Applied Econometrics with SAS / Goodwin, Barry.

Format:

Book

Author/Creator:

Goodwin, Barry, author.

Ramsey, A., author.

Chvosta, Jan, author.

Language:

English

Subjects (All):

Econometrics--Computer programs.

Econometrics.

SAS (Computer file).

Physical Description:

1 online resource (180 pages)

Edition:

1st edition

Place of Publication:

SAS Institute, 2018.

System Details:

text file

Summary:

Using Applied Econometrics with SAS: Modeling Demand, Supply, and Risk , you will quickly master SAS applications for implementing and estimating standard models in the field of econometrics. This guide introduces you to the major theories underpinning applied demand and production economics. For each of its three main topics—demand, supply, and risk—a concise theoretical orientation leads directly into consideration of specific economic models and econometric techniques, collectively covering the following: Double-log demand systems Linear expenditure systems Almost ideal demand systems Rotterdam models Random parameters logit demand models Frequency-severity models Compound distribution models Cobb-Douglas production functions Translogarithmic cost functions Generalized Leontief cost functions Density estimation techniques Copula models SAS procedures that facilitate estimation of demand, supply, and risk models include the following, among others: PROC MODEL PROC COPULA PROC SEVERITY PROC KDE PROC LOGISTIC PROC HPCDM PROC IML PROC REG PROC COUNTREG PROC QLIM An empirical example, SAS programming code, and a complete data set accompany each econometric model, empowering you to practice these techniques while reading. Examples are drawn from both major scholarly studies and business applications so that professors, graduate students, government economic researchers, agricultural analysts, actuaries, and underwriters, among others, will immediately benefit. This book is part of the SAS Press program.

Notes:

Online resource; Title from title page (viewed April 4, 2018)

Includes bibliographical references.

OCLC:

1033544274