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Econometrics : a modern introduction / Michael Murray.

By: Material type: TextTextSeries: The Addison-Wesley series in economicsPublisher: Boston : Pearson Addison Wesley, [2006]Description: xxxvi, 929 pages ; illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0321113616 (alk. paper)
Subject(s): DDC classification:
  • 330.015195 22 M.M.E.
Online resources:
Contents:
Part I - The Linear Regression Model 1. What is Econometrics? 2. Choosing Estimators: Intuition and Monte Carlo Methods 3. Linear Estimators and the Gauss-Markov Theorem 4. Blue Estimators for the Slope and Intercept of a Straight Line 5. Residuals 6. Multiple Regression Part II - Specification and Hypothesis Testing 7. Testing Single Hypotheses in Regression Models 8. Superfluous and Omitted Variables, Multicollinearity and Binary Variables 9. Testing Multiple Hypotheses Part III - Further Topics in Regression 10. Heteroskedastic Disturbances 11. Autoregressive Disturbances 12. Large Sample Properties Of Estimators: Consistency and Asymptotic Efficiency 13. Instrumental Variables Estimation 14. Systems of Equations 15. Randomized Experiments and Natural Experiments 16. Analyzing Panel Data 17. Forecasting 18. Stochastically Trending Variables 19. Logit and Probit Models: Truncated and Censored Samples Statistical Appendix WEB
Summary: Econometrics: A Modern Introduction conditions students to think like econometricians right from the start by opening with a unique Monte Carlo exercise, and connects econometrics to economic theory through a series of exemplary econometric analyses presented throughout the text.
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Item type Current library Collection Call number Status Date due Barcode
Books Books Main library A4 Faculty of Economics & Political (Political) 330.015195 M.M.E. (Browse shelf(Opens below)) Available 00000960

Includes bibliographical references and index.

Part I - The Linear Regression Model 1. What is Econometrics? 2. Choosing Estimators: Intuition and Monte Carlo Methods 3. Linear Estimators and the Gauss-Markov Theorem 4. Blue Estimators for the Slope and Intercept of a Straight Line 5. Residuals 6. Multiple Regression Part II - Specification and Hypothesis Testing 7. Testing Single Hypotheses in Regression Models 8. Superfluous and Omitted Variables, Multicollinearity and Binary Variables 9. Testing Multiple Hypotheses Part III - Further Topics in Regression 10. Heteroskedastic Disturbances 11. Autoregressive Disturbances 12. Large Sample Properties Of Estimators: Consistency and Asymptotic Efficiency 13. Instrumental Variables Estimation 14. Systems of Equations 15. Randomized Experiments and Natural Experiments 16. Analyzing Panel Data 17. Forecasting 18. Stochastically Trending Variables 19. Logit and Probit Models: Truncated and Censored Samples Statistical Appendix WEB

Econometrics: A Modern Introduction conditions students to think like econometricians right from the start by opening with a unique Monte Carlo exercise, and connects econometrics to economic theory through a series of exemplary econometric analyses presented throughout the text.

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