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A Guide to Econometrics, 6th Edition



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This is the perfect (and essential) supplement for all econometrics classes--from a rigorous first undergraduate course, to a first master's, to a PhD course. Explains what is going on in textbooks full of proofs and formulas Offers intuition, skepticism, insights, humor, and practical advice (do's and don'ts) Contains new chapters that cover instrumental variables and computational considerations Includes additional information on GMM, nonparametrics, and an introduction to wavelets

Author Biography

Peter Kennedy is Professor of Economics at Simon Fraser University. In addition to A Guide to Econometrics, he is author of Macroeconomic Essentials: Understanding Economics in the News, 2e (2000), and is Associate Editor of the International Journal of Forecasting, the Journal of Economic Education, and Economics Bulletin.

Table of Contents

Prefacep. x
Dedicationp. xii
Introductionp. 1
What is Econometrics?p. 1
The Disturbance Termp. 2
Estimates and Estimatorsp. 4
Good and Preferred Estimatorsp. 5
General Notesp. 6
Technical Notesp. 10
Criteria for Estimatorsp. 11
Introductionp. 11
Computational Costp. 11
Least Squaresp. 12
Highest R[superscript 2]p. 13
Unbiasednessp. 14
Efficiencyp. 16
Mean Square Errorp. 17
Asymptotic Propertiesp. 18
Maximum Likelihoodp. 21
Monte Carlo Studiesp. 22
Adding Upp. 25
General Notesp. 26
Technical Notesp. 32
The Classical Linear Regression Modelp. 40
Textbooks as Catalogsp. 40
The Five Assumptionsp. 41
The OLS Estimator in the CLR Modelp. 43
General Notesp. 44
Technical Notesp. 47
Interval Estimation and Hypothesis Testingp. 51
Introductionp. 51
Testing a Single Hypothesis: the t Testp. 51
Testing a Joint Hypothesis: the F Testp. 52
Interval Estimation for a Parameter Vectorp. 54
LR, W, and LM Statisticsp. 56
Bootstrappingp. 58
General Notesp. 59
Technical Notesp. 67
Specificationp. 71
Introductionp. 71
Three Methodologiesp. 72
General Principles for Specificationp. 75
Misspecification Tests/Diagnosticsp. 76
R[superscript 2] Againp. 79
General Notesp. 81
Technical Notesp. 89
Violating Assumption One: Wrong Regressors, Nonlinearities, and Parameter Inconstancyp. 93
Introductionp. 93
Incorrect Set of Independent Variablesp. 93
Nonlinearityp. 95
Changing Parameter Valuesp. 97
General Notesp. 100
Technical Notesp. 106
Violating Assumption Two: Nonzero Expected Disturbancep. 109
General Notesp. 111
Violating Assumption Three: Nonspherical Disturbancesp. 112
Introductionp. 112
Consequences of Violationp. 113
Heteroskedasticityp. 115
Autocorrelated Disturbancesp. 118
Generalized Method of Momentsp. 122
General Notesp. 123
Technical Notesp. 129
Violating Assumption Four: Instrumental Variable Estimationp. 137
Introductionp. 137
The IV Estimatorp. 141
IV Issuesp. 144
General Notesp. 146
Technical Notesp. 151
Violating Assumption Four: Measurement Errors and Autoregressionp. 157
Errors in Variablesp. 157
Autoregressionp. 160
General Notesp. 163
Technical Notesp. 167
Violating Assumption Four: Simultaneous Equationsp. 171
Introductionp. 171
Identificationp. 173
Single-Equation Methodsp. 176
Systems Methodsp. 180
General Notesp. 181
Technical Notesp. 186
Violating Assumption Five: Multicollinearityp. 192
Introductionp. 192
Consequencesp. 193
Detecting Multicollinearityp. 194
What To Dop. 196
General Notesp. 198
Technical Notesp. 202
Incorporating Extraneous Informationp. 203
Introductionp. 203
Exact Restrictionsp. 203
Stochastic Restrictionsp. 204
Pre-Test Estimatorsp. 204
Extraneous Information and MSEp. 206
General Notesp. 207
Technical Notesp. 211
The Bayesian Approachp. 213
Introductionp. 213
What is a Bayesian Analysis?p. 213
Advantages of the Bayesian Approachp. 216
Overcoming Practitioners' Complaintsp. 217
General Notesp. 220
Technical Notesp. 226
Dummy Variablesp. 232
Introductionp. 232
Interpretationp. 233
Adding Another Qualitative Variablep. 234
Interacting with Quantitative Variablesp. 235
Observation-Specific Dummiesp. 236
General Notesp. 237
Technical Notesp. 240
Qualitative Dependent Variablesp. 241
Dichotomous Dependent Variablesp. 241
Polychotomous Dependent Variablesp. 244
Ordered Logit/Probitp. 245
Count Datap. 246
General Notesp. 246
Technical Notesp. 254
Limited Dependent Variablesp. 262
Introductionp. 262
The Tobit Modelp. 263
Sample Selectionp. 265
Duration Modelsp. 267
General Notesp. 269
Technical Notesp. 273
Panel Datap. 281
Introductionp. 281
Allowing for Different Interceptsp. 282
Fixed Versus Random Effectsp. 284
Short Run Versus Long Runp. 286
Long, Narrow Panelsp. 287
General Notesp. 288
Technical Notesp. 292
Time Series Econometricsp. 296
Introductionp. 296
ARIMA Modelsp. 297
VARsp. 298
Error Correction Modelsp. 299
Testing for Unit Rootsp. 301
Cointegrationp. 302
General Notesp. 304
Technical Notesp. 314
Forecastingp. 331
Introductionp. 331
Causal Forecasting/Econometric Modelsp. 332
Time Series Analysisp. 333
Forecasting Accuracyp. 334
General Notesp. 335
Technical Notesp. 342
Robust Estimationp. 345
Introductionp. 345
Outliers and Influential Observationsp. 346
Guarding Against Influential Observationsp. 347
Artificial Neural Networksp. 349
Nonparametric Estimationp. 350
General Notesp. 352
Technical Notesp. 356
Applied Econometricsp. 361
Introductionp. 361
The Ten Commandments of Applied Econometricsp. 362
Getting the Wrong Signp. 368
Common Mistakesp. 372
What do Practitioners Need to Know?p. 373
General Notesp. 374
Technical Notesp. 383
Computational Considerationsp. 385
Introductionp. 385
Optimizing via a Computer Searchp. 386
Estimating Integrals via Simulationp. 388
Drawing Observations from Awkward Distributionsp. 390
General Notesp. 392
Technical Notesp. 397
Sampling Distributions, The Foundation of Statisticsp. 403
All About Variancep. 407
A Primer on Asymptoticsp. 412
Exercisesp. 417
Answers to Even-Numbered Questionsp. 479
Glossaryp. 503
Bibliographyp. 511
Name Indexp. 563
Subject Indexp. 573
Table of Contents provided by Ingram. All Rights Reserved.

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