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Using Econometrics : A Practical Guide,9780321316493
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Using Econometrics : A Practical Guide

by
Edition:
6th
ISBN13:

9780321316493

ISBN10:
0321316495
Format:
Hardcover
Pub. Date:
1/1/2011
Publisher(s):
Prentice Hall
List Price: $180.00
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Summary

"A. H. Studenmund's practical introduction to econometrics combines single-equation linear regression analysis with real-world examples and exercises. Using Econometrics: A Practical Guide provides a thorough introduction to econometrics that avoids complex matrix algebra and calculus, making it the ideal text for the beginning econometrics student, the regression user looking for a refresher or the experienced practitioner seeking a convenient reference."--BOOK JACKET.

Table of Contents

Preface xi
part I THE BASIC REGRESSION MODEL
1(160)
An Overview of Regression Analysis
2(33)
What Is Econometrics?
2(4)
What Is Regression Analysis?
6(10)
The Estimated Regression Equation
16(3)
A Simple Example of Regression Analysis
19(2)
Using Regression to Explain Housing Prices
21(3)
Summary and Exercises
24(11)
Ordinary Least Squares
35(31)
Estimating Single-Independent-Variable Models with OLS
35(5)
Estimating Multivariate Regression Models with OLS
40(9)
Evaluating the Quality of a Regression Equation
49(1)
Describing the Overall Fit of the Estimated Model
50(6)
An Example of the Misuse of R2
56(2)
Summary and Exercises
58(8)
Learning to Use Regression Analysis
66(22)
Steps in Applied Regression Analysis
66(9)
Using Regression Analysis to Pick Restaurant Locations
75(7)
Summary and Exercises
82(6)
The Classical Model
88(24)
The Classical Assumptions
88(9)
The Sampling Distribution of β
97(5)
The Gauss-Markov Theorem and the Properties of OLS Estimators
102(2)
Standard Econometric Notation
104(1)
Summary and Exercises
105(7)
Hypothesis Testing
112(49)
What Is Hypothesis Testing?
113(8)
The t-Test
121(9)
Examples of t-Tests
130(8)
Limitations of the t-Test
138(4)
Summary and Exercises
142(10)
Appendix: The F-Test
152(9)
part II VIOLATIONS OF THE CLASSICAL ASSUMPTIONS
161(258)
Specification: Choosing the Independent Variables
162(41)
Omitted Variables
163(7)
Irrelevant Variables
170(3)
An Illustration of the Misuse of Specification Criteria
173(3)
Specification Searches
176(5)
An Example of Choosing Independent Variables
181(4)
Summary and Exercises
185(12)
Appendix: Additional Specification Criteria
197(6)
Specification: Choosing a Functional Form
203(42)
The Use and Interpretation of the Constant Term
204(3)
Alternative Functional Forms
207(13)
Lagged Independent Variables
220(2)
Using Dummy Variables
222(3)
Slope Dummy Variables
225(4)
Problems with Incorrect Functional Forms
229(3)
Summary and Exercises
232(13)
Multicollinearity
245(68)
Perfect versus Imperfect Multicollinearity
246(4)
The Consequences of Multicollinearity
250(7)
The Detection of Multicollinearity
257(3)
Remedies for Multicollinearity
260(6)
Choosing the Proper Remedy
266(7)
Summary and Exercises
273(12)
Appendix: The SAT Interactive Regression Learning Exercise
285(28)
Serial Correlation
313(33)
Pure versus Impure Serial Correlation
314(8)
The Consequences of Serial Correlation
322(3)
The Durbin-Watson d Test
325(5)
Remedies for Serial Correlation
330(5)
Summary and Exercises
335(11)
Heteroskedasticity
346(44)
Pure versus Impure Heteroskedasticity
347(6)
The Consequences of Heteroskedasticity
353(2)
Testing for Heteroskedasticity
355(7)
Remedies for Heteroskedasticity
362(7)
A More Complete Example
369(7)
Summary and Exercises
376(14)
A Regression User's Handbook
390(29)
A Regression User's Checklist and Guide
391(4)
Running Your Own Regression Project
395(3)
Economic Data
398(4)
The Ethical Econometrician
402(2)
Practical Advice for Applied Econometricians
404(9)
Summary
413(1)
Appendix: The Housing Price Interactive Exercise
414(5)
part III EXTENSIONS OF THE BASIC REGRESSION MODEL
419(154)
Time-Series Models
420(27)
Dynamic Models
421(6)
Serial Correlation and Dynamic Models
427(4)
Granger Causality
431(1)
Spurious Correlation and Nonstationarity
432(9)
Summary and Exercises
441(6)
Dummy Dependent Variable Techniques
447(27)
The Linear Probability Model
447(7)
The Binomial Logit Mode
454(7)
Other Dummy Dependent Variable Techniques
461(3)
Summary and Exercises
464(10)
Simultaneous Equations
474(37)
Structural and Reduced-Form Equations
475(6)
The Bias of Ordinary Least Squares (OLS)
481(4)
Two-Stage Least Squares (2SLS)
485(9)
The Identification Problem
494(5)
Summary and Exercises
499(8)
Appendix: Errors in the Variables
507(4)
Forecasting
511(22)
What Is Forecasting?
512(5)
More Complex Forecasting Problems
517(8)
ARIMA Models
525(3)
Summary and Exercises
528(5)
Statistical Principles
533(40)
Gary Smith
Probability Distributions
533(14)
Sampling
547(4)
Estimation
551(8)
Hypothesis Tests
559(7)
Summary and Exercises
566(7)
Appendix A Answers to Even-Numbered Exercises 573(36)
Appendix B Statistical Tables 609(16)
Index 625


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