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Using Python for Introductory Econometrics - Paperback
Using Python for Introductory Econometrics - Paperback
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by Daniel Brunner (Author), Florian Heiss (Author)
- 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
Number of Pages: 430
Dimensions: 0.87 x 10 x 8 IN
Publication Date: May 25, 2020
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