The editors are pleased to offer the following papers to the reader in recognition and appreciation of the contributions to our literature made by Robert Engle and Sir Clive Granger, winners of the 2003 Nobel Prize in Economics. The basic themes of this part of Volume 20 of Advances in Econometrics are time varying betas of the capital asset pricing model, analysis of predictive densities of nonlinear models of stock returns, modelling multivariate dynamic correlations, flexible seasonal time series models, estimation of long-memory time series models, the application of the technique of boosting in volatility forecasting, the use of different time scales in GARCH modelling, out-of-sample evaluation of the Fed Model in stock price valuation, structural change as an alternative to long memory, the use of smooth transition auto-regressions in stochastic volatility modelling, the analysis of the balanced-ness of regressions analyzing Taylor-Type rules of the Fed Funds rate, a mixture-of-experts approach for the estimation of stochastic volatility, a modern assessment of Clives first published paper on Sunspot activity, and a new class of models of tail-dependence in time series subject to jumps.
*This Series: Aids in the diffusion of new econometric techniques
*Emphasis is placed on expositional clarity and ease of assimilation for readers who are unfamiliar with a given topic of a volume
*Illustrates new concepts

In the era of Big Data our society is given the unique opportunity to understand the inner dynamics and behavior of complex socio-economic systems. Advances in the availability of very large databases, in capabilities for massive data mining, as well as progress in complex systems theory, multi-agent simulation and computational social science open the possibility of modeling phenomena never before successfully achieved. This contributed volume from the Perm Winter School address the problems of the mechanisms and statistics of the socio-economics system evolution with a focus on financial markets powered by the high-frequency data analysis.

Experimental economists are leaving the reservation. They are recruiting subjects in the field rather than in the classroom, using field goods rather than induced valuations, and using field context rather than abstract terminology in instructions. This volume examines the methodology of field experiments, and offers a wide array of applications of field experiments.

The methodological issues revolve around the ability of field experimenters to ensure the same degree of control that lab experimenters claim. The applications cover issues such as risk and time preferences of the Danish population, savings decisions of the Canadian working poor, differences between the social preferences of American students and workers, the effect of educational vouchers on American school children, and differences in bargaining behavior across nations. This volume serves as an introduction to the issues and applications of this new area of experimental economics.

Panel data econometrics has evolved rapidly over the last decade. Dynamic panel data estimation, non-linear panel data methods and the phenomenal growth in non-stationary panel data econometrics makes this an exciting area of research in econometrics. The 11th international conference on panel data held at Texas A&M University, College Station, Texas, June 2004, witnessed about 150 participants and 100 papers on panel data. This volume includes some of the papers presented at that conference and other solicited papers that made it through the refereeing process. "Contributions to Economic Analysis" was established in 1952. The series purpose is to stimulate the international exchange of scientific information. The series includes books from all areas of macroeconomics and microeconomics.

This book provides new evidence on the magnitude and sources of pay inequalities between women and men in European countries and New Zealand on the basis of micro data. Particular attention is devoted to job access and workplace practices, promotions and wage growth, sectoral affiliation and rent-sharing, and unobserved heterogeneity and dynamics.

The theory of practical rationality does not belong to one academic discipline alone. There are quite divergent philosophical, economical, sociological, psychological and politological contributions. Sometimes the disciplinary boundaries impede theoretical progress. On the other hand it is an indication for the high complexity of the subject that so many divergent paradigms compete with one another, or - what is worse - live separately in a kind of splendid isolation. Decision theory in the broader sense, embracing the theory of games and collective choice theory, can help to understand practical reason in philosophical analysis. But there are interesting aspects which cannot be dealt with adequately within a decision-theoretic conceptual framework. To have both of these convictions justifies to neglect dis ciplinary boundaries and poses a problem for the orthodoxies of either sides. All the essays of this volume focus on the relation between economic rationality and practical reason and discuss different aspects of the same problem, i. e. a basic deficiency in the standard economic theory of practical rationality. But philosophical analysis would not be of much help if it just rejected the economic paradigm. It must rather help to integrate economic aspects into a broader view on practical reason."

This volume is the result of an Advances in Econometrics conference held in November of 2002 at Louisiana State University in recognition of Halbert White's pioneering work published in Econometrica in 1980 and 1982 on robust variance-covariance estimation and quasi-maximum likelihood estimation. It contains 11 papers on a range of related topics including the estimation of possibly misspecified error component and fixed effects panel models, estimation and inference in possibly misspecified quantile regression models, quasi-maximum likelihood estimation of linear regression models with bounded and symmetric errors and quasi-maximum likelihood estimation of models with parameter dependencies between the mean vector and error variance-covariance matrix. Other topics include GMM, HAC, Heckit, asymmetric GARCH, Cross-Entropy, and multivariate deterministic trend estimation and testing under various possible misspecifications.

Microsimulation models provide an exciting new tool for analysing the distributional impact and cost of government policy changes. They can also be used to analyse the current or future structure of society. This volume contains papers describing new developments at the frontiers of microsimulation modelling, and draws upon experiences in a wide range of countries. Some papers aim to share with other modellers, experience gained in designing and running microsimulation models and their use in government policy formulation. They also examine issues at the frontiers of the discipline, such as how to include usage of health, education and welfare services in models. Other chapters focus upon describing the innovative new approaches being taken in dynamic microsimulation modelling. They describe some of the policy applications for which dynamic models are being used in Europe, Australia and New Zealand. Topics covered include retirement income modelling, pension reform, the behavioural impact of tax changes, child care demand, and the inclusion of government services within models. Attention is also given to validating the results of models and estimating their statistical reliability.

Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete.

The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation).
A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference.

This book is the English translation of Modelisation et Statistique Spatiales published by Springer in the series Mathematiques & Applications, a series established by Societe de Mathematiques Appliquees et Industrielles (SMAI)."

This book examines the numerous aspects of exchange rates and the dynamics of macroeconomics, focusing on the PPP puzzle, volatility, levels, with an exploration of the real exchange rate misalignment of the Central European countries single equation approach, an examination of the real equilibrium exchange rate in China, exchange rate dynamics and pass-through effects in Russia and Hungary, and structural shocks on economies.

Japan is a tiny country that occupies only 0.25% of the world's total land area. However, this small country is the world's third largest in economy: the Japanese GDP is roughly equivalent to the sum of any two major countries in Europe as of 2012. This book is a first attempt to ask leaders of top Japanese companies, such as Toyota, about their thoughts on mathematics. The topics range from mathematical problems in specific areas (e.g., exploration of natural resources, communication networks, finance) to mathematical strategy that helps a leader who has to weigh many different issues and make decisions in a timely manner, and even to mathematical literacy that ensures quality control. The reader may notice that every article reflects the authors' way of life and thinking, which can be evident in even one sentence. This book is an enlarged English edition of the Japanese book What Mathematics Can Do for You: Essays and Tips from Japanese Industry Leaders. In this edition we have invited the contributions of three mathematicians who have been working to expand and strengthen the interaction between mathematics and industry. The role of mathematics is usually invisible when it is applied effectively and smoothly in science and technology, and mathematical strategy is often hidden when it is used properly and successfully. The business leaders in successful top Japanese companies are well aware of this invisible feature of mathematics in applications aside from the intrinsic depth of mathematics. What Mathematics Can Do for You ultimately provides the reader an opportunity to notice what is hidden but key to business strategy.

The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty in the context of information theory. In 1957 Jaynes made use of Shannon's entropy concept as a basis for estimation and inference in problems that are ill-suited for traditional statistical procedures. This volume consists of two sections. The first section contains papers developing econometric methods based on the entropy principle. An interesting array of applications is presented in the second section of the volume.

This book presents an extensive survey of the theory and empirics of international parity conditions which are critical to our understanding of the linkages between world markets and the movement of interest and exchange rates across countries. The book falls into three parts dealing with the theory, methods of econometric testing and existing empirical evidence. Although it is intended to provide a consensus view on the subject, the authors also make some controversial propositions, particularly on the purchasing power parity conditions.

This book presents the latest advances in the theory and practice of Marshall-Olkin distributions. These distributions have been increasingly applied in statistical practice in recent years, as they make it possible to describe interesting features of stochastic models like non-exchangeability, tail dependencies and the presence of a singular component. The book presents cutting-edge contributions in this research area, with a particular emphasis on financial and economic applications. It is recommended for researchers working in applied probability and statistics, as well as for practitioners interested in the use of stochastic models in economics. This volume collects selected contributions from the conference "Marshall-Olkin Distributions: Advances in Theory and Applications," held in Bologna on October 2-3, 2013.

Each chapter of Macroeconometrics is written by respected econometricians in order to provide useful information and perspectives for those who wish to apply econometrics in macroeconomics. The chapters are all written with clear methodological perspectives, making the virtues and limitations of particular econometric approaches accessible to a general readership familiar with applied macroeconomics. The real tensions in macroeconometrics are revealed by the critical comments from different econometricians, having an alternative perspective, which follow each chapter.

An analysis of, and factual details on, the economy, natural resources, populations, foreign economic activity, and radical economic reform in the Russian Far East. Features of the public and private sectors are discussed providing a comprehensive discussion of this area.

The worlds of Wall Street and The City have always held a certain allure, but in recent years have left an indelible mark on the wider public consciousness and there has been a need to become more financially literate. The quantitative nature of complex financial transactions makes them a fascinating subject area for mathematicians of all types, whether for general interest or because of the enormous monetary rewards on offer. An Introduction to Quantitative Finance concerns financial derivatives - a derivative being a contract between two entities whose value derives from the price of an underlying financial asset - and the probabilistic tools that were developed to analyse them. The theory in the text is motivated by a desire to provide a suitably rigorous yet accessible foundation to tackle problems the author encountered whilst trading derivatives on Wall Street. The book combines an unusual blend of real-world derivatives trading experience and rigorous academic background. Probability provides the key tools for analysing and valuing derivatives. The price of a derivative is closely linked to the expected value of its pay-out, and suitably scaled derivative prices are martingales, fundamentally important objects in probability theory. The prerequisite for mastering the material is an introductory undergraduate course in probability. The book is otherwise self-contained and in particular requires no additional preparation or exposure to finance. It is suitable for a one-semester course, quickly exposing readers to powerful theory and substantive problems. The book may also appeal to students who have enjoyed probability and have a desire to see how it can be applied. Signposts are given throughout the text to more advanced topics and to different approaches for those looking to take the subject further.

In recent years, as part of the increasing "informationization" of industry and the economy, enterprises have been accumulating vast amounts of detailed data such as high-frequency transaction data in nancial markets and point-of-sale information onindividualitems in theretail sector. Similarly,vast amountsof data arenow ava- able on business networks based on inter rm transactions and shareholdings. In the past, these types of information were studied only by economists and management scholars. More recently, however, researchers from other elds, such as physics, mathematics, and information sciences, have become interested in this kind of data and, based on novel empirical approaches to searching for regularities and "laws" akin to those in the natural sciences, have produced intriguing results. This book is the proceedings of the international conference THICCAPFA7 that was titled "New Approaches to the Analysis of Large-Scale Business and E- nomic Data," held in Tokyo, March 1-5, 2009. The letters THIC denote the Tokyo Tech (Tokyo Institute of Technology)-Hitotsubashi Interdisciplinary Conference. The conference series, titled APFA (Applications of Physics in Financial Analysis), focuses on the analysis of large-scale economic data. It has traditionally brought physicists and economists together to exchange viewpoints and experience (APFA1 in Dublin 1999, APFA2 in Liege ` 2000, APFA3 in London 2001, APFA4 in Warsaw 2003, APFA5 in Torino 2006, and APFA6 in Lisbon 2007). The aim of the conf- ence is to establish fundamental analytical techniques and data collection methods, taking into account the results from a variety of academic disciplines.

Two central problems in the pure theory of economic growth are analysed in this monograph: 1) the dynamic laws governing the economic growth processes, 2) the kinematic and geometric properties of the set of solutions to the dynamic systems. With allegiance to rigor and the emphasis on the theoretical fundamentals of prototype mathematical growth models, the treatise is written in the theorem-proof style. To keep the exposition orderly and as smooth as possible, the economic analysis has been separated from the purely mathematical issues, and hence the monograph is organized in two books. Regarding the scope and content of the two books, an "Introduction and Over view" has been prepared to offer both motivation and a brief account. The introduc tion is especially designed to give a recapitulation of the mathematical theory and results presented in Book II, which are used as the unifying mathematical framework in the analysis and exposition of the different economic growth models in Book I. Economists would probably prefer to go directly to Book I and proceed by consult ing the mathematical theorems of Book II in confirming the economic theorems in Book I. Thereby, both the independence and interdependence of the economic and mathematical argumentations are respected."

Jean-Jacques Rousseau wrote in the Preface to his famous Discourse on Inequality that "I consider the subject of the following discourse as one of the most interesting questions philosophy can propose, and unhappily for us, one of the most thorny that philosophers can have to solve. For how shall we know the source of inequality between men, if we do not begin by knowing mankind?" (Rousseau, 1754). This citation of Rousseau appears in an article in Spanish where Dagum (2001), in the memory of whom this book is published, also cites Socrates who said that the only useful knowledge is that which makes us better and Seneca who wrote that knowing what a straight line is, is not important if we do not know what rectitude is. These references are indeed a good illustration of Dagum's vast knowledge, which was clearly not limited to the ?eld of Economics. For Camilo the ?rst part of Rousseau's citation certainly justi?ed his interest in the ?eld of inequality which was at the centre of his scienti?c preoccupations. It should however be stressed that for Camilo the second part of the citation represented a "solid argument in favor of giving macroeconomic foundations to microeconomic behavior" (Dagum, 2001). More precisely, "individualism and methodological holism complete each other in contributing to the explanation of individual and social behavior" (Dagum, 2001).

This book presents a theory of the general dynamic economic equilibrium which is a development of the static theory of Walras and Pareto. The work has built up an analytical model of the effective, current movement of an economic system, founded on the logic of the individual changing programmes - a basis for finding out the laws of all types of endogenous and exogenous movements of the economy. Indeed, the model can be used in the treatment of the typical problems of dynamic economics, by means of the author's method of variational dynamic analysis.

Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.

The subject theory is important in finance, economics, investment strategies, health sciences, environment, industrial engineering, etc.

Tax policy questions may relate to specific problems, concerning perhaps the revenue implications of a particular tax, or they may involve an extensive analysis of the cost and redistributive effects of many taxes and transfer payments. This book is concerned with the ways in which tax policy design can be enhanced by the use of a behavioural tax microsimulation model capable of evaluating the effects of planned or actual tax reforms. An advantage of such a large-scale tax simulation model, which reflects the heterogeneity of the population and captures the details of the tax structure, is that it can examine detailed practical policy questions and can provide direct inputs into policy debates. After introducing behavioural models, the authors discuss the role of means testing, several hypothetical policy reforms, actual and proposed reforms and recent modelling developments.Tax Policy Design and Behavioural Microsimulation Modelling will be of interest to academics and researchers of economics, econometrics and public finance. It will also be useful reading for policymakers responsible for the formulation of taxation.

The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way. It covers four major parts of modern econometrics: linear and nonlinear estimation and testing, time series analysis, models with categorical and limited dependent variables, and, finally, a thorough analysis of linear and nonlinear panel data modeling. Distinctive features of this handbook are:

-A unified approach of both linear and nonlinear econometrics, with an integration of the theory and the practice in modern econometrics. Emphasis on sound theoretical and empirical relevance and intuition. Focus on econometric and statistical methods for the analysis of linear and nonlinear processes in economics and finance, including computational methods and numerical tools.

-Completely worked out empirical illustrations are provided throughout, the macroeconomic and microeconomic (household and firm level) data sets of which are available from the internet; these empirical illustrations are taken from finance (e.g. CAPM and derivatives), international economics (e.g. exchange rates), innovation economics (e.g. patenting), business cycle analysis, monetary economics, housing economics, labor and educational economics (e.g. demand for teachers according to gender) and many others.

-Exercises are added to the chapters, with a focus on the interpretation of results; several of these exercises involve the use of actual data that are typical for current empirical work and that are made available on the internet.

What is also distinguishable in Modern Linear and Nonlinear Econometrics is that everymajor topic has a number of examples, exercises or case studies. By this learning by doing' method the intention is to prepare the reader to be able to design, develop and successfully finish his or her own research and/or solve real world problems.