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Books > Business & Economics > Economics > Econometrics
This collection of original articles 8 years in the making
shines a bright light on recent advances in financial econometrics.
From a survey of mathematical and statistical tools for
understanding nonlinear Markov processes to an exploration of the
time-series evolution of the risk-return tradeoff for stock market
investment, noted scholars Yacine Ait-Sahalia and Lars Peter Hansen
benchmark the current state of knowledge while contributors build a
framework for its growth. Whether in the presence of statistical
uncertainty or the proven advantages and limitations of value at
risk models, readers will discover that they can set few
constraints on the value of this long-awaited volume.
Computational Economics: A Perspective from Computational Intelligence provides models of various economic and financial issues while using computational intelligence as a foundation. The scope of this volume comprises finance, economics, management, organizational theory and public policies. It explains the ongoing and novel research in this field, and displays the power of these computational methods in coping with difficult problems with methods from traditional perspectives. By encouraging the discussion of different views, this book serves as an introductory and inspiring volume that helps to flourish studies in computational economics.
A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories. The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research.
This book provides the first comprehensive introduction to multi-agent, multi-choice repetitive games, such as the Kolkata Restaurant Problem and the Minority Game. It explains how the tangible formulations of these games, using stochastic strategies developed by statistical physicists employing both classical and quantum physics, have led to very efficient solutions to the problems posed. Further, it includes sufficient introductory notes on information-processing strategies employing both classical statistical physics and quantum mechanics. Games of this nature, in which agents are presented with choices, from among which their goal is to make the minority choice, offer effective means of modeling herd behavior and market dynamics and are highly relevant to assessing systemic risk. Accordingly, this book will be of interest to economists, physicists, and computer scientists alike.
This second edition sees the light three years after the first one: too short a time to feel seriously concerned to redesign the entire book, but sufficient to be challenged by the prospect of sharpening our investigation on the working of econometric dynamic models and to be inclined to change the title of the new edition by dropping the "Topics in" of the former edition. After considerable soul searching we agreed to include several results related to topics already covered, as well as additional sections devoted to new and sophisticated techniques, which hinge mostly on the latest research work on linear matrix polynomials by the second author. This explains the growth of chapter one and the deeper insight into representation theorems in the last chapter of the book. The role of the second chapter is that of providing a bridge between the mathematical techniques in the backstage and the econometric profiles in the forefront of dynamic modelling. For this purpose, we decided to add a new section where the reader can find the stochastic rationale of vector autoregressive specifications in econometrics. The third (and last) chapter improves on that of the first edition by re- ing the fruits of the thorough analytic equipment previously drawn up."
A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement. This book contains methodology for the analysis of data that arise from such multiscale processes. The book brings together a number of recent developments and makes them accessible to a wider audience. Taking a Bayesian approach allows for full accounting of uncertainty, and also addresses the delicate issue of uncertainty at multiple scales. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice. The book is aimed at statisticians, applied mathematicians, and engineers working on problems dealing with multiscale processes in time and/or space, such as in engineering, finance, and environmetrics. The book will also be of interest to those working on multiscale computation research. The main prerequisites are knowledge of Bayesian statistics and basic Markov chain Monte Carlo methods. A number of real-world examples are thoroughly analyzed in order to demonstrate the methods and to assist the readers in applying these methods to their own work. To further assist readers, the authors are making source code (for R) available for many of the basic methods discussed herein.
This book offers a practical guide to Agent Based economic modeling, adopting a "learning by doing" approach to help the reader master the fundamental tools needed to create and analyze Agent Based models. After providing them with a basic "toolkit" for Agent Based modeling, it present and discusses didactic models of real financial and economic systems in detail. While stressing the main features and advantages of the bottom-up perspective inherent to this approach, the book also highlights the logic and practical steps that characterize the model building procedure. A detailed description of the underlying codes, developed using R and C, is also provided. In addition, each didactic model is accompanied by exercises and applications designed to promote active learning on the part of the reader. Following the same approach, the book also presents several complementary tools required for the analysis and validation of the models, such as sensitivity experiments, calibration exercises, economic network and statistical distributions analysis. By the end of the book, the reader will have gained a deeper understanding of the Agent Based methodology and be prepared to use the fundamental techniques required to start developing their own economic models. Accordingly, "Economics with Heterogeneous Interacting Agents" will be of particular interest to graduate and postgraduate students, as well as to academic institutions and lecturers interested in including an overview of the AB approach to economic modeling in their courses.
The book details the innovative TERM (The Enormous Regional Model) approach to regional and national economic modeling, and explains the conversion from a comparative-static to a dynamic model. It moves on to an adaptation of TERM to water policy, including the additional theoretical and database requirements of the dynamic TERM-H2O model. In particular, it examines the contrasting economic impacts of water buyback policy and recurring droughts in the Murray-Darling Basin. South-east Queensland, where climate uncertainty has been borne out by record-breaking drought and the worst floods in living memory, provides a chapter-length case study. The exploration of the policy background and implications of TERM's dynamic modeling will provide food for thought in policy making circles worldwide, where there is a pressing need for solutions to similarly intractable problems in water management.
This book explores a wide range of issues related to the methodology, organization, and technologies of analytical work, showing the potential of using analytical tools and statistical indicators for studying socio-economic processes, forecasting, organizing effective companies, and improving managerial decisions. At the level of "living knowledge" in the broad context, it describes the essence of analytical technologies and means of applying analytical and statistical work. The book is of interest to readers regardless of their specialization: scientific research, medicine, pedagogics, law, administrative work, or economic practice. Starting from the premise that readers are familiar with the theory of statistics, which has formulated the general methods and principles of establishing the quantitative characteristics of mass phenomena and processes, it describes the concepts, definitions, indicators and classifications of socio-economic statistics, taking into consideration the international standards and the present-day practice of statistics in Russia. Although concise, the book provides plenty of study material as well as questions at the end of each chapter It is particularly useful for those interested in self-study or remote education, as well as business leaders who are interested in gaining a scientific understanding of their financial and economic activities.
"A Companion to Theoretical Econometrics" provides a comprehensive
reference to the basics of econometrics. It focuses on the
foundations of the field and at the same time integrates popular
topics often encountered by practitioners. The chapters are written
by international experts and provide up-to-date research in areas
not usually covered by standard econometric texts.
This book is an exceptional reference for readers who require
quick access to the foundation theories in this field. Chapters are
organized to provide clear information and to point to further
readings on the subject. Important topics covered include:
This book covers the econometric methodsnecessary for a practicing applied economist or data analyst. This requiresboth an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations. FEATURES: Integration of econometrics methods with statistical foundations Worked examples of all models considered in the text Includes Excel datasheets to facilitate estimation and application of models Features instructor ancillaries for use as atextbook
Recent advancements in data collection will affect all aspects of businesses, improving and bringing complexity to management and demanding integration of all resources, principles, and processes. The interpretation of these new technologies is essential to the advancement of management and business. The Handbook of Research on Expanding Business Opportunities With Information Systems and Analytics is a vital scholarly publication that examines technological advancements in data collection that will influence major change in many aspects of business through a multidisciplinary approach. Featuring coverage on a variety of topics such as market intelligence, knowledge management, and brand management, this book explores new complexities to management and other aspects of business. This publication is designed for entrepreneurs, business managers and executives, researchers, business professionals, data analysts, academicians, and graduate-level students seeking relevant research on data collection advancements.
As conceived by the founders of the Econometric Society,
econometrics is a field that uses economic theory and statistical
methods to address empirical problems in economics. It is a tool
for empirical discovery and policy analysis. The chapters in this
volume embody this vision and either implement it directly or
provide the tools for doing so. This vision is not shared by those
who view econometrics as a branch of statistics rather than as a
distinct field of knowledge that designs methods of inference from
data based on models of human choice behavior and social
interactions. All of the essays in this volume and its companion
volume 6B offer guidance to the practitioner on how to apply the
methods they discuss to interpret economic data. The authors of the
chapters are all leading scholars in the fields they survey and
extend.
This book is written in the light of the latest developments in the field of multidimensional poverty measurement. It includes clear presentations of more than a dozen different quantitative techniques based respectively on information or fuzzy sets theory, the Rasch model, Factor, Cluster and Multiple Correspondence Analysis, MIMIC and structural equations models, efficiency analysis, axiomatic, subjective and ordinal approaches to the topic. The book provides empirical illustrations based on data sources from developed or developing countries.
An empirical econometric study that tests an earlier worldwide survey showing that advertising has had little impact on total alcohol consumption or adverse outcomes associated with drinking. The advertising executives, also trained as sociologists and statisticians, offer a conceptual model for advertising effects. They define and describe both predictor and outcome variables and how they are operationalized and measured. Statistical data are summarized and trends in predictor variables and alcohol consumption from 1950 to 1990 are identified. Data are analyzed in a regression context to isolate factors that significantly affect demand for alcohol and time series relationships are explored. In addition they focus on mortality rates over the 40 year study period of three diseases clearly related to the consumption of alcohol. Fisher and Cook simulate how rates and numbers of deaths might be affected if advertising or prices changed, and then they collect all their findings and draw conclusions. For academic and professional audiences of economists and sociologists, businessmen and women, policymakers, and communicators.
The series is designed to bring together those mathematicians who are seriously interested in getting new challenging stimuli from economic theories with those economists who are seeking effective mathematical tools for their research. A lot of economic problems can be formulated as constrained optimizations and equilibration of their solutions. Various mathematical theories have been supplying economists with indispensable machineries for these problems arising in economic theory. Conversely, mathematicians have been stimulated by various mathematical difficulties raised by economic theories.
Research on forecasting methods has made important progress over
recent years and these developments are brought together in the
Handbook of Economic Forecasting. The handbook covers developments
in how forecasts are constructed based on multivariate time-series
models, dynamic factor models, nonlinear models and combination
methods. The handbook also includes chapters on forecast
evaluation, including evaluation of point forecasts and probability
forecasts and contains chapters on survey forecasts and volatility
forecasts. Areas of applications of forecasts covered in the
handbook include economics, finance and marketing.
The explosive growth in computational power over the past several
decades offers new tools and opportunities for economists. This
handbook volume surveys recent research on Agent-based
Computational Economics (ACE), the computational study of economic
processes modeled as dynamic systems of interacting agents.
Empirical referents for "agents" in ACE models can range from
individuals or social groups with learning capabilities to physical
world features with no cognitive function. Topics covered include:
learning; empirical validation; network economics; social dynamics;
financial markets; innovation and technological change;
organizations; market design; automated markets and trading agents;
political economy; social-ecological systems; computational
laboratory development; and general methodological issues.
This is a practical guide to solutions for forecasting demand for services and products in international markets - and much more than just a listing of dry theoretical methods. Leading experts present studies on improving methods for forecasting numbers of incoming patent filings at the European Patent Office. These are reviewed by practitioners of the existing methods, revealing that it may not always be wise to trust established regression approaches.
The contributors present theoretical and empirical advances on business cycles analysis with particular attention to Euro-zone characteristics. The book also identifies applications of sophisticated tools by private and public institutions involved in the analysis of economic fluctuations.
Income Elasticity and Economic Development: Methods and Applications is mainly concerned with methods of estimating income elasticity. This field is connected with economic development that can be achieved by reducing income inequality. This is highly relevant in today's world, where the gap between rich and poor is widening with the growth of economic development. Income Elasticity and Economic Development: Methods and Applications provides a good example in showing how to calculate income elasticity, using a number of methods from widely available grouped data. Some of the techniques presented here can be used in a wide range of policy areas in all developed, developing and under-developed countries. Policy analysts, economists, business analysts and market researchers will find this book very useful.
Analyzing the Gross National Product (GNP) and other national economic statistics is one way to look at the financial well being of a country. Another more revealing and more interesting way is to analyze the variety and amount of goods and services consumed by citizens, businesses, and the various levels of government. The "Handbook" presents a systematic and statistical portrait of consumption and wealth, allowing readers to better understand America's economic, political, and cultural landscape. This handbook focuses on the latest statistical information available on U.S. spending habits by exploring a wide range of economic, demographic, and geographic variables.
The field of spatial econometrics has come to include the methods and models that deal with estimation and testing problems encountered when attempting to implement regional economic models. Those problems are often characterized by the difficulties associated with assessing the importance of spatial dependence and spatial heterogeneity. This book includes contributions on spatial proximity, spatial patterning and in particular the spatial association (dependence) contained in local map patterns.
This volume addresses important issues in economic theory and international trade with contributions from internationally renowned researchers - including some of Murray C. Kemp's many colleagues and former students.Economic Theory and International Trade begins with an examination of classical trade theory and welfare economics. It goes on to discuss international trade policy, including international trading agreements, taxation, tariffs and quotas. Attention then turns to the role of market structure in joint ventures, innovation, tariff policy and political economy. The final section is devoted to economic dynamics and international economics, with an emphasis on learning mechanisms, sustainable growth and immigration. This book will be indispensable to academics and graduate students in the area of international trade. Economic theorists and international trade specialists such as research units and researchers in government will also find this book of great interest. |
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