Pioneered by American economist Paul Samuelson, revealed preference theory is based on the idea that the preferences of consumers are revealed in their purchasing behavior. Researchers in this field have developed complex and sophisticated mathematical models to capture the preferences that are 'revealed' through consumer choice behavior. This study of consumer demand and behavior is closely tied up with econometrics (especially nonparametric econometrics), where testing the validity of different theoretical models is an important aspect of research. The theory of revealed preference has a very long and distinguished tradition in economics, but there was no systematic presentation of the theory until now. This book deals with basic questions in economic theory, such as the relation between theory and data, and studies the situations in which empirical observations are consistent or inconsistent with some of the best known theories in economics.

This book deals with the application of wavelet and spectral methods for the analysis of nonlinear and dynamic processes in economics and finance. It reflects some of the latest developments in the area of wavelet methods applied to economics and finance. The topics include business cycle analysis, asset prices, financial econometrics, and forecasting. An introductory paper by James Ramsey, providing a personal retrospective of a decade's research on wavelet analysis, offers an excellent overview over the field.

Designed for a one-semester course, Applied Statistics for Business and Economics offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world. Numerous interesting and important examples reflect real-life situations, stimulating students to think realistically in tackling these problems. Calculations can be performed using any standard spreadsheet package. To help with the examples, the author offers both actual and hypothetical databases on his website http://iwu.edu/~bleekley The text explores ways to describe data and the relationships found in data. It covers basic probability tools, Bayes' theorem, sampling, estimation, and confidence intervals. The text also discusses hypothesis testing for one and two samples, contingency tables, goodness-of-fit, analysis of variance, and population variances. In addition, the author develops the concepts behind the linear relationship between two numeric variables (simple regression) as well as the potentially nonlinear relationships among more than two variables (multiple regression). The final chapter introduces classical time-series analysis and how it applies to business and economics. This text provides a practical understanding of the value of statistics in the real world. After reading the book, students will be able to summarize data in insightful ways using charts, graphs, and summary statistics as well as make inferences from samples, especially about relationships.

This book provides a detailed introduction to the theoretical and methodological foundations of production efficiency analysis using benchmarking. Two of the more popular methods of efficiency evaluation are Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), both of which are based on the concept of a production possibility set and its frontier. Depending on the assumed objectives of the decision-making unit, a Production, Cost, or Profit Frontier is constructed from observed data on input and output quantities and prices. While SFA uses different maximum likelihood estimation techniques to estimate a parametric frontier, DEA relies on mathematical programming to create a nonparametric frontier. Yet another alternative is the Convex Nonparametric Frontier, which is based on the assumed convexity of the production possibility set and creates a piecewise linear frontier consisting of a number of tangent hyper planes. Three of the papers in this volume provide a detailed and relatively easy to follow exposition of the underlying theory from neoclassical production economics and offer step-by-step instructions on the appropriate model to apply in different contexts and how to implement them. Of particular appeal are the instructions on (i) how to write the codes for different SFA models on STATA, (ii) how to write a VBA Macro for repetitive solution of the DEA problem for each production unit on Excel Solver, and (iii) how to write the codes for the Nonparametric Convex Frontier estimation. The three other papers in the volume are primarily theoretical and will be of interest to PhD students and researchers hoping to make methodological and conceptual contributions to the field of nonparametric efficiency analysis.

Though globalisation of the world economy is currently a powerful force, people’s international mobility appears to still be very limited. The goal of this book is to improve our knowledge of the true effects of migration flows. It includes contributions by prominent academic researchers analysing the socio-economic impact of migration in a variety of contexts: interconnection of people and trade flows, causes and consequences of capital remittances, understanding the macroeconomic impact of migration and the labour market effects of people’s flows. The latest analytical methodologies are employed in all chapters, while interesting policy guidelines emerge from the investigations. The style of the volume makes it accessible for both non-experts and advanced readers interested in this hot topic of today’s world.

Economists can use computer algebra systems to manipulate symbolic models, derive numerical computations, and analyze empirical relationships among variables. Maxima is an open-source multi-platform computer algebra system that rivals proprietary software. Maxima's symbolic and computational capabilities enable economists and financial analysts to develop a deeper understanding of models by allowing them to explore the implications of differences in parameter values, providing numerical solutions to problems that would be otherwise intractable, and by providing graphical representations that can guide analysis. This book provides a step-by-step tutorial for using this program to examine the economic relationships that form the core of microeconomics in a way that complements traditional modeling techniques. Readers learn how to phrase the relevant analysis and how symbolic expressions, numerical computations, and graphical representations can be used to learn from microeconomic models. In particular, comparative statics analysis is facilitated. Little has been published on Maxima and its applications in economics and finance, and this volume will appeal to advanced undergraduates, graduate-level students studying microeconomics, academic researchers in economics and finance, economists, and financial analysts.

This edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise ("fuzzy") expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks.

​This publication provides insight into the agricultural sector. It illustrates new tendencies in agricultural economics and dynamics (interrelationship with other sectors in rural zones and multifunctionality) and the implications of the World Trade Organization negotiations in the international trade of agricultural products. Due to environmental problems, availability of budget, consumer preferences for food safety and pressure from the World Trade Organization, there are many changes in the agricultural sector. This book addresses those new developments and provides insights into possible future developments. The agricultural activity is an economic sector that is fundamental for a sustainable economic growth of every country. However, this sector has many particularities, namely those related with some structural problems (many farms with reduced dimension, sometimes lack of vocational training of the farmers, difficulties of put the farmers together in associations and cooperatives), variations of the productions and prices over the year and some environmental problems derived from the utilization of pesticides and fertilizers.

Presents recent developments of probabilistic assessment of systems dependability based on stochastic models, including graph theory, finite state automaton and language theory, for both dynamic and hybrid contexts.

This ambitious book looks 'behind the model' to reveal how economists use formal models to generate insights into the economy. Drawing on recent work in the philosophy of science and economic methodology, the book presents a novel framework for understanding the logic of economic modeling. It also reveals the ways in which economic models can mislead rather than illuminate. Importantly, the book goes beyond purely negative critique, proposing a concrete program of methodological reform to better equip economists to detect potential mismatches between their models and the targets of their inquiry. Ranging across economics, philosophy, and social science methods, and drawing on a variety of examples, including the recent financial crisis, Behind the Model will be of interest to anyone who has wondered how economics works - and why it sometimes fails so spectacularly.

This ambitious book looks 'behind the model' to reveal how economists use formal models to generate insights into the economy. Drawing on recent work in the philosophy of science and economic methodology, the book presents a novel framework for understanding the logic of economic modeling. It also reveals the ways in which economic models can mislead rather than illuminate. Importantly, the book goes beyond purely negative critique, proposing a concrete program of methodological reform to better equip economists to detect potential mismatches between their models and the targets of their inquiry. Ranging across economics, philosophy, and social science methods, and drawing on a variety of examples, including the recent financial crisis, Behind the Model will be of interest to anyone who has wondered how economics works - and why it sometimes fails so spectacularly.

The individual risks faced by banks, insurers, and marketers are less well understood than aggregate risks such as market-price changes. But the risks incurred or carried by individual people, companies, insurance policies, or credit agreements can be just as devastating as macroevents such as share-price fluctuations. A comprehensive introduction, The Econometrics of Individual Risk is the first book to provide a complete econometric methodology for quantifying and managing this underappreciated but important variety of risk. The book presents a course in the econometric theory of individual risk illustrated by empirical examples. And, unlike other texts, it is focused entirely on solving the actual individual risk problems businesses confront today. Christian Gourieroux and Joann Jasiak emphasize the microeconometric aspect of risk analysis by extensively discussing practical problems such as retail credit scoring, credit card transaction dynamics, and profit maximization in promotional mailing. They address regulatory issues in sections on computing the minimum capital reserve for coverage of potential losses, and on the credit-risk measure CreditVar. The book will interest graduate students in economics, business, finance, and actuarial studies, as well as actuaries and financial analysts.

Many economic theories depend on the presence or absence of a unit root for their validity, and econometric and statistical theory undergo considerable changes when unit roots are present. Thus, knowledge on unit roots has become so important, necessitating an extensive, compact, and nontechnical book on this subject. This book is rested on this motivation and introduces the literature on unit roots in a comprehensive manner to both empirical and theoretical researchers in economics and other areas. By providing a clear, complete, and critical discussion of unit root literature, In Choi covers a wide range of topics, including uniform confidence interval construction, unit root tests allowing structural breaks, mildly explosive processes, exuberance testing, fractionally integrated processes, seasonal unit roots and panel unit root testing. Extensive, up to date, and readily accessible, this book is a comprehensive reference source on unit roots for both students and applied workers.

Three leading experts have produced a landmark work based on a set of working papers published by the Center for Operations Research and Econometrics (CORE) at the Universite Catholique de Louvain in 1994 under the title 'Repeated Games', which holds almost mythic status among game theorists. Jean-Francois Mertens, Sylvain Sorin and Shmuel Zamir have significantly elevated the clarity and depth of presentation with many results presented at a level of generality that goes far beyond the original papers - many written by the authors themselves. Numerous results are new, and many classic results and examples are not to be found elsewhere. Most remain state of the art in the literature. This book is full of challenging and important problems that are set up as exercises, with detailed hints provided for their solutions. A new bibliography traces the development of the core concepts up to the present day.

Three leading experts have produced a landmark work based on a set of working papers published by the Center for Operations Research and Econometrics (CORE) at the Universite Catholique de Louvain in 1994 under the title 'Repeated Games', which holds almost mythic status among game theorists. Jean-Francois Mertens, Sylvain Sorin and Shmuel Zamir have significantly elevated the clarity and depth of presentation with many results presented at a level of generality that goes far beyond the original papers - many written by the authors themselves. Numerous results are new, and many classic results and examples are not to be found elsewhere. Most remain state of the art in the literature. This book is full of challenging and important problems that are set up as exercises, with detailed hints provided for their solutions. A new bibliography traces the development of the core concepts up to the present day.

This book investigates the relationship between environmental degradation and income, focusing on carbon dioxide (CO2) emissions from around the world, to explore the possibility of sustainable development under global warming. Although many researchers have tackled this problem by estimating the Environmental Kuznets Curve (EKC), unlike the approach to sulfur dioxide emissions, there seems to be little consensus about whether EKC is formed with regard to CO2 emissions. Thus, EKC is one of the most controversial issues in the field of environmental economics. This book contributes three points with academic rigor. First, an unbalanced panel dataset containing over 150 countries with the latest CO2 emission data between 1960 and 2010 is constructed. Second, based on this dataset, the CO2 emission-income relationship is analyzed using strict econometric methods such as the dynamic panel model. Third, as it is often pointed out that some factors other than income affect CO2 emission, several variables were added to the estimation model to examine the effects of changes of industrial structure, energy composition, and overseas trade on CO2 emission.

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 book is a comprehensive introduction of the reader into the simulation and modelling techniques and their application in the management of organisations. The book is rooted in the thorough understanding of systems theory applied to organisations and focuses on how this theory can apply to econometric models used in the management of organisations. The econometric models in this book employ linear and dynamic programming, graph theory, queuing theory, game theory, etc. and are presented and analysed in various fields of application, such as investment management, stock management, strategic decision making, management of production costs and the lifecycle costs of quality and non-quality products, production quality Management, etc.

This is a book on deterministic and stochastic Growth Theory and the computational methods needed to produce numerical solutions. Exogenous and endogenous growth models are thoroughly reviewed. Special attention is paid to the use of these models for fiscal and monetary policy analysis. Modern Business Cycle Theory, the New Keynesian Macroeconomics, the class of Dynamic Stochastic General Equilibrium models, can be all considered as special cases of models of economic growth, and they can be analyzed by the theoretical and numerical procedures provided in the textbook. Analytical discussions are presented in full detail. The book is self contained and it is designed so that the student advances in the theoretical and the computational issues in parallel. EXCEL and Matlab files are provided on an accompanying website (see Preface to the Second Edition) to illustrate theoretical results as well as to simulate the effects of economic policy interventions. The structure of these program files is described in "Numerical exercise"-type of sections, where the output of these programs is also interpreted. The second edition corrects a few typographical errors and improves some notation.

Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "hot" topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models. With its world-class editors and contributors, it succeeds in unifying leading studies of economic models, mathematical statistics and economic data. Our flourishing ability to address empirical problems in economics by using economic theory and statistical methods has driven the field of econometrics to unimaginable places. By designing methods of inference from data based on models of human choice behavior and social interactions, econometricians have created new subfields now sufficiently mature to require sophisticated literature summaries.

To what extent should anybody who has to make model forecasts generated from detailed data analysis adjust their forecasts based on their own intuition? In this book, Philip Hans Franses, one of Europe's leading econometricians, presents the notion that many publicly available forecasts have experienced an 'expert's touch', and questions whether this type of intervention is useful and if a lighter adjustment would be more beneficial. Covering an extensive research area, this accessible book brings together current theoretical insights and new empirical results to examine expert adjustment from an econometric perspective. The author's analysis is based on a range of real forecasts and the datasets upon which the forecasters relied. The various motivations behind experts' modifications are considered, and guidelines for creating more useful and reliable adjusted forecasts are suggested. This book will appeal to academics and practitioners with an interest in forecasting methodology.

The recent financial crisis has heightened the need for appropriate methodologies for managing and monitoring complex risks in financial markets. The measurement, management, and regulation of risks in portfolios composed of credits, credit derivatives, or life insurance contracts is difficult because of the nonlinearities of risk models, dependencies between individual risks, and the several thousands of contracts in large portfolios. The granularity principle was introduced in the Basel regulations for credit risk to solve these difficulties in computing capital reserves. In this book, authors Patrick Gagliardini and Christian Gourieroux provide the first comprehensive overview of the granularity theory and illustrate its usefulness for a variety of problems related to risk analysis, statistical estimation, and derivative pricing in finance and insurance. They show how the granularity principle leads to analytical formulas for risk analysis that are simple to implement and accurate even when the portfolio size is large."

The purpose of this book is to establish a connection between the traditional field of empirical economic research and the emerging area of empirical financial research and to build a bridge between theoretical developments in these areas and their application in practice. Accordingly, it covers broad topics in the theory and application of both empirical economic and financial research, including analysis of time series and the business cycle; different forecasting methods; new models for volatility, correlation and of high-frequency financial data and new approaches to panel regression, as well as a number of case studies. Most of the contributions reflect the state-of-art on the respective subject. The book offers a valuable reference work for researchers, university instructors, practitioners, government officials and graduate and post-graduate students, as well as an important resource for advanced seminars in empirical economic and financial research.

This volume systematically details both the basic principles and new developments in Data Envelopment Analysis (DEA), offering a solid understanding of the methodology, its uses, and its potential. New material in this edition includes coverage of recent developments that have greatly extended the power and scope of DEA and have lead to new directions for research and DEA uses. Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. The first nine chapters cover the basic principles of DEA, while the final seven chapters provide a more advanced treatment.

This textbook, now in its second edition, is an introduction to econometrics from the Bayesian viewpoint. It begins with an explanation of the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It then turns to the definitions of the likelihood function, prior distributions, and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. The Bernoulli distribution is used as a simple example. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the derivation of marginal posterior distributions, which leads to an explanation of classical and Markov chain Monte Carlo (MCMC) methods of simulation. The latter is proceeded by a brief introduction to Markov chains. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics, and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH, and stochastic volatility models. The new edition also emphasizes the R programming language, which has become the most widely used environment for Bayesian statistics.