Jati Sengupta – författare

Measuring productive efficiency for nonprofit organizations has posed a great challenge to applied researchers today. The problem has many facets and diverse implications for a number of disciplines such as economics, applied statistics, management science and information theory. This monograph discusses four major areas, which emphasize the applied economic and econometric as. pects of the production frontier analysis: A. Stochastic frontier theory, B. Data envelopment analysis, C. Clustering and estimation theory, D. Economic and managerial applications Besides containing an up-to-date survey of the mos. t recent developments in the field, the monograph presents several new results and theorems from my own research. These include but are not limited to the following: (1) interface with parametric theory, (2) minimax and robust concepts of production frontier, (3) game-theoretic extension of the Farrell and Johansen models, (4) optimal clustering techniques for data envelopment analysis and (5) the dynamic and stochastic generalizations of the efficiency frontier at the micro and macro levels. In my research work in this field I have received great support and inspiration from Professor Abraham Charnes of the University of Texas at Austin, who has basically founded the technique of data envelopment analysis, developed it and is still expanding it. My interactions with him have been most fruitful and productive. I am deeply grateful to him. Finally, I must record my deep appreciation to my wife and two children for their loving and enduring support. But for their support this work would not have been completed.

Econometrics as an applied discipline attempts to use information in a most efficient manner, yet the information theory and entropy approach developed by Shannon and others has not played much of a role in applied econometrics. "Econometrics of Information and Efficiency" aims to bridge the gap. Broadly viewed, information theory analyzes the uncertainty of a given set of data and its probabilistic characteristics. Whereas the economic theory of information emphasizes the value of information to agents in a market, the entropy theory stresses the various aspects of imprecision of data and their interactions with the subjective decision processes. The tools of information theory, such as the maximum entropy principle, mutual information and the minimum discrepancy are useful in several areas of statistical inference, for instance Bayesian estimation, expected maximum likelihood principle, and the fuzzy statistical regression. This volume analyzes the applications of these tools of information theory to the most commonly used models in econometrics.The features of the text include: a critical survey of the uses of information theory in economics and econometrics; an integration of applied information theory and economic efficiency analysis; and the development of a new economic hypotheses relating information theory to economic growth models. New lines of research are emphasized.

This volume assesses the techniques of data envelopment analysis in dynamic and stochastic fields. It features: a comprehensive treatment of productive efficiency analysis in the dynamic environment; insight into the stochastic aspects of efficiency analysis including modern control theory; and applications in systems theory including flexible manufacturing systems. Results and applications are stressed in: growth theory in economics; time series models; and the recent models of technological diffusion.

This volume provides an integrated, modern treatment of control theory in economics. In addition to synthesizing the different phases of control theory methods, including feedback, stochastic and adaptive control, it discusses several recent developments in applied control theory. Aspects of econometrics estimation receive special emphasis, because of their importance to empirical applications in economics. The text is intended as a general reference for researchers and graduate students of applied control theory methods, but also has extensive professional applications in dynamic portfolio models in finance, neoclassical models of optimal growth, stabilizing control policies in variable structure models and problems of forecasting and estimation in dynamic models of rational expectations.

Modern economies have undergone a dramatic change.  There has been a shift from large scale material manufacturing to the design and application of new technology with R&D and human capital.  The new information age has introduced significant productivity gains through increasing returns and learning by doing, which has challenged the traditional growth models based on competitive market structures.  Institutions outside the traditional markets and the genetic principle of survival of the fittest have dominated the current theory of industry growth. This book coordinates and integrates the two strands of economic growth and development: the endogenous theory of growth and the extra-market models of evolutionary economics dominated by innovation efficiency.  It presents this new paradigm in terms of both theory and historical experiences.  The book addresses the role of innovations and human capital, the impact of information technology, the role of institutions as mechanisms of evolutionary economies and the experiences of Asian growth miracles, and will be of interest to readers in economics and political science concerned with economic growth and development.

Control theory methods in economics have historically developed over three phases. The first involved basically the feedback control rules in a deterministic framework which were applied in macrodynamic models for analyzing stabilization policies. The second phase raised the issues of various types of inconsistencies in deterministic optimal control models due to changing information and other aspects of stochasticity. Rational expectations models have been extensively used in this plan to resolve some of the inconsistency problems. The third phase has recently focused on the various aspects of adaptive control. where stochasticity and information­ adaptivity are introduced in diverse ways e.g .• risk adjustment and risk sensitivity of optimal control, recursive updating rules via Kalman filtering and weighted recursive least squares and variable structure control methods in nonlinear framework. Problems of efficient econometric estimation of optimal control models have now acquired significant importance. This monograph provides an integrated view of control theory methods, synthesizing the three phases from feedback control to stochastic control and from stochastic control to adaptive control. Aspects of econometric estimation are strongly emphasized here, since these are very important in empirical applications in economics.

Economic growth of a country depends on its industries. The focus of modern growth theory is basically macroeconomics, although neoclassical models use competitive markets and the optimization behavior of households and firms in general equilibrium framework. The emphasis here is on industry growth, where the microfoundations of industry are analyzed in terms of economic efficiency. The various linkages which link firm growth with the industry growth are discerned here under various market structures both competitive and monopolistic. The role of information in facilitating market signals and allowing the adoption of new processes has been especially emphasized in this volume. Many issues of market failure and the suboptimality of competitive equilibria are due to incomplete and imperfect information structures and we need a comprehensive theory of information structures underlying the process of industry growth and its dynamics. This book will be of interest to economists studying economic and industry growth and innovation.

Modern economies have undergone a dramatic change.  There has been a shift from large scale material manufacturing to the design and application of new technology with R&D and human capital.  The new information age has introduced significant productivity gains through increasing returns and learning by doing, which has challenged the traditional growth models based on competitive market structures.  Institutions outside the traditional markets and the genetic principle of survival of the fittest have dominated the current theory of industry growth. This book coordinates and integrates the two strands of economic growth and development: the endogenous theory of growth and the extra-market models of evolutionary economics dominated by innovation efficiency.  It presents this new paradigm in terms of both theory and historical experiences.  The book addresses the role of innovations and human capital, the impact of information technology, the role of institutions as mechanisms of evolutionary economies and the experiences of Asian growth miracles, and will be of interest to readers in economics and political science concerned with economic growth and development.

Economic growth of a country depends on its industries. The focus of modern growth theory is basically macroeconomics, although neoclassical models use competitive markets and the optimization behavior of households and firms in general equilibrium framework. The emphasis here is on industry growth, where the microfoundations of industry are analyzed in terms of economic efficiency. The various linkages which link firm growth with the industry growth are discerned here under various market structures both competitive and monopolistic. The role of information in facilitating market signals and allowing the adoption of new processes has been especially emphasized in this volume. Many issues of market failure and the suboptimality of competitive equilibria are due to incomplete and imperfect information structures and we need a comprehensive theory of information structures underlying the process of industry growth and its dynamics. This book will be of interest to economists studying economic and industry growth and innovation.

The current economic theory of innovation mainly analyses the technology factor and its impact on economic growth. In today's world, growth in information technology and knowledge of new ideas has altered the business paradigm dramatically. Modern economies have undergone a dynamic shift from material manufacturing to a new information technology model with research and development (R&D) and human capital. Through information and communications technology efficient information usage has achieved substantial productivity gains through learning by doing and incremental innovations. The present volume discusses this new paradigm in terms of both theory and industry applications, including Schumpeter in his innovation model and the emphasis on new innovations replacing the old. Growth of business networking and R&D consortium have dramatically helped the modern business to reduce their unit costs and improve efficiency. This volume presents some new models emphasizing knowledge sharing and R&D cooperation. Rapid growth in recent times in some south Asian countries have been cited as growth miracles are largely caused by knowledge spillover and learning by doing, and this volume also investigates the role of incremental innovations. With a strong focus and extension of the current theory of innovation and industry growth experiences of both the US and Asian countries, this book will be of interest to MBA and graduate students in economics, innovation management, and applied industrial economics.

The current economic theory of innovation mainly analyses the technology factor and its impact on economic growth. Rapid growth in recent times in some south Asian countries have been cited as growth miracles are largely caused by knowledge spillover and learning by doing, and this volume also investigates the role of incremental innovations.

New efficiency theory refers to the various parametric and semi-parametric methods of estimating production and cost frontiers, which include data envelopment analysis (DEA) with its diverse applications in management science and operations research. This monograph develops and generalizes the new efficiency theory by highlighting the interface between economic theory and operations research.Some of the outstanding features of this monograph are: (1) integrating the theory of firm efficiency and industry equilibrium, (2) emphasizing growth efficiency in a dynamic setting, (3) incorporating uncertainty of market demand and prices, and (4) the implications of group efficiency by sharing investments. Applications discuss in some detail the growth and decline of US computer industry, and the relative performance of mutual fund portfolios.

New efficiency theory refers to the various parametric and semi-parametric methods of estimating production and cost frontiers, which include data envelopment analysis (DEA) with its diverse applications in management science and operations research. This monograph develops and generalizes the new efficiency theory by highlighting the interface between economic theory and operations research.Some of the outstanding features of this monograph are: (1) integrating the theory of firm efficiency and industry equilibrium, (2) emphasizing growth efficiency in a dynamic setting, (3) incorporating uncertainty of market demand and prices, and (4) the implications of group efficiency by sharing investments. Applications discuss in some detail the growth and decline of US computer industry, and the relative performance of mutual fund portfolios.

Use of information is basic to economic theory in two ways. As a basis for optimization, it is central to all normative hypotheses used in eco­ nomics, but in decision-making situations it has stochastic and evolution­ ary aspects that are more dynamic and hence more fundamental. This book provides an illustrative survey of the use of information in econom­ ics and other decision sciences. Since this area is one of the most active fields of research in modern times, it is not possible to be definitive on all aspects of the issues involved. However questions that appear to be most important in this author's view are emphasized in many cases, without drawing any definite conclusions. It is hoped that these questions would provoke new interest for those beginning researchers in the field who are currently most active. Various classifications of information structures and their relevance for optimal decision-making in a stochastic environment are analyzed in some detail. Specifically the following areas are illustrated in its analytic aspects: 1. Stochastic optimization in linear economic models, 2. Stochastic models in dynamic economics with problems of time-inc- sistency, causality and estimation, 3. Optimal output-inventory decisions in stochastic markets, 4. Minimax policies in portfolio theory, 5. Methods of stochastic control and differential games, and 6. Adaptive information structures in decision models in economics and the theory of economic policy.

This book presents the main applied aspects of stochas­ tic optimization in economic models. Stochastic processes and control theory are used under optimization to illustrate the various economic implications of optimal decision rules. Unlike econometrics which deals with estimation, this book emphasizes the decision-theoretic basis of uncertainty specified by the stochastic point of view. Methods of ap­ plied stochastic control using stochastic processes have now reached an exciti~g phase, where several disciplines like systems engineering, operations research and natural reso- ces interact along with the conventional fields such as mathematical economics, finance and control systems. Our objective is to present a critical overview of this broad terrain from a multidisciplinary viewpoint. In this attempt we have at times stressed viewpoints other than the purely economic one. We believe that the economist would find it most profitable to learn from the other disciplines where stochastic optimization has been successfully applied. It is in this spirit that we have discussed in some detail the following major areas: A. Portfolio models in ·:finance, B. Differential games under uncertainty, c. Self-tuning regulators, D. Models of renewable resources under uncertainty, and ix x PREFACE E. Nonparametric methods of efficiency measurement. Stochastic processes are now increasingly used in economic models to understand the various adaptive behavior implicit in the formulation of expectation and its application in decision rules which are optimum in some sense.

Econometrics as an applied discipline attempts to use information in a most efficient manner, yet the information theory and entropy approach developed by Shannon and others has not played much of a role in applied econometrics. Econometrics of Information and Efficiency bridges the gap. Broadly viewed, information theory analyzes the uncertainty of a given set of data and its probabilistic characteristics. Whereas the economic theory of information emphasizes the value of information to agents in a market, the entropy theory stresses the various aspects of imprecision of data and their interactions with the subjective decision processes. The tools of information theory, such as the maximum entropy principle, mutual information and the minimum discrepancy are useful in several areas of statistical inference, e.g., Bayesian estimation, expected maximum likelihood principle, the fuzzy statistical regression. This volume analyzes the applications of these tools of information theory to the most commonly used models in econometrics.The outstanding features of Econometrics of Information and Efficiency are: A critical survey of the uses of information theory in economics and econometrics; An integration of applied information theory and economic efficiency analysis; The development of a new economic hypothesis relating information theory to economic growth models; New lines of research are emphasized.

The volume extends the recent techniques of data envelopment analysis in dynamic and stochastic fields. Its outstanding features are: (1) a comprehensive and up-to-date treatment of productive efficiency analysis in the dynamic environment; (2) new insight into the stochastic aspects of efficiency analysis including modern control theory; and, (3) new applications in systems theory including flexible manufacturing systems. New results and applications are stressed in (1) new growth theory in economics, (2) new time series models and (3) the recent models of technological diffusion. Audience: The latest tools of efficiency analysis developed in this book, illustrated by numerous real life applications, are most suitable for graduate students and researchers in operations research, management science and applied econometrics.

This book presents the main applied aspects of stochas­ tic optimization in economic models. Stochastic processes and control theory are used under optimization to illustrate the various economic implications of optimal decision rules. Unlike econometrics which deals with estimation, this book emphasizes the decision-theoretic basis of uncertainty specified by the stochastic point of view. Methods of ap­ plied stochastic control using stochastic processes have now reached an exciti~g phase, where several disciplines like systems engineering, operations research and natural reso- ces interact along with the conventional fields such as mathematical economics, finance and control systems. Our objective is to present a critical overview of this broad terrain from a multidisciplinary viewpoint. In this attempt we have at times stressed viewpoints other than the purely economic one. We believe that the economist would find it most profitable to learn from the other disciplines where stochastic optimization has been successfully applied. It is in this spirit that we have discussed in some detail the following major areas: A. Portfolio models in ·:finance, B. Differential games under uncertainty, c. Self-tuning regulators, D. Models of renewable resources under uncertainty, and ix x PREFACE E. Nonparametric methods of efficiency measurement. Stochastic processes are now increasingly used in economic models to understand the various adaptive behavior implicit in the formulation of expectation and its application in decision rules which are optimum in some sense.

Measuring productive efficiency for nonprofit organizations has posed a great challenge to applied researchers today. The problem has many facets and diverse implications for a number of disciplines such as economics, applied statistics, management science and information theory. This monograph discusses four major areas, which emphasize the applied economic and econometric as. pects of the production frontier analysis: A. Stochastic frontier theory, B. Data envelopment analysis, C. Clustering and estimation theory, D. Economic and managerial applications Besides containing an up-to-date survey of the mos. t recent developments in the field, the monograph presents several new results and theorems from my own research. These include but are not limited to the following: (1) interface with parametric theory, (2) minimax and robust concepts of production frontier, (3) game-theoretic extension of the Farrell and Johansen models, (4) optimal clustering techniques for data envelopment analysis and (5) the dynamic and stochastic generalizations of the efficiency frontier at the micro and macro levels. In my research work in this field I have received great support and inspiration from Professor Abraham Charnes of the University of Texas at Austin, who has basically founded the technique of data envelopment analysis, developed it and is still expanding it. My interactions with him have been most fruitful and productive. I am deeply grateful to him. Finally, I must record my deep appreciation to my wife and two children for their loving and enduring support. But for their support this work would not have been completed.