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Introductory econometrics : using Monte Carlo simulation with Microsoft Excel / Humberto Barreto, Frank M. Howland.

By: Barreto, Humberto.
Contributor(s): Howland, Frank M.
Material type: TextTextPublisher: Cambridge ; New York : Cambridge University Press, 2006Description: xxiii, 774 p. : ill. ; 26 cm.ISBN: 9780521843195; 0521843197.Subject(s): Econometrics | Monte Carlo method -- Data processingDDC classification: 330.01518282 Online resources: Worldcat details | Ebook Fulltext
Contents:
1. Introduction; Part I. Description: 2. Correlation; 3. Pivot tables; 4. Computing regression; 5. Interpreting regression; 6. Functional form; 7. Multivariate regression; 8. Dummy variables; Part II. Inference: 9. Monte Carlo simulation; 10. Inferential statistics review; 11. Measurement box model; 12. Comparing two populations; 13. The classical econometric model; 14. The Gauss Markov theorem; 15. Understanding the standard error; 16. Hypothesis testing and confidence intervals; 17. F tests; 18. Omitted variable bias; 19. Heteroskedasticity; 20. Autocorrelation; 21. The series topics; 22. Dummy dependent variables; 23. Bootstrap; 24. Simultaneous equations. Table of contents
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Non-fiction 330.01518282 BAI 2006 (Browse shelf) C-1 Not For Loan 19627
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330.0151 MAT 2011 Mathematics for economics / 330.0151 MOQ 2000 Quantitative methods for business and economics / 330.01515642 CAF 2005 Foundations of dynamic economic analysis : 330.01518282 BAI 2006 Introductory econometrics : 330.015193 VEE 2003 Economics and the theory of games / 330.015195 ADD 2003 Dynamic economics : 330.015195 ANM 2009 Mostly harmless econometrics :

Includes bibliographical references and index.

1. Introduction; Part I. Description: 2. Correlation; 3. Pivot tables; 4. Computing regression; 5. Interpreting regression; 6. Functional form; 7. Multivariate regression; 8. Dummy variables; Part II. Inference: 9. Monte Carlo simulation; 10. Inferential statistics review; 11. Measurement box model; 12. Comparing two populations; 13. The classical econometric model; 14. The Gauss Markov theorem; 15. Understanding the standard error; 16. Hypothesis testing and confidence intervals; 17. F tests; 18. Omitted variable bias; 19. Heteroskedasticity; 20. Autocorrelation; 21. The series topics; 22. Dummy dependent variables; 23. Bootstrap; 24. Simultaneous equations. Table of contents

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