Essential Mathematics for Economics and Business is established as one of the leading introductory textbooks on mathematics for students of business and economics. Combining a user friendly approach to mathematics with practical applications to the subjects, the text provides students with a clear and comprehensible guide to mathematics. The fundamental mathematical concepts are explained in a simple and accessible style, using a wide selection of worked examples, progress exercises and real world applications. New to this Edition * Fully updated text with revised worked examples and updated material on Excel and Powerpoint * New exercises in mathematics and its applications to give further clarity and practice opportunities * Fully updated online material including animations and a new test bank * The fourth edition is supported by a companion website at www.wiley.com/college/bradley, which contains: Animations of selected worked examples providing students with a new way of understanding the problems Access to the Maple T.A. test bank, which features over 500 algorithmic questions Further learning material, applications, exercises and solutions. * Problems in context studies, which present the mathematics in a business or economics framework. * Updated PowerPoint slides, Excel problems and solutions. "The text is aimed at providing an introductory-level exposition of mathematical methods for economics and business students. In terms of level, pace, complexity of examples and user-friendly style the text is excellent - it genuinely recognises and meets the needs of students with minimal maths background." Colin Glass, Emeritus Professor, University of Ulster "One of the major strengths of this book is the range of exercises in both drill and applications. Also the 'worked examples' are excellent; they provide examples of the use of mathematics to realistic problems and are easy to follow." Donal Hurley, formerly of University College Cork "The most comprehensive reader in this topic yet, this book is an essential aid to the avid economist who loathes mathematics!" Amazon.co.uk

Gain an understanding of how econometrics can answer today's questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. Unlike traditional texts, this book's practical, yet professional, approach demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions across a variety of disciplines. The author has organized the book's presentation around the type of data being analyzed with a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, the text incorporates more than 100 data sets in different formats. Updates introduce the latest developments in the field, including the recent advances in the so-called "causal effects" or "treatment effects," to provide a complete understanding of the impact and importance of econometrics today.

Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, Design and Analysis of Time Series Experiments is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. Readers learn not only how-to skills but, also the underlying rationales for the design features and the analytical methods. ARIMA algebra, Box-Jenkins-Tiao models and model-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course, with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality and synthetic control group designs. Building on the earlier of the authors, Design and Analysis of Time Series Experiments includes more recent developments in modeling, and considers design issues in greater detail than any existing work. Additionally, the book appeals to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference.

Connections among different assets, asset classes, portfolios, and the stocks of individual institutions are critical in examining financial markets. Interest in financial markets implies interest in underlying macroeconomic fundamentals. In Financial and Macroeconomic Connectedness, Frank Diebold and Kamil Yilmaz propose a simple framework for defining, measuring, and monitoring connectedness, which is central to finance and macroeconomics. These measures of connectedness are theoretically rigorous yet empirically relevant. The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses.

This book collects results from ad hoc surveys on firms pricing behavior conducted in 2003 and 2004 by nine National central banks of the Euro area in the context of a joint research project (Eurosystem Inflation Persistence Network). These surveys have proved to be an efficient way to test theories on the pricing strategies of economic agents, documenting, in qualitative terms, the underlying rationale of the observed pricing patterns. The book provides an unprecedented amount of information from more than 11,000 euro area firms, addressing issues such as the relevance of nominal and real rigidities, the information set used by firms in the price setting process, the strategy followed to review prices, the frequency of both price reviews and price changes, the reasons underlying price stickiness, and asymmetries in price adjustment. It also compares results for the euro area to those obtained for other countries by similar studies. Finally, it draws the main implications for theoretical modeling and for monetary policy.

Panel data econometrics uses both time series and cross-sectional data sets that have repeated observations over time for the same individuals (individuals can be workers, households, firms, industries, regions, or countries). This book reviews the most important topics in the subject. The three parts, dealing with static models, dynamic models, and discrete choice and related models are organized around the themes of controlling for unobserved heterogeneity and modelling dynamic responses and error components.

Presenting innovative modelling approaches to the analysis of fiscal policy and government debt, this book moves beyond previous models that have relied upon the assumption that various age-specific rates and policy variables remain unchanged when it comes to generating government expenditures and tax revenues. As a result of population ageing, current policy settings in many countries are projected to lead to unsustainable levels of public debt; Tax Policy and Uncertainty explores models that allow for feedbacks and uncertainty to combat this. Applicable to any country, the models in the book explore the optimal timing and extent of tax changes in the face of anticipated high future debt. Chapters produce stochastic debt projections, including probability distribution of debt ratios at each point in time. It also offers important analysis of fiscal policy trade-offs as well as providing advice on when and by how much tax rates should be increased. Economics scholars focusing on fiscal policy will appreciate the improved models in this book that allow both for uncertainty and feedback effects arising from responses to increased debt. It will also be helpful to economic policy advisors and economists in government departments.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline. Key Features: A concise overview of spatial statistics theory and methods, looking at parallel developments in geostatistics and spatial econometrics, highlighting the eclipsing of centography and point pattern analysis by geostatistics and spatial autoregression, and the emergence of local analysis Contemporary descriptions of popular geospatial random variables, emphasizing one- and two-parameter spatial autoregression specifications, and Moran eigenvector spatial filtering coupled with a broad coverage of statistical estimation techniques A detailed articulation of a spatial statistical workflow conceptualization The helpful insights from empirical applications of spatial statistics in agronomy, criminology, demography, economics, epidemiology, geography, remotely sensed data, urban studies, and zoology/botany, will make this book a useful tool for upper-level students in these disciplines.

The Handbook of Experimental Game Theory offers a comprehensive analysis of the field, discussing foundational topics that are at the core of applied game theory. It highlights the nuances that scientific experiments have delivered to our understanding of strategic interactions among decision makers. Leading experts explore methodological considerations and games of complete and incomplete information to offer new directions for research in experimental game theory. Chapters demonstrate transformative behavioral research focused on classic topics in game theory such as cooperation and coordination games. Taking a scientific approach to the study of game theory, this innovative Handbook provides an insight into laboratory and field experiments that test game theoretic propositions and suggests new ways of modeling strategic behavior. It takes a forward-thinking position, addressing the challenges inherent in innovations surrounding the measurement of strategic behavior using experimental methods. This Handbook will prove to be a valuable resource for scholars and students who are looking to gain a broader understanding of experimental game theory and how to contribute to its advancement. It will also be of particular interest to researchers in experimental and behavioral economics.

Learn more about modern Econometrics with this comprehensive introduction to the field, featuring engaging applications and bringing contemporary theories to life. Introduction to Econometrics, 4th Edition, Global Edition by Stock and Watson is the ultimate introductory guide that connects modern theory with motivating, engaging applications. The text ensures you get a solid grasp of this challenging subject's theoretical background, building on the philosophy that applications should drive the theory, not the other way around. The latest edition maintains the focus on currency, focusing on empirical analysis and incorporating real-world questions and data by using results directly relevant to the applications. The text contextualises the study of Econometrics with a comprehensive introduction and review of economics, data, and statistics before proceeding to an extensive regression analysis studying the different variables and regression parameters. With a large data set increasingly used in Economics and related fields, a new chapter dedicated to Big Data will help you learn more about this growing and exciting area. Sharing a variety of resources and tools to help your understanding and critical thinking of the topics introduced, such as General Interest boxes, or end-of-chapter, and empirical exercises and summaries, this industry-leading text will help you acquire a sophisticated knowledge of this fascinating subject. Reach every student by pairing this text with Pearson MyLab (R) Economics MyLab is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab (R) personalises the learning experience and improves results for each student. If you would like to purchase both the physical text and MyLab Economics search for: 9781292264561 Introduction to Econometrics, 4th Edition, Global Edition with MyLab Economics Package consists of: 9781292264455 Introduction to Econometrics, 4th Edition, Global Edition 9781292264516 Introduction to Econometrics, 4th Edition, Global Edition MyLab Economics 9780136879787 Introduction to Econometrics, 4th Edition, Global Edition Pearson eText Pearson MyLab (R) Economics is not included. Students, if Pearson MyLab Economics is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN. Pearson MyLab (R) Economics should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.

Written in a comprehensive yet accessible style, this Handbook introduces readers to a range of modern empirical methods with applications in microeconomics, illustrating how to use two of the most popular software packages, Stata and R, in microeconometric applications. International contributors expertly investigate the development of advanced methods driven by the accumulation of numerous data sets at the level of individuals, households and firms, and by an increase in the capacity and speed of computers. The Handbook highlights that, while the more traditional empirical methods were largely limited to establishing correlations, these new methods aim to uncover causality. Examination of these advances shows new possibilities for applied research in microeconomics in the estimation of sophisticated structural models and the evaluation of policy interventions. This insightful Handbook is a must-read for graduate students and instructors in applied microeconomics as well as researchers in government departments and academia pursuing modern advanced methods of policy evaluation and data analysis.

'In Economics as Anatomy Peter Swann has produced a wonderful sequel to his earlier 2006 classic, Putting Econometrics into Its Place. In this powerful new book, Peter Swann shows how key ideas from the economics of innovation can reconstruct economics as an empirical science. The challenge for mainstream economists is to embrace diversity and help rebuild the subject of economics so that it is no less innovative and dynamic than the economy itself. Economists need to go back to their roots and build something different.' - Kevin Dowd, Durham University, UK 'This is an important, thought-provoking, well-argued and provocative work which questions the methodological basis of, and the status accorded to, econometric analyses. . . This book will prove useful to all economic researchers, whatever the stage of their career - from undergraduates to longstanding professors. This book should stimulate a lively debate and should result in all researching economists to reflect critically on their current approaches and become more open to methods other than the strictly econometric.' - Adrian Darnell, Durham University, UK There are two fundamentally different approaches to innovation: incremental and radical. In Economics as Anatomy, G.M. Peter Swann argues that economics as a discipline needs both perspectives in order to create the maximum beneficial effect for the economy. Chapters explore how and why mainstream economics is very good at incremental innovation but seems uncomfortable with radical innovation. Swann argues that economics should follow the example of many other disciplines, transitioning from one field to a range of semi-autonomous sub-disciplines. In this book, he compares the missing link in empirical economics to being the economic equivalent of anatomy, the basis of medical discourse. Working as a sequel to Swann's Putting Econometrics in its Place, this book will be a vital resource to those who are discontent with the state of mainstream economics, especially those actively seeking to promote change in the discipline. Students wishing to see progress in the teaching of economics will also benefit from this timely book.

Imad Moosa challenges convention with this comprehensive and compelling critique of the limitations and abuses of econometrics, condemning the common practices of misapplied statistical methods in both economics and finance. After reviewing the Keynesian, Austrian and mainstream criticisms of econometrics, it is demonstrated that by using standard econometric techniques, methods and models can be manipulated to produce any desired result. These hazardous analyses may then be relied upon to support flawed policy recommendations, ideological beliefs and private interests. Moosa proposes that the way forward should instead be to rely on clear thinking, intuition and common sense rather than continue with the reliance upon econometrics. The mathematization of economics has limited the accessibility and participation in economic discussion by making the area into a complex `science' when it should not be. Appealing to both academics and practitioners of economics and finance, this book serves to challenge the acceptance of econometrics as offering trustworthy analysis. Any individual interested in this sort of empirical work will find this book a captivating read on the limitations of econometrics.

For courses in Econometrics. A Clear, Practical Introduction to Econometrics Using Econometrics: A Practical Guide offers students an innovative introduction to elementary econometrics. Through real-world examples and exercises, the book covers the topic of single-equation linear regression analysis in an easily understandable format. The Seventh Edition is appropriate for all levels: beginner econometric students, regression users seeking a refresher, and experienced practitioners who want a convenient reference. Praised as one of the most important texts in the last 30 years, the book retains its clarity and practicality in previous editions with a number of substantial improvements throughout.

This book brings together the latest concepts and models in real-estate derivatives, the new frontier in financial markets. The importance of real-estate derivatives in managing property price risk that has destabilized economies frequently over the last hundred years has been brought into the limelight by Robert Shiller. In spite of his masterful campaign for the introduction of real-estate derivatives, these financial instruments are still in a state of infancy. This book aims to provide a state-of-the-art overview of real-estate derivatives, covering the description of these financial products, their applications, and the most important models proposed in the literature. In order to facilitate a better understanding of the situations when these products can be successfully used, ancillary topics such as real-estate indices, mortgages, securitization, and equity release mortgages are also discussed. The book examines econometric aspects of real-estate index prices time series and financial engineering non-arbitrage principles governing the pricing of derivatives. The emphasis is on understanding the financial instruments through their mechanics and comparative description. The examples are based on real-world data from exchanges or from major investment banks or financial houses in London. The numerical analysis is easily replicable with Excel and Matlab.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline. Key Features: A concise overview of spatial statistics theory and methods, looking at parallel developments in geostatistics and spatial econometrics, highlighting the eclipsing of centography and point pattern analysis by geostatistics and spatial autoregression, and the emergence of local analysis Contemporary descriptions of popular geospatial random variables, emphasizing one- and two-parameter spatial autoregression specifications, and Moran eigenvector spatial filtering coupled with a broad coverage of statistical estimation techniques A detailed articulation of a spatial statistical workflow conceptualization The helpful insights from empirical applications of spatial statistics in agronomy, criminology, demography, economics, epidemiology, geography, remotely sensed data, urban studies, and zoology/botany, will make this book a useful tool for upper-level students in these disciplines.

Nonlinear Models, Labour Markets and Exchange offers a number of broad introductory surveys in the areas of nonlinear modelling, labour economics and the economic analysis of exchange. This collection of articles consists largely of recently published refereed papers. The early chapters provide an introduction to the analysis of 'chaos and strange attractors' and the use of the very flexible generalised exponential family of frequency distributions in analysing both time series and cross-sectional distributions. The volume then provides syntheses of the theories of internal labour markets, trade union bargaining, and population ageing and its implications. It goes on to survey a range of topics in the broad area of the theory of exchange, which is central to the neoclassical economic model. Finally, the book provides some advice for students who are about to start their first piece of research. It ends with a unique survey of the history of economic analysis. Providing introductory material and syntheses of a wide range of topics, Nonlinear Models, Labour Markets and Exchange will be welcomed by economics academics and researchers interested in labour economics and econometrics.

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.

Applications of queueing network models have multiplied in the last generation, including scheduling of large manufacturing systems, control of patient flow in health systems, load balancing in cloud computing, and matching in ride sharing. These problems are too large and complex for exact solution, but their scale allows approximation. This book is the first comprehensive treatment of fluid scaling, diffusion scaling, and many-server scaling in a single text presented at a level suitable for graduate students. Fluid scaling is used to verify stability, in particular treating max weight policies, and to study optimal control of transient queueing networks. Diffusion scaling is used to control systems in balanced heavy traffic, by solving for optimal scheduling, admission control, and routing in Brownian networks. Many-server scaling is studied in the quality and efficiency driven Halfin-Whitt regime and applied to load balancing in the supermarket model and to bipartite matching in ride-sharing applications.