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mjv2146/README.md
  • 👋 I am PhD Candidate in Economics at Columbia University.
  • I use data to derive insights about how the world works.

🛠️ My Tools

Programming: Python (Pandas, NumPy, seaborn, Matplotlib)

Coding

Database: SQL (Postgres)

Database

Coding: VS Code, Vim, Git

Coding Environment

📚 Projects

Project Link Tools Description
🗺️ World Development Indicators PostgeSQL, Tableau Exploratory analysis and visualizations of worldwide national accounts.
🏧 Access to Financial Markets Python, Seaborn, Matplotlib, Tableau Cleaned and transformed household level data to study the determinants of access to financial markets.
🇲🇽 Forecasting Mexican National Accounts Python, Seaborn, Matplotlib Forecasted national accounts to study impact of recessions.
🍱 Household Consumption Python, Seaborn, Matplotlib, scikit-learn Studied how households differed in their responses to a recession.
📊 Stochastic Volatility Python, Matplotlib, PyStan Detecting (unobservable) changes in the standard deviation of GDP.
📈 Interest Rates in Emerging Markets Python, Matplotlib, Seaborn, Tableau Visualization of insights from Neumeyer-Perri (2006).

Tableau Profile

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  1. access-to-financial-markets access-to-financial-markets Public

    Study of how households differ in their access to financial markets

    Jupyter Notebook

  2. world-development-indicators world-development-indicators Public

    Exploratory data analysis in SQL and visualizations in Tableau

    Jupyter Notebook

  3. household-consumption household-consumption Public

    Study of household consumption responses during the Mexican Peso Crisis

    Jupyter Notebook

  4. forecasting-mexico-national-accounts forecasting-mexico-national-accounts Public

    Forecasting Mexican national accounts using regression and ARIMA

    Jupyter Notebook

  5. stochastic-volatility stochastic-volatility Public

    Detecting unobservable changes in standard deviation of GDP

    Jupyter Notebook

  6. interest-rates-emerging-markets interest-rates-emerging-markets Public

    Visualization of insights from Neumeyer-Perri (2006)

    Jupyter Notebook