Download or read book Mean Squared Prediction Error Reduction with Instrumental Variables written by Antonis Michis and published by . This book was released on 2016 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mean squared prediction error of the linear regression model is examined when estimation is performed with instrumental variables. It is shown that increasing the number of instruments in the estimation procedure, can reduce the mean squared prediction error of the model through more efficient estimation of the coefficient vector.
Download or read book Some Methods for Mean Squared Error Reduction in Stochastic Variable Prediction written by Greg M. Lepak and published by . This book was released on 1984 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Surface Temperature Reconstructions for the Last 2 000 Years written by National Research Council and published by National Academies Press. This book was released on 2007-01-05 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: In response to a request from Congress, Surface Temperature Reconstructions for the Last 2,000 Years assesses the state of scientific efforts to reconstruct surface temperature records for Earth during approximately the last 2,000 years and the implications of these efforts for our understanding of global climate change. Because widespread, reliable temperature records are available only for the last 150 years, scientists estimate temperatures in the more distant past by analyzing "proxy evidence," which includes tree rings, corals, ocean and lake sediments, cave deposits, ice cores, boreholes, and glaciers. Starting in the late 1990s, scientists began using sophisticated methods to combine proxy evidence from many different locations in an effort to estimate surface temperature changes during the last few hundred to few thousand years. This book is an important resource in helping to understand the intricacies of global climate change.
Download or read book Econometrics written by Bruce Hansen and published by Princeton University Press. This book was released on 2022-06-28 with total page 1081 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most authoritative and up-to-date core econometrics textbook available Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics. Covers the full breadth of econometric theory and methods with mathematical rigor while emphasizing intuitive explanations that are accessible to students of all backgrounds Draws on integrated, research-level datasets, provided on an accompanying website Discusses linear econometrics, time series, panel data, nonparametric methods, nonlinear econometric models, and modern machine learning Features hundreds of exercises that enable students to learn by doing Includes in-depth appendices on matrix algebra and useful inequalities and a wealth of real-world examples Can serve as a core textbook for a first-year PhD course in econometrics and as a follow-up to Bruce E. Hansen’s Probability and Statistics for Economists
Download or read book Forecasting Economic Time Series written by Michael Clements and published by Cambridge University Press. This book was released on 1998-10-08 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz. a non-constant, evolving economic system, and econometric models whose form and structure are unknown a priori. The authors find that conclusions which can be established formally for constant-parameter stationary processes and correctly-specified models often do not hold when unrealistic assumptions are relaxed. Despite the difficulty of proceeding formally when models are mis-specified in unknown ways for non-stationary processes that are subject to structural breaks, Hendry and Clements show that significant insights can be gleaned. For example, a formal taxonomy of forecasting errors can be developed, the role of causal information clarified, intercept corrections re-established as a method for achieving robustness against forms of structural change, and measures of forecast accuracy re-interpreted.
Download or read book Mostly Harmless Econometrics written by Joshua D. Angrist and published by Princeton University Press. This book was released on 2009-01-04 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to econometric essentials, this book covers important new extensions as well as how to get standard errors right. The authors explain why fancier econometric techniques are typically unnecessary and even dangerous.
Download or read book Applied Nonparametric Econometrics written by Daniel J. Henderson and published by Cambridge University Press. This book was released on 2015-01-12 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.
Download or read book Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model written by A. Terry Morris and published by . This book was released on 1999 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Reduced Asymptotic Mean Square Prediction Errors in a Nonlinear Simultaneous System written by and published by . This book was released on 1984 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exploring some uses for instrumental variable calibration weighting written by Phillip S. Kott and published by RTI Press. This book was released on 2013-01-01 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: The WTADJX procedure incorporated into the 2012 release of SUDAAN 11® does instrumental-variable calibration weighting using a flexible nonlinear weight-adjustment function. We review the theory behind this procedure and discuss two potential uses. The first tends to reduce mean squared errors in the absence of unit nonresponse or coverage errors. The second adjusts for unit nonresponse when the variables governing the response mechanism differ from the variables used to calibrate the weights. This occurs either because the survey variables of interest cannot be roughly modeled as a linear function of the response-model variables or because the values of the response-model variables are known only for the respondents.
Download or read book Principles of Econometrics written by R. Carter Hill and published by John Wiley & Sons. This book was released on 2018-02-21 with total page 1808 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Econometrics, Fifth Edition, is an introductory book for undergraduate students in economics and finance, as well as first-year graduate students in a variety of fields that include economics, finance, accounting, marketing, public policy, sociology, law, and political science. Students will gain a working knowledge of basic econometrics so they can apply modeling, estimation, inference, and forecasting techniques when working with real-world economic problems. Readers will also gain an understanding of econometrics that allows them to critically evaluate the results of others’ economic research and modeling, and that will serve as a foundation for further study of the field. This new edition of the highly-regarded econometrics text includes major revisions that both reorganize the content and present students with plentiful opportunities to practice what they have read in the form of chapter-end exercises.
Download or read book Statistical Regression and Classification written by Norman Matloff and published by CRC Press. This book was released on 2017-09-19 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Regression and Classification: From Linear Models to Machine Learning takes an innovative look at the traditional statistical regression course, presenting a contemporary treatment in line with today's applications and users. The text takes a modern look at regression: * A thorough treatment of classical linear and generalized linear models, supplemented with introductory material on machine learning methods. * Since classification is the focus of many contemporary applications, the book covers this topic in detail, especially the multiclass case. * In view of the voluminous nature of many modern datasets, there is a chapter on Big Data. * Has special Mathematical and Computational Complements sections at ends of chapters, and exercises are partitioned into Data, Math and Complements problems. * Instructors can tailor coverage for specific audiences such as majors in Statistics, Computer Science, or Economics. * More than 75 examples using real data. The book treats classical regression methods in an innovative, contemporary manner. Though some statistical learning methods are introduced, the primary methodology used is linear and generalized linear parametric models, covering both the Description and Prediction goals of regression methods. The author is just as interested in Description applications of regression, such as measuring the gender wage gap in Silicon Valley, as in forecasting tomorrow's demand for bike rentals. An entire chapter is devoted to measuring such effects, including discussion of Simpson's Paradox, multiple inference, and causation issues. Similarly, there is an entire chapter of parametric model fit, making use of both residual analysis and assessment via nonparametric analysis. Norman Matloff is a professor of computer science at the University of California, Davis, and was a founder of the Statistics Department at that institution. His current research focus is on recommender systems, and applications of regression methods to small area estimation and bias reduction in observational studies. He is on the editorial boards of the Journal of Statistical Computation and the R Journal. An award-winning teacher, he is the author of The Art of R Programming and Parallel Computation in Data Science: With Examples in R, C++ and CUDA.
Download or read book Mean Square Error of Prediction as a Criterion for Selecting Variables written by David Mitchell Allen and published by . This book was released on 1970 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep IV in Law written by Zhe Huang and published by Cambridge University Press. This book was released on 2022-08-25 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do US Circuit Courts' decisions on criminal appeals influence sentence lengths imposed by US District Courts? This Element explores the use of high-dimensional instrumental variables to estimate this causal relationship. Using judge characteristics as instruments, this Element implements two-stage models on court sentencing data for the years 1991 through 2013. This Element finds that Democratic, Jewish judges tend to favor criminal defendants, while Catholic judges tend to rule against them. This Element also finds from experiments that prosecutors backlash to Circuit Court rulings while District Court judges comply. Methodologically, this Element demonstrates the applicability of deep instrumental variables to legal data.
Download or read book A First Course in Linear Model Theory written by Nalini Ravishanker and published by CRC Press. This book was released on 2001-12-21 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the mathematical and statistical concepts and tools that form a foundation for studying the theory and applications of both univariate and multivariate linear models A First Course in Linear Model Theory systematically presents the basic theory behind linear statistical models with motivation from an algebraic as well as a geometric perspective. Through the concepts and tools of matrix and linear algebra and distribution theory, it provides a framework for understanding classical and contemporary linear model theory. It does not merely introduce formulas, but develops in students the art of statistical thinking and inspires learning at an intuitive level by emphasizing conceptual understanding. The authors' fresh approach, methodical presentation, wealth of examples, and introduction to topics beyond the classical theory set this book apart from other texts on linear models. It forms a refreshing and invaluable first step in students' study of advanced linear models, generalized linear models, nonlinear models, and dynamic models.
Download or read book Mean Squared Error of Estimation Or Prediction Under a General Linear Model written by D. A. Harville and published by . This book was released on 1989 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using Out of sample Mean Squared Prediction Errors to Test the Martingale Difference written by Todd E. Clark and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider using out-of-sample mean squared prediction errors (MSPEs) to evaluate the null that a given series follows a zero mean martingale difference against the alternative that it is linearly predictable. Under the null of no predictability, the population MSPE of the null "no change" model equals that of the linear alternative. We show analytically and via simulations that despite this equality, the alternative model's sample MSPE is expected to be greater than the null's. For rolling regression estimators of the alternative model's parameters, we propose and evaluate an asymptotically normal test that properly accounts for the upward shift of the sample MSPE of the alternative model. Our simulations indicate that our proposed procedure works well.
