https://github.com/v-mayya/programming-statistics-and-econometrics-resources

Programming, statistics and econometrics resources
https://github.com/v-mayya/programming-statistics-and-econometrics-resources

econometrics programming python r statistics

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Programming, statistics and econometrics resources

• Host: GitHub
• URL: https://github.com/v-mayya/programming-statistics-and-econometrics-resources
• Owner: V-Mayya
• Created: 2023-12-03T16:36:40.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-12-05T02:31:31.000Z (over 2 years ago)
• Last Synced: 2023-12-05T17:30:28.672Z (over 2 years ago)
• Topics: econometrics, programming, python, r, statistics
• Homepage:
• Size: 1.1 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# Programming, Statistics, and Econometrics Resources

--- 

```python

# 📌 Find

resources = ["Books", "Websites", "Other Repos", "Academic Papers"]

# 📌 on these 

topics = {"Programming": ["Python", "R"],

          "Statistics": ["Coming Soon!"],

          "Econometrics": ["OLS Regression Analysis & Time Series",

                           "Microeconometrics & Statistical Models",

                           "Applied Econometrics & Causal Inference",

                           "Computational Methods in Econometrics"],}  

```

Select the titles to go to the relevant sections.

### Resources 

  Programming  🧑‍💻 


 

 

## Contents

📌 **Python**

- [Fundamentals](#fundamentals_py)

- [Data analytics & Data Science](#data_py)

- [Machine Learning](#machine_py)

- [Algorithms & Data Structures](#algo_py)

- [Apps + Others](#apps_py)

 

📌 **R**

- [Fundamentals](#fundamentals_r)

- [Data analytics & Data Science](#data_r)

- [Machine Learning](#machine_r)

- [Algorithms & Data Structures](#algo_r)

- [Apps + Others](#apps_r)

(currently Python and R primarily)

  

## 🎯 Fundamentals  

> Python fundamentals: books, websites and other github repos

‣ Books 📚 

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

|  | |  | | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Python Cheatsheet | For quick reference, covering various topics (loops, functions, OOP and more). Based on 'Automate the Boring Stuff with Python' book and other sources. | [Link](https://www.pythoncheatsheet.org/) | Learn |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | ---- | --- |

| Full Speed Python | For self-learners with topics and exercises | [Link](https://github.com/joaoventura/full-speed-python) | Learn + Practice (exercises from the Superior School of Technology of Setúbal) |  

| Paragraph | Text | Link | Practice |

[Back to contents](#contents_prog)

  

## 🎯 Data analytics & Data Science 

> Python data analytics and data science resources: books, websites and other github repos

‣ Books 📚 

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| PandasAI | Combining data analysis with AI and making the process conversational! | [Link](https://docs.pandas-ai.com/en/latest/) | Practice |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Awesome Public Datasets | A list of public datasets in various domains (ranging from climate to cancer)| [Link](https://github.com/awesomedata/awesome-public-datasets#economics) | Practice | 

[Back to contents](#contents_prog)

  

## 🎯 Machine Learning 

> Machine Learning in Python: books, websites and other github repos

‣ Books 📚 

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

|  | |  | | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | ---- | --- |

| Paragraph | Text | Link | Practice |

[Back to contents](#contents_prog) 

 

## 🎯 Algorithms & Data Structures 

> Python algorithms and data structures: books, websites and other github repos

‣ Books 📚

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| The Algorithms | Search up any algorithm to find out more | [Link](https://github.com/TheAlgorithms/Python) | Learn |

| Advanced Data Structures with Python | Algorithms and data structures uses and examples, especially useful for competitive programming | [Link](https://github.com/bhavinjawade/Advanced-Data-Structures-with-Python) | Learn |

[Back to contents](#contents_prog)

 

## 🎯 Apps + Others

> Python apps + other areas: books, websites and other github repos

‣ Books 📚

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| ReactPy | Text | [Link](https://reactpy.dev/docs/index.html) | Practice |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn |

| PyWebIO | Building web applications without the need for HTML and JS | [Link](https://github.com/pywebio/PyWebIO) | Practice |

[Back to contents](#contents_prog)

 

  Statistics  📊 


 

Coming soon! 

 

  Econometrics + Causal Inference  📈 


 

 

## Contents

📌 **OLS regression analysis**

- [Fundamentals](#fundamentals_py)

- [OLS Violations](#data_py)

- [Programming Applications](#program_ols)

📌 **Microeconometrics & Statistical Models**

- [Fundamentals](#fundamentals_py)

- [Some Discrete Choice Models](#discrete)

- [Maximum Likelihood Estimation](#mle)

- [Logistic Regressions](#logistic)

- [Generalised Moment of Methods](#gmm)

- [Programming Applications](#program_micro)

📌 **Time Series**

- [Fundamentals: General](#fundamentals_py)

- [AR Models](#ar)

- [MA Models](#ma)

- [ARMA + ARIMA Models](#arma)

- [VAR Models](#var)

- [VECM Models](#vecm)

- [Others](#others_time)

- [Programming Applications](#program_time)

📌 **Applied Econometrics + Causal Inference**

- [Fundamentals of Causal Inference](#fundamentals_applied)

- [Difference in Differences](#diff_in_diff)

- [Regression Discontinuity Designs](#reg_design)

- [Instrumental Variables](#instru_var)

- [Fixed Effects](#fixed)

- [Causal Machine Learning + Programming Applications](#program_applied)

📌 **Computational Methods in Econometrics**

- [Fundamentals](#fundamentals_comp_econ)

 

## 🎯 Fundamentals of Causal Inference

> Causal inference fundamentals including Judea Pearl's work, DAGs, matching, and more!

‣ Books 📚

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| The Mixtape with Scott | A podcast involving discussions with economists, scientists and more. The site also includes sessions on causal inference methods. | [Link](https://causalinf.substack.com/podcast) | Learn |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn |

| | |  | Practice |

‣ Academic Papers

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn |

| | |  | Practice |

[Back to contents](#contents_econ)

 

## 🎯 Difference in Differences

> All about the estimating technique, assumptions, violations and more!

‣ Books 📚

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| Paragraph | Text | Link | Practice |

‣ Websites 💻

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn | 

| | Text | | Practice |

‣ Github repos

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn |

| | |  | Practice |

‣ Academic Papers

| Name | Description | Link 🔗 | Learn/Practice |

| --- | ----------- | --- | --- |

| Header | Title | Link | Learn |

| Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania | Labour market effects of an increase in the minimum wage in New Jersey in 1992 | [Link](https://davidcard.berkeley.edu/papers/njmin-aer.pdf) | Learn |

[Back to contents](#contents_econ)

..Others coming soon!  

 

### Questions

 How can I contribute? 




- Any contributions are welcome, as this repo is not exhaustive. 


 

- If you would like to, please get in touch on Linkedin or email (in my profile homepage: readme or site) or feel free to make a pull request.




- Don't forget to share this with anyone who might find it useful!

 Why these resources/areas in particular? 




- The topics interest me and will help me keep track of my progress and learning (and hope this does the same for you as well!) They are also suited for those interested in (academic or professional) careers or topics at the intersection of econometrics, statistics and programming.

 


- Resources in the econometrics and statistics sections provide guidance on statistical models, causal inference, time series analysis, and more, making them especially useful for those interested in data science and machine learning. Each of the statistics and econometrics areas has resources on applications to programming as well.

 


- Having everything in one place makes it much easier to find resources without having to search through the vast amount of information in various locations (that's probably not organised well too!) You're more likely to delve into an area if you're provided with sufficient details and can find adequate information and resources to get started.

 Are these resources suitable for those with a beginner, intermediate, or advanced background? 




- The resources are intended to suit individuals with varying backgrounds.    

 


- You can get an idea of the levels by reading the descriptions and selecting the relevant links.




- You're welcome to contribute by adding an additional column to the tables and providing this information!

 

 Additional notes 




- Resources with a github repository and website are only included in either of the two sections. 


 

- All of the resources listed here are intended to be entirely free to use, thereby omitting some popular resources. Please refer to the contribute section if you would like to add anything that's missing.




- I'm working to add more resources when I find any and get the time to.

 

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