πŸ“… 2023-10-25 β€” Session: Data Cleaning and Statistical Analysis Session

πŸ•’ 00:35–22:44
🏷️ Labels: Python, Data Cleaning, Variance Analysis, Econometrics, Latex, Comovements
πŸ“‚ Project: Dev
⭐ Priority: MEDIUM

Session Goal: The session aimed to address data cleaning in Python and explore statistical analyses related to economic data and variance transformations.

Key Activities:

  1. Converted β€˜agrupacion_id’ in a Pandas DataFrame to zero-filled strings, handling NaN values.
  2. Resolved a type conversion error in Python by adjusting the harmonize_agrupacion_id function.
  3. Conducted an analysis of variance in firm-level shocks transformation, exploring variance decomposition and implications for log-normal and log-Laplace distributions.
  4. Extended covariance analysis for shock transformations, focusing on relationships between variances and covariances.
  5. Analyzed the nonlinear impact on variance through micro shocks and explored the influence of comovements on variance in aggregated measures.
  6. Developed a LaTeX template for econometric papers and revised captions for data visualization plots.

Achievements:

  • Successfully cleaned and manipulated data in Python using Pandas.
  • Clarified statistical concepts related to variance and covariance in economic and complex systems.
  • Prepared a LaTeX template for future econometric research publications.

Pending Tasks:

  • Further research on the implications of comovements in agent-based models and variance scaling.
  • Explore more on the scaling exponent’s role in variance decay with population size.