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Applied Econometrics Using the SAS System by Vivek Ajmani (2009, Trade Paperback)

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Author Vivek Ajmani. Format Paperback. Edition 1st. Author Biography. Sports & Outdoors. ISBN-13 9780470129494.

About this product

Product Information

While many available books address statistical analysis using the SAS system, this is the first to cover SAS analysis of econometric data. This unique resource first introduces econometrics and econometric models, before describing how to analyze data using SAS.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0470129492
ISBN-13
9780470129494
eBay Product ID (ePID)
102905887

Product Key Features

Author
Vivek Ajmani
Publication Name
Applied Econometrics Using the SAS System
Format
Trade Paperback
Language
English
Publication Year
2009
Type
Textbook
Number of Pages
328 Pages

Dimensions

Item Length
11in
Item Height
0.8in
Item Width
8.5in
Item Weight
27.1 Oz

Additional Product Features

Lc Classification Number
Hb139.A46 2008
Reviews
"The text serves as a relevant and valuable reference for practitioners in the fields of business, economics, and finance. In addition, most students of econometrics are taught using GAUSS and STATA, yet SAS is the standard in the working world; therefore, this book is an ideal supplement for upper-undergraduate and graduate courses in statistics, economics, and other social sciences since it prepares readers for real-world careers." ( Zentralblatt MATH , 2012)
Table of Content
Preface. Acknowledgments. 1 Introduction to Regression Analysis. 1.1 Introduction. 1.2 Matrix Form of the Multiple Regression Model. 1.3 Basic Theory of Least Squares. 1.4 Analysis of Variance. 1.5 The Frisch-Waugh Theorem. 1.6 Goodness of Fit. 1.7 Hypothesis Testing and Confidence Intervals. 1.8 Some Further Notes. 2 Regression Analysis Using Proc IML and Proc Reg. 2.1 Introduction. 2.2 Regression Analysis Using Proc IML. 2.3 Analyzing the Data Using Proc Reg. 2.4 Extending the Investment Equation Model to the Complete Data Set. 2.5 Plotting the Data. 2.6 Correlation Between Variables. 2.7 Predictions of the Dependent Variable. 2.8 Residual Analysis. 2.9 Multicollinearity. 3 Hypothesis Testing. 3.1 Introduction. 3.2 Using SAS to Conduct the General Linear Hypothesis. 3.3 The Restricted Least Squares Estimator. 3.4 Alternative Methods of Testing the General Linear Hypothesis. 3.5 Testing for Structural Breaks in Data. 3.6 The CUSUM Test. 3.7 Models with Dummy Variables. 4 Instrumental Variables. 4.1 Introduction. 4.2 Omitted Variable Bias. 4.3 Measurement Errors. 4.4 Instrumental Variable Estimation. 4.5 Specification Tests. 5 Nonspherical Disturbances and Heteroscedasticity. 5.1 Introduction. 5.2 Nonspherical Disturbances. 5.3 Detecting Heteroscedasticity. 5.4 Formal Hypothesis Tests to Detect Heteroscedasticity. 5.5 Estimation of b Revisited. 5.6 Weighted Least Squares and FGLS Estimation. 5.7 Autoregressive Conditional Heteroscedasticity. 6 Autocorrelation. 6.1 Introduction. 6.2 Problems Associated with OLS Estimation Under Autocorrelation. 6.3 Estimation Under the Assumption of Serial Correlation. 6.4 Detecting Autocorrelation. 6.5 Using SAS to Fit the AR Models. 7 Panel Data Analysis. 7.1 What is Panel Data? 7.2 Panel Data Models. 7.3 The Pooled Regression Model. 7.4 The Fixed Effects Model 7.5 Random Effects Models.. 8 Systems of Regression Equations. 8.1 Introduction. 8.2 Estimation Using Generalized Least Squares. 8.3 Special Cases of the Seemingly Unrelated Regression Model. 8.4 Feasible Generalized Least Squares. 9 Simultaneous Equations. 9.1 Introduction. 9.2 Problems with OLS Estimation. 9.3 Structural and Reduced Form Equations. 9.4 The Problem of Identification. 9.5 Estimation of Simultaneous Equation Models. 9.6 Hausman''s Specification Test. 10 Discrete Choice Models. 10.1 Introduction. 10.2 Binary Response Models. 10.3 Poisson Regression. 11 Duration Analysis. 11.1 Introduction. 11.2 Failure Times and Censoring. 11.3 The Survival and Hazard Functions. 11.4 Commonly Used Distribution Functions in Duration Analysis. 11.5 Regression Analysis with Duration Data. 12 Special Topics. 12.1 Iterative FGLS Estimation Under Heteroscedasticity. 12.2 Maximum Likelihood Estimation Under Heteroscedasticity. 12.3 Harvey''s Multiplicative Heteroscedasticity. 12.4 Groupwise Heteroscedasticity. 12.5 Hausman-Taylor Estimator for the Random Effects Model. 12.6 Robust Estimation of Covariance Matrices in Panel Data. 12.7 Dynamic Panel Data Models. 12.8 Heterogeneity and Autocorrelation in Panel Data Models. 12.9 Autocorrelation in Panel Data. Appendix A Basic Matrix Algebra for Econometrics. B.1 Assigning Scalars. Appendix C Simulating the Large Sample Properties of the OLS Estimators. Appendix D Introduction to Bootstrap Estimation. Appendix E Complete Programs and Proc IML Routines. References. Index
Copyright Date
2009
Topic
Mathematical & Statistical Software, Probability & Statistics / General, Econometrics
Lccn
2008-004315
Dewey Decimal
330.0285/555
Intended Audience
Scholarly & Professional
Dewey Edition
22
Illustrated
Yes
Genre
Computers, Business & Economics, Mathematics

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Applied Econometrics Using the SAS System by Vivek Ajmani (2009, Trade Paperback)

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item 1 Applied Econometrics Using the SAS System by Ajmani, Vivek

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