Introductory Econometrics with Applications

Name: Introductory Econometrics with Applications
Price: 3.99 USD
Availability: InStock
ISBN: 9780030341861

ISBN-10: 0030341868

ISBN-13: 9780030341861

Edition: 5th 2002

Authors: Ramu Ramanathan

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Description:

Offers an ideal combination of econometric theory and hands-on practical training for undergraduate and graduate courses. The authors ambition is to provide realistic applications without sacrificing theoretical underpinnings. He uses a logical step-by-step approach to walk readers through numerous real-world examples of model specification, estimation, and hypothesis testing. The book also succeeds at being self-contained. By including background information on mathematics, probability, statistics, and software applications, readers have all the information they need in one place.

Book details

Edition: 5th
Copyright year: 2002
Publisher: Harcourt College Publishers
Binding: Hardcover
Weight: 3.124
Language: English

Background	p. 1
Introduction	p. 1
What Is Econometrics?	p. 2
Basic Ingredients of an Empirical Study	p. 4
Empirical Project	p. 13
Summary	p. 14
Key Terms	p. 15
Exercises	p. 15
Review of Probability and Statistics	p. 16
Random Variables and Probability Distributions	p. 16
Mathematical Expectation, Mean, and Variance	p. 20
Joint Probabilities, Covariance, and Correlation	p. 26
Random Sampling and Sampling Distributions	p. 35
Procedures for the Estimation of Parameters	p. 38
Properties of Estimators	p. 42
The Chi-square, t-and F-distributions	p. 47
Testing Hypotheses	p. 50
Interval Estimation	p. 56
Key Terms	p. 58
References	p. 59
Exercises	p. 60
Miscellaneous Derivations	p. 63
Certain Useful Results on Summations	p. 63
Maximization and Minimization	p. 64
More on Estimation	p. 71
Basics	p. 75
The Simple Linear Regression Model	p. 76
The Basic Model	p. 76
Estimation of the Basic Model by the Method of Ordinary Least Squares (OLS)	p. 80
Properties of Estimators	p. 85
The Precision of the Estimators and the Goodness of Fit	p. 91
Tests of Hypotheses	p. 95
Scaling and Units of Measurement	p. 105
Application: Estimating an Engel Curve Relation between Expenditure on Health Care and Income	p. 106
Confidence Intervals	p. 110
Forecasting	p. 110
Causality in a Regression Model	p. 113
Application: Relation between Patents and the Expenditures on Research and Development (RandD)	p. 116
Summary	p. 119
Key Terms	p. 121
References	p. 122
Exercises	p. 122
Miscellaneous Derivations	p. 133
Three-Dimensional Representation of the Simple Linear Model	p. 133
More Results on Summations	p. 133
Derivation of the Normal Equations by Least Squares	p. 135
Best Linear Unbiased Estimator (BLUE) and the Gauss-Markov Theorem	p. 135
Maximum Likelihood Estimation	p. 137
Derivation of the Variances of the Estimators	p. 138
Unbiased Estimator of the Variance of the Error Term	p. 139
Derivation of Equation 3.26	p. 140
Derivation of Equation 3.27a	p. 140
Proof That r[superscript 2 subscript xy]=R[superscript 2] for a Simple Regression Model	p. 141
Derivation of Equation 3.29	p. 142
Derivation of Equation 3.30	p. 143
Multiple Regression Models	p. 144
Normal Equations	p. 145
Goodness of Fit	p. 148
General Criteria for Model Selection	p. 151
Testing Hypotheses	p. 153
Specification Errors	p. 165
Application: The Determinants of the Number of Bus Travelers	p. 171
Application: Women's Labor Force Participation	p. 177
Empirical Example: Net Migration Rates and the Quality of Life	p. 183
Empirical Project	p. 185
Summary	p. 185
Key Terms	p. 187
References	p. 187
Exercises	p. 188
Miscellaneous Derivations	p. 205
The Three-Variable Regression Model	p. 205
Bias Due to the Omission of a Relevant Variable	p. 206
Proof of Property 4.4	p. 208
Multicollinearity	p. 210
Examples of Multicollinearity	p. 210
Exact Multicollinearity	p. 213
Near Multicollinearity	p. 214
Applications	p. 220
Summary	p. 225
Key Terms	p. 226
References	p. 226
Exercises	p. 227
Derivation of Equations (5.4) through (5.6)	p. 229
Extensions	p. 231
Choosing Functional Forms and Testing for Model Specification	p. 232
Review of Exponential and Logarithmic Functions	p. 232
Linear-Log Relationship	p. 235
Reciprocal Transformation	p. 238
Polynomial Curve-Fitting	p. 238
Interaction Terms	p. 241
Lags in Behavior (Dynamic Models)	p. 243
Application: Relation between Patents and RandD Expenses Revisited	p. 244
Log-Linear Relationship (or Semilog Model)	p. 250
Comparison of R[superscript 2] Values between Models	p. 254
The Double-Log (or Log-Log) Model	p. 255
Application: Estimating Elasticities of Bus Travel	p. 257
Miscellaneous Other Models	p. 258
The Hendry/LSE Approach of Modeling from "General to Simple"	p. 261
"Simple to General" Modeling Using the Lagrange Multiplier Test	p. 262
Ramsey's RESET Procedure for Regression Specification Error	p. 270
Summary	p. 271
Key Terms	p. 272
References	p. 272
Exercises	p. 274
More Details on LR, Wald, and LM Tests	p. 284
Likelihood Ratio Test	p. 284
The Wald Test	p. 286
The Lagrange Multiplier Test	p. 287
Qualitative (or Dummy) Independent Variables	p. 290
Qualitative Variables with Two Categories Only	p. 290
Qualitative Variable with Many Categories	p. 298
The Effect of Qualitative Variables on the Slope Term (Analysis of Covariance)	p. 302
Application: Covariance Analysis of the Wage Model	p. 305
Estimating Seasonal Effects	p. 312
Testing for Structural Change	p. 314
Empirical Example: Motor Carrier Deregulation	p. 320
Application: The Demand for a Sealant Used in Construction	p. 320
Empirical Project	p. 324
Summary	p. 325
Key Terms	p. 325
References	p. 325
Exercises	p. 326
Some Special Issues with Cross-Section and Time Series Data	p. 343
Heteroscedasticity	p. 344
Consequences of Ignoring Heteroscedasticity	p. 346
Testing for Heteroscedasticity	p. 347
Estimation Procedures	p. 355
Application: A Model of the Expenditure on Health Care in the United States	p. 363
Empirical Project	p. 365
Summary	p. 366
Key Terms	p. 367
References	p. 367
Exercises	p. 368
Properties of OLS Estimators in the Presence of Heteroscedasticity	p. 378
Serial Correlation	p. 380
Serial Correlation of the First Order	p. 382
Consequences of Ignoring Serial Correlation	p. 383
Testing for First-Order Serial Correlation	p. 386
Treatment of Serial Correlation	p. 389
Higher-Order Serial Correlation	p. 398
Engle's ARCH Test	p. 401
Application: Demand for Electricity	p. 406
Summary	p. 416
Key Terms	p. 417
References	p. 417
Exercises	p. 419
Miscellaneous Derivations	p. 431
Proof That the DW d is Approximately 2(1-[rho])	p. 431
Properties of u[subscript t] When It Is AR(1)	p. 431
Treatment of the First Observation under AR(1)	p. 432
Distributed Lag Models	p. 434
Lagged Independent Variables	p. 434
Lagged Dependent Variables	p. 442
Lagged Dependent Variables and Serial Correlation	p. 446
Estimation of Models with Lagged Dependent Variables	p. 449
Application: A Dynamic Model of Consumption Expenditures in the United Kingdom	p. 453
Application: Hourly Electricity Load Model Revisited	p. 454
Unit Roots and the Dickey-Fuller Tests	p. 455
Error Correction Models (ECM)	p. 461
Application: An Error Correction Model of U.S. Defense Expenditures	p. 464
Cointegration	p. 472
Causality	p. 475
Pooling Cross-Sectional and Time Series Data (or Panel Data)	p. 478
Empirical Project	p. 481
Summary	p. 482
Key Terms	p. 484
References	p. 484
Exercises	p. 487
Special Topics	p. 493
Forecasting	p. 494
Fitted Values Ex-post, and Ex-ante Forecasts	p. 495
Evaluation of Models	p. 496
Conditional and Unconditional Forecasts	p. 497
Forecasting from Time Trends	p. 498
Combining Forecasts	p. 504
Forecasting from Econometric Models	p. 510
Forecasting from Time Series Models	p. 514
Summary	p. 524
Key Terms	p. 525
References	p. 526
Exercises	p. 527
Qualitative and Limited Dependent Variables	p. 528
Linear Probability (or Binary Choice) Models	p. 529
The Probit Model	p. 530
The Logit Model	p. 532
Limited Dependent Variables	p. 534
Summary	p. 538
Key Terms	p. 539
References	p. 539
Exercises	p. 539
Simultaneous Equation Models	p. 542
Structure and Reduced Forms of Simultaneous Equation Models	p. 542
Consequences of Ignoring Simultaneity	p. 544
The Identification Problem	p. 546
Estimation Procedures	p. 551
Empirical Example: Regulation in the Contact Lens Industry	p. 556
Application: A Simple Keynesian Model	p. 558
Summary	p. 561
Key Terms	p. 561
References	p. 562
Exercises	p. 562
Derivation of the Limits for OLS Estimates	p. 565
Practice	p. 567
Carrying Out an Empirical Project	p. 568
Selecting a Topic	p. 568
Review of Literature	p. 573
Formulating a General Model	p. 574
Collecting the Data	p. 574
Empirical Analysis	p. 579
Key Terms	p. 582
References	p. 583
Statistical Tables	p. 585
Answers to Selected Problems	p. 607
Practice Computer Sessions	p. 635
Descriptions of the Data and Practice Computer Sessions	p. 639
Copyrights and Acknowledgments	p. 675
Name Index	p. 677
Subject Index	p. 679
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