Preface page xvii
User Guide 1
0.1. Conventions and Organization of Files 1
0.2. Preparing andWorking with Microsoft Excel R
3
1. Introduction 10
1.1. Definition of Econometrics 10
1.2. Regression Analysis 11
Cig.xls
1.3. Conclusion 28
1.4. Exercises 29
References 30
PART 1. DESCRIPTION
2. Correlation 33
2.1. Introduction 33
2.2. Correlation Basics 33
Correlation.xls
2.3. Correlation Dangers 40
Correlation.xls
IMRGDP.xls
2.4. Ecological Correlation 44
EcolCorr.xls
EcolCorrCPS.xls
2.5. Conclusion 50
2.6. Exercises 51
References 51
vii3. PivotTables 53
3.1. Introduction 53
3.2. The Basic PivotTable 53
IndianaFTWorkers.xls (in Basic Tools\InternetData\CPS)
Histogram.xla (Excel add-in)
3.3. The Crosstab and Conditional Average 59
IndianaFTWorkers.xls (in Basic Tools\InternetData\CPS)
3.4. PivotTables and the Conditional Mean Function 65
EastNorthCentralFTWorkers.xls
3.5. Conclusion 69
3.6. Exercises 70
References 71
4. Computing the OLS Regression Line 72
4.1. Introduction 72
4.2. Fitting the Ordinary Least Squares Regression Line 72
Reg.xls
4.3. Least Squares Formulas 82
Reg.xls
4.4. Fitting the Regression Line in Practice 84
Reg.xls
4.5. Conclusion 90
4.6. Exercises 90
References 91
Appendix: Deriving the Least Squares Formulas 91
5. Interpreting OLS Regression 95
5.1. Introduction 95
5.2. Regression as Double Compression 95
DoubleCompression.xls
EastNorthCentralFTWorkers.xls
5.3. Galton and Two Regression Lines 104
TwoRegressionLines.xls
5.4. Properties of the Sample Average and the Regression Line 107
OLSFormula.xls
5.5. Residuals and the Root-Mean-Square Error 114
ResidualPlot.xls
RMSE.xls
5.6. R-Squared (R2) 122
RSquared.xls
5.7. Limitations of Data Description with Regression 126
Anscombe.xls
IMRGDPReg.xlsSameRegLineDifferentData.xls
HourlyEarnings.xls
5.8. Conclusion 135
5.9. Exercises 135
References 136
Appendix: Proof that the Sample Average is a Least Squares
Estimator 136
6. Functional Form of the Regression 138
6.1. Introduction 138
6.2. Understanding Functional Form via an Econometric Fable 139
Galileo.xls
6.3. Exploring Two Other Functional Forms 144
IMRGDPFunForm.xls
6.4. The Earnings Function 148
SemiLogEarningsFn.xls
6.5. Elasticity 155
6.6. Conclusion 159
6.7. Exercises 160
References 160
Appendix: A Catalog of Functional Forms 161
FuncFormCatalog.xls
7. Multiple Regression 164
7.1. Introduction 164
7.2. Introducing Multiple Regression 165
MultiReg.xls
7.3. Improving Description via Multiple Regression 174
MultiReg.xls
7.4. Multicollinearity 184
Multicollinearity.xls
7.5. Conclusion 191
7.6. Exercises 192
References 194
Appendix: The Multivariate Least Squares Formula and the
Omitted Variable Rule 194
8. Dummy Variables 198
8.1. Introduction 198
8.2. Defining and Using Dummy Variables 199
Female.xls
8.3. Properties of Dummy Variables 202
Female.xls8.4. Dummy Variables as Intercept Shifters 205
Female.xls
8.5. Dummy Variable Interaction Terms 208
Female.xls
8.6. Conclusion 211
8.7. Exercises 212
References 212
PART 2. INFERENCE
9. Monte Carlo Simulation 215
9.1. Introduction 215
9.2. Random Number Generation Theory 216
RNGTheory.xls
9.3. Random Number Generation in Practice 220
RNGPractice.xls
9.4. Monte Carlo Simulation: An Example 225
MonteCarlo.xls
9.5. The Monte Carlo Simulation Add-In 232
MonteCarlo.xls
MCSim.xla (Excel add-in)
MCSimSolver.xla (Excel add-in)
9.6. Conclusion 235
9.7. Exercises 236
References 236
10. Review of Statistical Inference 238
10.1. Introduction 238
10.2. Introducing Box Models for Chance Processes 239
10.3. The Coin-Flip Box Model 242
BoxModel.xls
10.4. The Polling Box Model 251
PresidentialHeights.xls
10.5. Hypothesis Testing 257
PValue.xla (Excel add-in)
10.6. Consistent Estimators 262
Consistency.xls
10.7. The Algebra of Expectations 265
AlgebraofExpectations.xls
10.8. Conclusion 277
10.9. Exercises 277
References 278
Appendix: The Normal Approximation

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