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Using_R_for_Introductory_Econometrics_Wooldridge.pdf

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    Using R for Introductory metrics 。 。 Ee n Florian Heiss
    Using R for Introductory FlorianHeiss 2016. All rights Econome位ics 。 reserved Companion website: http: I /www. URfIE. net Address UniversitatsstraBe 1, Geb. 24.31.01.24 40225 Diisseldorf, Germany ISBN: 978 1523285136 ISBN 10: 1523285133
    37 Distributions 1.5.2. Continuous Histogram 1.5.3. Empirical tribution and Density Cumulative Dis 细 Function (ECDF) 川训 4 4 6 Distributions 1.5.4. Fundamental Statistics Distributions 1.6. Probability 1.6 1. Discrete 1.6.2. Continuous 1.6.3. Cumulative Distributions Distribution Function (CDF) 44 1.6.4. Random Draws from Prob­ ability Distributions 45 1.7. Con且denceIntervals and Statisti­ cal Inference 1.71. Con且denceIntervals 1.7.2. t Tests 1.7 3. p Values 1.7.4. Automatic calculations Execution 1.8 1. Conditional 1.8.2. Loops 1.8.3. Functions 1.8.4 Outlook 1.9. Monte Carlo Simulation of 1.91. Finite Sample Properties Estimators 58 A噎 A哑 EJ EJ EJ ZJ EJ EJ EJ EJ P3 7 7 0 1 2 6 6 6 7 7 8 1 1.8. Advanced R ntents c。 Preface 1. lntr 。 1.1. Getting n 。 ducti Started 3 3 3 1.1.1. So仕ware 4 1.1.2. R Scripts 7 1.1.3. Packages 1.1.4. File names and the Work OO QJ and Warnings QJ AU 1.1.5. Errors 1.1.6. 0出erResources ing Directory 1.2. Objects in R 1.2.1. Basic Calculations and Ob jects 1.2.2. Vectors 1.2.3. Special 1.2.4. Naming and Indexing 1.2.5. Matrices 1.2.6. 10 12 Types of Vectors 14 15 16 19 1.3. Data Frames and Data Files 20 20 21 22 1.3.1. Data Frames 1.3.2. Subsets of Data 1.3.3. R Data Files 1.3.4. Basic Information Lists on a Data Set 22 Vectors 1.3.5. lmport and Export of Text 1.3.6. Files lmport and Export of Other Data Formats 1.9.2. Asymptotic Properties of Estimators 61 1.9.3. Simulation of Con且dence Intervals and t Tests 64 23 I. Reg『essionAnalysis with C『·oss- Sectional Data 67 69 69 24 25 2 1.3.7. Data Sets in出eExamples 26 2.1. Simple OLS Regression 26 2.2. Coe他cients, eSimple Reg阻挡i ”、 del 1.4. Graphics n M 。 。 1.4.1. Basic Graphs 1.4.2. Customizing Graphs with Options Several 1.4.3. Overlaying 1.4.4. Legends 1.4.5. Expo国ngto a File Graphs 1.4.6. Statistics Advanced 1.5. Descriptive 1.5.1. Discrete quencies Tables 纽 约 Plots m m m Pre­ u Distributions: and Contingency 34 Residuals of Fit 2.3. Goodness 2.4. Nonlinearities 2.5. Regression Fitted Values, and 凡 响川 ” 仕uoughthe Origin and on a Constant Values， 飞1ariances, and Errors m但 UH 2.7. Monte Carlo Simulations UH wm 2.6. Expected Standard Regression One sample 2.7.1. 2.7.2. Many Samples 80
    2.7.3. 2.7.4. Violation Violation of SLR.4 of SLR.5 89 7. Multiple 89 itative Regress。『s Regression Analysis with Qual- 135 7.1. Linear Regression wi出Dummy as Regressors Variables tN 明J n 3. Multiple Regression Analysis: Estima- 91 in Practice 91 95 7.2. Logical 7.3. Factor 7.4. Breaking Variables variables 4. Multiple 4.1. The t Test , and and VIF Categories Regression 3.4. Standard lnterpretation mm a Numeric Variable lnto 97 7.5. lnteractions 3.1. Multiple ”。 3.2. OLS in Matrix Form Paribus 3.3. Ceteris Bias Variable Omitted Errors, Multicollinearity 139 and Differences Across Groups 141 99 8. Heteroscedasticity 143 143 03 Tests 147 103 Least Squares 150 4.1.1. General Setup 103 4.1.2. Standard case . 104 9. M 4.1.3. 0出erhypotheses 106 9.1. Functional 8.1. Heteroscedasti口ty-Robust 8.2. Heteroscedasti口ty 8.3. Weighted Form h咀sspeci且cation E国ssionFunctions lnferencel 4.2. Confidence 4.3. Linear Restrictions: 4.4. Reporting Regression lntervals 108 9.2. Measurement Error nSpecttication and Data Issues 155 155 157 F -Tests 109 9.3. Missing Data and Nonrandom 160 163 Results 113 Samples Observations lnference Analysis: Reg『ession in Re- re 。 。 9.4. Outlying 9.5. Least Absolute Deviations (LAD) Estimation 164 5. Multiple Reg阻挡i n Analysis: OLS 。 Asymptotlcs 5.1. Simulation 115 Exercises 115 Distributed Error 5.1.1. Normally Terms . 115 II. Re�『ession Analysis with Time 5.1.2. Non-Normal Error Terms 116 Series Data 5.1.3. (Not) Conditioning on由e Regressors 119 10. Basic Regre剧。nAnalysis with Time Se- 165 5.2. LM Test 121 rles Oatα 10.3. Other τ＂irne Series 10.1. Static古me 10.2. Time Series 10.2.1. 10.2.2. Time Series Series Data Types in R Equispa四dTime Series lrregular 167 Models 167 168 in R 168 in R 170 Models 173 The dynlm Package 173 Finite Distributed Models Trends Seasonality 173 176 177 Lag 10.3.1. 10.3.2. 10.3.3. 10.3.4. 6. Multlple Regre剧。nAnalysls: Fu叶herls- sues 6.1. Model Formulae Operations 6.1.1. Data Scaling: 123 123 An出emetic Within a Formula 123 6.1.2. Standardization: 125 6.1.3. Logarithms 126 6.1.4. Quadratics 126 6.1.5. lnteraction 自cients Beta C四ι 6.2. Prediction 6.2.1. Con且dencelntervals for and Polynomials Terms 128 11. Fu付he『IssuesIn Using OLS with Time Se- 130 rles Oatα 11.1. Asymptotics 179 with Time Series 179 Predictions 130 11.2. The Nature of Highly Persistent 6.2.2. Prediction 6.2.3. Effect lntervals 132 Time Series Plots for Nonlinear 11.3. Differences of Highly Persistent Speci自cations 133 Time Series 182 185
    11.4. Regression with First Differences 186 17 Limited Dependent Venable M dels 。 Probability Models 17.1.1. 17.1.2. 。ndSan、pleSelecti。n c。，recti。ns 235 17.1. Binary Responses 235 235 肉。A哇 Linear Logit and Probit Models Estimation 17 1.3. Inference 17.1.4. 17.1.5. Predictions Partial 7 0 1 A哇 242 Effects 句，＆ 句，＆ 句，＆ 17.2. Count Data: τ"he Poisson Regres 12 Serlal c。rrelatl。n and Heter，。seedas- In Time Series Reg阻挡l ns tlclty 12.1. T，四tingfor Serial 。 187 Correlation 187 191 of仕回 12.2. FGLS Estimation 12.3. Serial Correlation Robust Infer Error Term ence wi出OLS 12.4. Autoregressive Conditional Het eroscedastic均 192 193 Ill. Advanced Topics 195 17.3. Corner Solution Responses: The sionModel Tobit Model 245 248 17.4. Censored and Truncated Regres- sion Models 251 Corrections 253 17.5. Sample Selection 197 18. Advanced Time Serles T 13.P。ollngCross-Secti。nsAcross Time 。 ds Slmple Panel Data Meth 255 13.1. Pooled Cross Sections 197 18.1. lnfinite Distributed Lag Models 255 13.2. Difference 257 13.3. Organizing Regression 260 13.4. Panel spec1且ccomputations 202 18.4. Cointegration 13.5. First Differenced in Differences 198 18.2. Testing for Unit Roots Panel Data 201 18.3. Spurious Estimator 204 and Error Correc- tion Models pies 。 14.Advanced Panel Data Meth。ds Effects Estimation 14.1. Fixed 14.2. Random Effects Models 14.3. Dummy Variable Regression and Correlated Random E旺ects 14.4. Robust (Clustered) Standard Errors 216 15.lnst阳mental Varlables Estlmati。nand Tw StageLeast Squares 15.1. Instrumental Variables in Simple 219 。 Regression Models 15.2. More Exogenous Regressors 15.3. Two Stage Least Squares 15.4. 1日estingfor Exogeneity of the Re- 262 263 18.5. For配asting 207 207 19.Carrylng 209 19.1. Working 19.2. Logging 212 19.3. Formatted Out an Empirical Pr，。，Ject267 m出 RScripts 267 Output in Text Files 269 Documents and Re- ，。 ，。7 Features ports Wl出RMarkdown 19 .3.1. Basics 19.3.2. 19 .3.3. Bottom Line Advanced 句，－ 吨，＆ 句，＆ 句，＆ 鸣，＆ 句，＆ oy oy nU 7 7 A哇 19.4. Combining R with LaTeX 219 221 222 19.4.1. Document Gen­ using Sweave and Automatic eration knitr Separating 19.4.2. 274 Rand 也可＇.｝＇. code 278 gressors 15.5. Testing 15.6. Instrumental Overidentifyi Variables 224 ng Restriction s 225 IV. Appendices 225 R Scripts with Panel Data 16.Slmultane。usEquatl。nsM。dels 16.1. Setup and Notation 16.2. Estimation 16.3. Joint Estimation 16.4. Outlook: Estimation of System by 3SLS by 2SLS 1. Scripts Used in Chapter 229 2. Scripts Used in Chapter 229 3. Scripts Used in Chapter 23口 4. Scripts Used in Chapter 231 Scripts Used in Chapter Scrip恒Usedin Chapter 233 01 02 03 04 05 06 281 00 3 2 3 2 00 3 2 QJ 9 2 QJ 1 3 AU 3 3 AU 5 3 AU
    7. Scripts Used in Chapter 8. Scripts Used in Chapter 9. Scripts Used in Chapter 10 Scrip国U目din Chapter 11. Scripts Used in Chapter 12. Scripts Used in Chapter 13. Scripts Used in Chapter 14. Scripts Used in Chapter 15. Scripts Used in Chapter 16 Scripts Used in Chapter 17. Scripts Used in Chapter 18. Scripts Used in Chapter 19 Scripts Used in Chapter O 7 • • 30 7 08 09 10 11 12 13 14 15 16 17 18 19 309 311 314 316 318 320 322 324 326 326 330 333 Bibll graphy 。 335 List of w ldridge(2016) examples 337 。。 Index 339
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