Book picks similar to
Econometric Analysis by William H. Greene


economics
econometrics
statistics
data-science

Probability and Statistics


Morris H. DeGroot - 1975
    Other new features include a chapter on simulation, a section on Gibbs sampling, what you should know boxes at the end of each chapter, and remarks to highlight difficult concepts.

The Enigma of Capital and the Crises of Capitalism


David Harvey - 2010
    In The Enigma of Capital, he delivers an impassioned account of how unchecked neoliberalism produced the system-wide crisis that now engulfs the world. Beginning in the 1970s, profitability pressures led the capitalist class in advanced countries to shift away from investment in industrial production at home toward the higher returns that financial products promised. Accompanying this was a shift towards privatization, an absolute decline in the bargaining power of labor, and the dispersion of production throughout the developing world. The decades-long and ongoing decline in wages that accompanied this turn produced a dilemma: how can goods--especially real estate--sell at the same rate as before if workers are making less in relative terms? The answer was a huge expansion of credit that fueled the explosive growth of both the financial industry and the real estate market. When one key market collapsed--real estate--the other one did as well, and social devastation resulted. Harvey places today's crisis in the broadest possible context: the historical development of global capitalism itself from the industrial era onward. Moving deftly between this history and the unfolding of the current crisis, he concentrates on how such crises both devastate workers and create openings for challenging the system's legitimacy. The battle now will be between the still-powerful forces that want to reconstitute the system of yesterday and those that want to replace it with one that prizes social justice and economic equality. The new afterword focuses on the continuing impact of the crisis and the response to it in 2010. One of Huffington Post's Best Social and Political Awareness Books of 2010 Winner of the Isaac and Tamara Deutscher Memorial Prize for 2010 Praise for the Hardcover: "A lucid and penetrating account of how the power of capital shapes our world."--Andrew Gamble, Independent "Elegant... entertainingly swashbuckling... Harvey's analysis is interesting not only for the breadth of his scholarship but his recognition of the system's strengths."--John Gapper, Financial Times

A Man for All Markets


Edward O. Thorp - 2016
    Thorp invented card counting, proving the seemingly impossible: that you could beat the dealer at the blackjack table. As a result he launched a gambling renaissance. His remarkable success--and mathematically unassailable method--caused such an uproar that casinos altered the rules of the game to thwart him and the legions he inspired. They barred him from their premises, even put his life in jeopardy. Nonetheless, gambling was forever changed.Thereafter, Thorp shifted his sights to "the biggest casino in the world" Wall Street. Devising and then deploying mathematical formulas to beat the market, Thorp ushered in the era of quantitative finance we live in today. Along the way, the so-called godfather of the quants played bridge with Warren Buffett, crossed swords with a young Rudy Giuliani, detected the Bernie Madoff scheme, and, to beat the game of roulette, invented, with Claude Shannon, the world's first wearable computer.Here, for the first time, Thorp tells the story of what he did, how he did it, his passions and motivations, and the curiosity that has always driven him to disregard conventional wisdom and devise game-changing solutions to seemingly insoluble problems. An intellectual thrill ride, replete with practical wisdom that can guide us all in uncertain financial waters, A Man for All Markets is an instant classic--a book that challenges its readers to think logically about a seemingly irrational world.Praise for A Man for All Markets"In A Man for All Markets, [Thorp] delightfully recounts his progress (if that is the word) from college teacher to gambler to hedge-fund manager. Along the way we learn important lessons about the functioning of markets and the logic of investment."--The Wall Street Journal"[Thorp] gives a biological summation (think Richard Feynman's Surely You're Joking, Mr. Feynman!) of his quest to prove the aphorism 'the house always wins' is flawed. . . . Illuminating for the mathematically inclined, and cautionary for would-be gamblers and day traders"-- Library Journal

Public Finance and Public Policy


Jonathan Gruber - 2004
    The new edition, fully updated with the most recent data and research possible, includes new coverage of the Medicare drug benefit, changes in the tax code, Hurricane Katrina, and the ongoing debate over privatization.

Python Machine Learning


Sebastian Raschka - 2015
    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

Macroeconomics


Olivier J. Blanchard - 1991
    Its fundamental goals are to provide an integrated view of macroeconomics, and to make close contact with current macroeconomic events.

Statistics for People Who (Think They) Hate Statistics


Neil J. Salkind - 2000
    The book begins with an introduction to the language of statistics and then covers descriptive statistics and inferential statistics. Throughout, the author offers readers:- Difficulty Rating Index for each chapter′s material- Tips for doing and thinking about a statistical technique- Top tens for everything from the best ways to create a graph to the most effective techniques for data collection- Steps that break techniques down into a clear sequence of procedures- SPSS tips for executing each major statistical technique- Practice exercises at the end of each chapter, followed by worked out solutions.The book concludes with a statistical software sampler and a description of the best Internet sites for statistical information and data resources. Readers also have access to a website for downloading data that they can use to practice additional exercises from the book. Students and researchers will appreciate the book′s unhurried pace and thorough, friendly presentation.

Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences


Jacob Cohen - 1975
    Readers profit from its verbal-conceptual exposition and frequent use of examples.The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 .Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

Linear Algebra Done Right


Sheldon Axler - 1995
    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

Economics of Strategy


David Besanko - 1995
    By presenting basic concepts of economic theory with ideas in modern strategy literature, the book provides an economic lens for viewing the broad sweep of the strategic activities of the firm. The book begins by focusing on the boundaries of the firm and examines competitive strategy from the perspective of industrial organization (IO) economics, particularly Porter's Five Forces. It then explores strategic positioning and dynamics as well as topics associated with internal organization, including personnel economics, organization structure, and strategic fit. Features of the Fourth Edition * Chapters on human resources management, entry, positioning, dynamics, technological change, and organizational structure are substantially revised. * An updated chapter on business history covers the recent dot-com bubble. * Presents economic principles without overemphasizing the math. * Rigorous treatment of organizational topics such as structure and culture enables you to experience the full scope of strategic thinking. * The authors use Porter's Five Forces as a tool for organizing industry analysis, building on the coverage of industrial organization and game theory. The text also considers the Value Net, another tool for organizing industry analysis. * Includes coverage of make or buy decisions (Chapters 2-4) and benefit and cost advantage and sustaining advantage (Chapters 11-13). * Fascinating examples, including many new to this edition, bring the economic models to life. Many of the examples involve businesses outside of the United States.

The Signal and the Noise: Why So Many Predictions Fail—But Some Don't


Nate Silver - 2012
    He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of FiveThirtyEight.com. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the "prediction paradox": The more humility we have about our ability to make predictions, the more successful we can be in planning for the future.In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good-or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary-and dangerous-science.Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise.

Causality: Models, Reasoning, and Inference


Judea Pearl - 2000
    It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable. Professor of Computer Science at the UCLA, Judea Pearl is the winner of the 2008 Benjamin Franklin Award in Computers and Cognitive Science.

The Worldly Philosophers


Robert L. Heilbroner - 1953
    In this seventh edition, Robert L. Heilbroner provides a new theme that connects thinkers as diverse as Adam Smith and Karl Marx. The theme is the common focus of their highly varied ideas—namely, the search to understand how a capitalist society works. It is a focus never more needed than in this age of confusing economic headlines.In a bold new concluding chapter entitled “The End of the Worldly Philosophy?” Heilbroner reminds us that the word “end” refers to both the purpose and limits of economics. This chapter conveys a concern that today’s increasingly “scientific” economics may overlook fundamental social and political issues that are central to economics. Thus, unlike its predecessors, this new edition provides not just an indispensable illumination of our past but a call to action for our future. (amazon.com)

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Technical Analysis of the Financial Markets


John J. Murphy - 1986
    Murphy has updated his landmark bestseller Technical Analysis of the Futures Markets, to include all of the financial markets.This outstanding reference has already taught thousands of traders the concepts of technical analysis and their application in the futures and stock markets. Covering the latest developments in computer technology, technical tools, and indicators, the second edition features new material on candlestick charting, intermarket relationships, stocks and stock rotation, plus state-of-the-art examples and figures. From how to read charts to understanding indicators and the crucial role technical analysis plays in investing, readers gain a thorough and accessible overview of the field of technical analysis, with a special emphasis on futures markets. Revised and expanded for the demands of today's financial world, this book is essential reading for anyone interested in tracking and analyzing market behavior.