Описание: 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.
Описание: "Undergraduate Econometrics" clearly shows readers why econometrics is necessary and provides them with the ability to utilize basic econometric tools.
They'll learn how to apply these tools to estimation, inference, and forecasting in the context of real world economic problems. In order to make concepts more accessible, it also offers
lucid descriptions of
techniques as well as appropriate applications to today's situations.
Along the way, readers will find introductions to simple economic models and questions to enhance critical
Описание: An Introduction to Survival Analysis Using Stata, Revised Third Edition is the ideal tutorial for professional data analysts who want to learn survival analysis for the first time or who are well versed in survival analysis but are not as dexterous in using Stata to analyze survival data. This text also serves as a valuable reference to those readers who already have experience using Stata’s survival analysis routines. The revised third edition has been updated for Stata 14, and it includes a new section on predictive margins and marginal effects, which demonstrates how to obtain and visualize marginal predictions and marginal effects using the margins and marginsplot commands after survival regression models. Survival analysis is a field of its own that requires specialized data management and analysis procedures. To meet this requirement, Stata provides the st family of commands for organizing and summarizing survival data. This book provides statistical theory, step-by-step procedures for analyzing survival data, an in-depth usage guide for Stata's most widely used st commands, and a collection of tips for using Stata to analyze survival data and to present the results. This book develops from first principles the statistical concepts unique to survival data and assumes only a knowledge of basic probability and statistics and a working knowledge of Stata. The first three chapters of the text cover basic theoretical concepts: hazard functions, cumulative hazard functions, and their interpretations; survivor functions; hazard models; and a comparison of nonparametric, semiparametric, and parametric methodologies. Chapter 4 deals with censoring and truncation. The next three chapters cover the formatting, manipulation, stsetting, and error checking involved in preparing survival data for analysis using Stata's st analysis commands. Chapter 8 covers nonparametric methods, including the Kaplan–Meier and Nelson–Aalen estimators and the various nonparametric tests for the equality of survival experience. Chapters 9–11 discuss Cox regression and include various examples of fitting a Cox model, obtaining predictions, interpreting results, building models, model diagnostics, and regression with survey data. The next four chapters cover parametric models, which are fit using Stata's streg command. These chapters include detailed derivations of all six parametric models currently supported in Stata and methods for determining which model is appropriate, as well as information on stratification, obtaining predictions, and advanced topics such as frailty models. Chapter 16 is devoted to power and sample-size calculations for survival studies. The final chapter covers survival analysis in the presence of competing risks.
Автор: Subal C. Kumbhakar Название: Stochastic Frontier Analysis ISBN: 0521666635 ISBN-13(EAN): 9780521666633 Издательство: Cambridge Academ Рейтинг: Цена: 4929 р. Наличие на складе: Поставка под заказ.
Описание: Modern textbook presentations of production economics typically treat producers as successful optimizers. Conventional econometric practice has generally followed this paradigm, and least squares based regression techniques have been used to estimate production, cost, profit and other functions. In such a framework deviations from maximum output, from minimum cost and cost minimizing input demands, and from maximum profit and profit maximizing output supplies and input demands, are attributed exclusively to random statistical noise. However casual empiricism and the business press both make persuasive cases for the argument that, although producers may indeed attempt to optimize, they do not always succeed. This book develops econometric techniques for the estimation of production, cost and profit frontiers, and for the estimation of the technical and economic efficiency with which producers approach these frontiers. Since these frontiers envelop rather than intersect the data, and since the authors continue to maintain the traditional econometric belief in the presence of external forces contributing to random statistical noise, the work is titled Stochastic Frontier Analysis.
Описание: The service economy is now the largest portion of the industrialized world's economic activity. This development has dramatically raised the importance of maximizing productivity excellence in service organizations. The need for productivity excellence has led service organization managers to use benchmarking techniques to identify and adopt best practices in their organizations. Benchmarking has enabled service organizations to continuously improve by allowing service units to learn from methods that prove the most efficient and effective. Service Productivity Management systematically explores complex service issues and suggests the most appropriate methods to improve service productivity, quality, and profitability. The book provides insights and methods to answer questions on a range of productivity issues: How do you manage profitability of a network of hundreds or thousands of branch offices disbursed over several states and countries? How can managed-care organizations manage the quality and cost of hundreds of physicians providing health services to millions of plan members? What methods would enable a government to ensure that the multiple offices serving citizens across a country are operating at low cost while meeting the required service quality? Each of these service settings are examples of the many service providers that deliver a complex set of services to a widely diversified set of customers. . Service Productivity Management is an in-depth guide to using the most powerful available benchmarking technique to improve service organization performance вЂ” Data Envelopment Analysis (DEA). The underlying concepts that drive DEA and enable it to increase productivity and profitability of service organizations are explained in non-technical language. It describes how DEA: (1) Identifies best practice service units; (2) Exposes high cost inefficient service units; (3) Identifies specific changes to each service unit to elevate performance to the best practice level that provides high quality service at low cost; and most important, (4) Guides the improvement process. Use of basic and advanced DEA methods are all supported by case-study applications of organizations that have successfully improved their performance. The techniques discussed in the book are accessible to all managers with access to MicrosoftВ® Excel spreadsheet software (Excel). The book provides step-by-step guidance to enable the reader to apply DEA and Excel software to their organization. Packaged with the book is a ready-to-use DEA software CD that includes the DEAFrontier software. DEAFrontier is a MicrosoftВ® Excel Add-in designed to run DEA analyses on any set of organizations of interest to the reader. For a free trial version of the DEAFrontier software, please visit www.deafrontier.com.
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