Using Monte Carlo Simulation with Microsoft Excel [With CDROM]
Buch, Englisch, 798 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1671 g
ISBN: 978-0-521-84319-5
Verlag: Cambridge University Press
This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
Weitere Infos & Material
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.




