This book provides a quantitative framework for the analysis of conflict dynamics and for estimating the economic costs associated with civil wars. The author develops modified Lotka-Volterra equations to model conflict dynamics, to yield realistic representations of battle processes, and to allow us to assess prolonged conflict traps. The economic costs of civil wars are evaluated with the help of two alternative methods: Firstly, the author employs a production function to determine how the destruction of human and physical capital stocks undermines economic growth in the medium term. Secondly, he develops a synthetic control approach, where the cost is obtained as the divergence of actual economic activity from a hypothetical path in the absence of civil war. The difference between the two approaches gives an indication of the adverse externalities impinging upon the economy in the form of institutional destruction. By using detailed time-series regarding battle casualties, local socio-economic indicators, and capital stock destruction during the Greek Civil War (1946-1949), a full-scale application of the above framework is presented and discussed.

Microsimulation Modelling involves the application of simulation methods to micro data for the purposes of evaluating the effectiveness and improving the design of public policy. The field has existed for over 50 years and has been applied to many different policy areas and is a methodology that is applied within both government and academia. This handbook brings together leading authors in the field to describe and discuss the main current issues within the field. The handbook provides an overview of current developments across each of the sub-fields of microsimulation modelling such as tax-benefit, pensions, spatial, health, labour, consumption, transport and land use policy as well as macro-micro, environmental and demographic issues. It focuses also on the modelling different micro units such as households, firms and farms. Each chapter discusses its sub-field under the following headings: the main methodologies of the sub-field; survey the literature in the area; critique the literature; and propose future directions for research within the sub-field.

Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A presents novel contributions to the analysis of time series and panel data with applications in macroeconomics, finance, cognitive science and psychology, neuroscience, and labor economics. Part B examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression. Individual chapters, written by both distinguished researchers and promising young scholars, cover many important topics in statistical and econometric theory and practice. Papers primarily, though not exclusively, adopt Bayesian methods for estimation and inference, although researchers of all persuasions should find considerable interest in the chapters contained in this work. The volume was prepared to honor the career and research contributions of Professor Dale J. Poirier. For researchers in econometrics, this volume includes the most up-to-date research across a wide range of topics.

Within the subprime crisis (2007) and the recent global financial crisis of 2008-2009, we have observed significant decline, corrections and structural changes in most US and European financial markets. Furthermore, it seems that this crisis has been rapidly transmitted toward the most developed and emerging countries and has strongly affected the whole economy. This volume aims to present recent researches in linear and nonlinear modelling of economic and financial time-series. The several discussions of empirical results of its chapters clearly help to improve the understanding of the financial mechanisms inherent to this crisis. They also yield an important overview on the sources of the financial crisis and its main economic and financial consequences. The book provides the audience a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It addresses the empirical techniques needed by economic agents to analyze the dynamics of these markets and illustrates how they can be applied to the actual data. It also presents and discusses new research findings and their implications.

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 30th volume of the International Symposia in Economic Theory and Econometrics explores the latest social and financial developments across Asian markets. Chapters cover a range of topics such as the impact of COVID-19 related events in Southeast Asia along the determinants of capital structure before and during the pandemic; the influence of new distribution concepts on macro and micro economic levels; as well as the effects of long-term cross-currency basis swaps on government bonds. These peer-reviewed papers touch on a variety of timely, interdisciplinary subjects such as real earnings impact and the effects of public policy. Together, Quantitative Analysis of Social and Financial Market Development is a crucial resource of current, cutting-edge research for any scholar of international finance and economics.

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:
serial correlation
heteroskedasticity
nonparametric and semiparametric models
count and panel data regression models
spatial correlation

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.
*Part of the renowned Handbooks in Economics Series
*Updates and expands the exisiting "Handbook of Econometrics" volumes
*An invaluable reference written by some of the world's leading econometricians.

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.

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.

Dynamic factor models (DFM) constitute an active and growing area of research, both in econometrics, in macroeconomics, and in finance. Many applications lie at the center of policy questions raised by the recent financial crises, such as the connections between yields on government debt, credit risk, inflation, and economic growth. This volume collects a key selection of up-to-date contributions that cover a wide range of issues in the context of dynamic factor modeling, such as specification, estimation, and application of DFMs. Examples include further developments in DFM for mixed-frequency data settings, extensions to time-varying parameters and structural breaks, for multi-level factors associated with subsets of variables, in factor augmented error correction models, and in many other related aspects. A number of contributions propose new estimation procedures for DFM, such as spectral expectation-maximization algorithms and Bayesian approaches. Numerous applications are discussed, including the dating of business cycles, implied volatility surfaces, professional forecaster survey data, and many more.

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.