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Ph.D. candidate in Applied Economics at the University of Minnesota

Welcome to my profile! I'm currently pursuing my Ph.D. in Applied Economics at the University of Minnesota. I'm passionate about researching how policy changes affect childcare labor markets and the role minimum wages play in the childcare industry.

🔎 Research Interests

I'm interested in causal inference, econometrics, economic modeling, and machine learning. I believe that combining these fields can lead to powerful insights into economic phenomena.

📚 Learning

I'm always looking to expand my knowledge in different areas of economics. Currently, I'm diving into Industrial Organization and Structural Modeling. I believe that understanding different fields within economics can help me to approach problems from different angles and provide more robust solutions.

💻 Work Experience

I'm currently a Graduate Research Assistant for Elizabeth Davis (University of Minnesota) and Aaron Sojourner (UPJOHN Institute). Through this experience, I've had the opportunity to work on projects that have real-world impacts.

📫 Contact me

If you have any questions, feel free to contact me at [email protected]. I'm always open to connecting with new people and learning about their experiences.

🔥 My Stats

Want to see my contributions on GitHub? Check out my stats below!

GitHub Streak

Top Langs

⚡ Fun Fact

When I'm not busy with research, I enjoy nerding out with multiplayer video games, and reading for fun. Did you know that I'm fluent in three languages? Most are programming languages :)

Don't hesitate to reach out to me if you're interested in collaborating or just want to chat about economics or anything else. Thanks for stopping by!

Rodrigo Franco's Projects

abce icon abce

Agent-based computational Economics, the Python library that makes AB modelling easier

addaandcooper icon addaandcooper

Code to solve exercises from Adda and Cooper's "Dynamic Economics" book

agentesheterogeneos icon agentesheterogeneos

Notas y códigos de un curso de como resolver modelos básicos de agentes heterogéneos

annecon icon annecon

Artificial Neural Networks on Economic Forecasting

bertopic icon bertopic

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

blockcv icon blockcv

The blockCV package creates spatially or environmentally separated training and testing folds for cross-validation to provide a robust error estimation in spatially structured environments. See

causalml icon causalml

Uplift modeling and causal inference with machine learning algorithms

causalml-teaching icon causalml-teaching

This repository consolidates my teaching material for "Causal Machine Learning".

census-api-averages icon census-api-averages

This repository provides Python scripts for downloading and analyzing US Census data. It features functions to retrieve data, compute population-based averages, and outputs raw and processed DataFrames.

dash_board_access icon dash_board_access

This repo creates a dashboard for access measures to childcare in Minnesota using flexdashboard in R

data-science-ipython-notebooks icon data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

descriptiver icon descriptiver

Make Summary Statistics And Cleaning Column Names Easier

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