Econometrics and economic statistics Books

Book SynopsisMany of the complex problems faced by decision makers involve uncertainty as well as multiple conflicting objectives. This book provides a complete understanding of the types of objective functions that should be used in multiattribute decision making. By using tools such as preference, value, and utility functions, readers will learn state-of-the-art methods to analyze prospects to guide decision making and will develop a process that guarantees a defensible analysis to rationalize choices. Summarizing and distilling classical techniques and providing extensive coverage of recent advances in the field, the author offers practical guidance on how to make good decisions in the face of uncertainty. This text will appeal to graduate students and practitioners alike in systems engineering, operations research, business, management, government, climate change, energy, and healthcare.Trade Review'Ali E. Abbas' new book on utility theory is a comprehensive treatment ranging from simple distinctions about facing uncertainty to general multiattribute utility theory. Beginning with a general approach to MAU, it then specializes to show how popular versions, such as additive utility, are actually very restrictive and other simple approaches, such as additive value functions with risk aversion, are much more general. He derives the complete forms of multiattribute utility functions having additive value functions. With utility transversality, he also demonstrates that there is only one dimension of risk attitude, as the value function translates risk attitude across dimensions. Abbas's book promises to be the standard reference work for decades to come.' Jim Matheson, Chairman and CFO, SmartOrg, Inc.'Foundations of Multiattribute Utility provides a much-needed update, a comprehensive structure, and indeed a vision for a field that has blossomed in the forty years since Keeney and Raiffa's Decisions with Multiple Objectives. The book synthesizes recent results by others and by the author, including an elegant copula representation. Thanks to the book's accessible style - which even includes Socratic dialogues - readers will appreciate its place within the rich mathematics of preference and economic utility theory and the rich practice of decision analysis. The book offers many rewards for modelers in these fields, while for researchers it is required reading.' Jeffrey M. Keisler, University of Massachusetts, Boston'The definitive work on preference, value, and utility that can serve the full range of decision situations. If you need to tackle a complex multiattribute preference problem, the answer is in this book. Ali E. Abbas has created a great text of a graduate course and a valuable reference for the practitioner.' Carl Spetzler, Strategic Decisions Group and author of Decision Quality'In Foundations of Multiattribute Utility, Ali E. Abbas has brought together divergent themes of research in decision-making with multiple objectives into a single, coherent whole. This book can serve as an introduction for decision-makers who want to think carefully about making trade-offs. It is also a reference for researchers who want to understand the latest developments in the field. I know I will be keeping this book close at hand in my office for years to come.' Jason Merrick, Virginia Commonwealth University'This book is a long overdue. It is encyclopedic in nature, chronicling many recent developments in utility theory, while summarizing the classical results in the field. The book is a perfect companion to Keeney and Raiffa's (1976) seminal book on multiattribute utility. It should be on the desk of any decision analyst, economist, or statistician who does research in or teaches utility theory.' Kenneth C. Lichtendahl, Jr, University of VirginiaTable of ContentsPart I. Foundations of Preference, Value, and Utility: 1. Preference, value, and utility; 2. Foundations of expected utility; 3. Some flawed methods of decision making; Part II. Deterministic Decisions: 4. The order rule: preferences for deterministic consequences; 5. Getting the attributes right; 6. Preference functions for single attributes; 7. Preference functions for multiple attributes; 8. Additive preference functions; 9. Valuing deterministic consequences – value functions; Part III. Decisions with Uncertainty: Multi-attribute Utility Functions Using a Value Measure: 10. Single-attribute utility function; 11. Multi-attribute utility functions using preference and value functions; 12. Utility functions over additive preference or value functions; Part IV. Decisions with Uncertainty: Properties of Single-Attribute Utility Functions: 13. The role of the utility function in valuing uncertain deals; 14. The risk aversion function; 15. Scale transformations applied to lottery outcomes; 16. The invariant transformation of a utility function; 17. Valuing changes in investment opportunities; 18. One-switch utility functions; 19. Utility transversality; 20. Multi-attribute risk aversion; Part V. Decisions with Uncertainty: Multi-attribute Utility Functions without Preference or Value Functions: 21. Attribute dominance utility; 22. The two-attribute utility tree; 23. Independence conditions for two attributes; 24. The multi-attribute utility tree; 25. Independence conditions for three or more attributes; 26. Higher-order independence conditions; 27. One-switch utility independence; Part VI. Utility Copula Formulations: 28. Multi-attribute utility copulas; 29. Archimedean utility copulas; 30. Assessing Archimedean utility copulas; 31. Utility copula functions matching all boundary assessments; 32. Bidirectional one-switch ordinal copulas; 33. Reflections of what we have learned.

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Book SynopsisDesigned for the intellectually curious, this book provides a solid foundation in basic probability theory in a charming style, without technical jargon. This text will immerse the reader in a mathematical view of the world, and teach them techniques to solve real-world problems both inside and outside the casino.Trade Review'Probability is a subject of fundamental importance that's often taught as a dry slog through ball-filled urns. Fat Chance, a snappy and example-rich text, is the perfect antidote and a great choice for a general-audience math course.' Jordan Ellenberg, University of Wisconsin-Madison'Mathematics is a minority sport. Only very few understand, say, algebraic geometry or ergodic theory, and that's perfectly OK. Yet, probability theory is different. We are surrounded by chance and uncertainty. You cannot be a fully-fledged, functioning twenty-first-century human, whether at work, as a consumer or as an active citizen, without understanding the basic rules that govern chance. This is a book explaining chance and probability to non-mathematicians: accessible, not expecting any prior knowledge - but, there being no free lunch, assuming basic intelligence and an open mind. A small price for great enlightenment.' Arieh Iserles, University of Cambridge'Fat Chance is a fun and friendly introduction to the big ideas of risk, probability, and uncertainty in our everyday lives and in the world around us. It's written by three of the greatest mathematicians - and teachers - anywhere on the planet. I loved it! And according to my calculations, there's a high probability you'll love it too.' Steven Strogatz, Cornell University, and author of Infinite Powers'… Fat Chance is an enjoyable small introductory book that, without the pretension of serving as a reference textbook, will certainly help undergraduate students to approach the fascinating world of probability but will also be appreciated by whoever desires to learn the basics through self-education.' Massimo Nespolo, Journal of Applied Crystallography'The book is an excellent text for anyone looking for a very enjoyable introduction to probability. It can be read on its own or used as a textbook for a math course for non-math majors.' Thomas Hagedorn, MAA ReviewsTable of ContentsPart I. Counting: 1. Simple counting; 2. The multiplication principle; 3. The subtraction principle; 4. Collections; 5. Games of chance; Interlude; 6. The binomial theorem; 7. Advanced counting; Part II. Probability: 8. Expected value; 9. Conditional probability; 10. Unfair coins and loaded dice; 11. Geometric probability; Part III. Probability in the Large: 12. Games and their payoffs; 13. The normal distribution; 14. Don't try this at home.

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Book SynopsisAt the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.Trade ReviewFrom the reviews: "This is certainly a very valuable book for anyone interested in this new methodology." N.D.C. Veraverbeke for Short Book Reviews of the ISI, December 2006 "The present book does bring something new and, indeed some novel theoretical investigations into the kinds of functional data problems … . I do think the present book is a worthy contribution to the literature. The authors have done a nice job of summarizing some of ongoing research … . Researchers in the growing functional statistics community should be glad to have a copy of the book." (Z. Q. John Lu, Technometrics, Vol. 49 (2), 2007) "This book presents new nonparametric staustical methods for samples of functional data … . The computational aspects of the book are oriented toward practitioners whereas open problems emerging from this new field of statistics will attract Ph. D. students and academic researchers. This book is also accessible to graduate students starting out in the area of functional statistics." (Fazil A. Aliev, Mathematical Reviews, Issue 2007 b) "Nonparametric Functional Data Analysis explores nonparametric methods as that can be applied to functional data, developing new methods and providing theoretical results for the conditional and unconditional mean, median, and mode for independent and dependent functional data. … As a resource for those interested in FDA research and methods, it is highly recommended. … This book should spur new and exciting research in FDA, and it provides new tools that are ready for application to real data sets." (Mark Greenwood, Journal of the American Statistical Association, Vol. 102 (479), 2007) "Example data sets that motivate the development of the models are also provided. … The index provided seems to be fairly complete and is helpful in looking up topics discusses in this monograph. Several chapters end in a section in which the authors provide additional comments, discussions and pose some open problems in this area, which should be appealing for researchers in this field. … This book should be useful for all people interested in the area of functional data analysis." (Anatolij Dvurecenskij, Zentralblatt MATH, Vol. 1119 (21), 2007)Table of ContentsIntroduction to functional nonparametric statistics.- Some functional datasets and associated statistical problematics.- What is a well adapted space for functional data?.- Local weighting of functional variables.- Functional nonparametric prediction methodologies.- Some selected asymptotics.- Computational issues.- Nonparametric supervised classification for functional data.- Nonparametric unsupervised classification for functional data.- Mixing, nonparametric and functional statistics.- Some selected asymptotics.- Application to continuous time processes prediction.- Small ball probabilities, semi-metric spaces and nonparametric statistics.- Conclusion and perspectives.

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Book SynopsisTo facilitate the use of R, the authors have developed an R package called Benchmarking, which implements the main methods within both DEA and SFA.The book uses mathematical formulations of models and assumptions, but it de-emphasizes the formal proofs - in part by placing them in appendices -- or by referring to the original sources.Trade ReviewFrom the reviews:“Benchmarking with DEA, SFA, and R covers data envelopment analysis (DEA) and stochastic frontier analysis (SFA) … . Although more advanced readers … will gain more from reading this book, it contains something for all who are interested in the principles underlying DEA and SFA and who want to know how to use these methods … . the book is appropriate for readers who have a fairly good foundation in the methods of DEA and SFA and wish to raise their level of understanding.” (Emmanuel Thanassoulis, Interfaces, Vol. 42 (3), May-June, 2012)Table of Contents1. Introduction to Benchmarking.- 2. Efficiency Measures.- 3. Production Models and Technology.- 4. Data Envelopment Analysis DEA.- 5. Additional Topics in DEA.- 6. Statistical Analysis in DEA.- 7. Stochastic Frontier Analysis SFA.- 8. Additional Topics in SFA.- 9. Merger Analysis.- 10. Regulation and Contracting.- Appendix. Getting Started with R: A Quick Introduction.

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Book SynopsisThis business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes.It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together.The first three chapters provide an introduction to BA, importance of analytics, types of BA—descriptive, predictive, and prescriptive—along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics—machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics.

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Book SynopsisThis brief addresses the estimation of quantile regression models from a practical perspective, which will support researchers who need to use conditional quantile regression to measure economic relationships among a set of variables. It will also benefit students using the methodology for the first time, and practitioners at private or public organizations who are interested in modeling different fragments of the conditional distribution of a given variable. The book pursues a practical approach with reference to energy markets, helping readers learn the main features of the technique more quickly. Emphasis is placed on the implementation details and the correct interpretation of the quantile regression coefficients rather than on the technicalities of the method, unlike the approach used in the majority of the literature. All applications are illustrated with R. Table of ContentsWhy and When Should Quantile Regression Be Used?- A Case of Study: Modelling Energy Markets by the Means of Quantile Regression.- Quantile Regression: A Methodological Overview.- Cross-Sectional Quantile Regression.- Time Series Quantile Regression.- Goodness of Fit in Quantile Regression Models.- Novel Approaches in Quantile Regression.- What Have We Learned from Quantile Regression? Implications for Economics and Finance.- Appendix: Programs for Quantile Regression and Implementation in R.

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Book SynopsisThis book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance.Table of Contents1. Introduction.- I. Subject of Time Series.- 2. Random Processes.- II. Decomposition of Economic Time Series.- 3. Trend.- 4. Seasonality and Periodicity.- 5. Residual Component.- III. Autocorrelation Methods for Univariate Time Series.- 6. Box-Jenkins Methodology.- 7. Autocorrelation Methods in Regression Models.- IV. Financial Time Series.- 8. Volatility of Financial Time Series.- 9. Other Methods for Financial Time Series.- 10. Models of Development of Financial Assets.- 11. Value at Risk.- V. Multivariate Time Series.- 12. Methods for Multivariate Time Series.- 13. Multivariate Volatility Modeling.- 14. State Space Models of Time Series.- References.- Index.

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Book SynopsisIntroduction to Econometrics and Linear Regression.- Hypothesis(es) testing.- Dynamic modelling in Econometrics Foundational knowledge.- Theoretical overview: Capital Asset Pricing and Arbitrage Pricing Theory.- Model implementation and testing.- January effect.- Key takeaways.

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Book SynopsisIntroduction.- Teaching Applied Econometrics.- Reflections on the Teaching of Bayesian Econometrics.- Teaching Financial Econometrics to Students Converting to Finance.- Teaching Panel Data Econometrics.- The Harm that Good Teachers Do and Other Stories.- Teaching Reproducibility and Replicability while Teaching Econometrics in the Classroom.- Learning Basic Bayesian Econometrics Using EViews.- A Software for Teaching Multivariate Time Series Analysis.- Explaining Ridge Regression and LASSO.- Nonparametric Identification.- Teaching Econometrics Students how to Model Bivariate Time Series Using Monte Carlo Data for the Purpose of Validating Leading Indicators.- Reflections on a Life of Teaching Econometrics.- Asymmetric AdaBoost for Maximum Score Estimation of High-dimension Binary Choice Regression Models.- Using Replication to Teach and Understand Econometrics.- Reflections of an Applied Econometrician.- Imputing Missing Waves for Pseudo Panels: A Generalized Scoring and Matching Method.- Quarto the Assassin.- Teaching Statistical Learning in Econometrics.- Teaching Mathematics for Economists.

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Book Synopsis Stata is one of the most popular statistical software in the world and suited for all kinds of users, from absolute beginners to experienced veterans. This book offers a clear and concise introduction to the usage and the workflow of Stata. Included topics are importing and managing datasets, cleaning and preparing data, creating and manipulating variables, producing descriptive statistics and meaningful graphs as well as central quantitative methods, like linear (OLS) and binary logistic regressions and matching. Additional information about diagnostical tests ensures that these methods yield valid and correct results that live up to academic standards. Furthermore, users are instructed how to export results that can be directly used in popular software like Microsoft Word for seminar papers and publications. Lastly, the book offers a short yet focussed introduction to scientific writing, which should guide readers through the process of writing a first quantitative seminar paper or research report. The book underlines correct usage of the software and a productive workflow which also introduces aspects like replicability and general standards for academic writing. While absolute beginners will enjoy the easy to follow point-and-click interface, more experienced users will benefit from the information about do-files and syntax which makes Stata so popular. Lastly, a wide range of user-contributed software („Ados") is introduced which further improves the general workflow and guarantees the availability of state of the art statistical methods.

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Book Synopsis Vertiefung der „Kurzgefassten Statistik" von Jürgen Bortz Auch ohne mathematische Vorkenntnisse verständlich Mit 47 Signifikanztafeln Table of Contents1. Wahrscheinlichkeitslehre.- 2. Beobachtungen, Hypothesen und Tests.- 3. Datenerhebung und Datenaufbereitung.- 4. Verteilungsfreie und parametrische Tests.- 5. Analyse von Häufigkeiten.- 6. Analyse von Rangdaten.- 7. Analyse von Meßwerten.- 8. Zusammenhangsmaße und Regression.- 9. Urteilerübereinstimmung.- 10. Verteilungsfreie Sequenzanalyse.- 11. Abfolgen und Zeitreihen.- Anhang (47 Signifikanzfafeln).

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Book SynopsisDas Arbeitsbuch führt in die Nutzung der Software Statistiklabor ein. Die Funktionalität wird im ersten Teil detailliert beschrieben, der zweite Teil illustriert Standardauswertungen. Die Software kann kostenfrei unter www.statistiklabor.de heruntergeladen werden. Sie bietet eine interaktive Arbeitsumgebung, um statistische Funktionen und Darstellungsmöglichkeiten leicht und intuitiv bearbeiten zu können, und erlaubt einen wesentlich einfacheren Zugang zu der umfangreichen Funktionalität der Statistik-Programmierumgebung R.Table of ContentsEine erste Beispielauswertung.- Die Oberfläche.- Ein- und Ausgabe.- Statistische Objekte.- Der Kalkulator.- Einiges zu R.- R-Grafik.- Spezielle Aspekte des Labors.- Beschreibung von Daten.- Wahrscheinlichkeitsrechnung.- Stichproben und Punktschätzungen.- Tests und Konfidenzintervalle.- Regression.- Tabellarische Überblicke.- Referenzen von R-Funktionen.- Liste typischer Auswertungen

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Book SynopsisBack in the good old days on the fourth floor of the Altbau of Bonn's Ju­ ridicum, Werner Hildenbrand put an end to a debate about a festschrift in honor of an economist on the occasion of his turning 60 with a laconic: "Much too early." Remembering his position five years ago, we did not dare to think about one for him. But now he has turned 65. If consulted, he would most likely still answer: "Much too early." However, he has to take his official re­ tirement, and we believe that this is the right moment for such an endeavor. No doubt Werner Hildenbrand will not really retire. As professor emeritus, free from the constraints of a rigid teaching schedule and the burden of com­ mittee meetings, he will be able to indulge his passions. We expect him to pursue, with undiminished enthusiasm, his research, travel, golfing, the arts, and culinary pleasures - escaping real retirement.Table of ContentsThe Rationale for Measurability.- Inferior Goods, Giffen Goods, and Shochu.- Information and Efficiency in Coordination Games: Recent Experimental Results.- Market Innovation and Entrepreneurship: A Knightian View.- Objectives of an Imperfectly Competitive Firm: A Surplus Approach.- Monetary Equilibria.- Strategic Multilateral Exchange and Taxes.- Walras Equilibrium with Coordination.- On the Robustness of the Analysis of Expectational Coordination: From 3 to n + 2 goods.- Nonparametric Estimation of Additive Models with Homogeneous Components.- A Reinforcement Procedure Leading to Correlated Equilibrium.- A Theoretical Analysis of the Mean Slutsky-Income Effect in the CAPM.- Demand Dispersion, Metonymy and Ideal Panel Data.- Some Problems and Perspectives in Economic Theory.- Time Trends in the Joint Distributions of Income and Age.- The Economics of Network Industries.- On Price Competition with Heterogeneous Consumers.- On the Core of a Cartel.- Blame Avoidance as Motivating Force in the First Price Sealed Bid Private Value Auction.- Evasion of Tax on Interest Income in a Two-Country Model.

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Book SynopsisComplex dynamics constitute a growing and increasingly important area as they offer a strong potential to explain and formalize natural, physical, financial and economic phenomena. This book pursues the ambitious goal to bring together an extensive body of knowledge regarding complex dynamics from various academic disciplines. Beyond its focus on economics and finance, including for instance the evolution of macroeconomic growth models towards nonlinear structures as well as signal processing applications to stock markets, fundamental parts of the book are devoted to the use of nonlinear dynamics in mathematics, statistics, signal theory and processing. Numerous examples and applications, almost 700 illustrations and numerical simulations based on the use of Matlab make the book an essential reference for researchers and students from many different disciplines who are interested in the nonlinear field. An appendix recapitulates the basic mathematical concepts required to use the book.Table of ContentsInvestigationMethods of Complex and Chaotic Nonlinear Dynamics.- Nonlinear Theory.- Delay Model, SSA and Brownian Motion.- Statistics of Complex and Chaotic Nonlinear Dynamics: Invariants and Rare Events.- Nonlinear Processes and Discrimination.- Statistical and Topological Invariants and Ergodicity.- Spectral and Time-Frequency Theories and Waveforms: Regularity and Singularity.- Spectral and Time–Frequency Analyses and Signal Processing.- The Atomic Decompositions of Signals.- Economic Growth, Instability and Nonlinearity.- Evolution of Economic Growth Models.- Efficiency and Random Walk.

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Book SynopsisThis book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series, bridging the gap between methods and realistic applications. It presents the most important approaches to the analysis of time series, which may be stationary or nonstationary. Modelling and forecasting univariate time series is the starting point. For multiple stationary time series, Granger causality tests and vector autogressive models are presented. As the modelling of nonstationary uni- or multivariate time series is most important for real applied work, unit root and cointegration analysis as well as vector error correction models are a central topic. Tools for analysing nonstationary data are then transferred to the panel framework. Modelling the (multivariate) volatility of financial time series with autogressive conditional heteroskedastic models is also treated. Table of ContentsIntroduction and Basics.- Univariate Stationary Processes.- Granger Causality.- Vector Autoregressive Processes.- Nonstationary Processes.- Cointegration.- Nonstationary Panel Data.- Autoregressive Conditional Heteroscedasticity.

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Book SynopsisDieses Buch umfasst genau den Stoff, der typischerweise in Klausuren zu Einführungsvorlesungen "Statistik" an wirtschaftswissenschaftlichen Fachbereichen abgeprüft wird. Es enthält mehr als 100 ehemalige Klausuraufgaben mit Lösungen auf der Verlagsseite, die das Klausurtraining erleichtern sollen. Weiterhin finden sich über 60 vollständig durchgerechnete und ausformulierte Beispiele und Fallstudien.Trade Review“… Die statistischen Methoden werden im Seminarstil vorgestellt und behandelt. ... Insgesamt eine nützliche Hilfe, statistische Kenntnisse zu festigen.” (Controller Magazin, Jg. 43, Heft 6, November-Dezember 2018)Table of ContentsEinführung.- Beschreibende Methoden univariater Datenanalyse.- Weiterführende Methoden und Zusammenhangsanalysen.- Wahrscheinlichkeitsrechnung.- Zufallsvariablen und Verteilungen.- Verteilungsmodelle.- Summen und Mittel von Stichprobenvariablen.- Parameterschätzung.- Konfidenzintervalle.- Statistische Tests.- Weitere spezielle Testprobleme.- Das lineare Regressionsmodell.

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Book SynopsisPeter P. Eckstein bietet in diesem Lehrbuch einen umfangreichen Katalog praktischer und theoretischer Problemstellungen zur Deskriptiven Statistik, Stochastik und Induktiven Statistik an. Die nach inhaltlichen Schwerpunkten gegliederten 220 Übungs- und Klausuraufgaben decken ein vielfältiges Anspruchsniveau ab und sind eine zielführende und hilfreiche Ergänzung des vom selben Autor in achter Auflage erschienenen Lehrbuches „Repetitorium Statistik“. Die ausführlichen Lösungen ermöglichen nicht nur für Studierende ein effektives Selbststudium und eine gezielte Klausurvorbereitung, sie sind auch für Lehrende ein nützliches Kompendium.Table of ContentsAufgaben mit Lösungen zur.- Deskriptiven Statistik.- Stochastik.- Induktiven Statistik.

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Book SynopsisMotivations.- Series methods.- Applications of series methods.- Mathematical foundations.

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