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Using Python for Introductory Econometrics

Using Python for Introductory Econometrics
Florian Heiss, "Using Python for Introductory Econometrics"
English | 2020 | ASIN: B08924H17Y | PDF | pages: 428 | 102.7 mb
- 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



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