The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association. The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website.

    This title is aimed at courses in applied econometrics, political methodology, and sociological methods or a one-year graduate course in econometrics for social scientists.

    The Third Edition expands on the earlier editions in two ways. First, the coverage has been rewritten and rearranged. Second, chapters have been added on game theory, oligopoly, asset markets, and information economics. The new chapters fully update the text, highlighting significant developments of the last decade at a level that is accessible for first-year graduate students.

    This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.-- "Journal of Economics"

    It introduces first year Ph.D. students to standard graduate econometrics material from a modern perspective. It covers all the standard material necessary for understanding the principal techniques of econometrics from ordinary least squares through cointegration. The book is also distinctive in developing both time-series and cross-section analysis fully, giving the reader a unified framework for understanding and integrating results.Econometrics has many useful features and covers all the important topics in econometrics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models (such as probit and tobit) are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient manner. Eight of the ten chapters include a serious empirical application drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises at the end of each chapter provide students a hands-on experience applying the techniques covered in the chapter. The exposition is rigorous yet accessible to students who have a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions, so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text.For those who intend to write a thesis on applied topics, the empirical applications of the book are a good way to learn how to conduct empirical research. For the theoretically inclined, the no-compromise treatment of the basic techniques is a good preparation for more advanced theory courses.

    In the modern experimentalist paradigm, these techniques address clear causal questions such as: Do smaller classes increase learning? Should wife batterers be arrested? How much does education raise wages? Mostly Harmless Econometrics shows how the basic tools of applied econometrics allow the data to speak.In addition to econometric essentials, Mostly Harmless Econometrics covers important new extensions--regression-discontinuity designs and quantile regression--as well as how to get standard errors right. Joshua Angrist and Jorn-Steffen Pischke explain why fancier econometric techniques are typically unnecessary and even dangerous. The applied econometric methods emphasized in this book are easy to use and relevant for many areas of contemporary social science.An irreverent review of econometric essentials A focus on tools that applied researchers use most Chapters on regression-discontinuity designs, quantile regression, and standard errors Many empirical examples A clear and concise resource with wide applications

    The book emphasizes a general introduction to probability theory and provides a detailed discussion of specific designs and analyses that are typically encountered in ecology and environmental science. Appropriate for use as either a stand-alone or supplementary text for upper-division undergraduate or graduate courses in ecological and environmental statistics, ecology, environmental science, environmental studies, or experimental design, the Primer also serves as a resource for environmental professionals who need to use and interpret statistics daily but have little or no formal training in the subject.

    Reviewed are fundamental statistical concepts--such as correlation, regressions, data preparation and screening, path analysis, and confirmatory factor analysis--as well as more advanced methods, including the evaluation of nonlinear effects, measurement models and structural regression models, latent growth models, and multilevel SEM. The companion Web page offers data and program syntax files for many of the research examples, electronic overheads that can be downloaded and printed by instructors or students, and links to SEM-related resources.

    Essentially, you make an initial guess, and then get more data to improve it. Bayes Theorem, or Bayes Rule, has a ton of real world applications, from estimating your risk of a heart attack to making recommendations on Netflix But It Isn't That Complicated This book is a short introduction to Bayes Theorem. It is only 15 pages long, and is intended to show you how Bayes Theorem works as quickly as possible. The examples are intentionally kept simple to focus solely on Bayes Theorem without requiring that the reader know complicated probability distributions. If you want to learn the basics of Bayes Theorem as quickly as possible, with some easy to duplicate examples, this is a good book for you.

    It can be freely downloaded and it works on multiple computer platforms. This book provides an elementary introduction to R. In each chapter, brief introductory sections are followed by code examples and comments from the computational and statistical viewpoint. A supplementary R package containing the datasets can be downloaded from the web.

    "Using Econometrics: A Practical Guide "provides readers with a practical introduction that combines single-equation linear regression analysis with real-world examples and exercises. This text also avoids complex matrix algebra and calculus, making it an ideal text for beginners. New problem sets and added support make "Using Econometrics" modern and easier to use.

    eGrade Plus offers an integrated suite of teaching and learning resources, including an online version of Black's Business Statistics for Contemporary Decision Making, Fourth Edition Update, in one easy-to-use Web site. Organized around the essential activities you perform in class, eGrade Plus helps you: Create class presentation using a wealth of Wiley-provided resources. you may easily adapt, customize, and add to his content to meet the needs of your course. Automate the assigning and grading of homework or quizzes by using Wiley-provided question banks, or by writing your won. Student results will be automatically graded and recorded in your gradebook. Track your students' progress. An instructor's gradebook allows you to an analyze individual and overall class results to determine each student's progress and level of understanding. Administer your course. eGrade Plus can easily be integrated with another course management system, gradebook, or other resources you are using in your class. Provide students with problem-solving support. eGrade Plus can link homework problems to the relevant section of the online text, providing context-sensitive help. Best of all, instructors can arrange to have eGrade Plus packaged FREE with new copies of Business Statistics for Contemporary Decision Making, Fourth Edition Update, All instructors have to do is adopt the eGrade Plus version of this book and activate their eGrade Plus course.

    Masterfully combining the results of years of teaching microeconomics at Harvard University, Andreu Mas-Colell, Michael Whinston, and Jerry Green have filled that conspicuous vacancy with their groundbreaking text, Microeconomic Theory.The authors set out to create a solid organizational foundation upon which to build the effective teaching tool for microeconomic theory. The result presents unprecedented depth of coverage in all the essential topics, while allowing professors to tailor-make their course to suit personal priorities and style. Topics such as noncooperative game theory, information economics, mechanism design, and general equilibrium under uncertainty receive the attention that reflects their stature within the discipline. The authors devote an entire section to game theory alone, making it free-standing to allow instructors to return to it throughout the course when convenient. Discussion is clear, accessible, and engaging, enabling the student to gradually acquire confidence as well as proficiency. Extensive exercises within each chapter help students to hone their skills, while the text's appendix of terms, fully cross-referenced throughout the previous five sections, offers an accessible guide to the subject matter's terminology. Teachers of microeconomics need no longer rely upon scattered lecture notes to supplement their textbooks. Deftly written by three of the field's most influential scholars, Microeconomic Theory brings the readability, comprehensiveness, and versatility to the first-year graduate classroom that has long been missing.

    This book develops statistical thinking over rote drill and practice. The Nature of Statistics; Organizing Data; Descriptive Measures; Probability Concepts; Discrete Random Variables; The Normal Distribution; The Sampling Distribution of the Sample Menu; Confidence Intervals for One Population Mean; Hypothesis Tests for One Population Mean; Inferences for Two Population Means; Inferences for Population Standard Deviations; Inferences for Population Proportions; Chi-Square Procedures; Descriptive Methods in Regression and Correlation; Inferential Methods in Regression and Correlation; Analysis of Variance (ANOVA) For all readers interested in Introductory Statistics.

    Survey Methodology describes the basic principles of survey design discovered in methodological research over recent years and offers guidance for making successful decisions in the design and execution of high quality surveys. Written by six nationally recognized experts in the field, this book covers the major considerations in designing and conducting a sample survey. Topical, accessible, and succinct, this book represents the state of the science in survey methodology. Employing the "total survey error" paradigm as an organizing framework, it merges the science of surveys with state-of-the-art practices. End-of-chapter terms, references, and exercises enhance its value as a reference for practitioners and as a text for advanced students.