Managerial economics

About: Managerial economics is a research topic. Over the lifetime, 1524 publications have been published within this topic receiving 83965 citations.

Game and economic theory : selected contributions in honor of Robert J. Aumann

Abstract: "Game and Economic Theory" studies the interactions of decision makers whose decisions affect each other. The analysis is from a rational viewpoint: every participant would like to obtain the outcome that he prefers most. However, each one has to take into account that the others are doing the same--trying to get what they prefer most. At times this leads to fierce competition; at other times, to mutually beneficial cooperation; and in general, to an appropriate combination of these two extreme behaviors. Game theory, which may be viewed as a sort of "unified field" theory for the rational side of social science, develops the theoretical foundations for the analysis of such multi-person interactive situations, and then applies these to many disciplines: economics, political science, biology, psychology. computer science, statistics and law. Foremost among these is economic theory, where game theory is playing a central role.This volume consists of twenty-two selected contributions to various areas of game and economic theory. These important and pathbreaking contributions are all by former students of Robert J. Aumann, to whom this volume is dedicated. The volume will no doubt shed light on the far-reaching pertinence of game theory and its application to economics, and also on the monumental impact of Aumann on this discipline.Sergiu Hart is Alice Kusiel de Vorreuter Professor of Mathematical Economics and Director of the Center for Rationality and Interactive Decision Theory, The Hebrew University of Jerusalem. Abraham Neyman is Professor of Mathematics, The Hebrew University of Jerusalem, and Leading Professor of Economics and Mathematics, State University of New York at Stony Brook.

Estimation and testing of dynamic econometric models from panel data.

Abstract: This research develops methods of estimation and test statistics of dynamic single equation models from panel data when the errors are serially correlated. It is assumed that the number of time periods is fixed while the number of cross-section observations is large. This makes it possible to consider prediction equations of the initial observations based on the exogenous variables corresponding to all periods available in the sample, as well as to leave unrestricted the covariances of the prediction errors with the remaining errors in the model. The concentrated likelihood function is derived both for cases where the prediction error is left unrestricted and where it is assumed to have the marginal distribution of the stationary process. The performance of maximum likelihood methods is investigated, either for correct models or under several misspecifications, by resorting to Monte Carlo methods using antithetic variates. Dynamic models from panel data can be seen as a specialisation of a triangular system with covariance restrictions. In this context, the asymptotic distribution of the estimators that maximise the gaussian likelihood function is derived when normality holds and also when the errors are non-normal. In particular, it is shown that in the latter case the estimator that takes into account the covariance restrictions is not generally more efficient than the estimator that leaves the co-variance matrix unrestricted. The possibility of obtaining consistent estimates of the unrestricted intertemporal covariance matrix is used to develop test statistics of covariance restrictions arising from various random effects specifications. A Wald test and a minimum chi-square test, which are robust to the non-normality of the errors, and appropriate asymptotic probability limits for the quasi-likelihood ratio test are proposed. Monte Carlo experiments are conducted to study the performance of these test criteria. In order to illustrate these procedures, QML estimates of dynamic earnings functions from the Michigan Panel are obtained.-4-Joint minimum distance estimators of slope and covariance parameters are defined that are generally efficient relative to QML estimators when normality is not imposed and the covariance matrix is restricted. Finally, it is shown that there exist separate minimum distance estimators of the covariance parameters and generalised least squares estimators of the slope parameters that are efficient. A simulation is also carried out to examine the performance of these methods.

Application of Operations Research to Managerial Decision Making

Abstract: Beyond the routine actions of the industrial executive are the decisionmaking or planning activities. Operations research has been successful in developing and applying scientific methods to aid decision makers. This article has a fivefold purpose: to outline the decision-making process and the role of the decision maker in this process; to indicate the utility of operations research in solving decision-making problems, to show how analytic models are constructed and solved, to note some tools and techniques for solving such models; and to forecast some possible future developments of operations research techniques and their possible effects upon decision making. Burton V. Dean is associate professor in the operations research group, Department of Engineering Administration, Case Institute of Technology.

Economic Theory and Public Decisions: Selected Essays of Robert Dorfman

Abstract: Contents: Acknowledgements Introduction Part I: Statistics Part II: Mathematical Methods Part III: Economic Theory Part IV: Natural Resource and Environmental Economics Part V: Social Decisions Part VI: History of Economics Index