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Applied Econometrics

A Practical Guide

Medium: Buch
ISBN: 978-0-367-11033-8
Verlag: Routledge
Erscheinungstermin: 26.02.2019
Lieferfrist: bis zu 10 Tage

Applied Econometrics: A Practical Guide is an extremely user-friendly and application-focused book on econometrics. Unlike many econometrics textbooks which are heavily theoretical on abstractions, this book is perfect for beginners and promises simplicity and practicality to the understanding of econometric models. Written in an easy-to-read manner, the book begins with hypothesis testing and moves forth to simple and multiple regression models. It also includes advanced topics:

- Endogeneity and Two-stage Least Squares

- Simultaneous Equations Models

- Panel Data Models

- Qualitative and Limited Dependent Variable Models

- Vector Autoregressive (VAR) Models

- Autocorrelation and ARCH/GARCH Models

- Unit Root and Cointegration

The book also illustrates the use of computer software (EViews, SAS and R) for economic estimating and modeling. Its practical applications make the book an instrumental, go-to guide for solid foundation in the fundamentals of econometrics. In addition, this book includes excerpts from relevant articles published in top-tier academic journals. This integration of published articles helps the readers to understand how econometric models are applied to real-world use cases.


Produkteigenschaften


  • Artikelnummer: 9780367110338
  • Medium: Buch
  • ISBN: 978-0-367-11033-8
  • Verlag: Routledge
  • Erscheinungstermin: 26.02.2019
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2019
  • Serie: Routledge Advanced Texts in Economics and Finance
  • Produktform: Kartoniert
  • Gewicht: 562 g
  • Seiten: 312
  • Format (B x H x T): 174 x 246 x 17 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

1. Review of Estimation and Hypothesis Tests 2. Simple Linear Regression Models 3. Multiple Linear Regression Models 4. Dummy Explanatory Variables 5. More on Multiple Regression Analysis 6. Endogeneity and Two-Stage Least Squares Estimation 7. Models for Panel Data 8. Simultaneous Equations Models 9. Vector Autoregressive (VAR) Models 10. Autocorrelation and ARCH/GARCH 11. Unit Root, Cointegration and Error Correction Model 12. Qualitative and Limited Dependent Variable Models