A classic treatise that defined the field of applied demand analysis, Consumer Demand in the United States: Prices, Income, and Consumption Behavior is now fully updated and expanded for a new generation. Consumption expenditures by households in the United States account for about 70% of America's GDP. The primary focus in this book is on how households adjust these expenditures in response to changes in price and income. Econometric estimates of price and income elasticities are obtained for an exhaustive array of goods and services using data from surveys conducted by the Bureau of Labor Statistics and aggregate consumption expenditures from the National Income and Product Accounts, providing a better understanding of consumer demand. Practical models for forecasting future price and income elasticities are also demonstrated. Fully revised with over a dozen new chapters and appendices, the book revisits the original Houthakker-Taylor models while examining new material as well, such as the use of quantile regression and the stationarity of consumer preference. It also explores the emerging connection between neuroscience and consumer behavior, integrating the economic literature on demand theory with psychology literature. The most comprehensive treatment of the topic to date, this volume will be an essential resource for any researcher, student or professional economist working on consumer behavior or demand theory, as well as investors and policymakers concerned with the impact of economic fluctuations.

This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate the econometric methods with real applications and using computer codes to enable the practical implementation of these methods. Intuitive explanations throughout the book ensure that readers understand the basic technical tools of stochastic dominance.

Reformation of Econometrics is a sequel to The Formation of Econometrics: A Historical Perspective (1993, OUP) which traces the formation of econometric theory during the period 1930-1960. This book provides an account of the advances in the field of econometrics since the 1970s. Based on original research, it focuses on the reformists' movement and schools of thought and practices that attempted a paradigm shift in econometrics in the 1970s and 1980s. It describes the formation and consolidation of the Cowles Commission (CC) paradigm and traces and analyses the three major methodological attempts to resolve problems involved in model choice and specification of the CC paradigm. These attempts have reoriented the focus of econometric research from internal questions (how to optimally estimate a priori given structural parameters) to external questions (how to choose, design, and specify models). It also examines various modelling issues and problems through two case studies - modelling the Phillips curve and business cycles. The third part of the book delves into the development of three key aspects of model specification in detail - structural parameters, error terms, and model selection and design procedures. The final chapter uses citation analyses to study the impact of the CC paradigm over the span of three and half decades (1970-2005). The citation statistics show that the impact has remained extensive and relatively strong in spite of certain weakening signs. It implies that the reformative attempts have fallen short of causing a paradigm shift.

This volume is in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Jean Paelinck, arguably, is the founder of modern spatial econometrics. The impact on the profession through his work in spatial econometrics, regional science, and more conventional economics can be measured in many ways: through the work of his students, his devotion to and activism in facilitating the diffusion of regional science to Poland, the formulation and development of his FLEUR model, his co-founding of the French-speaking Regional Science Association, the voluminous references to his scholarly publications, his many invitations to be a featured speaker at conferences and universities throughout the world, the offices he has held in scholarly and professional associations, Erasmus University Rotterdam and the Netherlands Economic Institute, and the numerous honorary degrees he has been awarded. A series of special sessions in honour of Jean Paelinck were organized at the most prominent regional science meetings around the world. A number of prominent scholars in the field organized and participated in special sessions labelled In Honour of Professor Paelinck.' These sessions reflect a truly global reach of the techniques and methods pioneered by him. As an outgrowth of six conferences final versions of the selection of papers are collected in this volume. Prominent ideas contained in each of the selected contributions can be traced explicitly to work by Jean Paelinck.

Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs.

Studies in Consumer Demand - Econometric Methods Applied to Market Data contains eight previously unpublished studies of consumer demand. Each study stands on its own as a complete econometric analysis of demand for a well-defined consumer product. The econometric methods range from simple regression techniques applied in the first four chapters, to the use of logit and multinomial logit models used in chapters 5 and 6, to the use of nested logit models in chapters 6 and 7, and finally to the discrete/continuous modeling methods used in chapter 8. Emphasis is on applications rather than econometric theory. In each case, enough detail is provided for the reader to understand the purpose of the analysis, the availability and suitability of data, and the econometric approach to measuring demand.

This book provides the first ever comprehensive economic evaluation of the long-standing German system of works councils and worker directors on company boards. This system of codetermination, or "Mitbestimmung, " is unique in the degree of information provision, consultation, and participation ceded employees. Addison analyzes the effects of works councils on establishment productivity, profitability, investment in physical and intangible capital, employment, training, wages and organizational flexibility, as well as the influence of worker directors on some of the same indicators plus, critically, shareholder value. Today, works councils are in decline while worker directors have scarcely been embraced either from within or without. This book examines these challenges and addresses the likely evolution of codetermination.

Places, Towns and Townships is an excellent resource for anyone in need of data for all of the nation's cities, towns, townships, villages, and census-designated places in one convenient source. It compiles essential information about places in the United States and the people who live in them such as: * population * housing * income * education * employment * crime * and much more! In addition to the tables, Places, Towns and Townships includes text that describes key findings, figures that call attention to noteworthy trends in data, and rankings of the largest cities by various demographics. Compiled from multiple government sources, the data in this unique reference volume represents the most current and accurate information available. This data will not be updated for several years, making Places, Towns and Townships an invaluable resource in the years to come.

This book addresses environmental and climate change induced migration from the vantage point of migration studies, offering a broad spectrum of approaches for considering the environment/climate/migration nexus. Research on the subject is still frequently narrowed down to climate change vulnerability and the environmental push factor. The book establishes the interconnections between societal and environmental vulnerability, and migration and capability, allowing appreciation of migration in the frame of climate as a case of spatial and social mobility, that is, as a strategy of persons and groups to deal with a grossly unequal distribution of life chances across the world. In their introduction, the editors fan out the current debate and state the need to transcend predominantly policy-oriented approaches to migration. The first section of the volume focuses on "Methodologies and Methods" and presents very distinct approaches to think climate induced migration. Subsequent chapters explore the sensitivity of existing migration flows to climate change in Ghana and Bangladesh, the complex relationship between migration, demographic change and coping capacities in Canada, methodological challenges of a household survey on the significance of migration and remittances for adaptation in the Hindu Kush region and an econometric study of the aftermath of the 1998 floods in Bangladesh. The second part, "Areas of Concern: Politics and Human Rights", deepens the analysis of discourses as well as of the implications of proposed and implemented policies. Contributors discuss such topics as environmental migration as a multi-causal problem, climate migration as a consequence in an alarmist discourse and climate migration as a solution. A study of an integrated relocation program in Papua New Guinea is followed by chapters on the promise and the flaws of planned relocation policy, global policy on protection of environmental migrants including both internally displaced peoples and those who cross international borders. A concluding chapter places human agency at centre stage and explores the interplay between human rights, capability and migration.

A systematic treatment of dynamic decision making and performance measurement Modern business environments are dynamic. Yet, the models used to make decisions and quantify success within them are stuck in the past. In a world where demands, resources, and technology are interconnected and evolving, measures of efficiency need to reflect that environment. In Dynamic Efficiency and Productivity Measurement, Elvira Silva, Spiro E. Stefanou, and Alfons Oude Lansink look at the business process from a dynamic perspective. Their systematic study covers dynamic production environments where current production decisions impact future production possibilities. By considering practical factors like adjustments over time, this book offers an important lens for contemporary microeconomic analysis. Silva, Stefanou, and Lansink develop the analytical foundations of dynamic production technology in both primal and dual representations, with an emphasis on directional distance functions. They cover concepts measuring the production structure (economies of scale, economies of scope, capacity utilization) and performance (allocative, scale and technical inefficiency, productivity) in a methodological and comprehensive way. Through a unified approach, Dynamic Efficiency and Productivity Measurement offers a guide to how firms maximize potential in changing environments and an invaluable contribution to applied microeconomics.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

This book offers a series of statistical tests to determine if the "crowd out" problem, known to hinder the effectiveness of Keynesian economic stimulus programs, can be overcome by monetary programs. It concludes there are programs that can do this, specifically "accommodative monetary policy." They were not used to any great extent prior to the Quantitative Easing program in 2008, causing the failure of many fiscal stimulus programs through no fault of their own. The book includes exhaustive statistical tests to prove this point. There is also a policy analysis section of the book. It examines how effectively the Federal Reserve's anti-crowd out programs have actually worked, to the extent they were undertaken at all. It finds statistical evidence that using commercial and savings banks instead of investment banks when implementing accommodating monetary policy would have markedly improved their effectiveness. This volume, with its companion volume Why Fiscal Stimulus Programs Fail, Volume 2: Statistical Tests Comparing Monetary Policy to Growth, provides 1000 separate statistical tests on the US economy to prove these assertions.

The University of Oxford has been and continues to be one of the most important global centres for economics. With six chapters on themes in Oxford economics and 24 chapters on the lives and work of Oxford economists, this volume shows how economics became established at the University, how it produced some of the world's best-known economists, including Francis Ysidro Edgeworth, Roy Harrod and David Hendry, and how it remains a global force for the very best in teaching and research in economics. With original contributions from a stellar cast, this volume provides economists - especially those interested in macroeconomics and the history of economic thought - with the first in-depth analysis of Oxford economics.

Since its establishment in the 1950s the American Economic Association's Committee on Economic Education has sought to promote improved instruction in economics and to facilitate this objective by stimulating research on the teaching of economics. These efforts are most apparent in the sessions on economic education that the Committee organizes at the Association's annual meetings. At these sessions economists interested in economic education have opportunities to present new ideas on teaching and research and also to report the findings of their research. The record of this activity can be found in the Proceedings of the American Eco nomic Review. The Committee on Economic Education and its members have been actively involved in a variety of other projects. In the early 1960s it organized the National Task Force on Economic Education that spurred the development of economics teaching at the precollege level. This in turn led to the development of a standardized research instrument, a high school test of economic understanding. This was followed later in the 1960s by the preparation of a similar test of understanding college economics. The development of these two instruments greatly facilitated research on the impact of economics instruction, opened the way for application of increasingly sophisticated statistical methods in measuring the impact of economic education, and initiated a steady stream of research papers on a subject that previously had not been explored."

Thorough presentation of the problem of portfolio optimization, leading in a natural way to the Capital Market Theory Dynamic programming and the optimal portfolio selection-consumption problem through time An intuitive approach to Brownian motion and stochastic integral models for continuous time problems The Black-Scholes equation for simple European option values, derived in several different ways A chapter on several types of exotic options and one on material on the management of risk in several contexts

The second book in a set of ten on quantitative finance for practitioners Presents the theory needed to better understand applications Supplements previous training in mathematics Built from the author's four decades of experience in industry, research, and teaching

Features: New chapters on Barrier Options, Lookback Options, Asian Options, Optimal Stopping Theorem, and Stochastic Volatility. Contains over 235 exercises, and 16 problems with complete solutions. Added over 150 graphs and figures, for more than 250 in total, to optimize presentation. 57 R coding examples now integrated into the book for implementation of the methods. Substantially class-tested, so ideal for course use or self-study.

In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their parameters. This is done by taking the prior information and via Bayes theorem implementing Bayesian inferences of estimation, testing hypotheses, and prediction. The methods are demonstrated using both R and WinBUGS. The R package is primarily used to generate observations from a given time series model, while the WinBUGS packages allows one to perform a posterior analysis that provides a way to determine the characteristic of the posterior distribution of the unknown parameters. Features Presents a comprehensive introduction to the Bayesian analysis of time series. Gives many examples over a wide variety of fields including biology, agriculture, business, economics, sociology, and astronomy. Contains numerous exercises at the end of each chapter many of which use R and WinBUGS. Can be used in graduate courses in statistics and biostatistics, but is also appropriate for researchers, practitioners and consulting statisticians. About the author Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books for Chapman & Hall/CRC include Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.

THE GUIDE FOR ANYONE AFRAID TO LEARN STATISTICS & ANALYTICS UPDATED WITH NEW EXAMPLES & EXERCISES This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldn't learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. You'll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects. Create tabular and visual summaries and learn to avoid common charting errors Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others Understand the probability concepts that underlie inferential statistics Learn how to apply hypothesis tests, using Z, t, chi-square, ANOVA, and other techniques Develop skills using regression analysis, the most commonly-used Inferential statistical method Explore results produced by predictive analytics software Choose the right statistical or analytic techniques for any data analysis task Optionally, read the "Equation Blackboards," designed for readers who want to learn about the mathematical foundations of selected methods

Operation Research methods are often used in every field of modern life like industry, economy and medicine. The authors have compiled of the latest advancements in these methods in this volume comprising some of what is considered the best collection of these new approaches. These can be counted as a direct shortcut to what you may search for. This book provides useful applications of the new developments in OR written by leading scientists from some international universities. Another volume about exciting applications of Operations Research is planned in the near future. We hope you enjoy and benefit from this series!

This volume presents new methods and applications in longitudinal data estimation methodology in applied economic. Featuring selected papers from the 2020 the International Conference on Applied Economics (ICOAE 2020) held virtually due to the corona virus pandemic, this book examines interdisciplinary topics such as financial economics, international economics, agricultural economics, marketing and management. Country specific case studies are also featured.

This book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric and machine learning techniques? 2) To what extent can machine learning techniques assist econometric investigation? Specifically, how robust or stable is the prediction from machine learning algorithms given the ever-changing nature of human behavior? 3) Can machine learning techniques assist in testing statistical hypotheses and identifying causal relationships in 'big data? 4) How can existing econometric techniques be extended by incorporating machine learning concepts? 5) How can new econometric tools and approaches be elaborated on based on machine learning techniques? 6) Is it possible to develop machine learning techniques further and make them even more readily applicable in econometrics? As the data structures in economic and financial data become more complex and models become more sophisticated, the book takes a multidisciplinary approach in developing both disciplines of machine learning and econometrics in conjunction, rather than in isolation. This volume is a must-read for scholars, researchers, students, policy-makers, and practitioners, who are using econometrics in theory or in practice.

In the theory and practice of econometrics the model, the method and the data are all interdependent links in information recovery-estimation and inference. Seldom, however, are the economic and statistical models correctly specified, the data complete or capable of being replicated, the estimation rules ‘optimal’ and the inferences free of distortion. Faced with these problems, Maximum Entropy Economeirics provides a new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined and the data are partial or incomplete. By extending the maximum entropy formalisms used in the physical sciences, the authors present a new set of generalized entropy techniques designed to recover information about economic systems. The authors compare the generalized entropy techniques with the performance of the relevant traditional methods of information recovery and clearly demonstrate theories with applications including

• Pure inverse problems that include first order Markov processes, and input-output, multisectoral or SAM models to
• Inverse problems with noise that include statistical models subject to ill-conditioning, non-normal errors, heteroskedasticity, autocorrelation, censored, multinomial and simultaneous response data, as well as model selection and non-stationary and dynamic control problems

The Super Bowl is the most watched sporting event in the United States. But what does participating in this event mean for the players, the halftime performers, and the cities who host the games? Is there an economic benefit from being a part of the Super Bowl and if so, how much? This Palgrave Pivot examines the economic consequences for those who participate in the Super Bowl. The book fills in gaps in the literature by examining the benefits and costs of being involved in the game. Previously, the literature has largely ignored the affect the game has had on the careers of the players, particularly the stars of the game. The economic benefit of being the halftime performer has not been considered in the literature at all. While there have been past studies about the economic impact on the cities who host of the game, this book will expand on previous research and update it with new data.

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.