Using Python for Introductory Econometrics
Language: English
Published by Independently Published, 2020
- Softcover
- New

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Softcover
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- Title
- Using Python for Introductory Econometrics
- Author
- Daniel Brunner, Florian Heiss
- Publisher
- Independently Published
- Publication year
- 2020
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798648436763
- Item weight
- 848 grams
- Introduces the popular, powerful and free programming language and software package Python
- Focus: implementation of standard tools and methods used in econometrics
- Compatible with "Introductory Econometrics" by Jeffrey M. Wooldridge in terms of topics, organization, terminology and notation
- Companion website with full text, all code for download and other goodies
Topics:
- A gentle introduction to Python
- Simple and multiple regression in matrix form and using black box routines
- Inference in small samples and asymptotics
- Monte Carlo simulations
- Heteroscedasticity
- Time series regression
- Pooled cross-sections and panel data
- Instrumental variables and two-stage least squares
- Simultaneous equation models
- Limited dependent variables: binary, count data, censoring, truncation, and sample selection
- Formatted reports using Jupyter Notebooks
"Synopsis" may belong to another edition of this title.
Rarewaves.com UK
London, United Kingdom
5-star seller
AbeBooks seller since June 11, 2025
Shipping rates from United Kingdom to U.S.A.
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|---|---|---|
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