Portfolio theory and much of asset pricing, as well as many empirical applications, depend on the use of multivariate probability distributions to describe asset returns. Traditionally, this has meant the multivariate normal (or Gaussian) distribution. More recently, theoretical and empirical work in financial economics has employed the multivariate Student (and other) distributions which are members of the elliptically symmetric class. There is also a growing body of work which is based on skew-elliptical distributions. These probability models all exhibit the property that the marginal distributions differ only by location and scale parameters or are restrictive in other respects. Very often, such models are not supported by the empirical evidence that the marginal distributions of asset returns can differ markedly. Copula theory is a branch of statistics which provides powerful methods to overcome these shortcomings. This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. Multivariate non-Gaussian dependence is a fact of life for many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features of financial data. This book was originally published as a special issue of the European Journal of Finance.

This volume provides a coherent analysis of the economic, monetary and political aspects of growth dynamics in the Euro area. The different relevant aspects in this debate, presented and discussed by leading scholars and representatives of international organizations, include an assessment of the newest theoretical growth models for open economies, and empirical investigation of: the growth divergence between the US and Europe the extent to which fiscal co-ordination is desirable in a monetary union the role of product and labor market reforms the complex relationships between exchange rates and growth the contribution of monetary policy to economic growth and the prospects for economic growth in monetary unions. Although primarily focused on the Euro area, the analysis is equally relevant to all other common currency areas and will be welcomed by academics and students with an interest in European studies and financial economics, as well as policy and decision makers in international organisations, national institutions and central banks.

This compendium contains and explains essential statistical formulas within an economic context. A broad range of aids and supportive examples will help readers to understand the formulas and their practical applications. This statistical formulary is presented in a practice-oriented, clear, and understandable manner, as it is needed for meaningful and relevant application in global business, as well as in the academic setting and economic practice. The topics presented include, but are not limited to: statistical signs and symbols, descriptive statistics, empirical distributions, ratios and index figures, correlation analysis, regression analysis, inferential statistics, probability calculation, probability distributions, theoretical distributions, statistical estimation methods, confidence intervals, statistical testing methods, the Peren-Clement index, and the usual statistical tables. Given its scope, the book offers an indispensable reference guide and is a must-read for undergraduate and graduate students, as well as managers, scholars, and lecturers in business, politics, and economics.

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.

A Hands-On Approach to Understanding and Using Actuarial Models Computational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/C++ embedded codes. After an introduction to the R language, the book is divided into four parts. The first one addresses methodology and statistical modeling issues. The second part discusses the computational facets of life insurance, including life contingencies calculations and prospective life tables. Focusing on finance from an actuarial perspective, the next part presents techniques for modeling stock prices, nonlinear time series, yield curves, interest rates, and portfolio optimization. The last part explains how to use R to deal with computational issues of nonlife insurance. Taking a do-it-yourself approach to understanding algorithms, this book demystifies the computational aspects of actuarial science. It shows that even complex computations can usually be done without too much trouble. Datasets used in the text are available in an R package (CASdatasets).

First Published in 1970. Econometric model-building, on the other hand, has been largely confined to the advanced industrialised countries. In the few cases where macro-models have been built for underdeveloped countries (e.g. the Narasimham model (112) for India) the underlying assumptions have been largely of the Keynesian type, and thus in the authors opinion unconnected with the theory of economic development. This study is a modest attempt at econometric model-building on the basis of a model of development of an underdeveloped country.

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.

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.

Discover how statistical information impacts decisions in today's business world as Anderson/Sweeney/Williams/Camm/Cochran/Fry/Ohlmann's leading ESSENTIALS OF STATISTICS FOR BUSINESS AND ECONOMICS, 9E connects concepts in each chapter to real-world practice. This edition delivers sound statistical methodology, a proven problem-scenario approach and meaningful applications that reflect the latest developments in business and statistics today. More than 350 new and proven real business examples, a wealth of practical cases and meaningful hands-on exercises highlight statistics in action. You gain practice using leading professional statistical software with exercises and appendices that walk you through using JMP (R) Student Edition 14 and Excel (R) 2016. WebAssign's online course management systems is available separately to further strengthen this business statistics approach and helps you maximize your course success.

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.

Volume 39A of Research in the History of Economic Thought and Methodology features a selection of essays presented at the 2019 Conference of the Latin American Society for the History of Economic Thought (ALAHPE), edited by Felipe Almeida and Carlos Eduardo Suprinyak, as well as a new general-research essay by Daniel Kuehn, an archival discovery by Katia Caldari and Luca Fiorito, and a book review by John Hall.

This book constitutes the first serious attempt to explain the basics of econometrics and its applications in the clearest and simplest manner possible. Recognising the fact that a good level of mathematics is no longer a necessary prerequisite for economics/financial economics undergraduate and postgraduate programmes, it introduces this key subdivision of economics to an audience who might otherwise have been deterred by its complex nature.

In this book, Nancy and Richard Ruggles demonstrate their unique grasp of the measurement and analysis of macro and micro data and elucidate ways of integrating the two data sets. Their analysis of macrodata is used to examine the economic growth of the United States from the 1920s to the present day. They focus particularly on recession and recovery between 1929 and 1974 and the measurement of short-run economic growth. They also examine the measurement of saving, investment and capital formation in the United States. On a microeconomic level, they analyse economic intelligence in World War II, offer a study of fertility in the United States in the pre-war era and analyse longitudinal establishment data. Finally they integrating the two approaches to provide a method of providing a more complete picture of social and economic performance.

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.

"Transportation Economics" explores the efficient use of society's scarce resources for the movement of people and goods. This book carefully examines transportation markets and standard economic tools, how these resources are used, and how the allocation of society resources affects transportation activities.

This textbook is unique in that it uses a detailed analysis of econometric results from current transportation literature to provide an integrated collection of theory and application. Its numerous case studies illustrate the economic principles, discuss testable hypotheses, analyze econometric results, and examine each study's implications for public policy. These features make this a well-developed introduction to the foundations of transportation economics.

Additional case studies on a spectrum of domestic and international transportation topics available at http: //www.blackwellpublishers.co.uk/mccarthy in order to keep students abreast of recent developments in the field and their implications for public policy.

The paperback edition of this book is not available from Blackwell in the US or Canda.

This two volume set is a collection of 30 classic papers presenting ideas which have now become standard in the field of Bayesian inference. Topics covered include the central field of statistical inference as well as applications to areas of probability theory, information theory, utility theory and computational theory. It is organized into seven sections: foundations, information theory and prior distributions; robustness and outliers; hierarchical, multivariate and non-parametric models; asymptotics; computations and Monte Carlo methods; and Bayesian econometrics.

Thoroughly classroom tested, this introductory text covers all the topics that constitute a foundation for basic econometrics, with concise and intuitive explanations of technical material. Important proofs are shown in detail; however, the focus is on developing regression models and understanding the residual

The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.

Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.

This book develops the theory of productivity measurement using the empirical index number approach. The theory uses multiplicative indices and additive indicators as measurement tools, instead of relying on the usual neo-classical assumptions, such as the existence of a production function characterized by constant returns to scale, optimizing behavior of the economic agents, and perfect foresight. The theory can be applied to all the common levels of aggregation (micro, meso, and macro), and half of the book is devoted to accounting for the links existing between the various levels. Basic insights from National Accounts are thereby used. The final chapter is devoted to the decomposition of productivity change into the contributions of efficiency change, technological change, scale effects, and input or output mix effects. Applications on real-life data demonstrate the empirical feasibility of the theory. The book is directed to a variety of overlapping audiences: statisticians involved in measuring productivity change; economists interested in growth accounting; researchers relating macro-economic productivity change to its industrial sources; enterprise micro-data researchers; and business analysts interested in performance measurement.

'Fascinating . . . timely' Daily Mail '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.

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.

This book provides an analytical and computational approach to solving and simulating the Mahalanobis model and the papers surrounding it. The book comes up, perhaps for the first time, with a holistic examination of an important growth model that emerged out of India in the 1950s. It contains detailed derivations of the Mahalanobis model and the several critiques and extensions surrounding it with an organized synthesis of the main results. Computationally, the book simulates the model and its many variants, thus making it accessible to a wider audience. Advanced undergraduates and beginning graduate students in the fields of Economics, Mathematics, and Statistics will gain immensely from understanding both the mathematical aspects as well as the computational aspects of the Mahalanobis model. In the absence of a single 'go-to' source on all aspects of the model -- analytical and computational -- this book is a definitive volume on the Mahalanobis model that has all the derivations of all the papers surrounding the model, its dissents and critiques, and extensions as in the wage goods model suggested by Vakil and Brahmananda.

The Handbook of U.S. Labor Statistics is recognized as an authoritative resource on the U.S. labor force. It continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labor Statistics. It allows the user to understand recent developments as well as to compare today's economy with past history. The 24th edition includes the new employment projections from 2019 to 2029. New projections are only released every two years. The Handbook is a comprehensive reference providing an abundance of data on a variety of topics including: Employment and unemployment; Earnings; Prices; Productivity; Consumer expenditures; Occupational safety and health; Union membership; Working poor Recent trends in the labor force And much more! Features of the publication In addition to over 215 tables that present practical data, the Handbook provides: Introductory material for each chapter that contains highlights of salient data and figures that call attention to noteworthy trends in the data Notes and definitions, which contain concise descriptions of the data sources, concepts, definitions, and methodology from which the data are derived References to more comprehensive reports which provide additional data and more extensive descriptions of estimation methods, sampling, and reliability measures