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Books > Business & Economics > Economics > Econometrics > General
The field of Computational Economics is a fast growing area. Due to the limitations in analytical modeling, more and more researchers apply numerical methods as a means of problem solving. In tum these quantitative results can be used to make qualitative statements. This volume of the Advanced Series in Theoretical and Applied and Econometrics comprises a selected number of papers in the field of computational economics presented at the Annual Meeting of the Society Economic Dynamics and Control held in Minneapolis, June 1990. The volume covers ten papers dealing with computational issues in Econo metrics, Economics and Optimization. The first five papers in these proceedings are dedicated to numerical issues in econometric estimation. The following three papers are concerned with computational issues in model solving and optimization. The last two papers highlight some numerical techniques for solving micro models. We are sure that Computational Economics will become an important new trend in Economics in the coming decade. Hopefully this volume can be one of the first contributions highlighting this new trend. The Editors H.M. Amman et a1. (eds), Computational Economics and Econometrics, vii. (c) 1992 Kluwer Academic Publishers. PART ONE ECONOMETRICS LIKELIHOOD EVALUATION FOR DYNAMIC LATENT VARIABLES 1 MODELS DAVID F. HENDRY Nuffield College, Oxford, U.K. and JEAN-FRANc;mS RICHARD ISDS, Pittsburgh University, Pittsburgh, PA, U.S.A."
Economics has been basically a study of the interactions between organizations, with some organizations being so small we only have one person in them. The internal organization of the largest hierarchies has indeed been looked at, but a good reason for working less on these organizations is that the internal reactions are much harder to understand. It is sensible to solve the problems we can solve and put the others off until later. The author's basic purpose here is to look at these larger hierarchical organizations, and develop a scientific account of them. In Economic Hierarchies, Organization and the Structure of Production Gordon Tullock examines the internal functioning and organization of the corporation. In the author's personal tradition, the book relies on narrative analysis rather than mathematical complexity to convey insights into the functioning of the corporation.
Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.
The present work is an extension of my doctoral thesis done at Stanford in the early 1970s. In one clear sense it responds to the call for consilience by Edward O. Wilson. I agree with Wilson that there is a pressing need in the sciences today for the unification of the social with the natural sciences. I consider the present work to proceed from the perspective of behavioral ecology, specifically a subfield which I choose to call interpersonal behavioral ecology th Ecology, as a general field, has emerged in the last quarter of the 20 century as a major theme of concern as we have become increasingly aware that we must preserve the planet whose limited resources we share with all other earthly creatures. Interpersonal behavioral ecology, however, focuses not on the physical environment, but upon our social environment. It concerns our interpersonal behavioral interactions at all levels, from simple dyadic one-to-one personal interactions to our larger, even global, social, economic, and political interactions. Interpersonal behavioral ecology, as I see it, then, is concerned with our behavior toward each other, from the most obvious behaviors of war between nations, to excessive competition, exploitation, crime, abuse, and even to the ways in which we interact with each other as individuals in the family, in our social lives, in the workplace, and in the marketplace.
Technology Commercialization: DEA and Related Analytical Methods for Evaluating The Use and Implementation of Technical Innovation examines both general Research & Development commercialization and targeted new product innovation. New product development is a major occupation of the technical sector of the global economy and is viewed in many ways as a means of economic stability for a business, an industry, and a country. The heart of the book is a detailing of the analytical methods-with special, but not exclusive emphasis on DEA methods-for evaluating and ranking the most promising R & D and technical innovation being developed. The sponsors of the research and development may involve universities, countries, industries, and corporations-all of these sources are covered in the book. In addition, the trade-off of environmental problems vis-a-vis new product development is discussed in a section of the book. Sten Thore (editor and author) has woven together the chapter contributions by a strong group of international researchers into a book that has characteristics of both a monograph and a unified edited volume of well-written papers in DEA, technology evaluation, R&D, and environmental economics. Finally, the use of DEA as an evaluation method for product innovation is an important new development in the field of R&D commercialization.
Since 1993 a major research programme, "Stochastic Decision Analysis in Forest Management" has been running at Department of Economics and Natural Resources, The Royal Veterinary and Agricultural University (KVL), Copenhagen, in collaboration with Institute of Mathematical Statistics, University of Copenhagen (KU). The research is funded by the two Universities; The Danish Agricultural and Veterinary Research Council; The Danish Research Academy; The National Forest and Nature Agency; and Danish Informatics Network in the Agricultural Sciepces (DINA). A first international workshop in the research programme was held 5 - 8 August, 1996 at Eldrupgaard, Denmark, within the frameworkofacollaborationagreementbetween University of California at Berkeley (UCB) and the Danish Universities, and funded by The Danish Research Academy and the L0venholm Foundation. Having participated in the workshop, Professor Peter Berck (UCB) suggested that the papers be published along with selected papers in the same scientific field, i.e. mainly cointegration analysis of time series in forestry. The editors express their sincere appreciations to the many persons who have contributed to the realisation of the present book: participants in the research programme and the workshop, in particular Professors S0ren Johansen (KU) and Peter Berck (UCB); authors outside the programme/workshop; reviewers of the papers not previously published, in particuler Associate Professors Niels Haldrup (Aarhus University) and Henrik Hansen (KVL); and finally Mrs Mette Riis and Lizzie Rohde who did the tedious work of giving the papers a uniform style. Copenhagen, October 1998.
In this book, we synthesize a rich and vast literature on econometric challenges associated with accounting choices and their causal effects. Identi?cation and es- mation of endogenous causal effects is particularly challenging as observable data are rarely directly linked to the causal effect of interest. A common strategy is to employ logically consistent probability assessment via Bayes' theorem to connect observable data to the causal effect of interest. For example, the implications of earnings management as equilibrium reporting behavior is a centerpiece of our explorations. Rather than offering recipes or algorithms, the book surveys our - periences with accounting and econometrics. That is, we focus on why rather than how. The book can be utilized in a variety of venues. On the surface it is geared - ward graduate studies and surely this is where its roots lie. If we're serious about our studies, that is, if we tackle interesting and challenging problems, then there is a natural progression. Our research addresses problems that are not well - derstood then incorporates them throughout our curricula as our understanding improves and to improve our understanding (in other words, learning and c- riculum development are endogenous). For accounting to be a vibrant academic discipline, we believe it is essential these issues be confronted in the undergr- uate classroom as well as graduate studies. We hope we've made some progress with examples which will encourage these developments.
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."
In economics, many quantities are related to each other. Such
economic relations are often much more complex than relations in
science and engineering, where some quantities are independence and
the relation between others can be well approximated by
linear To make economic models more adequate, we need more accurate
techniques for describing dependence. Such techniques are currently
being developed. This book contains description of state-of-the-art
techniques for modeling dependence and economic applications
of
Econophysics is an emerging interdisciplinary field that takes advantage of the concepts and methods of statistical physics to analyse economic phenomena. This book expands the explanatory scope of econophysics to the real economy by using methods from statistical physics to analyse the success and failure of companies. Using large data sets of companies and income-earners in Japan and Europe, a distinguished team of researchers show how these methods allow us to analyse companies, from huge corporations to small firms, as heterogeneous agents interacting at multiple layers of complex networks. They then show how successful this approach is in explaining a wide range of recent findings relating to the dynamics of companies. With mathematics kept to a minimum, the book is not only a lively introduction to the field of econophysics but also provides fresh insights into company behaviour.
The manuscript reviews some key ideas about artificial intelligence, and relates them to economics. These include its relation to robotics, and the concepts of synthetic emotions, consciousness, and life. The economic implications of the advent of artificial intelligence, such as its effect on prices and wages, appropriate patent policy, and the possibility of accelerating productivity, are discussed. The growing field of artificial economics and the use of artificial agents in experimental economics is considered.
Macroeconomic Modelling has undergone radical changes in the last few years. There has been considerable innovation in developing robust solution techniques for the new breed of increasingly complex models. Similarly there has been a growing consensus on their long run and dynamic properties, as well as much development on existing themes such as modelling expectations and policy rules. This edited volume focuses on those areas which have undergone the most significant and imaginative developments and brings together the very best of modelling practice. We include specific sections on (I) Solving Large Macroeconomic Models, (II) Rational Expectations and Learning Approaches, (III) Macro Dynamics, and (IV) Long Run and Closures. All of the contributions offer new research whilst putting their developments firmly in context and as such will influence much future research in the area. It will be an invaluable text for those in policy institutions as well as academics and advanced students in the fields of economics, mathematics, business and government. Our contributors include those working in central banks, the IMF, European Commission and established academics.
This 2005 volume brings together twelve papers by many of the most prominent applied general equilibrium modelers honoring Herbert Scarf, the father of equilibrium computation in economics. It deals with developments in applied general equilibrium, a field which has broadened greatly since the 1980s. The contributors discuss some traditional as well as some modern topics in the field, including non-convexities in economy-wide models, tax policy, developmental modeling and energy modeling. The book also covers a range of distinct approaches, conceptual issues and computational algorithms, such as calibration and areas of application such as macroeconomics of real business cycles and finance. An introductory chapter written by the editors maps out issues and scenarios for the future evolution of applied general equilibrium.
Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, ... , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t< t*), and fJt = fJo + t1fJ (t"?:. t*), where t* is known.
Swaps, futures, options, structured instruments - a wide range of derivative products is traded in today's financial markets. Analyzing, pricing and managing such products often requires fairly sophisticated quantitative tools and methods. This book serves as an introduction to financial mathematics with special emphasis on aspects relevant in practice. In addition to numerous illustrative examples, algorithmic implementations are demonstrated using "Mathematica" and the software package "UnRisk" (available for both students and teachers). The content is organized in 15 chapters that can be treated as independent modules. In particular, the exposition is tailored for classroom use in a Bachelor or Master program course, as well as for practitioners who wish to further strengthen their quantitative background.
This tutorial presents a hands-on introduction to a new discrete choice modeling approach based on the behavioral notion of regret-minimization. This so-called Random Regret Minimization-approach (RRM) forms a counterpart of the Random Utility Maximization-approach (RUM) to discrete choice modeling, which has for decades dominated the field of choice modeling and adjacent fields such as transportation, marketing and environmental economics. Being as parsimonious as conventional RUM-models and compatible with popular software packages, the RRM-approach provides an alternative and appealing account of choice behavior. Rather than providing highly technical discussions as usually encountered in scholarly journals, this tutorial aims to allow readers to explore the RRM-approach and its potential and limitations hands-on and based on a detailed discussion of examples. This tutorial is written for students, scholars and practitioners who have a basic background in choice modeling in general and RUM-modeling in particular. It has been taken care of that all concepts and results should be clear to readers that do not have an advanced knowledge of econometrics.
Charles de Gaulle commence ses Memoires d'Espoir, ainsi: 'La France vient du fond des ages. Elle vito Les Siecles l'appellent. Mais elle demeure elle-meme au long du temps. Ses limites peuvent se modifier sans que changent Ie relief, Ie climat, les fleuves, les mers, qui la marquent indefmiment. Y habitent des peuples qu'etreignent, au cours de l'Histoire, les epreuves les plus diverses, mais que la nature des choses, utilisee par la politique, petrit sans cesse en une seule nation. Celle-ci a embrasse de nombreuses generations. Elle en comprend actuellement plusieurs. Elle en enfantera beaucoup d'autres. Mais, de par la geograpbie du pays qui est Ie sien, de par Ie genie des races qui la composent, de par les voisinages qui l'entourent, elle revet un caractere constant qui fait dependre de leurs peres les Fran ais de chaque epoque et les engage pour leurs descendants. A moins de se rompre, cet ensemble humain, sur ce territoire, au sein de cet univers, comporte donc un passe, un present, un avenir, indissolubles. Aussi l'ttat, qui repond de la France, est-il en charge, a la fois, de son heritage d'bier, de ses interets d'aujourd'hui et de ses espoirs de demain. ' A la lurniere de cette idee de nation, il est clair, qu'un dialogue entre nations est eminemment important et que la Semaine Universitaire Franco Neerlandaise est une institution pour stimuler ce dialogue."
This important collection brings together leading econometricians to discuss advances in the areas of the econometrics of panel data. The papers in this collection can be grouped into two categories. The first, which includes chapters by Amemiya, Baltagi, Arellano, Bover and Labeaga, primarily deal with different aspects of limited dependent variables and sample selectivity. The second group of papers, including those by Nerlove, Schmidt and Ahn, Kiviet, Davies and Lahiri, consider issues that arise in the estimation of dyanamic (possibly) heterogeneous panel data models. Overall, the contributors focus on the issues of simplifying complex real-world phenomena into easily generalisable inferences from individual outcomes. As the contributions of G. S. Maddala in the fields of limited dependent variables and panel data were particularly influential, it is a fitting tribute that this volume is dedicated to him.
Game Theory has provided an extremely useful tool in enabling economists to venture into unknown areas. Its concepts of conflict and cooperation apply whenever the actions of several agents are interdependent; providing language to formulate as well as to structure, analyze, and understand strategic scenarios. Economic Behavior, Game Theory, and Technology in Emerging Markets explores game theory and its deep impact in developmental economics, specifically the manner in which it provides a way of formalizing institutions. This is particularly important for emerging economies which have not yet received much attention in the academic world. This publication is useful for academics, professors, and researchers in this field, but it has also been compiled to meet the needs of non-specialists as well.
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This book reports the results of five empirical studies undertaken in the early seventies by a collaboration headed by Professor Morishima. It deals with applications of the general equilibrium models whose theoretical aspects have been one of Professor Morishima's main interests. Four main econometric models are constructed for the USA, the UK, and Japan. These are used as a basis for the discussion of various topics in economic theory, such as: the existence and stability or instability of the neoclassical path of full employment growth equilibrium and a von Neumann-type path of balanced growth at constant proces; the antimony between price-stability and full employment; the Samuelson-LeChatelier principle; the theory of the balanced-budget multiplier; the three Hicksian laws of the gross substitutes system; the Brown-Jones super-multipliers of international trade, and so on. In addition, this 1972 work makes a quantitative evaluation for the US economy of monetary and fiscal policies as short-run measures for achieving full employment; the effectiveness of built-in flexibility of taxes in the UK economy is discussed; and estimates are made of the rapid decrease in disguised unemployment in post-war Japan.
New Directions in Computational Economics brings together for the first time a diverse selection of papers, sharing the underlying theme of application of computing technology as a tool for achieving solutions to realistic problems in computational economics and related areas in the environmental, ecological and energy fields. Part I of the volume addresses experimental and computational issues in auction mechanisms, including a survey of recent results for sealed bid auctions. The second contribution uses neural networks as the basis for estimating bid functions for first price sealed bid auctions. Also presented is the `smart market' computational mechanism which better matches bids and offers for natural gas. Part II consists of papers that formulate and solve models of economics systems. Amman and Kendrick's paper deals with control models and the computational difficulties that result from nonconvexities. Using goal programming, Nagurney, Thore and Pan formulate spatial resource allocation models to analyze various policy issues. Thompson and Thrall next present a rigorous mathematical analysis of the relationship between efficiency and profitability. The problem of matching uncertain streams of assets and liabilities is solved using stochastic optimization techniques in the following paper in this section. Finally, Part III applies economic concepts to issues in computer science in addition to using computational techniques to solve economic models.
All humans eventually die, but life expectancies differ over time and among different demographic groups. Teasing out the various causes and correlates of death is a challenge, and it is one we take on in this book. A look at the data on mortality is both interesting and suggestive of some possible relationships. In 1900 life expectancies at birth were 46. 3 and 48. 3 years for men and women respectively, a gender differential of a bit less than 5 percent. Life expectancies for whites then were about 0. 3 years longer than that of the whole population, but life expectancies for blacks were only about 33 years for men and women. At age 65, the remaining life expectancies were about 12 and 11 years for whites and blacks respectively. Fifty years later, life expectancies at birth had grown to 66 and 71 years for males and females respectively. The percentage differential between the sexes was now almost up to 10 percent. The life expectancies of whites were about one year longer than that for the entire population. The big change was for blacks, whose life expectancy had grown to over 60 years with black females living about 5 percent longer than their male counterparts. At age 65 the remaining expected life had increased about two years with much larger percentage gains for blacks.
This book was first published in 1989. Inference and prediction in human affairs are characterised by a cognitive and reactive sample space, the elements of which are aware both of the statistician and of each other. It is therefore not surprising that methodologies borrowed from classical statistics and the physical sciences have yielded disappointingly few lasting empirical insights and have sometimes failed in predictive mode. This book puts the underlying methodology of socioeconomic statistics on a firmer footing by placing it within the ambit of inferential and predictive games. It covers such problems as learning, publication, non-response, strategic response, the nature and possibility of rational expectations, time inconsistency, intrinsic nonstationarity, and the existence of probabilities. Ideas are introduced such as real-time survey schemes, argument instability and reaction-proof forecasting based on stochastic approximation. Applications are canvassed to such topics as attitude measurement, political polling, econometric modelling under heterogeneous information, and the forecasting of hallmark events.
Cost Structure and the Measurement of Economic Performance is designed to provide a comprehensive guide for students, researchers or consultants who wish to model, construct, interpret, and use economic performance measures. The topical emphasis is on productivity growth and its dependence on the cost structure. The methodological focus is on application of the tools of economic analysis - the `thinking structure' provided by microeconomic theory - to measure technological or cost structure, and link it with market and regulatory structure. This provides a rich basis for evaluation of economic performance and its determinants. The format of the book stresses topics or questions of interest rather than the theoretical tools for analysis. Traditional productivity growth modeling and measurement practices that result in a productivity residual often called the `measure of our ignorance' are initially overviewed, and then the different aspects of technological, market and regulatory structure that might underlie this residual are explored. The ultimate goal is to decompose or explain the residual, by modeling and measuring a multitude of impacts that determine the economic performance of firms, sectors, and economies. The chapters are organized with three broad goals in mind. The first is to introduce the overall ideas involved in economic performance measurement and traditional productivity growth analysis. Issues associated with different types of (short and long run, internal and external) cost economies, market and regulatory impacts, and other general cost efficiencies that might impact these measures are then explored. Finally, some of the theoretical, data construction and econometric tools necessary to justify and implement these models are emphasized. |
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