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.

As the world economy becomes more integrated, products become more globalized. Airplanes, automobiles, computers, watches, and garments are among products whose constituent parts are made all over the world. This volume presents arguments and evidence showing that this process is benign: it raises competitiveness, creates jobs, and enhances economic welfare.

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.

The collection of chapters in Volume 43 Part B of Advances in Econometrics serves as a tribute to Professor M. Hashem Pesaran. Hashem is one of the most innovative, influential, and productive econometricians of his generation, with over 200 papers published in leading scientific journals to his credit along with highly influential books on both theoretical and applied topics, significantly pushing forward the frontiers of knowledge in econometrics and economics. Thanks to his profound and pioneering work on theoretical and empirical questions, the economics profession has gained a much better understanding of both the power and limitations of econometric analysis. Reflecting the diversity of Hashem's many contributions, this volume includes chapters on a wide variety of topics, including panel modelling, micro applications, and econometric methodology. The long list of topics includes studies analysing multiple treatment effects in panels, heterogeneity and aggregation, an exploration of the Orthogonal to Backwards Means (OBM) estimator, and an examination of potential reasons for anaemic productivity growth in Italy using recent dynamic heterogeneous panel data methods developed by Hashem Pesaran and his co-authors.

Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been grouped into seven topical sections: Section I deals with periodic modeling of time series, introducing, applying, and comparing various seasonally periodic models Section II examines the estimation of time series components when models for series are misspecified in some sense, and the broader implications this has for seasonal adjustment and business cycle estimation Section III examines the quantification of error in X-11 seasonal adjustments, with comparisons to error in model-based seasonal adjustments Section IV discusses some practical problems that arise in seasonal adjustment: developing asymmetric trend-cycle filters, dealing with both temporal and contemporaneous benchmark constraints, detecting trading-day effects in monthly and quarterly time series, and using diagnostics in conjunction with model-based seasonal adjustment Section V explores outlier detection and the modeling of time series containing extreme values, developing new procedures and extending previous work Section VI examines some alternative models and inference procedures for analysis of seasonal economic time series Section VII deals with aspects of modeling, estimation, and forecasting for nonseasonal economic time series By presenting new methodological developments as well as pertinent empirical analyses and reviews of established methods, the book provides much that is stimulating and practically useful for the serious researcher and analyst of economic time series.

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.

Master the proven, traditional methods in project management as well as the latest agile practices with Kloppenborg/Anantatmula/Wells' CONTEMPORARY PROJECT MANAGEMENT, 5E. This edition presents project management techniques and expert examples drawn from successful practice and the latest research. All content reflects the knowledge areas and processes of the 6th edition of the PMBOK (R) Guide as well as the domains and principles of the 7th edition of the PMBOK (R) Guide. The book's focused approach helps you build a strong portfolio to showcase project management skills. New features, glossary and an integrated case highlight agile practices, mindset and techniques, while PMP (R)-style questions prepare you for the new 2021 PMP (R) certification exam. You also learn to use Microsoft (R) Project to automate processes. Gain the expertise you need to become a Certified Associate in Project Management (CAPM (R)) or Certified Project Management Professional (PMP (R)) with this edition and MindTap digital resources.

World Inequality Report 2018 is the most authoritative and up-to-date account of global trends in inequality. Researched, compiled, and written by a team of the world’s leading economists of inequality, it presents—with unrivaled clarity and depth—information and analysis that will be vital to policy makers and scholars everywhere. Inequality has taken center stage in public debate as the wealthiest people in most parts of the world have seen their share of the economy soar relative to that of others, many of whom, especially in the West, have experienced stagnation. The resulting political and social pressures have posed harsh new challenges for governments and created a pressing demand for reliable data. The World Inequality Lab at the Paris School of Economics and the University of California, Berkeley, has answered this call by coordinating research into the latest trends in the accumulation and distribution of income and wealth on every continent. This inaugural report analyzes the Lab’s findings, which include data from major countries where information has traditionally been difficult to acquire, such as China, India, and Brazil. Among nations, inequality has been decreasing as traditionally poor countries’ economies have caught up with the West. The report shows, however, that inequality has been steadily deepening within almost every nation, though national trajectories vary, suggesting the importance of institutional and policy frameworks in shaping inequality. World Inequality Report 2018 will be a key document for anyone concerned about one of the most imperative and contentious subjects in contemporary politics and economics.

Statistics is used in two senses, singular and plural. In the singular, it concerns with the whole subject of statistics, as a branch of knowledge. In the plural sense, it relates to the numerical facts, data gathered systematically with some definite object in view. Thus, Statistics is the science, which deals with the collection, analysis and interpretation of data. An understanding of the logic and theory of statistics is essential for the students of agriculture who are expected to know the technique of analyzing numerical data and drawing useful conclusions. It is the intention of the author to keep the practical manual at a readability level at appropriate for students who do not have a mathematical background. This book has been prepared for the students and teachers as well to acquaint the basic concepts of statistical principles and procedures of calculations as per the syllabi of 5th Dean's committee of ICAR for undergraduate courses in agriculture and allied sciences.

The present book has been well prepared to meet the requirements of the students of Animal and Veterinary Science, Animal Biotechnology and other related fields. The book will serve as a text book not only for students in Veterinary science but also for those who want to know "What statistics in all about" or who need to be familiar with at least the language and fundamental concepts of statistics. The book will serve well to build necessary background for those who will take more advanced courses in statistics including the specialized applications. The salient features are: The book has been designed in accordance with the new VCI syllabus, 2016 (MSVE-2016). The book will be very useful for students of SAU's/ICAR institutes and those preparing for JRF/SRF/various competitive examinations. Each chapter of this book contains complete self explanatory theory and a fairly number of solved examples. Solved examples for each topic are given in an elegant and more interesting way to make the users understand them easily. Subject matter has been explained in a simple way that the students can easily understand and feel encouraged to solve questions themselves given in unsolved problems.

Social media has made charts, infographics and diagrams ubiquitous-and easier to share than ever. While such visualisations can better inform us, they can also deceive by displaying incomplete or inaccurate data, suggesting misleading patterns-or misinform by being poorly designed. Many of us are ill equipped to interpret the visuals that politicians, journalists, advertisers and even employers present each day, enabling bad actors to easily manipulate visuals to promote their own agendas. Public conversations are increasingly driven by numbers and to make sense of them, we must be able to decode and use visual information. By examining contemporary examples ranging from election-result infographics to global GDP maps and box-office record charts, How Charts Lie teaches us how to do just that.

This book presents a unique collection of contributions on modern topics in statistics and econometrics, written by leading experts in the respective disciplines and their intersections. It addresses nonparametric statistics and econometrics, quantiles and expectiles, and advanced methods for complex data, including spatial and compositional data, as well as tools for empirical studies in economics and the social sciences. The book was written in honor of Christine Thomas-Agnan on the occasion of her 65th birthday. Given its scope, it will appeal to researchers and PhD students in statistics and econometrics alike who are interested in the latest developments in their field.

This book analyzes the following four distinct, although not dissimilar, areas of social choice theory and welfare economics: nonstrategic choice, Harsanyi's aggregation theorems, distributional ethics and strategic choice. While for aggregation of individual ranking of social states, whether the persons behave strategically or non-strategically, the decision making takes place under complete certainty; in the Harsanyi framework uncertainty has a significant role in the decision making process. Another ingenious characteristic of the book is the discussion of ethical approaches to evaluation of inequality arising from unequal distributions of achievements in the different dimensions of human well-being. Given its wide coverage, combined with newly added materials, end-chapter problems and bibliographical notes, the book will be helpful material for students and researchers interested in this frontline area research. Its lucid exposition, along with non-technical and graphical illustration of the concepts, use of numerical examples, makes the book a useful text.

This volume in Advances in Econometrics showcases fresh methodological and empirical research on the econometrics of networks. Comprising both theoretical, empirical and policy papers, the authors bring together a wide range of perspectives to facilitate a dialogue between academics and practitioners for better understanding this groundbreaking field and its role in policy discussions. This edited collection includes thirteen chapters which covers various topics such as identification of network models, network formation, networks and spatial econometrics and applications of financial networks. Readers can also learn about network models with different types of interactions, sample selection in social networks, trade networks, stochastic dynamic programming in space, spatial panels, survival and networks, financial contagion, spillover effects, interconnectedness on consumer credit markets and a financial risk meter. The topics covered in the book, centered on the econometrics of data and models, are a valuable resource for graduate students and researchers in the field. The collection is also useful for industry professionals and data scientists due its focus on theoretical and applied works.

The chapters in this book describe various aspects of the application of statistical methods in finance. It will interest and attract statisticians to this area, illustrate some of the many ways that statistical tools are used in financial applications, and give some indication of problems which are still outstanding. The statisticians will be stimulated to learn more about the kinds of models and techniques outlined in the book - both the domain of finance and the science of statistics will benefit from increased awareness by statisticians of the problems, models, and techniques applied in financial applications. For this reason, extensive references are given. The level of technical detail varies between the chapters. Some present broad non-technical overviews of an area, while others describe the mathematical niceties. This illustrates both the range of possibilities available in the area for statisticians, while simultaneously giving a flavour of the different kinds of mathematical and statistical skills required. Whether you favour data analysis or mathematical manipulation, if you are a statistician there are problems in finance which are appropriate to your skills.

Agricultural Statistics is published each year to meet the diverse need for a reliable reference book on agricultural production, supplies, consumption, facilities, costs, and returns. Its tables of annual data cover a wide variety of facts in forms suited to most common use. Statistics presented in many of the tables represent actual counts of the items covered. Most of the statistics relating to foreign trade and to government programs, such as numbers and amounts of loans made to farmers, and amounts of loans made by the Commodity Credit Corporation, etc., are data of this type. A large number of other tables, however, contain data that are estimates made by the Department of Agriculture. The estimates for crops, livestock, and poultry made by the U.S. Department of Agriculture are prepared mainly to give timely current state and national totals and averages. They are based on data obtained by sample surveys of farmers and of people who do business with farmers. The survey data are supplemented by information from the Censuses of Agriculture taken every five years and check data from various sources. Being estimates, they are subject to revision as more data become available from commercial or government sources. Unless otherwise indicated, the totals for the United States shown in the various tables on area, production, numbers, price, value, supplies, and disposition are based on official Department estimates. They exclude states for which no official estimates are compiled. Extensive table data include statistics of the following: *Statistics of Grain and Feed *Cotton, Tobacco, Sugar Crops, and Honey *Oilseeds, Fats, and Oils *Vegetables and Melons *Hay, Seeds, and Minor Field Crops *Cattle, Hogs, and Sheep *Dairy and Poultry *Insurance, Credit & Cooperatives *Agricultural Conservation & Forestry *Consumption & Family Living *Fertilizers & Pesticides Miscellaneous Agricultural Statistics such as Foreign Agricultural Trade Statistics including exports, fisheries and more. Professionals in the following fields to include farmers, ranchers, soil conservationists, surveyors, agricultural economist consultants, livestock manufacturers, livestock feedlot operators, food distributors, animal scientists, food chemists, food brokers, farm and land appraisers (and more) may have the greatest interest in this volume.

Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides over 80 years of annual, quarterly, and monthly data in industrial and demographic detail including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy. Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies. Business Statistics of the United States provides a rich and deep picture of the American economy and contains approximately 3,500 time series in all. The data are predominately from federal government sources including: *Board of Governors of the Federal Reserve System *Bureau of Economic Analysis *Bureau of Labor Statistics *Census Bureau *Employment and Training Administration *Energy Information Administration *Federal Housing Finance Agency *U.S. Department of the Treasury

The book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution. Key features: Links data generation process with statistical distributions in multivariate domain Provides step by step procedure for estimating parameters of developed models Provides blueprint for data driven decision making Includes practical examples and case studies relevant for intended audiences The book will help everyone involved in data driven problem solving, modeling and decision making.

Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A presents novel contributions to the analysis of time series and panel data with applications in macroeconomics, finance, cognitive science and psychology, neuroscience, and labor economics. Part B examines innovations in stochastic frontier analysis, nonparametric and semiparametric modeling and estimation, A/B experiments, big-data analysis, and quantile regression. Individual chapters, written by both distinguished researchers and promising young scholars, cover many important topics in statistical and econometric theory and practice. Papers primarily, though not exclusively, adopt Bayesian methods for estimation and inference, although researchers of all persuasions should find considerable interest in the chapters contained in this work. The volume was prepared to honor the career and research contributions of Professor Dale J. Poirier. For researchers in econometrics, this volume includes the most up-to-date research across a wide range of topics.

Agricultural Statistics is published each year to meet the diverse need for a reliable reference book on agricultural production, supplies, consumption, facilities, costs, and returns. Its tables of annual data cover a wide variety of facts in forms suited to most common use. Statistics presented in many of the tables represent actual counts of the items covered. Most of the statistics relating to foreign trade and to government programs, such as numbers and amounts of loans made to farmers, and amounts of loans made by the Commodity Credit Corporation, etc., are data of this type. A large number of other tables, however, contain data that are estimates made by the Department of Agriculture. The estimates for crops, livestock, and poultry made by the U.S. Department of Agriculture are prepared mainly to give timely current state and national totals and averages. They are based on data obtained by sample surveys of farmers and of people who do business with farmers. The survey data are supplemented by information from the Censuses of Agriculture taken every five years and check data from various sources. Being estimates, they are subject to revision as more data become available from commercial or government sources. Unless otherwise indicated, the totals for the United States shown in the various tables on area, production, numbers, price, value, supplies, and disposition are based on official Department estimates. They exclude states for which no official estimates are compiled. Extensive table data include statistics of the following: *Statistics of Grain and Feed *Cotton, Tobacco, Sugar Crops, and Honey *Oilseeds, Fats, and Oils *Vegetables and Melons *Hay, Seeds, and Minor Field Crops *Cattle, Hogs, and Sheep *Dairy and Poultry *Insurance, Credit & Cooperatives *Agricultural Conservation & Forestry *Consumption & Family Living *Fertilizers & Pesticides Miscellaneous Agricultural Statistics such as Foreign Agricultural Trade Statistics including exports, fisheries and more. Professionals in the following fields to include farmers, ranchers, soil conservationists, surveyors, agricultural economist consultants, livestock manufacturers, livestock feedlot operators, food distributors, animal scientists, food chemists, food brokers, farm and land appraisers (and more) may have the greatest interest in this volume.

Statistical Programming in SAS Second Edition provides a foundation for programming to implement statistical solutions using SAS, a system that has been used to solve data analytic problems for more than 40 years. The author includes motivating examples to inspire readers to generate programming solutions. Upper-level undergraduates, beginning graduate students, and professionals involved in generating programming solutions for data-analytic problems will benefit from this book. The ideal background for a reader is some background in regression modeling and introductory experience with computer programming. The coverage of statistical programming in the second edition includes Getting data into the SAS system, engineering new features, and formatting variables Writing readable and well-documented code Structuring, implementing, and debugging programs that are well documented Creating solutions to novel problems Combining data sources, extracting parts of data sets, and reshaping data sets as needed for other analyses Generating general solutions using macros Customizing output Producing insight-inspiring data visualizations Parsing, processing, and analyzing text Programming solutions using matrices and connecting to R Processing text Programming with matrices Connecting SAS with R Covering topics that are part of both base and certification exams.

Plenty of literature review and applications of various tests provided to cover all the aspects of research methodology Various examination questions have been provided Strong Pedagogy along with regular features such as Concept Checks, Text Overviews, Key Terms, Review Questions, Exercises and References Though the book is primarily addressed to students,it will be equally useful to Researchers and Entrepreneurs More than other research textbooks, this book addresses the students' need to comprehend all aspects of the research process which includes Research process, clarification of the research problem, Ethical issues, Survey research, Research report preparation and presentation.

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.S. students. Basic theoretical results are presented in a mathematically convincing way, and the methods of data analysis are developed through examples and exercises parsed in R. A student with a basic course in mathematical statistics will learn both how to analyze time series and how to interpret the results. The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling. The second half of the book focuses on statistical inference, the fitting of time series models, as well as computational facets of forecasting. Many time series of interest are nonlinear in which case classical inference methods can fail, but bootstrap methods may come to the rescue. Distinctive features of the book are the emphasis on geometric notions and the frequency domain, the discussion of entropy maximization, and a thorough treatment of recent computer-intensive methods for time series such as subsampling and the bootstrap. There are more than 600 exercises, half of which involve R coding and/or data analysis. Supplements include a website with 12 key data sets and all R code for the book's examples, as well as the solutions to exercises.