Download or read book Stata cross sectional time series reference manual release 8 written by and published by . This book was released on 2003-12-31 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stata Cross sectional Time series written by Stata Corporation and published by . This book was released on 2003 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stata Time series written by Stata Corporation and published by Statacorp. This book was released on 2004 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Time Series Using Stata written by Sean Becketti and published by . This book was released on 2020-03-02 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Time Series Using Stata, Revised Edition, by Sean Becketti, is a practical guide to working with time-series data using Stata. In this book, Becketti introduces time-series techniques--from simple to complex--and explains how to implement them using Stata. The many worked examples, concise explanations that focus on intuition, and useful tips based on the author's experience make the book insightful for students, academic researchers, and practitioners in industry and government.Becketti is a financial industry veteran with decades of experience in academics, government, and private industry. He was also a developer of Stata in its infancy and has been a regular Stata user since its inception. He wrote many of the first time-series commands in Stata. With his abundant knowledge of Stata and extensive experience with real-world time-series applications, Becketti provides readers with unique insights and motivation throughout the book.For those new to Stata, the book begins with a mild yet fast-paced introduction to Stata, highlighting all the features you need to know to get started using Stata for time-series analysis. Before diving into analysis of time series, Becketti includes a quick refresher on statistical foundations such as regression and hypothesis testing.The discussion of time-series analysis begins with techniques for smoothing time series. As the moving-average and Holt-Winters techniques are introduced, Becketti explains the concepts of trends, cyclicality, and seasonality and shows how they can be extracted from a series. The book then illustrates how to use these methods for forecasting. Although these techniques are sometimes neglected in other time-series books, they are easy to implement, can be applied quickly, often produce forecasts just as good as more complicated techniques, and, as Becketti emphasizes, have the distinct advantage of being easily explained to colleagues and policy makers without backgrounds in statistics.Next, the book focuses on single-equation time-series models. Becketti discusses regression analysis in the presence of autocorrelated disturbances as well as the ARIMA model and Box-Jenkins methodology. An entire chapter is devoted to applying these techniques to develop an ARIMA-based model of U.S. GDP; this will appeal to practitioners, in particular, because it goes step by step through a real-world example: here is my series, now how do I fit an ARIMA model to it? The discussion of single-equation models concludes with a self-contained summary of ARCH/GARCH modeling.In the final portion of the book, Becketti discusses multiple-equation models. He introduces VAR models and uses a simple model of the U.S. economy to illustrate all key concepts, including model specification, Granger causality, impulse-response analyses, and forecasting. Attention then turns to nonstationary time-series. Becketti masterfully navigates the reader through the often-confusing task of specifying a VEC model, using an example based on construction wages in Washington, DC, and surrounding states.Introduction to Time Series Using Stata, Revised Edition, by Sean Becketti, is a first-rate, example-based guide to time-series analysis and forecasting using Stata. This is a must-have resource for researchers and students learning to analyze time-series data and for anyone wanting to implement time-series methods in Stata. [ed.]
Download or read book Computational Econometrics written by Charles G. Renfro and published by IOS Press. This book was released on 2004 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This publication contains a substantial amount of detail about the broad history of the development of econometric software based on the personal recollections of many people. For economists, the computer has increasingly become the primary applied research tool, and it is software that makes the computer work.
Download or read book An Introduction to Modern Econometrics Using Stata written by Christopher F. Baum and published by Stata Press. This book was released on 2006-08-17 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.
Download or read book A Visual Guide to Stata Graphics Second Edition written by Michael N. Mitchell and published by Stata Press. This book was released on 2008-06-04 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Power of Stata Graphics at Your Fingertips Whether you are new to Stata graphics or a seasoned veteran, this book teaches you how to use Stata to make high-quality graphs that stand out and enhance statistical results. With over 900 illustrated examples and quick-reference tabs, it offers a guide to creating and customizing graphs for any type of statistical data using either Stata commands or the Graph Editor. The author displays each graph example in full color with simple and clear instructions. He shows how to produce various types of graph elements, including marker symbols, lines, legends, captions, titles, axis labels, and grid lines. Reflecting the new graphics features of Stata, this thoroughly updated and expanded edition contains a new chapter that explains how to exploit the power of the new Graph Editor. This edition also includes additional examples and illustrates nearly every example with the Graph Editor.
Download or read book Stata Time series Reference Manual written by and published by Stata Press. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stata Time series Reference Manual written by StataCorp LP. and published by Stata Press. This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Survival Analysis Using Stata Second Edition written by Mario Cleves and published by Stata Press. This book was released on 2008-05-15 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: "[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.
Download or read book Econometric Analysis of Cross Section and Panel Data second edition written by Jeffrey M. Wooldridge and published by MIT Press. This book was released on 2010-10-01 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
Download or read book Handbook of Statistical Analyses Using Stata written by Brian S. Everitt and published by CRC Press. This book was released on 2006-11-15 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Download or read book A Practitioner s Guide to Stochastic Frontier Analysis Using Stata written by Subal C. Kumbhakar and published by Cambridge University Press. This book was released on 2015-01-26 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practitioner's Guide to Stochastic Frontier Analysis Using Stata provides practitioners in academia and industry with a step-by-step guide on how to conduct efficiency analysis using the stochastic frontier approach. The authors explain in detail how to estimate production, cost, and profit efficiency and introduce the basic theory of each model in an accessible way, using empirical examples that demonstrate the interpretation and application of models. This book also provides computer code, allowing users to apply the models in their own work, and incorporates the most recent stochastic frontier models developed in academic literature. Such recent developments include models of heteroscedasticity and exogenous determinants of inefficiency, scaling models, panel models with time-varying inefficiency, growth models, and panel models that separate firm effects and persistent and transient inefficiency. Immensely helpful to applied researchers, this book bridges the chasm between theory and practice, expanding the range of applications in which production frontier analysis may be implemented.
Download or read book A Practical Guide to Using Panel Data written by Simonetta Longhi and published by SAGE. This book was released on 2014-12-01 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely, thoughtful book provides a clear introduction to using panel data in research. It describes the different types of panel datasets commonly used for empirical analysis, and how to use them for cross sectional, panel, and event history analysis. Longhi and Nandi then guide the reader through the data management and estimation process, including the interpretation of the results and the preparation of the final output tables. Using existing data sets and structured as hands-on exercises, each chapter engages with practical issues associated with using data in research. These include: Data cleaning Data preparation Computation of descriptive statistics Using sample weights Choosing and implementing the right estimator Interpreting results Preparing final output tables Graphical representation Written by experienced authors this exciting textbook provides the practical tools needed to use panel data in research.
Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Download or read book Stata Programming written by and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Interpreting and Visualizing Regression Models Using Stata written by MICHAEL N. MITCHELL and published by Stata Press. This book was released on 2020-12-18 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.
