It examines a distinctive stage in the development of capitalism that began in the 1980s, in order to understand where we are now and how capitalism has evolved since. The book discusses the crisis tendencies of capitalism--including the S.E. Asian banking crisis, the collapse of the Russian economy, and the 1997-1998 global financial crisis--asking whether capitalism is doomed to fail. In the end, the author ruminates on a possible alternative to capitalism, discussing socialism, communal and cooperative experiments, and alternatives proposed by environmentalists.About the Series: Combining authority with wit, accessibility, and style, Very Short Introductions offer an introduction to some of life's most interesting topics. Written by experts for the newcomer, they demonstrate the finest contemporary thinking about the central problems and issues in hundreds of key topics, from philosophy to Freud, quantum theory to Islam.

    * An increased international focus with more coverage of IASC and non-US GAAPs and more non-US examples.

    And so, too often, 'the bland lead the bland'. Our unfamiliar problems need a new approach, and the reception given to this famous book has shown the value of its fresh, lively ideas.'A compelling challenge to conventional thought'  The New York Times'He shows himself a truly sensitive and civilized man, whose ideas are grounded in the common culture of the two continents, and may serve as a link between them; his book is of foremost importance for them both'  The Times Literary SupplementJohn Kenneth Galbraith (1908-2006) was a Canadian-American economist. A Keynesian and an institutionalist, Galbraith was a leading proponent of 20th-century American liberalism and progressivism. Galbraith was the author of 30 books, including The Economics of Innocent Fraud, The Great Crash: 1929, and A History of Economics.

    This must change to insure a capitalism that works for us all.In this scathing indictment of our current global financial system, The Value of Everything rigorously scrutinizes the way in which economic value has been determined and reveals how the difference between value creation and value extraction has become increasingly blurry. Mariana Mazzucato argues that this blurriness allowed certain actors in the economy to portray themselves as value creators, while in reality they were just moving existing value around or, even worse, destroying it.The book uses case studies - from Silicon Valley to the financial sector to big pharma - to show how the foggy notions of value create confusion between rents and profits, a difference that distorts the measurements of growth and GDP.The lesson here is urgent and sobering: to rescue our economy from the next, inevitable crisis and to foster long-term economic growth, we will need to rethink capitalism, rethink the role of public policy and the importance of the public sector, and redefine how we measure value in our society.

    Students know that Schaum's delivers the goods—in faster learning curves,better test scores,and higher grades!If you don't have a lot of time but want to excel in class,this book helps you: Brush up before tests; Find answers fast; Study quickly and more effectively; Get the big picture without spending hours poring over dull texts Schaum's Outlines give you the information teachers expect you to know in a handy and succinct format—without overwhelming you with unnecessary details. You get a complete overview of the subject—and no distracting minutiae. Plus,you get plenty of practice exercises to test your skill. Compatible with any classroom text,Schaum's lets you study at your own pace and reminds you of all the important facts you need to remember—fast! And Schaum's is so complete it's the perfect tool for preparing for graduate or professional exams! Students of mathematical economics apply complex formulas—a challenging task that even the best students find daunting. But this Schaum's guide demystifies tough problems and gives you plenty of fully worked examples! Chapters include: Review. Economic Applications of Graphs and Equations. The Derivative and the Rules of Differentiation. Uses of the Derivative in Mathematics and Economics. Calculus of Multivariable Functions. Calculus of Multivariable Functions in Economics. Exponential and LogarithmicFunctions. Exponential and Logarithmic Functions in Economics. Differentiation of Exponential and Logarithmic Functions. The Fundamentals of Linear (or Matrix) Algebra. Matrix Inversion. Special Determinants and Matrices and Their Use in Economics. Linear Programming: A Graphic Approach. Linear Programming: The Simplex Algorithm. Linear Programming: The Dual. Integral Calculus: The Indefinite Integral. Integral Calculus: The Definite Integral. Differential Equations. Difference Equations. Second-Order Differential Equations and Difference Equations. The Calculus of Variations

    It provides a simple, thorough survey of elementary topics, starting with set theory and advancing to metric and topological spaces, connectedness, and compactness. 1975 edition.

    Freedom, Sen argues, is both the end and most efficient means of sustaining economic life and the key to securing the general welfare of the world's entire population. Releasing the idea of individual freedom from association with any particular historical, intellectual, political, or religious tradition, Sen clearly demonstrates its current applicability and possibilities. In the new global economy, where, despite unprecedented increases in overall opulence, the contemporary world denies elementary freedoms to vast numbers—perhaps even the majority of people—he concludes, it is still possible to practically and optimistically regain a sense of social accountability. Development as Freedom is essential reading.

    His chief work, Principles of Political Economy and Taxation, first published in 1817, had a profound impact and remains one of the groundworks of modern economics. Ricardo's labor theory of value, as well as his elaboration of the division of incomes, and the function of wages, rent, and trade, deeply influenced the economic philosophies of Karl Marx, John Stuart Mill, Alfred Marshall, and many others.

    Topics covered include matrix multiplication, row reduction, matrix inverse, orthogonality and computation. The self-teaching book is loaded with examples and graphics and provides a wide array of probing problems, accompanying solutions, and a glossary. Chapter 1: Introduction to Vectors; Chapter 2: Solving Linear Equations; Chapter 3: Vector Spaces and Subspaces; Chapter 4: Orthogonality; Chapter 5: Determinants; Chapter 6: Eigenvalues and Eigenvectors; Chapter 7: Linear Transformations; Chapter 8: Applications; Chapter 9: Numerical Linear Algebra; Chapter 10: Complex Vectors and Matrices; Solutions to Selected Exercises; Final Exam. Matrix Factorizations. Conceptual Questions for Review. Glossary: A Dictionary for Linear Algebra Index Teaching Codes Linear Algebra in a Nutshell.

    Darrell Huff runs the gamut of every popularly used type of statistic, probes such things as the sample study, the tabulation method, the interview technique, or the way the results are derived from the figures, and points up the countless number of dodges which are used to fool rather than to inform.

    Sullivan Elin M. Wicks C. Patrick Koelling   A succinct job description for an engineer consists of just two words: problem solver. Broadly speaking, engineers use knowledge to find new ways of doing things economically. Engineering design solutions do not exist in a vacuum, but within the context of a business opportunity. Truly, every problem has multiple solutions, so the question is, “How does one rationally select the design solution with the most favorable economic result?” The answer to this question can also be put forth in two words: engineering economy. This field of engineering provides a systematic framework for evaluating the economic aspects of competing design solutions. Just as engineers model the stress on a support column or the thermodynamic properties of a steam turbine, they must also model the economic impact of their engineering recommendations. Engineering economy is the subject of this textbook.   Highlights of Engineering Economy, Fourteenth Edition: ×           Fifty percent of end-of-chapter problems are new or revised. ×           A bank of algorithmically generated test questions is available to adopting instructors. ×           Fundamentals of Engineering (FE) exam-style questions are included among the end-of-chapter problem sets. ×           Spreadsheet models are integratedthroughout. ×           An appendix on the basics of accounting is included in Chapter 2. ×           Chapter 3 on Cost Estimation appears early in the book. ×           An appendix on techniques for using Excel in engineering economy is available for reference. ×           Numerous comprehensive examples and case studies appear throughout the book. ×           Extended learning exercises appear in most chapters. ×           Personal finance problems are featured in most chapters. ×           Many pointers to relevant Web sites are provided.   ISBN-13: 978-0-13-614297-3 ISBN-10: 0-13-614297-4

    

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    In this Very Short Introduction, Robert C. Allen shows how the interplay of geography, globalization, technological change, and economic policy has determined the wealth and poverty of nations. Allen shows how the industrial revolution was Britain's path-breaking response to the challenge of globalization. Western Europe and North America joined Britain to form a club of rich nations, pursuing four polices--creating a national market by abolishing internal tariffs and investing in transportation, erecting an external tariff to protect their fledgling industries from British competition, creating banks to stabilize the currency and mobilize domestic savings for investment, and promoting mass education to prepare people for industrial work. Together these countries pioneered new technologies that have made them ever richer. A few countries--Japan, Soviet Russia, South Korea, Taiwan, and perhaps China--have caught up with the West through creative responses to the technological challenge and with Big Push industrialization that has achieved rapid growth through coordinated investment.

    Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.