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Author: Rolla Edward Park Publisher: ISBN: Category : Mathematics Languages : en Pages : 54
Book Description
A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).
Author: Rolla Edward Park Publisher: ISBN: Category : Mathematics Languages : en Pages : 54
Book Description
A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).
Author: L. Phlips Publisher: Springer Science & Business Media ISBN: 9401117950 Category : Business & Economics Languages : en Pages : 261
Book Description
In this testament to the distinguished career of H.S. Houthakker a number of Professor Houthakker's friends, former colleagues and former students offer essays which build upon and extend his many contributions to economics in aggregation, consumption, growth and trade. Among the many distinguished contributors are Paul Samuelson, Werner Hildenbrand, John Muellbauer and Lester Telser. The book also includes four previously unpublished papers and notes by its distinguished dedicatee.
Author: Robert A. Pollak Publisher: Oxford University Press ISBN: 0198023405 Category : Business & Economics Languages : en Pages : 232
Book Description
This book explores the principal issues involved in bridging the gap between the pure theory of consumer behavior and its empirical implementation. The theoretical starting point is the familiar static, one-period, utility maximizing model in which the consumer allocates a fixed budget among competing categories of goods. The authors focus upon four issues of primary importance in empirical demand analysis: the structure of preferences, the treatment of demographic variables, treatment of dynamics, and the specification of the stochastic structure of the demand system.
Author: Rolla Edward Park Publisher: ISBN: Category : Autocorrelation (Statistics) Languages : en Pages : 40
Book Description
A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).
Author: Michael H. Kutner Publisher: McGraw-Hill/Irwin ISBN: 9780072386882 Category : Mathematics Languages : en Pages : 1396
Book Description
Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Author: Thomas B. Fomby Publisher: Springer Science & Business Media ISBN: 1441987460 Category : Business & Economics Languages : en Pages : 637
Book Description
This book had its conception in 1975in a friendly tavern near the School of Businessand PublicAdministration at the UniversityofMissouri-Columbia. Two of the authors (Fomby and Hill) were graduate students of the third (Johnson), and were (and are) concerned about teaching econometrics effectively at the graduate level. We decided then to write a book to serve as a comprehensive text for graduate econometrics. Generally, the material included in the bookand itsorganization have been governed by the question, " Howcould the subject be best presented in a graduate class?" For content, this has meant that we have tried to cover " all the bases " and yet have not attempted to be encyclopedic. The intended purpose has also affected the levelofmathematical rigor. We have tended to prove only those results that are basic and/or relatively straightforward. Proofs that would demand inordinant amounts of class time have simply been referenced. The book is intended for a two-semester course and paced to admit more extensive treatment of areas of specific interest to the instructor and students. We have great confidence in the ability, industry, and persistence of graduate students in ferreting out and understanding the omitted proofs and results. In the end, this is how one gains maturity and a fuller appreciation for the subject in any case. It is assumed that the readers of the book will have had an econometric methods course, using texts like J. Johnston's Econometric Methods, 2nd ed.
Author: John C. Brocklebank, Ph.D. Publisher: SAS Institute ISBN: 1629605441 Category : Computers Languages : en Pages : 616
Book Description
To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
Author: Rolla Edward Park
Author: Rolla Edward Park
Author: Rand Corporation
Author: L. Phlips
Author: Robert A. Pollak
Author: 
Author: Rolla Edward Park
Author: Rolla Edward Park
Author: Michael H. Kutner
Author: Thomas B. Fomby
Author: John C. Brocklebank, Ph.D.