Econometrics and economic statistics Books
Cambridge University Press Experimental Auctions Methods and Applications in Economic and Marketing Research Quantitative Methods for Applied Economics and Business Research
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£52.25
Cambridge University Press Driving Forces in Physical Biological and Socioeconomic Phenomena
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£70.29
Cambridge University Press Confidence Likelihood Probability
Book SynopsisThis is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.Trade Review'This book presents a detailed and wide-ranging account of an approach to inference that moves the discipline towards increased cohesion, avoiding the artificial distinction between testing and estimation. Innovative and thorough, it is sure to have an impact both in the foundations of inference and in a wide range of practical applications of inference.' Nancy Reid, University Professor of Statistical Sciences, University of Toronto'I recommend this book very enthusiastically to any researcher interested in learning more about advanced likelihood theory, based on concepts like confidence distributions and fiducial distributions, and their links with other areas. The book explains in a very didactical way the concepts, their use, their interpretation, etc., illustrated by an impressive number of examples and data sets from a wide range of areas in statistics.' Ingrid Van Keilegom, Université Catholique de LouvainTable of Contents1. Confidence, likelihood, probability: an invitation; 2. Interference in parametric models; 3. Confidence distributions; 4. Further developments for confidence distribution; 5. Invariance, sufficiency and optimality for confidence distributions; 6. The fiducial argument; 7. Improved approximations for confidence distributions; 8. Exponential families and generalised linear models; 9. Confidence distributions in higher dimensions; 10. Likelihoods and confidence likelihoods; 11. Confidence in non- and semiparametric models; 12. Predictions and confidence; 13. Meta-analysis and combination of information; 14. Applications; 15. Finale: summary, and a look into the future.
£72.19
Cambridge University Press Principles of Statistical Inference
Book SynopsisNo one is better placed than D. R. Cox to give the comprehensive, balanced account of the theory of statistical inference, its main ideas and controversies, that is now needed. This book is for every serious user or student of statistics - for anyone serious about the scientific understanding of uncertainty.Trade Review'A deep and beautifully elegant overview of statistical inference, from one of the towering figures who created modern statistics. This book should be essential reading for all who call themselves 'statistician'.' David Hand, Imperial College London'The explanations of key concepts are written so clearly … that they may be understood even if the mathematical details are skipped.' MAA Online'The text is very well written and gives a balanced view of the frequentist and Bayesian notions of probability, without favouring one over the other.' Journal of Applied Statistics'… ideally suited for statisticians at all levels who want to refresh their own understanding of the theory of statistical inference without having to wade through theorems and proofs.' Biometrics'This is a great book by a great statistician. Buy it and read it.' Journal of the American Statistical AssociationTable of ContentsPreface; 1. Preliminaries; 2. Some concepts and simple applications; 3. Significance tests; 4. More complicated situations; 5. Some interpretational issues; 6. Asymptotic theory; 7. Further aspects of maximum likelihood; 8. Additional objectives; 9. Randomization-based analysis; Appendix A. A brief history; Appendix B. A personal view; References; Author index; Index.
£80.74
Cambridge University Press An Information Theoretic Approach to Econometrics
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£62.70
Cambridge University Press Advances in Economics and Econometrics Volume 1 Theory and Applications Ninth World Congress 39 Econometric Society Monographs Series Number 41
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£65.55
Cambridge University Press Advances in Economics and Econometrics Volume 2 Theory and Applications Ninth World Congress Theory and Applications Ninth World Congress Volume II 3 Econometric Society Monographs
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£65.55
Cambridge University Press Advances in Economics and Econometrics Volume 3 Theory and Applications Ninth World Congress Econometric Society Monographs Series Number 43
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£55.10
Cambridge University Press Urban Labor Economics
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£68.40
Cambridge University Press Fundamentals of Nonparametric Bayesian Inference 44 Cambridge Series in Statistical and Probabilistic Mathematics Series Number 44
Book SynopsisExplosive growth in computing power has made Bayesian methods for infinite-dimensional models - Bayesian nonparametrics - a nearly universal framework for inference, finding practical use in numerous subject areas. Written by leading researchers, this authoritative text draws on theoretical advances of the past twenty years to synthesize all aspects of Bayesian nonparametrics, from prior construction to computation and large sample behavior of posteriors. Because understanding the behavior of posteriors is critical to selecting priors that work, the large sample theory is developed systematically, illustrated by various examples of model and prior combinations. Precise sufficient conditions are given, with complete proofs, that ensure desirable posterior properties and behavior. Each chapter ends with historical notes and numerous exercises to deepen and consolidate the reader's understanding, making the book valuable for both graduate students and researchers in statistics and machineTrade Review'Probabilistic inference of massive and complex data has received much attention in statistics and machine learning, and Bayesian nonparametrics is one of the core tools. Fundamentals of Nonparametric Bayesian Inference is the first book to comprehensively cover models, methods, and theories of Bayesian nonparametrics. Readers can learn basic ideas and intuitions as well as rigorous treatments of underlying theories and computations from this wonderful book.' Yongdai Kim, Seoul National University'Bayesian nonparametrics has seen amazing theoretical, methodological, and computational developments in recent years. This timely book gives an authoritative account of the current state of the art by two leading scholars in the field. They masterfully cover all major aspects of the discipline, with an emphasis on asymptotics, and achieve the rare feat of being simultaneously broad and deep, while preserving the utmost mathematical rigor. This book is, without doubt, a must-read for Ph.D. students and researchers in statistics and probability.' Igor Prünster, Università Commerciale Luigi Bocconi, Milan'Worth waiting for, this book gives a both global and precise overview on the fundamentals of Bayesian nonparametrics. It will be extremely valuable as a textbook for Masters and Ph.D. students, along with more experienced researchers, as the authors have managed to gather, link together, and present with great clarity a large part of the major advances in Bayesian nonparametric modeling and theory.' Judith Rousseau, Université Paris-Dauphine'This book can serve as a textbook for a graduate course on Bayesian nonparametrics. It can also be used as a reference book for researchers in both statistics and machine learning, as well as application areas such as econometrics and biostatistics.' Yuehua Wu, MathSciNetTable of ContentsPreface; Glossary of symbols; 1. Introduction; 2. Priors on function spaces; 3. Priors on spaces of probability measures; 4. Dirichlet processes; 5. Dirichlet process mixtures; 6. Consistency: general theory; 7. Consistency: examples; 8. Contraction rates: general theory; 9. Contraction rates: examples; 10. Adaptation and model selection; 11. Gaussian process priors; 12. Infinite-dimensional Bernstein–von Mises theorem; 13. Survival analysis; 14. Discrete random structures; Appendices; References; Author index; Subject index.
£75.04
Cambridge University Press Error and Inference
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£55.10
Cambridge University Press RATS Handbook to Accompany Introductory Econometrics for Finance
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£86.56
Cambridge University Press Imperfect Perception and Stochastic Choice in Experiments
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£17.00
Cambridge University Press Quantitative Risk and Portfolio Management
Book SynopsisA modern introduction to risk and portfolio management for advanced undergraduate and beginning graduate students who will become practitioners in the field of quantitative finance, including extensive live data and Python code as online supplements which allow the application of theory to real-world situations.Trade Review'This is the book I wish I had had when I started my career in quantitative finance twenty years ago. It is written with the rigor of an academic, the insight of an experienced practitioner, and the didactic style of an empathetic and engaging teacher. Winston connects with his readers through insightful and entertaining discussions of historical background and of how actual financial markets behave or misbehave. At the same time, he provides rigorous but crystal clear and unhurried explanations of technical concepts. His choice of topics reflects current practice. A practitioner will find much to learn and enjoy in this book. A student who masters this material will be well prepared for a career in quantitative finance.' Colm O'Cinneide, Franklin Templeton Investments'Ken Winston has created a concise, valuable reference for the quantitatively minded that, in addition to describing our standard approaches for asset pricing and risk management, shows how these tools can and must be extended to reflect the more complicated risks we actually face.' David Germany, Pitzer College'This book is a remarkable combination of finance theory, mathematics, and practice. The development of finance theory is deep enough to challenge the most advanced students, yet it is full of applications. The author's long history of developing risk models is evident in every chapter. The book belongs in the curricula of the best graduate programs in finance and economics.' Charles Trzcinka, Indiana University'Few people are as qualified as Ken Winston to provide an academically disciplined practitioner view of how to manage and profit from investment risk-taking. Trained as a mathematician, Ken was the chief risk officer for some of the world's largest investment managers. Successful risk managers must have excellent quantitative and people skills, and Ken has both. The value of quantitative skill is evident in a game of numbers. People skills are necessary to communicate and successfully enforce limits on managers who too often dream of unachievable profits. Ken drew on both sets of skills to produce this innovative book, already well tested in his classrooms at Cal Tech and NYU. It is an essential read for all aspiring investment managers.' Larry Harris, University of Southern California'This is the book that I wish I had been able to have when I switched from applied math/ engineering to applied finance more than thirty years ago. In essence, the book fills a very important void: how to approach financial engineering problems from the practitioner's viewpoint. A must-have for risk managers and investment professionals.' Arturo Cifuentes, Chile Sovereign FundTable of ContentsPreface; 1. What is risk?; 2. Risk metrics; 3. Fixed income modeling; 4. Equity modeling; 5. Convex optimization; 6. Factor models; 7. Distributions; 8. Simulation, scenarios and stress testing; 9. Time-varying volatility; 10. Modeling relationships; 11. Credit modeling; 12. Hedging; References; Index.
£51.29
Cambridge University Press Time Series for Economics and Finance
Book Synopsis
£114.00
Cambridge University Press Ethics in Econometrics
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£81.00
Cambridge University Press Introduction to Catastrophe Risk Modelling
978-1009437387
£104.50
Cambridge University Press Imperfect Perception and Stochastic Choice in Experiments
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£47.49
Cambridge University Press Advances in Economics and Econometrics Volume 2
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£123.50
Cambridge University Press Dynamic Programming
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£35.14
Cambridge University Press Dynamic Programming
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£99.00
Cambridge University Press Brownian Motion the Fredholm Determinant and Time Series Analysis
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£112.50
Cambridge University Press One Hundred Years of Game Theory
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£103.50
Cambridge University Press Regression and Other Stories
Book SynopsisMost textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors'' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.Trade Review'Gelman, Hill and Vehtari provide an introductory regression book that hits an amazing trifecta: it motivates regression using real data examples, provides the necessary (but not superfluous) theory, and gives readers tools to implement these methods in their own work. The scope is ambitious - including introductions to causal inference and measurement - and the result is a book that I not only look forward to teaching from, but also keeping around as a reference for my own work.' Elizabeth Tipton, Northwestern University'Regression and Other Stories is simply the best introduction to applied statistics out there. Filled with compelling real-world examples, intuitive explanations, and practical advice, the authors offer a delightfully modern perspective on the subject. It's an essential resource for students and practitioners across the statistical and social sciences.' Sharad Goel, Department of Management Science and Engineering, Stanford University'With modern software it is very easy to fit complex regression models, and even easier to get their interpretation completely wrong. This wonderful book, summarising the authors' years of experience, stays away from mathematical proofs, and instead focuses on the insights to be gained by careful plotting and modelling of data. In particular the chapters on causal modelling, and the challenges of working with selected samples, provide some desperately needed lessons.' David Spiegelhalter, University of Cambridge'Gelman and Hill, have done it again, this time with Aki Vehtari. They have written a textbook that should be on every applied quantitative researcher's bookshelf. Most importantly they explain how to do and interpret regression with real world, complicated examples. Practicing academics in addition to students will benefit from giving this book a close read.' Christopher Winship, Harvard University, Massachusetts'Comprehensive and charming, this regression manual belongs on every regressor's shelf.' Joshua Angrist, Massachusetts Institute of TechnologyTable of ContentsPreface; Part I. Fundamentals: 1. Overview; 2. Data and measurement; 3. Some basic methods in mathematics and probability; 4. Statistical inference; 5. Simulation; Part II. Linear Regression: 6. Background on regression modeling; 7. Linear regression with a single predictor; 8. Fitting regression models; 9. Prediction and Bayesian inference; 10. Linear regression with multiple predictors; 11. Assumptions, diagnostics, and model evaluation; 12. Transformations and regression; Part III. Generalized Linear Models: 13. Logistic regression; 14. Working with logistic regression; 15. Other generalized linear models; Part IV. Before and After Fitting a Regression: 16. Design and sample size decisions; 17. Poststratification and missing-data imputation; Part V. Causal Inference: 18. Causal inference and randomized experiments; 19. Causal inference using regression on the treatment variable; 20. Observational studies with all confounders assumed to be measured; 21. Additional topics in causal inference; Part VI. What Comes Next?: 22. Advanced regression and multilevel models; Appendices: A. Computing in R; B. 10 quick tips to improve your regression modelling; References; Author index; Subject index.
£75.04
Cambridge University Press Stochastic Processes
Book SynopsisThis definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.Table of Contents1. Introduction and review of probability; 2. Poisson processes; 3. Gaussian random vectors and processes; 4. Finite-state Markov chains; 5. Renewal processes; 6. Countable-state Markov chains; 7. Markov processes with countable state spaces; 8. Detection, decisions, and hypothesis testing; 9. Random walks, large deviations, and martingales; 10. Estimation.
£64.59
Cambridge University Press Optimization Models
Book SynopsisEmphasizing practical understanding over the technicalities of specific algorithms, this elegant textbook is an accessible introduction to the field of optimization, focusing on powerful and reliable convex optimization techniques. Students and practitioners will learn how to recognize, simplify, model and solve optimization problems - and apply these principles to their own projects. A clear and self-contained introduction to linear algebra demonstrates core mathematical concepts in a way that is easy to follow, and helps students to understand their practical relevance. Requiring only a basic understanding of geometry, calculus, probability and statistics, and striking a careful balance between accessibility and rigor, it enables students to quickly understand the material, without being overwhelmed by complex mathematics. Accompanied by numerous end-of-chapter problems, an online solutions manual for instructors, and relevant examples from diverse fields including engineering, data Trade Review'In Optimization Models, Calafiore and El Ghaoui have created a beautiful and very much needed on-ramp to the world of modern mathematical optimization and its wide range of applications. They lead an undergraduate, with not much more than basic calculus behind her, from the basics of linear algebra all the way to modern optimization-based machine learning, image processing, control, and finance, to name just a few applications. Until now, these methods and topics were accessible only to graduate students in a few fields, and the few undergraduates who brave the daunting prerequisites. The book's seamless integration of mathematics and applications, and its focus on modeling practical problems and algorithmic solution methods, will be very appealing to a wide audience.' Stephen Boyd, Stanford University, CaliforniaTable of Contents1. Introduction; Part I. Linear Algebra: 2. Vectors; 3. Matrices; 4. Symmetric matrices; 5. Singular value decomposition; 6. Linear equations and least-squares; 7. Matrix algorithms; Part II. Convex Optimization: 8. Convexity; 9. Linear, quadratic and geometric models; 10. Second-order cone and robust models; 11. Semidefinite models; 12. Introduction to algorithms; Part III. Applications: 13. Learning from data; 14. Computational finance; 15. Control problems; 16. Engineering design.
£59.84
Cambridge University Press Handbook of Computational Social Choice
Book SynopsisThe rapidly growing field of computational social choice, at the intersection of computer science and economics, deals with the computational aspects of collective decision making. This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively. Chapters devoted to each of the field''s major themes offer detailed introductions. Topics include voting theory (such as the computational complexity of winner determination and manipulation in elections), fair allocation (such as algorithms for dividing divisible and indivisible goods), coalition formation (such as matching and hedonic games), and many more. Graduate students, researchers, and professionals in computer science, economics, mathematics, political science, and philosophy will benefit from this accessible and self-contained book.Trade Review'The book offers to noneconomists an outstanding self-contained introduction to normative themes in contemporary economics and to economists a thorough discussion of the computational limits of their art. But I also recommend it to anyone with a taste for axiomatics: it is replete with new and open questions that will be with us for some time.' Hervé Moulin, from the Foreword'… anyone who knows a fair amount about the field will find much enjoyable reading in any given chapter. Those who wish to know more should first read the compact but well-organized overview of many of the classical questions in Chapter 2, and then skip to a self-contained chapter of one's choice. Bribery? The internet? Cake cutting? It's all there, waiting for discovery.' Karl-Dieter Crisman, MAA Reviews'Since the field of computational social choice is growing rapidly, a handbook such as this at this juncture is the need of the hour. The handbook is the product of the efforts of 36 outstanding members of the computational social choice community. It provides elaborate initiations to the major areas of the field. The handbook has already become an authoritative reference work and has been cited over 100 times since its publication. It contains many interesting open questions which will serve as fodder for hungry researchers … The book is a treasure trove of ideas from economics and computer science. Academicians, professionals, researchers, and students in many disciplines including economics, computer science, game theory, mathematics, philosophy, and political science will gain from this approachable and self-contained handbook.' S. V. Nagaraj, SIGACT News'As a final comment, let me say that this Handbook is a most remarkable volume. I was unable to detect defects or weaknesses. All chapters are well written, with an obvious objective regarding readership. Introduction sections are clear. The authors are capable of transmitting their knowledge, whatever the difficulty. I can only repeat myself by saying that it is highly recommended to all social scientists and all computer scientists interested in voting and in social choice in general.' Maurice Salles, OEconomia'If readers are looking for a short and concise introduction to (computational) social choice and for in-depth descriptions of essential theoretical problems and computational solutions covering a wide range of topics (voting, allocation, etc.), then this handbook may really be useful.' Roman Seidl, Journal of Artificial Societies and Social SimulationTable of ContentsForeword Hervé Moulin; 1. Introduction to computational social choice Felix Brandt, Vincent Conitzer, Ulle Endriss, Jérôme Lang and Ariel D. Procaccia; Part I. Voting: 2. Introduction to the theory of voting William S. Zwicker; 3. Tournament solutions Felix Brandt, Markus Brill and Paul Harrenstein; 4. Weighted tournament solutions Felix Fischer, Olivier Hudry and Rolf Niedermeier; 5. Dodgson's rule and Young's rule Ioannis Caragiannis, Edith Hemaspaandra and Lane A. Hemaspaandra; 6. Barriers to manipulation in voting Vincent Conitzer and Toby Walsh; 7. Control and bribery in voting Piotr Faliszewski and Jörg Rothe; 8. Rationalizations of voting rules Edith Elkind and Arkadii Slinko; 9. Voting in combinatorial domains Jérôme Lang and Lirong Xia; 10. Incomplete information and communication in voting Craig Boutilier and Jeffrey S. Rosenschein; Part II. Fair Allocation: 11. Introduction to the theory of fair allocation William Thomson; 12. Fair allocation of indivisible goods Sylvain Bouveret, Yann Chevaleyre and Nicolas Maudet; 13. Cake cutting algorithms Ariel D. Procaccia; Part III. Coalition Formation: 14. Matching under preferences Bettina Klaus, David F. Manlove and Francesca Rossi; 15. Hedonic games Haris Aziz and Rahul Savani; 16. Weighted voting games Georgios Chalkiadakis and Michael Wooldridge; Part IV. Additional Topics: 17. Judgment aggregation Ulle Endriss; 18. The axiomatic approach and the internet Moshe Tennenholtz and Aviv Zohar; 19. Knockout tournaments Virginia Vassilevska-Williams.
£51.29
Cambridge University Press Structural Vector Autoregressive Analysis
Book SynopsisStructural vector autoregressive (VAR) models are widely used in many fields of economics. This book traces the evolution of the structural VAR approach and reviews its econometric foundations. It provides guidance to empirical researchers as to the most appropriate methods of estimating and evaluating structural VAR models.Trade Review'The book by Kilian and Lütkepohl will become the new benchmark textbook for teaching structural vector autoregressive analysis. This book thus devotes considerable space to the issue of identification, including sign restrictions, to Bayesian methods, to Factor Vector Autoregressions and to non-fundamental shocks. These are key to understanding much of recent research. The authors do an excellent job of assembling and lucidly explaining it all. This book is destined to become a classic.' Harald Uhlig, University of Chicago'Structural vector autoregressions (SVARs) are an essential tool in empirical macroeconomics. This book provides a thorough and long-overdue digest of a literature that has been thriving for over 35 years and seen a lot of exciting developments in the past decade. The authors masterfully blend theoretical foundations, guidance for practitioners, and detailed empirical applications. This is a must-read for anyone working with SVARs.' Frank Schorfheide, University of PennsylvaniaTable of Contents1. Introduction; 2. Vector autoregressive models; 3. Vector error correction models; 4. Structural VAR tools; 5. Bayesian VAR analysis; 6. The relationship between VAR models and other macroeconometric models; 7. A historical perspective on causal inference in macroeconometrics; 8. Identification by short-run restrictions; 9. Estimation subject to short-run restrictions; 10. Identification by long-run restrictions; 11. Estimation subject to long-run restrictions; 12. Inference in models identified by short-run or long-run restrictions; 13. Identification by sign restrictions; 14. Identification by heteroskedasticity or non-gaussianity; 15. Identification based on extraneous data; 16. Structural VAR analysis in a data-rich environment; 17. Nonfundamental shocks; 18. Nonlinear structural VAR models; 19. Practical issues related to trends, seasonality, and structural change; References; Index.
£145.35
Cambridge University Press British Historical Statistics
Book SynopsisThis 1988 reference book provides the major economic and social statistical series for the British Isles from the twelfth century up until 198081. The text provides informed access to a wide range of economic data, without the labour of identifying sources or of transforming many different annual sources into a comparable time series.Table of ContentsPreface; List of abbreviations; 1. Population and vital statistics; 2. Labour force; 3. Agriculture; 4. Fuel and energy; 5. Metals; 6. Textiles; 7. Building; 8. Miscellaneous industrial statistics; 9. External trade; 10. Transport and communications; 11. Public finance; 12. Financial institutions; 13. Consumption; 14. Prices; 15. Miscellaneous statistics; 16. National accounts; Index.
£54.14
Cambridge University Press A Practitioners Guide to Stochastic Frontier Analysis Using Stata
Book SynopsisA Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. Immensely helpful to the applied researcher, it bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.Trade Review'A competent empirical application of Stochastic Frontier Analysis (SFA) requires a clear understanding of both the production economics and the econometric theory behind the specified model side by side with adequate programming skills to write the necessary software codes. Apart from a clear exposition of the economic theory behind various stochastic frontier models that represent the technology (like the Distance Functions) and/or producer behavior (like the Cost or Profit Functions) and the relevant econometric theory, the authors offer detailed instructions on how to write the commands for various models in Stata and explain how to interpret the results. This book will prove to be invaluable for every serious researcher using SFA to measure production efficiency.' Subhash C. Ray, University of Connecticut'This book is a significant contribution to an applied introduction to stochastic frontier analysis. The authors explain clearly many of the models used in efficiency estimation, which has become a standard tool in the arsenal of applied economics. They explain clearly the models and the assumptions and provide a thorough introduction to estimating performance and efficiency for the practitioner. The many scientific fields in which efficiency and performance measurement are important will benefit immensely from the book not only because of its clarity and concreteness but also because the models are taken directly to practice using Stata, standard software used by many researchers. The combination of theory and practical application is masterfully done in this book, and practitioners in a vast number of fields will find it indispensable for their research.' Mike G. Tsionas, Athens University of Economics and BusinessTable of Contents1. Introduction; 2. Production, distance, cost, and profit functions; 3. Production frontier models; 4. Cost frontier models; 5. Profit frontier models; 6. Cost system models; 7. Profit system models; 8. Primal cost models; 9. Profit primal models; 10. Panel models; 11. Productivity and profitability; 12. Looking ahead.
£42.74
Cambridge University Press Regression Analysis of Count Data 53 Econometric Society Monographs Series Number 53
Book SynopsisStudents in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book, now in its second edition, provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics and quantitative social sciences. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter onTable of Contents1. Introduction; 2. Model specification and estimation; 3. Basic count regression; 4. Generalized count regression; 5. Model evaluation and testing; 6. Empirical illustrations; 7. Time series data; 8. Multivariate data; 9. Longitudinal data; 10. Endogenous regressors and selection; 11. Flexible methods for counts; 12. Bayesian methods for counts; 13. Measurement errors.
£46.54
Cambridge University Press AgentBased Models in Economics
Book SynopsisEdited by several of the leading figures in the field, this is the first book to provide a state-of-the-art, accessibly written methodological introduction to the tools and techniques of agent-based modelling. Using these building blocks, readers will learn how to design, simulate, and validate agent-based models in economics.Trade Review'Some 25 years ago, Frank Hahn a leading economic theorist said, '… wildly complex systems need simulating … while there will be work for the computer scientist, I very much doubt that economists will be able to establish general propositions in any but very special examples'. Economists have reacted by saying 'show us an alternative'. This book does just that. It provides the elements of an alternative computational approach in which aggregate phenomena such as crises do not appear from the blue, but emerge from the interaction between simple but heterogeneous agents.' Alan Kirman, University of Aix-Marseille III'The authors conceive of economies as complex systems of heterogeneous interacting agents with bounded rationality and limited information, and they view agent-based modeling as a necessary tool for the exploration of such systems. In this book the authors provide a comprehensive introduction to agent-based modeling. Although macroeconomic applications are stressed, the coverage of topics such as rationality, behavior, expectations, and learning will be of value for many other applications as well. A particularly welcome aspect of the book is its attention to historical antecedents and its inclusion of chapters devoted to empirical validation and estimation issues.' Leigh Tesfatsion, Iowa State UniversityTable of Contents1. Introduction; 2. Agent-based computational economics: what, why, when; 3. Agent-based models as recursive systems; 4. Rationality, behaviour and expectations; 5. Agents' behaviour and learning; 6. Interaction; 7. The agent-based experiment; 8. Empirical validation of agent-based models; 9. Estimation of agent-based models; 10. Epilogue.
£25.64
Cambridge University Press A First Course in Quantitative Finance
Book SynopsisA First Course in Quantitative Finance is suitable for economics, finance, econometrics and mathematics students with an interest in quantitative finance. Covering all topics from the architecture of financial markets to derivatives, it uses stereoscopic images to allow 3D visualisation of complex subjects without the need for additional tools.Trade Review'A First Course in Quantitative Finance is a gentle introduction in a complicated subject. It covers most important topics - such as portfolio optimisation, derivative pricing, and fixed income products - and discusses them from the perspective of financial economics and financial mathematics. It provides the necessary mathematical background, contains the financial discussion, and is full of illustrative examples. It will be useful for anyone who wants to study the subject area on an advanced level.' Rüdiger Kiesel, Universität Duisburg-Essen'This is a remarkably complete book on all aspects of modern finance, covering topics from the puzzles of financial economics, through modern portfolio management to the pricing of exotic options under stochastic volatility at an equally accessible yet state-of-the-art level. Quants, portfolio managers, students and teachers of finance alike will find it to be an invaluable source of insights and a must-have reference to have on their desks.' Peter Tankov, École nationale de la statistique et de l'administration économiqueTable of Contents1. Introduction; Part I. Technical Basics: 2. A primer on probability; 3. Vector spaces; 4. Utility theory; Part II. Financial Markets and Portfolio Theory: 5. Architecture of financial markets; 6. Modern portfolio theory; 7. CAPM and APT; 8. Portfolio performance and management; 9. Financial economics; 10. Behavioral finance; Part III. Derivatives: 11. Forwards, futures and options; 12. The binomial model; 13. The Black–Scholes theory; 14. Exotics in the Black–Scholes model; 15. Deterministic volatility; 16. Stochastic volatility; 17. Processes with jumps; Part IV. The Fixed-Income World: 18. Basic fixed-income instruments; 19. Plain vanilla fixed-income derivatives; 20. Term structure models; 21. The LIBOR market model; Appendix A. Complex analysis; Appendix B. Solutions to problems.
£85.49
Cambridge University Press A Short Course in Intermediate Microeconomics
Book SynopsisThis second edition retains the positive features of being clearly written, well organized, and incorporating calculus in the text, while adding expanded coverage on game theory, experimental economics, and behavioural economics. It remains more focused and manageable than similar textbooks, and provides a concise yet comprehensive treatment of the core topics of microeconomics, including theories of the consumer and of the firm, market structure, partial and general equilibrium, and market failures caused by public goods, externalities and asymmetric information. The book includes helpful solved problems in all the substantive chapters, as well as over seventy new mathematical exercises and enhanced versions of the ones in the first edition. The authors make use of the book''s full color with sharp and helpful graphs and illustrations. This mathematically rigorous textbook is meant for students at the intermediate level who have already had an introductory course in microeconomics, anTrade Review'There are many textbooks covering intermediate microeconomics, but this one is distinctive for how clearly yet concisely it conveys the material. I highly recommend it.' Eric Maskin, Nobel Laureate in Economics, Harvard University, Massachusetts'This thoughtfully conceived and beautifully written textbook covers all of the material that one would hope to see in a modern course on intermediate microeconomics, from consumer theory and general equilibrium, to game theory and markets with asymmetric information. Rich examples and exercises follow each chapter and, all-combined, make this a masterfully executed book.' Philip J. Reny, Hugo F. Sonnenschein Distinguished Service Professor in Economics, University of ChicagoTable of Contents1. Introduction; Part I. Theory of the Consumer: 2. Preferences and utility; 3. The budget constraint and the consumer's optimal choice; 4. Demand functions; 5. Supply functions for labor and savings; 6. Welfare economics 1: the one-person case; 7. Welfare economics 2: the many-person case; Part II. Theory of the Producer: 8. Theory of the firm 1: the single-input model; 9. Theory of the firm 2: the long run, multiple-input model; 10. Theory of the firm 3: the short run, multiple-input model; Part III. Partial Equilibrium: Market Structure: 11. Perfectly competitive markets; 12. Monopoly and monopolistic competition; 13. Duopoly; 14. Game theory; Part IV. General Equilibrium: 15. An exchange economy; 16. A production economy; Part V. Market Failure: 17. Externalities; 18. Public goods; 19. Uncertainty and expected utility; 20. Uncertainty and asymmetric information.
£52.24
Cambridge University Press InputOutput Analysis
Book SynopsisThis essential reference for students and scholars in the input-output research and applications community has been fully revised and updated to reflect important developments in the field. Expanded coverage includes construction and application of multiregional and interregional models, including international models and their application to global economic issues such as climate change and international trade; structural decomposition and path analysis; linkages and key sector identification and hypothetical extraction analysis; the connection of national income and product accounts to input-output accounts; supply and use tables for commodity-by-industry accounting and models; social accounting matrices; non-survey estimation techniques; and energy and environmental applications. Input-Output Analysis is an ideal introduction to the subject for advanced undergraduate and graduate students in many scholarly fields, including economics, regional science, regional economics, city, regiTrade Review'It is not an exaggeration to call this book the Bible of input-output practitioners. Past editions of this book have served as the undergraduate and post-graduate textbook, introducing scholars from outside the Economics discipline to extended topics such as social accounting, resource depletion, pollution, and environmental impacts. The book has recently enjoyed increased popularity and attention at higher levels of academic and decision-making impact. Therefore, this latest edition book is a timely update of a truly seminal foundation.' Manfred Lenzen, The University of Sydney'This book comes just at a time when multi-country input-output analysis has become the key instrument to understand the economic, social and environmental consequences of international trade flows between sectors, global value chains or supply chains disruptions, caused for example by COVID-19. The authors draw on the traditional literature and expand it again very smartly to incorporate the latest advances in input-output analysis, thus offering the reader a reference unique for students, professionals, researchers and policy makers around the world.' José M. Rueda-Cantuche, European Commission Joint Research Centre'Since the publication of the second edition of this book, the world changed rapidly when production activities became organized in global value chains and we started to realize that our consumption at home also had environmental consequences on the other side of the globe. To handle the new circumstances, today's analyses require global input-output tables and models. This new, third edition includes a discussion of such tables and models, and their application to relevant issues such as climate change and international trade. In other words, the input-output textbook is up-to-date again.' Erik Dietzenbacher, University of Groningen'The expanding community of scholars and practitioners who have used the prior two editions will welcome the addition of a third version that addresses the increasing use of input-output systems in environmental and trade modeling, with attention to life-cycle analysis and value chains. This edition retains the book's stature as an amazingly valuable digestion of an ever-expanding literature that is presented in a logical and clear fashion.' Geoffrey J.D. Hewings, University of Illinois'It is highly difficult if not impossible for input-output researchers to write a new textbook on the field, because they already have at hand Input-Output Analysis: Foundations and Extensions. This book is so comprehensive in coverage and continuously evolving for updates, allowing very little room for other scholars to supplement. The book also embraces readers of differing levels and areas of interest, from university undergraduates to professionals, from trade economists to environmental analysts, which again makes it hard to imagine a substitute of any kind. The book is really a must-read literature.' Satoshi Inomata, The President of the International Input-Output Association & Chief Senior Researcher of Institute of Developing Economies, JETROTable of Contents1. Introduction and overview; 2. Foundations of input-output analysis; 3. Input-output models at the regional level; 4. Organization of basic data for input-output models; 5. The commodity-by-industry approach in input-output models; 6. Multipliers in the input-output model; 7. Supply-side models, linkages, and important coefficients; 8. Decomposition approaches; 9. Nonsurvey and partial-survey methods – fundamentals; 10. Nonsurvey and partial-survey methods – extensions; 11. Social accounting matrices; 12. Energy input-output analysis; 13. Environmental input-output analysis; 14. Mixed and dynamic models; 15. Additional topics; Postscript.
£137.75
Cambridge University Press A Practical Introduction to Regression
Book SynopsisIn this Element and its accompanying second Element, A Practical Introduction to Regression Discontinuity Designs: Extensions, Matias Cattaneo, NicolásIdrobo, and Rociìo Titiunik provide an accessible and practical guide for the analysis and interpretation of regression discontinuity (RD) designs that encourages the use of a common set of practices and facilitates the accumulation of RD-based empirical evidence. In this Element, the authors discuss the foundations of the canonical SharpRD design, which has the following features: (i) the score is continuously distributed and has only one dimension, (ii) there is only one cutoff, and (iii) compliance with the treatment assignment is perfect. In the second Element, the authors discuss practical and conceptual extensions to this basic RD setup.Table of Contents1. Introduction; 2. The sharp RD design; 3. RD plots; 4. The continuity-based approach to RD analysis; 5. Validation and falsification of the RD design; 6. Final remarks.
£17.00
Cambridge University Press Solutions Manual for Actuarial Mathematics for Life Contingent Risks
Book SynopsisThis must-have manual provides detailed solutions to all of the 300 exercises in Dickson, Hardy and Waters'' Actuarial Mathematics for Life Contingent Risks, 3 edition. This groundbreaking text on the modern mathematics of life insurance is required reading for the Society of Actuaries'' (SOA) LTAM Exam. The new edition treats a wide range of newer insurance contracts such as critical illness and long-term care insurance; pension valuation material has been expanded; and two new chapters have been added on developing models from mortality data and on changing mortality. Beyond professional examinations, the textbook and solutions manual offer readers the opportunity to develop insight and understanding through guided hands-on work, and also offer practical advice for solving problems using straightforward, intuitive numerical methods. Companion Excel spreadsheets illustrating these techniques are available for free download.Table of ContentsPreface; 1. Solutions for Chapter 1; 2. Solutions for Chapter 2; 3. Solutions for Chapter 3; 4. Solutions for Chapter 4; 5. Solutions for Chapter 5; 6. Solutions for Chapter 6; 7. Solutions for Chapter 7; 8. Solutions for Chapter 8; 9. Solutions for Chapter 9; 10. Solutions for Chapter 10; 11. Solutions for Chapter 11; 12. Solutions for Chapter 12; 13. Solutions for Chapter 13; 14. Solutions for Chapter 14; 15. Solutions for Chapter 15; 16. Solutions for Chapter 16; 17. Solutions for Chapter 17; 18. Solutions for Chapter 18; 19. Solutions for Chapter 19.
£37.99
Cambridge University Press Structural Vector Autoregressive Analysis
Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader''s understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.
£56.99
Cambridge University Press Applied Stochastic Differential Equations
Book SynopsisStochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic RungeKutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book''s practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-Trade Review'Stochastic differential equations have long been used by physicists and engineers, especially in filtering and prediction theory, and more recently have found increasing application in the life sciences, finance and an ever-increasing range of fields. The authors provide intended users with an intuitive, readable introduction and overview without going into technical mathematical details from the often-demanding theory of stochastic analysis, yet clearly pointing out the pitfalls that may arise if its distinctive differences are disregarded. A large part of the book deals with underlying ideas and methods, such as analytical, approximative and computational, which are illustrated through many insightful examples. Linear systems, especially with additive noise and Gaussian solutions, are emphasized, though nonlinear systems are not neglected, and a large number of useful results and formulas are given. The latter part of the book provides an up to date survey and comparison of filtering and parameter estimation methods with many representative algorithms, and culminates with their application to machine learning.' Peter Kloeden, Johann Wolfgang Goethe-Universität Frankfurt am Main'Overall, this is a very well-written and excellent introductory monograph to SDEs, covering all important analytical properties of SDEs, and giving an in-depth discussion of applied methods useful in solving various real-life problems.' Igor Cialenco, MathSciNet'Chapters are rich in examples, numerical simulations, illustrations, derivations and computational assignment' Martin Ondreját, the European Mathematical Society and the Heidelberg Academy of Sciences and HumanitiesTable of Contents1. Introduction; 2. Some background on ordinary differential equations; 3. Pragmatic introduction to stochastic differential equations; 4. Ito calculus and stochastic differential equations; 5. Probability distributions and statistics of SDEs; 6. Statistics of linear stochastic differential equations; 7. Useful theorems and formulas for SDEs; 8. Numerical simulation of SDEs; 9. Approximation of nonlinear SDEs; 10. Filtering and smoothing theory; 11. Parameter estimation in SDE models; 12. Stochastic differential equations in machine learning; 13. Epilogue.
£35.14
McGraw-Hill Education - Europe Aleks Bus Stat Access Card 1 Sem Bundle
Book Synopsis
£103.33
McGraw Hill LLC Connect 1Semester Access Card for Essentials of
Book Synopsis
£154.39
McGraw-Hill Education - Europe Essentials of Business Statistics
Book Synopsis
£174.60
Pearson Education (US) Student Solutions Manual for Basic Business
Book SynopsisMark L. Berenson is Professor of Information Management and Business Analytics at Montclair State University and Professor Emeritus of Information Systems and Statistics at Baruch College. He currently teaches graduate and undergraduate courses in statistics and operations management in the School of Business, and an undergraduate course in international justice and human rights that he co-developed in the College of Humanities and Social Sciences. Berenson received a BA in economic statistics and an MBA in business statistics from City College of New York and a PhD in business from the City University of New York. Berenson's research has been published in Decision Sciences Journal of Innovative Education, Review of Business Research, The American Statistician, Communications in Statistics, Psychometrika, Educational and Psychological Measurement, Journal of MTable of ContentsBrief Contents First Things First (online) Defining and Collecting Data Organizing and Visualizing Variables Numerical Descriptive Measures Basic Probability Discrete Probability Distributions The Normal Distribution and Other Continuous Distributions Sampling Distributions Confidence Interval Estimation Fundamentals of Hypothesis Testing: One-Sample Tests Two-Sample Tests Analysis of Variance Chi-Square and Nonparametric Tests Simple Linear Regression Introduction to Multiple Regression Multiple Regression Model Building Time-Series Forecasting Business Analytics Getting Ready to Analyze Data in the Future Statistical Applications in Quality Management (online) Decision Making (online)
£58.59
University of Chicago Press The Economics of PropertyCasualty Insurance
Book SynopsisA study of key aspects of the economics of the property-casualty insurance industry. The volume explores areas such as external financing and insurance cycles, performance of stock and mutual insurance companies, rate regulation and the system of regulating insurance companies in the USA.Table of ContentsAcknowledgments Introduction by David F. Bradford 1: External Financing and Insurance Cycles Anne Gron, Deborah Lucas. 2: The Effects of Tax Law Changes on Property-Casualty Insurance Prices David F. Bradford, Kyle D. Logue. 3: The Causes and Consequences of Rate Regulation in the Auto Insurance Industry Dwight M. Jaffee, Thomas Russell. 4: Rate Regulation and the Industrial Organization of Automobile Insurance Susan J. Suponcic, Sharon Tennyson. 5: The Costs of Insurance Company Failures James G. Bohn, Brian J. Hall. 6: Organizational Form and Insurance Company Performance: Stocks versus Mutuals Patricia Born, William M. Gentry, W. Kip Viscusi [et al.]. Contributors Author Index Subject Index
£999.99
University of Chicago Press The Measurement of Capital Volume 45 NBER
Book SynopsisHow is real capital measured by government statistical agencies? How could this measure be improved to correspond more closely to an economist's ideal measure of capital in economic analysis and prediction? It is possible to construct a single, reliable time series for allcapital goods, regardless of differences in vintage, technological complexity, and rates of depreciation? These questions represent the common themes of this collection of papers, originally presented at a 1976 meeting of the Conference on Income and Wealth.
£999.99
MIT Press Ltd Natural Resources as Capital MIT Press The MIT
Book SynopsisAn introduction to the concepts and tools of natural resource economics, including dynamic models, market failures, and institutional remedies.This introduction to natural resource economics treats resources as a type of capital; their management is an investment problem requiring forward-looking behavior within a dynamic setting. Market failures are widespread, often associated with incomplete or nonexistent property rights, complicated by policy failures. The book covers standard resource economics topics, including both the Hotelling model for nonrenewable resources and models for renewable resources. The book also includes some topics in environmental economics that overlap with natural resource economics, including climate change.The text emphasizes skills and intuition needed to think about dynamic models and institutional remedies in the presence of both market and policy failures. It presents the nuts and bolts of resource economics as applied to nonrenewable r
£50.00
Cengage Learning, Inc Business Analytics
Book SynopsisDevelop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 5E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals clearly illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R or the Python-based Orange data mining software to perform advanced analytics. Practical, relevant problems at all levels of difficulty let you apply what you've learned. Updates throughout this edition address topics beyond traditional quantitative concepts, such as data wrangling, data visualization and data mining, which are increasingly important in today's business environment. MindTap and WebAssign online learning platforms are also available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations to strengthen your understanding of key concepts.Table of Contents1. Introduction. 2. Descriptive Statistics. 3. Data Visualization. 4. Data Wrangling. 5. Probability: An Introduction to Modeling Uncertainty. 6. Descriptive Data Mining. 7. Statistical Inference. 8. Linear Regression. 9. Time Series Analysis and Forecasting. 10. Predictive Data Mining: Regression. 11. Predictive Data Mining: Classification. 12. Spreadsheet Modeling. 13. Monte Carlo Simulation. 14. Linear Optimization Models. 15. Integer Linear Optimization Models. 16. Nonlinear Optimization Models. 17. Decision Analysis. Appendix A: Basics of Excel. Appendix B: Database Basics with Microsoft Access. Appendix C: Solutions to Even-Numbered Questions (online).
£239.11
WW Norton & Co Statistics
Book SynopsisRenowned for its clear prose and no-nonsense emphasis on core concepts, Statistics covers fundamentals using real examples to illustrate the techniques.
£115.00
