle, depending on the aggregate mix of regimes. The model is estimated with quarterly data for Switzerland. Various simulation experiments clearly demonstrate the potential of this type of model for empirical business cycle analysis and policy discussions.
This collection of papers gives a broad overview of the state of the art in Multiple Criteria Decision Making (MCDM), in both theory and practice. Topical sections are ranging from preference modelling and methodological developments to a number of applications of MCDM thinking. Special sections are devoted to applications in natural resources and environmental management issues, to negotiation and group decision support, and to philosophical issues, particularly in the interface between systems thinking and MCDM. The book will be relevant not only to those working in the area of MCDM, but also to researchers and practitioners concerned with broader areas of management science, especially those concerned with decision support systems and negotiation support.
Billions of dollars are tied up in the inventories of manufacturing companies which cause large (interest) costs. A small decrease of the inventory and/or production costs without reduction of the service level can increase the profit substantially. Especially in the case of scarce capacity, efficient production schedules are fundamental for short delivery time and on-time delivery which are important competitive priorities. To support decision makers by improving their manufacturing resource planning system with appropriate methods is one of the most of production planning. interesting challenges The following chapters contain new models and new solution strategies which may be helpful for decision makers and for further research in the areas of production planning and operations research. The main subject is on lotsizing and scheduling. The objectives and further characteristics of such problems can be inferred from practical need. Thus, before an outline is given, we consider the general objectives of lotsizing and scheduling and classify the most important characteristics of such problems in the following sections.
This book presents statistical methods for the analysis of events. The primary focus is on single equation cross section models. The book addresses both the methodology and the practice of the subject and it provides both a synthesis of a diverse body of literature that hitherto was available largely in pieces, as well as a contribution to the progress of the methodology, establishing several new results and introducing new models. Starting from the standard Poisson regression model as a benchmark, the causes, symptoms and consequences of misspecification are worked out. Both parametric and semi-parametric alternatives are discussed. While semi-parametric models allow for robust interference, parametric models can identify features of the underlying data generation process.
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does not conform to certain specifications, it must be repaired or replaced by a new item. This means that we have to return to a preceding stage of the production process. In other words, there is feedback. Note that the result of the inspection is that a certain percentage of the parts tested do not conform. That is, there is a positive probability (strictly less than 1) that any part is defective.
This book describes a series of laboratory experiments (with a total of 167 independent subjects) on forecasting behavior. In all experiments, the time series to be forecasted was generated by an abstract econometric model involving two or three artificial exogenous variables. This designprovides an optimal background for rational expectations and least-squares learning. As expected, these hypotheses do not explain observed forecasting behavior satisfactorily. Some phenomena related to this lack of rationality are studied: Concentration on changes rather than levels,underestimation of changes and overvaluation of volatile exogenous variables. Some learning behavior is observed. Finally, some aspects of individual forecasts such as prominence of "round" number, dispersion, etc.,are studied.
This report portrays the results of experimental research on dynamic duopoly markets with demand inertia. Two methods of experimentation are studied: game-playing experiments where subjects interact spontaneously via computer terminals, and computer tournaments between strategies designed by subjects. The principal aim of this study is the understanding of boundedly rational decision making in the dynamic duopoly situation. 1. 1 Motivation The experiments examine a multistage duopoly game where prices in each period are the only decision variables. Sales depend on current prices and also on past sales (demand inertia). Applying the game-theoretic concept of subgame perfect equilibrium, the game is solved by backward induction. The result is a uniquely determined system of decision rules. However, we can hardly expect that human beings behave according to the equilibrium strategy of this game. It is unlikely that subjects are able to compute the equilibrium. And even if a subject is able to compute it, he might not make use of this knowledge. Only if he expects the others to behave according to the equilibrium, it is optimal for him to play the equilibrium strategy. We have evidence from several earlier experimental studies on oligopoly markets that, even in less complex oligopoly situations where the equilibrium solutions are very easy to compute, human behavior often is different from what is prescribed by normative theory. ! Normative theory is based on the concept of ideal rationality. However, human capabilities impose cognitive limits on rationality.