Introduction to econometrics:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boston ; Munich [u.a.]
Pearson Addison Wesley
2008
|
| Edition: | Brief ed., Pearson internat. ed. |
| Series: | The Addison-Wesley series in economics
|
| Subjects: | |
| Online Access: | Table of contents only Inhaltsverzeichnis |
| Physical Description: | XXVI, 379 S. graph. Darst. |
| ISBN: | 0321442962 9780321442963 |
Staff View
MARC
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| 245 | 1 | 0 | |a Introduction to econometrics |c James H. Stock ; Mark W. Watson |
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| 264 | 1 | |a Boston ; Munich [u.a.] |b Pearson Addison Wesley |c 2008 | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface
PART ONE Introduction and Review
CHAPTER
1.
Question
Education?
Question
Quantitative Questions, Quantitative Answers
1.2
Estimation of Causal Effects
Forecasting and Causality
1.3
Experimental versus Observational Data
Cross-Sectional Data
Time Series Data
Panel Data
chapter
2.1
Probabilities, the Sample Space, and Random Variables
Probability Distribution of a Discrete Random Variable
Probability Distribution of a Continuous Random Variable
2.2
The Expected Value of a Random Variable
The Standard Deviation and Variance
Mean and Variance of a Linear Function of a Random Variable
Other Measures of the Shape of a Distribution
2.3
Joint and Marginal Distributions
Conditional Distributions
VII
viii CONTENTS
Independence
Covariance and Correlation
The Mean and Variance of Sums of Random Variables
2.4
The Normal Distribution
The Chi-Squared Distribution
The Student
The
2.5
Random Sampling
The Sampling Distribution of the Sample Average
2.6
The Law of Large Numbers and Consistency
The Central Limit Theorem
AP
CHAPTERS Review of Statistics
3.1
Estimators and Their Properties
Properties of
The Importance of Random Sampling
3.2
Null and Alternative Hypotheses
Thep-Value
Calculating the p-Value When
The Sample Variance, Sample Standard Deviation, and Standard Error
Calculating the p-Value When
The i-Statistic
Hypothesis Testing with a Prespecified Significance Level
One-Sided Alternatives
3.3
3.4
Hypothesis Tests for the Difference Between Two Means
Confidence Intervals for the Difference Between Two Population Means
3.5
Using Experimental Data
The Causal Effect as a Difference of Conditional Expectations
Estimation of the Causal Effect Using Differences of Means
CONTENTS
3.6
The
Use of the Student
3.7
Scatterplots
Sample Covariance and Correlation
APPENDIX
APPENDIX
APPENDIX
PART TWO Fundamentals of Regression Analysis
CHAPTER
4.1
4.2
The Ordinary Least Squares Estimator
OLS Estimates of the Relationship Between Test Scores and the
Student-Teacher Ratio
Why Use the OLS Estimator?
4.3
The/?2
The Standard Error of the Regression
Application to the Test Score Data
4.4
Assumption
ofZero
Assumption
and Identically Distributed
Assumption
Use of the Least Squares Assumptions
4.5
The Sampling Distribution of the OLS Estimators
4.6
APPENDIX
APPENDIX
APPENDIX
CONTENTS
CHAPTER
and Confidence Intervals
5.1
Regression Coefficients
Two-Sided Hypotheses Concerning
One-Sided Hypotheses Concerning
Testing Hypotheses About the Intercept
5.2
5.3
Interpretation of the Regression Coefficients
5.4
What Are Heteroskedasticity and Homoskedasticity?
Mathematical Implications of Homoskedasticity
What Does This Mean in Practice?
5.5
Linear Conditionally Unbiased Estimators and the Gauss-Markov Theorem
Regression Estimators Other Than OLS
5.6
the Sample Size Is Small
The t-Statistic and the Student
Use of the Student
5.7
APPENDIX
APPENDIX
of the Gauss-Markov Theorem
CHAPTER
6.1
Definition of Omitted Variable Bias
A Formula for Omitted Variable Bias
Addressing Omitted Variable Bias by Dividing the Data into Groups
6.2
The Population Regression Line
The Population Multiple Regression Model
6.3
The OLS Estimator
Application to Test Scores and the Student-Teacher Ratio
CONTENTS xi
6.4
The Standard Error of the Regression
The/?2
The Adjusted/?2
Application to Test Scores
6.5
Assumption
Has a Mean of Zero
Assumption
Assumption
Assumption
6.6
in Multiple Regression
6.7
Examples of Perfect Multicollinearity
Imperfect Multicollinearity
6.8
APPENDIX
APPENDIX
Regressors and Homoskedastic Errors
APPENDIX
CHAPTER
in Multiple Regression
7.1
for a Single Coefficient
Standard Errors for the OLS Estimators
Hypothesis Tests for a Single Coefficient
Confidence Intervals for a Single Coefficient
Application to Test Scores and the Student-Teacher Ratio
7.2
Testing Hypotheses on Two or More Coefficients
The F-Statistic
Application to Test Scores and the Student-Teacher Ratio
The Homoskedasticity-Only
7.3
Involving Multiple Coefficients
7.4
xii
CONTENTS
7.5
Omitted Variable Bias in Multiple Regression
Model Specification in Theory and in Practice
Interpreting the R2 and the Adjusted R2 in Practice
7.6
7.7
APPENDIX
CHAPTER
8.1
Regression Functions
Test Scores and District Income
The Effect on
A General Approach to Modeling Nonlinearities Using Multiple Regression
8.2
Polynomials
Logarithms
Polynomial and Logarithmic Models of Test Scores and District Income
8.3
Interactions Between Two Binary Variables
Interactions Between a Continuous and a Binary Variable
Interactions Between Two Continuous Variables
8.4
Discussion of Regression Results
Summary of Findings
8.5
APPENDIX
in the Parameters
CHAPTER
9.1
Threats to Internal Validity
Threats to External Validity
9.2
Omitted Variable Bias
Misspecification of the Functional Form of the Regression Function
Errors-in-Variables
Sample Selection
CONTENTS xiii
Simultaneous Causality
Sources of Inconsistency of OLS Standard Errors
9.3
for Forecasting
Using Regression Models for Forecasting
Assessing the Validity of Regression Models for Forecasting
9.4
External Validity
Internal Validity
Discussion and Implications
9.5
APPENDIX
CHAPTER
10.1
10.2
Finding a Data Set
Time Series Data and Panel Data
Preparing the Data for Regression Analysis
10.3
10.4
Appendix
References
Answers to Review the Concepts Questions
Glossary
Index
|
| adam_txt |
Contents
Preface
PART ONE Introduction and Review
CHAPTER
1.
Question
Education?
Question
Quantitative Questions, Quantitative Answers
1.2
Estimation of Causal Effects
Forecasting and Causality
1.3
Experimental versus Observational Data
Cross-Sectional Data
Time Series Data
Panel Data
chapter
2.1
Probabilities, the Sample Space, and Random Variables
Probability Distribution of a Discrete Random Variable
Probability Distribution of a Continuous Random Variable
2.2
The Expected Value of a Random Variable
The Standard Deviation and Variance
Mean and Variance of a Linear Function of a Random Variable
Other Measures of the Shape of a Distribution
2.3
Joint and Marginal Distributions
Conditional Distributions
VII
viii CONTENTS
Independence
Covariance and Correlation
The Mean and Variance of Sums of Random Variables
2.4
The Normal Distribution
The Chi-Squared Distribution
The Student
The
2.5
Random Sampling
The Sampling Distribution of the Sample Average
2.6
The Law of Large Numbers and Consistency
The Central Limit Theorem
AP
CHAPTERS Review of Statistics
3.1
Estimators and Their Properties
Properties of
The Importance of Random Sampling
3.2
Null and Alternative Hypotheses
Thep-Value
Calculating the p-Value When
The Sample Variance, Sample Standard Deviation, and Standard Error
Calculating the p-Value When
The i-Statistic
Hypothesis Testing with a Prespecified Significance Level
One-Sided Alternatives
3.3
3.4
Hypothesis Tests for the Difference Between Two Means
Confidence Intervals for the Difference Between Two Population Means
3.5
Using Experimental Data
The Causal Effect as a Difference of Conditional Expectations
Estimation of the Causal Effect Using Differences of Means
CONTENTS
3.6
The
Use of the Student
3.7
Scatterplots
Sample Covariance and Correlation
APPENDIX
APPENDIX
APPENDIX
PART TWO Fundamentals of Regression Analysis
CHAPTER
4.1
4.2
The Ordinary Least Squares Estimator
OLS Estimates of the Relationship Between Test Scores and the
Student-Teacher Ratio
Why Use the OLS Estimator?
4.3
The/?2
The Standard Error of the Regression
Application to the Test Score Data
4.4
Assumption
ofZero
Assumption
and Identically Distributed
Assumption
Use of the Least Squares Assumptions
4.5
The Sampling Distribution of the OLS Estimators
4.6
APPENDIX
APPENDIX
APPENDIX
CONTENTS
CHAPTER
and Confidence Intervals
5.1
Regression Coefficients
Two-Sided Hypotheses Concerning
One-Sided Hypotheses Concerning
Testing Hypotheses About the Intercept
5.2
5.3
Interpretation of the Regression Coefficients
5.4
What Are Heteroskedasticity and Homoskedasticity?
Mathematical Implications of Homoskedasticity
What Does This Mean in Practice?
5.5
Linear Conditionally Unbiased Estimators and the Gauss-Markov Theorem
Regression Estimators Other Than OLS
5.6
the Sample Size Is Small
The t-Statistic and the Student
Use of the Student
5.7
APPENDIX
APPENDIX
of the Gauss-Markov Theorem
CHAPTER
6.1
Definition of Omitted Variable Bias
A Formula for Omitted Variable Bias
Addressing Omitted Variable Bias by Dividing the Data into Groups
6.2
The Population Regression Line
The Population Multiple Regression Model
6.3
The OLS Estimator
Application to Test Scores and the Student-Teacher Ratio
CONTENTS xi
6.4
The Standard Error of the Regression
The/?2
The'Adjusted/?2"
Application to Test Scores
6.5
Assumption
Has a Mean of Zero
Assumption
Assumption
Assumption
6.6
in Multiple Regression
6.7
Examples of Perfect Multicollinearity
Imperfect Multicollinearity
6.8
APPENDIX
APPENDIX
Regressors and Homoskedastic Errors
APPENDIX
CHAPTER
in Multiple Regression
7.1
for a Single Coefficient
Standard Errors for the OLS Estimators
Hypothesis Tests for a Single Coefficient
Confidence Intervals for a Single Coefficient
Application to Test Scores and the Student-Teacher Ratio
7.2
Testing Hypotheses on Two or More Coefficients
The F-Statistic
Application to Test Scores and the Student-Teacher Ratio
The Homoskedasticity-Only
7.3
Involving Multiple Coefficients
7.4
xii
CONTENTS
7.5
Omitted Variable Bias in Multiple Regression
Model Specification in Theory and in Practice
Interpreting the R2 and the Adjusted R2 in Practice
7.6
7.7
APPENDIX
CHAPTER
8.1
Regression Functions
Test Scores and District Income
The Effect on
A General Approach to Modeling Nonlinearities Using Multiple Regression
8.2
Polynomials
Logarithms
Polynomial and Logarithmic Models of Test Scores and District Income
8.3
Interactions Between Two Binary Variables
Interactions Between a Continuous and a Binary Variable
Interactions Between Two Continuous Variables
8.4
Discussion of Regression Results
Summary of Findings
8.5
APPENDIX
in the Parameters
CHAPTER
9.1
Threats to Internal Validity
Threats to External Validity
9.2
Omitted Variable Bias
Misspecification of the Functional Form of the Regression Function
Errors-in-Variables
Sample Selection
CONTENTS xiii
Simultaneous Causality
Sources of Inconsistency of OLS Standard Errors
9.3
for Forecasting
Using Regression Models for Forecasting
Assessing the Validity of Regression Models for Forecasting
9.4
External Validity
Internal Validity
Discussion and Implications
9.5
APPENDIX
CHAPTER
10.1
10.2
Finding a Data Set
Time Series Data and Panel Data
Preparing the Data for Regression Analysis
10.3
10.4
Appendix
References
Answers to "Review the Concepts" Questions
Glossary
Index |
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| id | DE-604.BV022470248 |
| illustrated | Illustrated |
| index_date | 2024-07-02T17:44:19Z |
| indexdate | 2024-07-09T20:58:17Z |
| institution | BVB |
| isbn | 0321442962 9780321442963 |
| language | English |
| lccn | 2006039352 |
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| spelling | Stock, James H. Verfasser (DE-588)12457131X aut Introduction to econometrics James H. Stock ; Mark W. Watson Brief ed., Pearson internat. ed. Boston ; Munich [u.a.] Pearson Addison Wesley 2008 XXVI, 379 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier The Addison-Wesley series in economics Econometrics Ökonometrie (DE-588)4132280-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Ökonometrie (DE-588)4132280-0 s DE-604 Watson, Mark W. 1952- Verfasser (DE-588)124571344 aut http://www.loc.gov/catdir/toc/ecip075/2006039352.html Table of contents only Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015677748&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Stock, James H. Watson, Mark W. 1952- Introduction to econometrics Econometrics Ökonometrie (DE-588)4132280-0 gnd |
| subject_GND | (DE-588)4132280-0 (DE-588)4123623-3 |
| title | Introduction to econometrics |
| title_auth | Introduction to econometrics |
| title_exact_search | Introduction to econometrics |
| title_exact_search_txtP | Introduction to econometrics |
| title_full | Introduction to econometrics James H. Stock ; Mark W. Watson |
| title_fullStr | Introduction to econometrics James H. Stock ; Mark W. Watson |
| title_full_unstemmed | Introduction to econometrics James H. Stock ; Mark W. Watson |
| title_short | Introduction to econometrics |
| title_sort | introduction to econometrics |
| topic | Econometrics Ökonometrie (DE-588)4132280-0 gnd |
| topic_facet | Econometrics Ökonometrie Lehrbuch |
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