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Python Code for UTexas econometrics

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Solutions and code for Econometrics

Solutions for textbook exercises, notes, and code some of which are from weekly TA sessions for first year Ph.D. econometrics at the University of Texas at Austin. The exercises solved and corresponding textbooks are listed by week.

Datasets

The data folder contains miscellaneous data sets from various econometrics textbooks.

Notebooks

  • panel_ols.ipynb Notes on the within transformation in Python to estimate fixed effects regression. Code included to perform the transformation. For a more complete fixed effects package see this repo.
  • pre-trends.ipynb Notes on pre-trend plots in Python for differences and differences with average treatment effect on the treated interpretation of differences in differences (Work in progress).

Section notes from Econometrics I at UT Austin

Probability Theory

Textbook: Introduction to Econometrics by Bruce Hansen

Week 1: Exercises 1.1, 1.2, 1.6, 1.8, 1.10, 1.11, 1.17, 1.22

Week 2: Exercises 1.5, 1.12, 1.14, 1.19, 1.21, 2.1, 2.8, 2.13, 3.1

Week 3: Exercises 2.2, 2.6, 2.11, 2.14, 3.2,3.3

Week 4: Exercises 3.6, 3.11, 4.1, 4.6, 4.7, 4.8, 4.9, 4.14, 4.15

Estimation and Inference with Regression models

Textbook: Econometrics by Bruce Hansen

Week 6: Exercises 2.4, 2.5, 2.14, 3.10, 3.22

Week 7: Exercises 2.16, 2.21, 3.4, 3.11, 3.19, 3.23

Week 8: Exercises 4.1, 4.7, 4.23, 7.9, 7.14

Week 9: Exercises 4.7, 4.20, 7.11, 7.20, 7.28

Week 10: Exercises 8.2, 8.3, 9.1, 9.2, 9.4

Week 11: Exercises 8.19, 8.22, 9.7, 9.8, 9.17, 9.20, 12.3, 12.8

Week 12: Exercises 12.7, 13.13

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Python Code for UTexas econometrics

License:MIT License


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