The rich, multi-faceted and multi-disciplinary field of matching-based market design is an active and important one due to its highly successful applications with economic and sociological impact. Its home is economics, but with intimate connections to algorithm design and operations research. With chapters contributed by over fifty top researchers from all three disciplines, this volume is unique in its breadth and depth, while still being a cohesive and unified picture of the field, suitable for the uninitiated as well as the expert. It explains the dominant ideas from computer science and economics underlying the most important results on market design and introduces the main algorithmic questions and combinatorial structures. Methodologies and applications from both the pre-Internet and post-Internet eras are covered in detail. Key chapters discuss the basic notions of efficiency, fairness and incentives, and the way market design seeks solutions guided by normative criteria borrowed from social choice theory.

Economists have long sought to develop quantitative models of economic behaviour, which blend economic theory with data evidence. Econometric modelling of economic time series has strived to achieve this by seeking to discover sustainable and interpretable relationships. This important two-volume collection focuses on a central method used in selecting such models, namely simplification of an initially general model that adequately characterizes the empirical evidence within the investigators' theoretical framework. The volumes feature a wealth of evidence that has accrued over the last five years displaying its excellent abilities for model selection, based on Monte Carlo studies of automatic algorithms. These also throw light on several major methodological issues, and prompt many new ideas, which are discussed. The collection will be valuable to all empirical economists and econometricians.

Showcasing fuzzy set theory, this book highlights the enormous potential of fuzzy logic in helping to analyse the complexity of a wide range of socio-economic patterns and behaviour. The contributions to this volume explore the most up-to-date fuzzy-set methods for the measurement of socio-economic phenomena in a multidimensional and/or dynamic perspective. Thus far, fuzzy-set theory has primarily been utilised in the social sciences in the field of poverty measurement. These chapters examine the latest work in this area, while also exploring further applications including social exclusion, the labour market, educational mismatch, sustainability, quality of life and violence against women. The authors demonstrate that real-world situations are often characterised by imprecision, uncertainty and vagueness, which cannot be properly described by the classical set theory which uses a simple true-false binary logic. By contrast, fuzzy-set theory has been shown to be a powerful tool for describing the multidimensionality and complexity of social phenomena. This book will be of significant interest to economists, statisticians and sociologists utilising quantitative methods to explore socio-economic phenomena.

"Econometrics textbooks see their subject as a set of techniques; Magnus and Morgan see it as a set of practices. A combination of controlled experiment and anthropology of science, Methodology and Tacit Knowledge gives a rare inside view of how econometricians work, why econometrics is an art and not a set of simple recipes, and why, like all artists, econometricians differ in their techniques and finished works. This is economic methodology at its best." Kevin Hoover, University of California, Davis

"The tacit knowledge experiment was a highly commendable initiative. Its exploration of the theme of how knowledge is acquired and used in applied econometrics is unique and produced some fascinating insights into this process." Adrian Pagan, Australian National University

"It is rare, perhaps unique, to find leading empirical economists face the prospect of modelling the same phenomena, with the same data within the same limited time frame. A valuable and illuminating experiment in comparative research methodologies, made all the more provocative when compared to the excellent original study by Tobin." Richard Blundell, University College London

This book will be of considerable interest to economists and to econometricians concerned about the methodology of their own discipline, and will provide valuable material for researchers in science studies and for teachers of econometrics.

Predicting foreign exchange rates has presented a long-standing challenge for economists. However, the recent advances in computational techniques, statistical methods, newer datasets on emerging market currencies, etc., offer some hope. While we are still unable to beat a driftless random walk model, there has been serious progress in the field. This book provides an in-depth assessment of the use of novel statistical approaches and machine learning tools in predicting foreign exchange rate movement. First, it offers a historical account of how exchange rate regimes have evolved over time, which is critical to understanding turning points in a historical time series. It then presents an overview of the previous attempts at modeling exchange rates, and how different methods fared during this process. At the core sections of the book, the author examines the time series characteristics of exchange rates and how contemporary statistics and machine learning can be useful in improving predictive power, compared to previous methods used. Exchange rate determination is an active research area, and this book will appeal to graduate-level students of international economics, international finance, open economy macroeconomics, and management. The book is written in a clear, engaging, and straightforward way, and will greatly improve access to this much-needed knowledge in the field.

The essays in this special volume survey some of the most recent advances in the global analysis of dynamic models for economics, finance and the social sciences. They deal in particular with a range of topics from mathematical methods as well as numerous applications including recent developments on asset pricing, heterogeneous beliefs, global bifurcations in complementarity games, international subsidy games and issues in economic geography. A number of stochastic dynamic models are also analysed. The book is a collection of essays in honour of the 60th birthday of Laura Gardini.

Handbook of Field Experiments, Volume Two explains how to conduct experimental research, presents a catalog of research to date, and describes which areas remain to be explored. The new volume includes sections on field experiments in education in developing countries, how to design social protection programs, a section on how to combat poverty, and updates on data relating to the impact and determinants of health levels in low-income countries. Separating itself from circumscribed debates of specialists, this volume surpasses the many journal articles and narrowly-defined books written by practitioners. This ongoing series will be of particular interest to scholars working with experimental methods. Users will find results from politics, education, and more.

The collapse in commodity prices since 1980 has been a major cause of the economic crisis in a large number of developing countries. This book investigates whether the commodity-producing countries, by joint action, could have prevented the price collapse by appropriate supply management. The analysis is focused on the markets for the tropical beverage crops: coffee, cocoa, and tea. Using new econometric models for each market, the impact of alternative supply management schemes on supply, consumption, prices, and export earnings is simulated for the later 1980s. The results indicate that supply management by producing countries would, indeed, have been a viable alternative to the `free market' approach favoured by the developed countries. This has important implications for current international commodity policy, and, in particular, for future joint action by producing countries to overcome persistent commodity surpluses as a complement to needed diversification.

This book addresses the functioning of financial markets, in particular the financial market model, and modelling. More specifically, the book provides a model of adaptive preference in the financial market, rather than the model of the adaptive financial market, which is mostly based on Popper's objective propensity for the singular, i.e., unrepeatable, event. As a result, the concept of preference, following Simon's theory of satisficing, is developed in a logical way with the goal of supplying a foundation for a robust theory of adaptive preference in financial market behavior. The book offers new insights into financial market logic, and psychology: 1) advocating for the priority of behavior over information - in opposition to traditional financial market theories; 2) constructing the processes of (co)evolution adaptive preference-financial market using the concept of fetal reaction norms - between financial market and adaptive preference; 3) presenting a new typology of information in the financial market, aimed at proving point (1) above, as well as edifying an explicative mechanism of the evolutionary nature and behavior of the (real) financial market; 4) presenting sufficient, and necessary, principles or assumptions for developing a theory of adaptive preference in the financial market; and 5) proposing a new interpretation of the pair genotype-phenotype in the financial market model. The book's distinguishing feature is its research method, which is mainly logically rather than historically or empirically based. As a result, the book is targeted at generating debate about the best and most scientifically beneficial method of approaching, analyzing, and modelling financial markets.

The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian thresholding methods in hierarchical graphical models, adaptive reversible jump MCMC, LASSO estimators, parameter expansion algorithms, the implementation of parameter and non-parameter-based approaches to variable selection, a survey of key results in objective Bayesian model selection methodology, and a careful look at the modeling of endogeneity in discrete data settings. Important contemporary questions are examined in applications in macroeconomics, finance, banking, labor economics, industrial organization, and transportation, among others, in which model uncertainty is a central consideration.

This is the eighth volume in a ten-volume set designed for publication in 1997. It reprints in book form a selection of the most important and influential articles on probability, econometrics and economic games which cumulatively have had a major impact on the development of modern economics. There are 242 articles, dating from 1936 to 1996. Many of them were originally published in relatively inaccessible journals and may not, therefore, be available in the archives of many university libraries. The volumes are available separately and also as a complete ten-volume set. The contributors include D. Ellsberg, R.M. Hogart, J.B. Kadane, B.O. Koopmans, E.L. Lehman, D.F. Nicholls, H. Rubin, T.J. Sarjent, L.H. Summers and C.R. Wymer. This particular volume deals with the time series models.

Computational Finance Using C and C#: Derivatives and Valuation, Second Edition provides derivatives pricing information for equity derivatives, interest rate derivatives, foreign exchange derivatives, and credit derivatives. By providing free access to code from a variety of computer languages, such as Visual Basic/Excel, C++, C, and C#, it gives readers stand-alone examples that they can explore before delving into creating their own applications. It is written for readers with backgrounds in basic calculus, linear algebra, and probability. Strong on mathematical theory, this second edition helps empower readers to solve their own problems. *Features new programming problems, examples, and exercises for each chapter. *Includes freely-accessible source code in languages such as C, C++, VBA, C#, and Excel.. *Includes a new chapter on the history of finance which also covers the 2008 credit crisis and the use of mortgage backed securities, CDSs and CDOs. *Emphasizes mathematical theory.

These essays honor Professor Peter C.B. Phillips of Yale University and his many contributions to the field of econometrics. Professor Phillips's research spans many topics in econometrics including: non-stationary time series and panel models partial identification and weak instruments Bayesian model evaluation and prediction financial econometrics and finite-sample statistical methods and results. The papers in this volume reflect additions to and amplifications of many of Professor Phillips' research contributions. Some of the topics discussed in the volume include panel macro-econometric modeling, efficient estimation and inference in difference-in-difference models, limiting and empirical distributions of IV estimates when some of the instruments are endogenous, the use of stochastic dominance techniques to examine conditional wage distributions of incumbents and newly hired employees, long-horizon predictive tests in financial markets, new developments in information matrix testing, testing for co-integration in Markov switching error correction models, and deviation information criteria for comparing vector autoregressive models.

The interaction between mathematicians and statisticians reveals to be an effective approach to the analysis of insurance and financial problems, in particular in an operative perspective.

The Maf2006 conference, held at the University of Salerno in 2006, had precisely this purpose and the collection published here gathers some of the papers presented at the conference and successively worked out to this aim. They cover a wide variety of subjects in insurance and financial fields.

Using data from the World Values Survey, this book sheds light on the link between happiness and the social group to which one belongs. The work is based on a rigorous statistical analysis of differences in the probability of happiness and life satisfaction between the predominant social group and subordinate groups. The cases of India and South Africa receive deep attention in dedicated chapters on cast and race, with other chapters considering issues such as cultural bias, religion, patriarchy, and gender. An additional chapter offers a global perspective. On top of this, the longitudinal nature of the data facilitates an examination of how world happiness has evolved between 1994 and 2014. This book will be a valuable reference for advanced students, scholars and policymakers involved in development economics, well-being, development geography, and sociology.

Now in its third edition, Essential Econometric Techniques: A Guide to Concepts and Applications is a concise, student-friendly textbook which provides an introductory grounding in econometrics, with an emphasis on the proper application and interpretation of results. Drawing on the author's extensive teaching experience, this book offers intuitive explanations of concepts such as heteroskedasticity and serial correlation, and provides step-by-step overviews of each key topic. This new edition contains more applications, brings in new material including a dedicated chapter on panel data techniques, and moves the theoretical proofs to appendices. After Chapter 7, students will be able to design and conduct rudimentary econometric research. The next chapters cover multicollinearity, heteroskedasticity, and autocorrelation, followed by techniques for time-series analysis and panel data. Excel data sets for the end-of-chapter problems are available as a digital supplement. A solutions manual is also available for instructors, as well as PowerPoint slides for each chapter. Essential Econometric Techniques shows students how economic hypotheses can be questioned and tested using real-world data, and is the ideal supplementary text for all introductory econometrics courses.

"Students of econometrics and their teachers will find this book to be the best introduction to the subject at the graduate and advanced undergraduate level. Starting with least squares regression, Hayashi provides an elegant exposition of all the standard topics of econometrics, including a detailed discussion of stationary and non-stationary time series. The particular strength of the book is the excellent balance between econometric theory and its applications, using GMM as an organizing principle throughout. Each chapter includes a detailed empirical example taken from classic and current applications of econometrics."--Dale Jorgensen, Harvard University

""Econometrics" will be a very useful book for intermediate and advanced graduate courses. It covers the topics with an easy to understand approach while at the same time offering a rigorous analysis. The computer programming tips and problems should also be useful to students. I highly recommend this book for an up-to-date coverage and thoughtful discussion of topics in the methodology and application of econometrics."--Jerry A. Hausman, Massachusetts Institute of Technology

""Econometrics" covers both modern and classic topics without shifting gears. The coverage is quite advanced yet the presentation is simple. Hayashi brings students to the frontier of applied econometric practice through a careful and efficient discussion of modern economic theory. The empirical exercises are very useful. . . . The projects are carefully crafted and have been thoroughly debugged."--Mark W. Watson, Princeton University

""Econometrics" strikes a good balance between technical rigor and clear exposition. . . . The use of empiricalexamples is well done throughout. I very much like the use of old 'classic' examples. It gives students a sense of history--and shows that great empirical econometrics is a matter of having important ideas and good data, not just fancy new methods. . . . The style is just great, informal and engaging."--James H. Stock, John F. Kennedy School of Government, Harvard University

This book contains some of the results from the research project "Demand for Food in the Nordic Countries," which was initiated in 1988 by Professor Olof Bolin of the Agricultural University in Ultuna, Sweden and by Professor Karl Iohan Weckman, of the University of Helsinki, Finland. A pilot study was carried out by Bengt Assarsson, which in 1989 led to a successful application for a research grant from the NKJ (The Nordic Contact Body for Agricultural Research) through the national research councils for agricultural research in Denmark, Finland, Norway and Sweden. We are very grateful to Olof Bolin and Karl Iohan Weckman, without whom this project would not have come about, and to the national research councils in the Nordic countries for the generous financial support we have received for this project. We have received comments and suggestions from many colleagues, and this has improved our work substantially. At the start of the project a reference group was formed, consisting of Professor Olof Bolin, Professor Anders Klevmarken, Agr. lie. Gert Aage Nielsen, Professor Karl Iohan Weckman and Cando oecon. Per Halvor Vale. Gert Aage Nielsen left the group early in the project for a position in Landbanken, and was replaced by Professor Lars Otto, while Per Halvor Vale soon joined the research staff. The reference group has given us useful suggestions and encouraged us in our work. Weare very grateful to them.

'Experiments in Organizational Economics' highlights the importance of replicating previous economic experiments. Replication enables experimental findings to be subjected to rigorous scrutiny. Despite this obvious advantage, direct replication remains relatively scant in economics. One possible explanation for this situation is that publication outlets favor novel work over tests of robustness. Readers will gain a better understanding of the role that replication plays in economic discovery as well as valuable insights into the robustness of previously reported findings.

This book bridges the gap between economic theory and spatial econometric techniques. It is accessible to those with only a basic statistical background and no prior knowledge of spatial econometric methods. It provides a comprehensive treatment of the topic, motivating the reader with examples and analysis. The volume provides a rigorous treatment of the basic spatial linear model, and it discusses the violations of the classical regression assumptions that occur when dealing with spatial data.

This volume investigates the accuracy and dynamic performance of a high-frequency forecast model for the Japanese and United States economies based on the Current Quarter Model (CQM) or High Frequency Model (HFM) developed by the late Professor Emeritus Lawrence R. Klein. It also presents a survey of recent developments in high-frequency forecasts and gives an example application of the CQM model in forecasting Gross Regional Products (GRPs).

Based on economic knowledge and logical reasoning, this book proposes a solution to economic recessions and offers a route for societal change to end capitalism. The author starts with a brief review of the history of economics, and then questions and rejects the trend of recent decades that has seen econometrics replace economic theory. By reviewing the different schools of economic thought and by examining the limitations of existing theories to business cycles and economic growth, the author forms a new theory to explain cyclic economic growth. According to this theory, economic recessions result from innovation scarcity, which in turn results from the flawed design of the patent system. The author suggests a new design for the patent system and envisions that the new design would bring about large economic and societal changes. Under this new patent system, the synergy of the patent and capital markets would ensure that economic recessions could be avoided and that the economy would grow at the highest speed.

Mathematical Economics is an authoritative collection of the most influential contributions essential to an understanding of this important area of economic science. These seminal papers illustrate the development of the field from its inception in the 19th century up to the present, and exhibit the power of mathematics to lead to new thinking which can illuminate the scientific structures underlying economic arguments. Many of these papers started new fields of economics, influencing deeply the way economists think about their world. They illustrate the extensive range of topics to which mathematics has been applied productively, and show the areas of mathematics which have proved valuable, including functional analysis, linear algebra, algebraic and differential topology, stochastic processes and dynamical systems. They also show the extent to which today's policy analysis rests on yesterday's mathematical economics. Anyone with an interest in economics as a science will find this collection indispensable. The collection is an essential part of any course using mathematical economics.

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.

The behaviour of commodity prices never ceases to marvel economists, financial analysts, industry experts, and policymakers. Unexpected swings in commodity prices used to occur infrequently but have now become a permanent feature of global commodity markets. This book is about modelling commodity price shocks. It is intended to provide insights into the theoretical, conceptual, and empirical modelling of the underlying causes of global commodity price shocks. Three main objectives motivated the writing of this book. First, to provide a variety of modelling frameworks for documenting the frequency and intensity of commodity price shocks. Second, to evaluate existing approaches used for forecasting large movements in future commodity prices. Third, to cover a wide range and aspects of global commodities including currencies, rare-hard-lustrous transition metals, agricultural commodities, energy, and health pandemics. Some attempts have already been made towards modelling commodity price shocks. However, most tend to narrowly focus on a subset of commodity markets, i.e., agricultural commodities market and/or the energy market. In this book, the author moves the needle forward by operationalizing different models, which allow researchers to identify the underlying causes and effects of commodity price shocks. Readers also learn about different commodity price forecasting models. The author presents the topics to readers assuming less prior or specialist knowledge. Thus, the book is accessible to industry analysts, researchers, undergraduate and graduate students in economics and financial economics, academic and professional economists, investors, and financial professionals working in different sectors of the commodity markets. Another advantage of the book's approach is that readers are not only exposed to several innovative modelling techniques to add to their modelling toolbox but are also exposed to diverse empirical applications of the techniques presented.