Analytics is one of a number of terms which are used to describe a data-driven more scientific approach to management. Ability in analytics is an essential management skill: knowledge of data and analytics helps the manager to analyze decision situations, prevent problem situations from arising, identify new opportunities, and often enables many millions of dollars to be added to the bottom line for the organization. The objective of this book is to introduce analytics from the perspective of the general manager of a corporation. Rather than examine the details or attempt an encyclopaedic review of the field, this text emphasizes the strategic role that analytics is playing in globally competitive corporations today. The chapters of this book are organized in two main parts. The first part introduces a problem area and presents some basic analytical concepts that have been successfully used to address the problem area. The objective of this material is to provide the student, the manager of the future, with a general understanding of the tools and techniques used by the analyst.

Developed over 20 years of teaching academic courses, the Handbook of Financial Risk Management can be divided into two main parts: risk management in the financial sector; and a discussion of the mathematical and statistical tools used in risk management. This comprehensive text offers readers the chance to develop a sound understanding of financial products and the mathematical models that drive them, exploring in detail where the risks are and how to manage them. Key Features: Written by an author with both theoretical and applied experience Ideal resource for students pursuing a master's degree in finance who want to learn risk management Comprehensive coverage of the key topics in financial risk management Contains 114 exercises, with solutions provided online at www.crcpress.com/9781138501874

The small sample properties of estimators and tests are frequently too complex to be useful or are unknown. Much econometric theory is therefore developed for very large or asymptotic samples where it is assumed that the behaviour of estimators and tests will adequately represent their properties in small samples. Refined asymptotic methods adopt an intermediate position by providing improved approximations to small sample behaviour using asymptotic expansions. Dedicated to the memory of Michael Magdalinos, whose work is a major contribution to this area, this book contains chapters directly concerned with refined asymptotic methods. In addition, there are chapters focusing on new asymptotic results; the exploration through simulation of the small sample behaviour of estimators and tests in panel data models; and improvements in methodology. With contributions from leading econometricians, this collection will be essential reading for researchers and graduate students concerned with the use of asymptotic methods in econometric analysis.

How can organizations ensure that they can get best value for money in their procurement decisions? How can they stimulate innovations from their dedicated suppliers? With contributions from leading academics and professionals, this 2006 handbook offers expert guidance on the fundamental aspects of successful procurement design and management in firms, public administrations, and international institutions. The issues addressed include the management of dynamic procurement; the handling of procurement risk; the architecture of purchasing systems; the structure of incentives in procurement contracts; methods to increase suppliers' participation in procurement contests and e-procurement platforms; how to minimize the risk of collusion and of corruption; pricing and reputation mechanisms in e-procurement platforms; and how procurement can enhance innovation. Inspired by frontier research, it provides practical recommendations to managers, engineers and lawyers engaged in private and public procurement design.

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 new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.

Table of Contents

Introduction

Basic Descriptive Techniques

Some Linear Time Series Models

Fitting Time Series Models in the Time Domain

Forecasting

Stationary Processes in the Frequency Domain

Spectral Analysis

Bivariate Processes

Linear Systems

State-Space Models and the Kalman Filter

Non-Linear Models

Volatility Models

Multivariate Time Series Modelling

Some More Advanced Topics

Appendix A Fourier, Laplace, and z-Transforms

Appendix B Dirac Delta Function

Appendix C Covariance and Correlation

Answers to Exercises

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This textbook contains and explains essential mathematical 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 mathematical 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: mathematical signs and symbols, logic, arithmetic, algebra, linear algebra, combinatorics, financial mathematics, optimisation of linear models, functions, differential calculus, integral calculus, elasticities, economic functions, and the Peren theorem. 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.

This is a concise and elementary introduction to stochastic control and mathematical modelling. This book is designed for researchers in stochastic control theory studying its application in mathematical economics and those in economics who are interested in mathematical theory in control. It is also a good guide for graduate students studying applied mathematics, mathematical economics, and non-linear PDE theory. Contents include the basics of analysis and probability, the theory of stochastic differential equations, variational problems, problems in optimal consumption and in optimal stopping, optimal pollution control, and solving the Hamilton-Jacobi-Bellman (HJB) equation with boundary conditions. Major mathematical prerequisites are contained in the preliminary chapters or in the appendix so that readers can proceed without referring to other materials.

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.

Running Regressions introduces first-year social science undergraduates, particularly those studying economics and business, to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach. It shows that statistical analysis can be simultaneously straightforward, useful and interesting, and can deal with topical, real-world issues. Each chapter introduces an economic theory or idea by relating it to an issue of topical interest, and explains how data and econometric analysis can be used to test it. The book can be used as a self-standing text or to supplement conventional econometric texts. It is also ideally suited as a guide to essays and project work.

Running Regressions introduces first-year social science undergraduates, particularly those studying economics and business, to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach. It shows that statistical analysis can be simultaneously straightforward, useful and interesting, and can deal with topical, real-world issues. Each chapter introduces an economic theory or idea by relating it to an issue of topical interest, and explains how data and econometric analysis can be used to test it. The book can be used as a self-standing text or to supplement conventional econometric texts. It is also ideally suited as a guide to essays and project work.

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.

This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.

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.

Offers a practical introduction to regression modeling with spatial and spatial-temporal data relevant to research and teaching in the social and economic sciences Focuses on a few key datasets and data analysis using the open source software WinBUGS, R, and GeoDa Provides data and programming codes to allow users to undertake their own analyses Ends each chapter with a set of short exercises and questions for further study

Mit diesem Buch liegen kompakte Beschreibungen von Prognoseverfahren vor, die vor allem in Systemen der betrieblichen Informationsverarbeitung eingesetzt werden. Praktiker mit langjahriger Prognoseerfahrung zeigen ausserdem, wie die einzelnen Methoden in der Unternehmung Verwendung finden und wo die Probleme beim Einsatz liegen. Das Buch wendet sich gleichermassen an Wissenschaft und Praxis. Das Spektrum reicht von einfachen Verfahren der Vorhersage uber neuere Ansatze der kunstlichen Intelligenz und Zeitreihenanalyse bis hin zur Prognose von Softwarezuverlassigkeit und zur kooperativen Vorhersage in Liefernetzen. In der siebenten, wesentlich uberarbeiteten und erweiterten Auflage werden neue Vergleiche von Prognosemethoden, GARCH-Modelle zur Finanzmarktprognose, Predictive Analytics" als Variante der Business Intelligence" und die Kombination von Vorhersagen mit Elementen der Chaostheorie berucksichtigt."

Over the last thirty years there has been extensive use of continuous time econometric methods in macroeconomic modelling. This monograph presents the first continuous time macroeconometric model of the United Kingdom incorporating stochastic trends. Its development represents a major step forward in continuous time macroeconomic modelling. The book describes the new model in detail and, like earlier models, it is designed in such a way as to permit a rigorous mathematical analysis of its steady-state and stability properties, thus providing a valuable check on the capacity of the model to generate plausible long-run behaviour. The model is estimated using newly developed exact Gaussian estimation methods for continuous time econometric models incorporating unobservable stochastic trends. The book also includes discussion of the application of the model to dynamic analysis and forecasting.

Most textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is about using regression to solve real problems of comparison, estimation, prediction, and causal inference. Unlike other books, it focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use immediately. Real examples, real stories from the authors' experience demonstrate what regression can do and its limitations, with practical advice for understanding assumptions and implementing methods for experiments and observational studies. They make a smooth transition to logistic regression and GLM. The emphasis is on computation in R and Stan rather than derivations, with code available online. Graphics and presentation aid understanding of the models and model fitting.

This book is a collection of essays written in honor of Professor Peter C. B. Phillips of Yale University by some of his former students. The essays analyze a number of state of the art issues in econometrics, all of which Professor Phillips has directly influenced through his seminal scholarly contribution as well as through his remarkable achievements as a teacher. The essays are organized to cover topics in higher-order asymptotics, deficient instruments, nonstationary, LAD and quantile regression, and nonstationary panels. These topics span both theoretical and applied approaches and are intended for use by professionals and advanced graduate students.

Matrix Algebra is the first volume of the Econometric Exercises Series. It contains exercises relating to course material in matrix algebra that students are expected to know while enrolled in an (advanced) undergraduate or a postgraduate course in econometrics or statistics. The book contains a comprehensive collection of exercises, all with full answers. But the book is not just a collection of exercises; in fact, it is a textbook, though one that is organized in a completely different manner than the usual textbook. The volume can be used either as a self-contained course in matrix algebra or as a supplementary text.

In der IT-Organisation geht es um die zuverlassige, zeit-, kosten- und qualitatsoptimale Bereitstellung geschaftsprozessunterstutzender IT-Dienstleistungen. Renommierte Wissenschaftler, erfahrene Unternehmensberater und Fuhrungskrafte diskutieren die Strategien, Instrumente, Konzepte und Organisationsansatze fur das IT-Management von morgen.
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Originally published in 2005, Weather Derivative Valuation covers all the meteorological, statistical, financial and mathematical issues that arise in the pricing and risk management of weather derivatives. There are chapters on meteorological data and data cleaning, the modelling and pricing of single weather derivatives, the modelling and valuation of portfolios, the use of weather and seasonal forecasts in the pricing of weather derivatives, arbitrage pricing for weather derivatives, risk management, and the modelling of temperature, wind and precipitation. Specific issues covered in detail include the analysis of uncertainty in weather derivative pricing, time-series modelling of daily temperatures, the creation and use of probabilistic meteorological forecasts and the derivation of the weather derivative version of the Black-Scholes equation of mathematical finance. Written by consultants who work within the weather derivative industry, this book is packed with practical information and theoretical insight into the world of weather derivative pricing.

This book is based on two Sir Richard Stone lectures at the Bank of England and the National Institute for Economic and Social Research. Largely non-technical, the first part of the book covers some of the broader issues involved in Stone's and others' work in statistics. It explores the more philosophical issues attached to statistics, econometrics and forecasting and describes the paradigm shift back to the Bayesian approach to scientific inference. The first part concludes with simple examples from the different worlds of educational management and golf clubs. The second, more technical part covers in detail the structural econometric time series analysis (SEMTSA) approach to statistical and econometric modeling.

This book develops econometric techniques for the estimation of production, cost and profit frontiers, and for the estimation of the technical and economic efficiency with which producers approach these frontiers. Since these frontiers envelop rather than intersect the data, and since the authors continue to maintain the traditional econometric belief in the presence of external forces contributing to random statistical noise, the work is titled Stochastic Frontier Analysis. Hb ISBN (2000): 0-521-48184-8