This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.

This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics. This historical volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The coverage ranges from the fundamental concepts and operations of Bayesian inference to analysis of applications in specific econometric problems and the testing of hypotheses and models.

Originally published in 1984. This book brings together a reasonably complete set of results regarding the use of Constraint Item estimation procedures under the assumption of accurate specification. The analysis covers the case of all explanatory variables being non-stochastic as well as the case of identified simultaneous equations, with error terms known and unknown. Particular emphasis is given to the derivation of criteria for choosing the Constraint Item. Part 1 looks at the best CI estimators and Part 2 examines equation by equation estimation, considering forecasting accuracy.

Business students need the ability to think statistically about how to deal with uncertainty and its effect on decision-making in business and management. Traditional statistics courses and textbooks tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the needs of future managers. Statistical Thinking in Business, Second Edition responds to the growing recognition that we must change the way business statistics is taught. It shows how statistics is important in all aspects of business and equips students with the skills they need to make sensible use of data and other information. The authors take an interactive, scenario-based approach and use almost no mathematical formulas, opting to use Excel for the technical work. This allows them to focus on using statistics to aid decision-making rather than how to perform routine calculations. New in the Second Edition A completely revised chapter on forecasting Re-arrangement of the material on data presentation with the inclusion of histograms and cumulative line plots A more thorough discussion of the analysis of attribute data Coverage of variable selection and model building in multiple regression End-of-chapter summaries More end-of-chapter problems A variety of case studies throughout the book The second edition also comes with a wealth of ancillary materials provided on downloadable resources packaged with the book. These include automatically-marked multiple-choice questions, answers to questions in the text, data sets, Excel experiments and demonstrations, an introduction to Excel, and the StiBstat Add-In for stem and leaf plots, box plots, distribution plots, control charts and summary statistics.

Employers Can Reduce Their Employees' Health Care Costs by Thinking Out of The BoxEmployee health care costs have skyrocketed, especially for small business owners. But employers have options that medical entrepreneurs have crafted to provide all businesses with plans to improve their employees' wellness and reduce their costs. Thus, the cost of employee health care benefits can be reduced markedly by choosing one of numerous alternatives to traditional indemnity policies. The Finance of Health Care provides business decision makers with the information they need to match the optimal health care plan with the culture of their workforce. This book is a must guide for corporate executives and entrepreneurs who want to attract-and keep--the best employees in our competitive economy.

In order to make informed decisions, there are three important elements: intuition, trust, and analytics. Intuition is based on experiential learning and recent research has shown that those who rely on their "gut feelings" may do better than those who don't. Analytics, however, are important in a data-driven environment to also inform decision making. The third element, trust, is critical for knowledge sharing to take place. These three elements-intuition, analytics, and trust-make a perfect combination for decision making. This book gathers leading researchers who explore the role of these three elements in the process of decision-making.

Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike most books on multivariate methods, this one makes straightforward analyses easy to perform for those who are unfamiliar with advanced mathematical formulae. An easily understood dataset is used throughout to illustrate the techniques. The accompanying add-in for Microsoft Excel can be used to carry out the analyses in the text. The dataset and Excel add-in are available for download on the book's CRC Press web page. Providing a firm foundation in the most commonly used multivariate techniques, this text helps readers choose the appropriate method, learn how to apply it, and understand how to interpret the results. It prepares them for more complex analyses using software such as Minitab, R, SAS, SPSS, and Stata.

Originally published in 1987. This collection of original papers deals with various issues of specification in the context of the linear statistical model. The volume honours the early econometric work of Donald Cochrane, late Dean of Economics and Politics at Monash University in Australia. The chapters focus on problems associated with autocorrelation of the error term in the linear regression model and include appraisals of early work on this topic by Cochrane and Orcutt. The book includes an extensive survey of autocorrelation tests; some exact finite-sample tests; and some issues in preliminary test estimation. A wide range of other specification issues is discussed, including the implications of random regressors for Bayesian prediction; modelling with joint conditional probability functions; and results from duality theory. There is a major survey chapter dealing with specification tests for non-nested models, and some of the applications discussed by the contributors deal with the British National Accounts and with Australian financial and housing markets.

This study analyses the newly available statistical evidence on income distribution in the former Soviet Union both by social group and by republic, and considers the significance of inequalities as a factor contributing to the demise of the Communist regime. Among the topics covered are wage distribution (interbranch and skill differentials and distribution in terms of gender, education, and age), income distribution for the former USSR as a whole, and wage and income distribution patterns for each republic, with analysis of regional differences.

This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound. Particular emphasis is placed on the common foundation of many models used in practice. In addition, the book focuses on the formulation of appropriate statistical models to study problems in business, economics, and the social sciences, as well as on how to interpret the results from statistical analyses. The book will be useful to students who are interested in rigorous applications of statistics to problems in business, economics and the social sciences, as well as students who have studied statistics in the past, but need a more solid grounding in statistical techniques to further their careers. Jacco Thijssen is professor of finance at the University of York, UK. He holds a PhD in mathematical economics from Tilburg University, Netherlands. His main research interests are in applications of optimal stopping theory, stochastic calculus, and game theory to problems in economics and finance. Professor Thijssen has earned several awards for his statistics teaching.

Written in a highly accessible style, A Factor Model Approach to Derivative Pricing lays a clear and structured foundation for the pricing of derivative securities based upon simple factor model related absence of arbitrage ideas. This unique and unifying approach provides for a broad treatment of topics and models, including equity, interest-rate, and credit derivatives, as well as hedging and tree-based computational methods, but without reliance on the heavy prerequisites that often accompany such topics. Key features A single fundamental absence of arbitrage relationship based on factor models is used to motivate all the results in the book A structured three-step procedure is used to guide the derivation of absence of arbitrage equations and illuminate core underlying concepts Brownian motion and Poisson process driven models are treated together, allowing for a broad and cohesive presentation of topics The final chapter provides a new approach to risk neutral pricing that introduces the topic as a seamless and natural extension of the factor model approach Whether being used as text for an intermediate level course in derivatives, or by researchers and practitioners who are seeking a better understanding of the fundamental ideas that underlie derivative pricing, readers will appreciate the book's ability to unify many disparate topics and models under a single conceptual theme. James A Primbs is an Associate Professor of Finance at the Mihaylo College of Business and Economics at California State University, Fullerton.

The composition of portfolios is one of the most fundamental and important methods in financial engineering, used to control the risk of investments. This book provides a comprehensive overview of statistical inference for portfolios and their various applications. A variety of asset processes are introduced, including non-Gaussian stationary processes, nonlinear processes, non-stationary processes, and the book provides a framework for statistical inference using local asymptotic normality (LAN). The approach is generalized for portfolio estimation, so that many important problems can be covered. This book can primarily be used as a reference by researchers from statistics, mathematics, finance, econometrics, and genomics. It can also be used as a textbook by senior undergraduate and graduate students in these fields.

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.

'Refreshingly clear and engaging' Tim Harford 'Delightful . . . full of unique insights' Prof Sir David Spiegelhalter There's no getting away from statistics. We encounter them every day. We are all users of statistics whether we like it or not. Do missed appointments really cost the NHS GBP1bn per year? What's the difference between the mean gender pay gap and the median gender pay gap? How can we work out if a claim that we use 42 billion single-use plastic straws per year in the UK is accurate? What did the Vote Leave campaign's GBP350m bus really mean? How can we tell if the headline 'Public pensions cost you GBP4,000 a year' is correct? Does snow really cost the UK economy GBP1bn per day? But how do we distinguish statistical fact from fiction? What can we do to decide whether a number, claim or news story is accurate? Without an understanding of data, we cannot truly understand what is going on in the world around us. Written by Anthony Reuben, the BBC's first head of statistics, Statistical is an accessible and empowering guide to challenging the numbers all around us.

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. In particular, the GAMLSS statistical framework enables flexible regression and smoothing models to be fitted to the data. The GAMLSS model assumes that the response variable has any parametric (continuous, discrete or mixed) distribution which might be heavy- or light-tailed, and positively or negatively skewed. In addition, all the parameters of the distribution (location, scale, shape) can be modelled as linear or smooth functions of explanatory variables. Key Features: Provides a broad overview of flexible regression and smoothing techniques to learn from data whilst also focusing on the practical application of methodology using GAMLSS software in R. Includes a comprehensive collection of real data examples, which reflect the range of problems addressed by GAMLSS models and provide a practical illustration of the process of using flexible GAMLSS models for statistical learning. R code integrated into the text for ease of understanding and replication. Supplemented by a website with code, data and extra materials. This book aims to help readers understand how to learn from data encountered in many fields. It will be useful for practitioners and researchers who wish to understand and use the GAMLSS models to learn from data and also for students who wish to learn GAMLSS through practical examples.

Despite numerous books on research methodology, many have failed to present a complete, hands-on, practical book to lead college classes or individuals through the research process. We are seeing more and more scientific papers from all research fields that fail to meet the basic criteria in terms of research methods, as well as the structure, writing style and presentation of results. This book aims to address this gap in the market by providing an authoritative, easy to follow guide to research methods and how to apply them. Qualitative Methods in Economics is focused not only on the research methods/techniques but also the methodology. The main objective of this book is to discuss qualitative methods and their use in economics and social science research. Chapters identify several of the research approaches commonly used in social studies, from the importance of the role of science through to the techniques of data collection. Using an example research paper to examine the methods used to present the research, the second half of this book breaks down how to present and format your results successfully. This book will be of use to students and researchers who want to improve their research methods and read up on the new and cutting edge advances in research methods, as well as those who like to study ways to improve the research process.

In How to Make the World Add Up, Tim Harford draws on his experience as both an economist and presenter of the BBC's radio show 'More or Less' to take us deep into the world of disinformation and obfuscation, bad research and misplaced motivation to find those priceless jewels of data and analysis that make communicating with numbers so rewarding. Through vivid storytelling he reveals how we can evaluate the claims that surround us with confidence, curiosity and a healthy level of scepticism. It is a must-read for anyone who cares about understanding the world around them.

The first book for a popular audience on the transformative, democratising technology of 'DeFi'.

After over a decade of Bitcoin, which has now moved beyond lore and hype into an increasingly robust star in the firmament of global assets, a new and more important question has arisen. What happens beyond Bitcoin? The answer is decentralised finance - 'DeFi'.

Tech and finance experts Steven Boykey Sidley and Simon Dingle argue that DeFi - which enables all manner of financial transactions to take place directly, person to person, without the involvement of financial institutions - will redesign the cogs and wheels in the engines of trust, and make the remarkable rise of Bitcoin look quaint by comparison. It will disrupt and displace fine and respectable companies, if not entire industries.

Sidley and Dingle explain how DeFi works, introduce the organisations and individuals that comprise the new industry, and identify the likely winners and losers in the coming revolution.

How the obsession with quantifying human performance threatens business, medicine, education, government-and the quality of our lives Today, organizations of all kinds are ruled by the belief that the path to success is quantifying human performance, publicizing the results, and dividing up the rewards based on the numbers. But in our zeal to instill the evaluation process with scientific rigor, we've gone from measuring performance to fixating on measuring itself-and this tyranny of metrics now threatens the quality of our organizations and lives. In this brief, accessible, and powerful book, Jerry Muller uncovers the damage metrics are causing and shows how we can begin to fix the problem. Filled with examples from business, medicine, education, government, and other fields, the book explains why paying for measured performance doesn't work, why surgical scorecards may increase deaths, and much more. But Muller also shows that, when used as a complement to judgment based on personal experience, metrics can be beneficial, and he includes an invaluable checklist of when and how to use them. The result is an essential corrective to a harmful trend that increasingly affects us all.

Mastering the basic concepts of mathematics is the key to understanding other subjects such as Economics, Finance, Statistics, and Accounting. Mathematics for Finance, Business and Economics is written informally for easy comprehension. Unlike traditional textbooks it provides a combination of explanations, exploration and real-life applications of major concepts. Mathematics for Finance, Business and Economics discusses elementary mathematical operations, linear and non-linear functions and equations, differentiation and optimization, economic functions, summation, percentages and interest, arithmetic and geometric series, present and future values of annuities, matrices and Markov chains. Aided by the discussion of real-world problems and solutions, students across the business and economics disciplines will find this textbook perfect for gaining an understanding of a core plank of their studies.

Economic evaluation has become an essential component of clinical trial design to show that new treatments and technologies offer value to payers in various healthcare systems. Although many books exist that address the theoretical or practical aspects of cost-effectiveness analysis, this book differentiates itself from the competition by detailing how to apply health economic evaluation techniques in a clinical trial context, from both academic and pharmaceutical/commercial perspectives. It also includes a special chapter for clinical trials in Cancer. Design & Analysis of Clinical Trials for Economic Evaluation & Reimbursement is not just about performing cost-effectiveness analyses. It also emphasizes the strategic importance of economic evaluation and offers guidance and advice on the complex factors at play before, during, and after an economic evaluation. Filled with detailed examples, the book bridges the gap between applications of economic evaluation in industry (mainly pharmaceutical) and what students may learn in university courses. It provides readers with access to SAS and STATA code. In addition, Windows-based software for sample size and value of information analysis is available free of charge-making it a valuable resource for students considering a career in this field or for those who simply wish to know more about applying economic evaluation techniques. The book includes coverage of trial design, case report form design, quality of life measures, sample sizes, submissions to regulatory authorities for reimbursement, Markov models, cohort models, and decision trees. Examples and case studies are provided at the end of each chapter. Presenting first-hand insights into how economic evaluations are performed from a drug development perspective, the book supplies readers with the foundation required to succeed in an environment where clinical trials and cost-effectiveness of new treatments are central. It also includes thought-provoking exercises for use in classroom and seminar discussions.

Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety of applications. Throughout the book, historical remarks and further readings highlight active research in the field, including new results, streamlined presentations, and new proofs of old results. After covering the essentials of copula theory, the book addresses the issue of modeling dependence among components of a random vector using copulas. It then presents copulas from the point of view of measure theory, compares methods for the approximation of copulas, and discusses the Markov product for 2-copulas. The authors also examine selected families of copulas that possess appealing features from both theoretical and applied viewpoints. The book concludes with in-depth discussions on two generalizations of copulas: quasi- and semi-copulas. Although copulas are not the solution to all stochastic problems, they are an indispensable tool for understanding several problems about stochastic dependence. This book gives you the solid and formal mathematical background to apply copulas to a range of mathematical areas, such as probability, real analysis, measure theory, and algebraic structures.

A unique and comprehensive source of information, this book is the only international publication providing economists, planners, policymakers and business people with worldwide statistics on current performance and trends in the manufacturing sector. The Yearbook is designed to facilitate international comparisons relating to manufacturing activity and industrial development and performance. It provides data which can be used to analyse patterns of growth and related long term trends, structural change and industrial performance in individual industries. Statistics on employment patterns, wages, consumption and gross output and other key indicators are also presented.

The main objective of politicians is to maximise economic growth, which heavily drives political policy and decision-making. Critics of the maximisation of growth as the central aim of economic policy have argued that growth in itself is not necessarily a good thing, particularly for the environment; however, what would replace the system and how it would be measured are questions that have been rarely answered satisfactorily. First published in 1991, this book was the first to lay out an entirely new set of practical proposals for developing new economic measurement tools, with the aim of being sustainable, 'green' and human-centred. Victor Anderson proposes that a whole set of indicators, rather than a single one, should play all the roles that GNP (Gross National Product) is responsible for. With a detailed overview of the central debates between the advocates and opponents of continued economic growth and an analysis of the various proposals for modification, this title will be of particular value to students interested in the diversity of measurement tools and the notion that economies should also be evaluated by their social and environmental consequences.

A unique and comprehensive source of information, this book is the only international publication providing economists, planners, policymakers and business people with worldwide statistics on current performance and trends in the manufacturing sector. The Yearbook is designed to facilitate international comparisons relating to manufacturing activity and industrial development and performance. It provides data which can be used to analyse patterns of growth and related long term trends, structural change and industrial performance in individual industries. Statistics on employment patterns, wages, consumption and gross output and other key indicators are also presented.