🌍 Week 11 Homework — Feedback

Student: Lorenzo Ilari Assignment: VAR Estimation and Identification

✅ Overall Assessment

Result: ✅ Pass

Excellent submission. The code is very well-structured, implements the VAR analysis correctly, and produces comprehensive output including a full 3x3 grid of Impulse Response Functions.

🔍 Task-by-Task Check

Task Description Status Notes
1.1 Data Loading & Cleanup ✅ Correctly loads and cleans data
1.2 Data Transformation ✅ Correctly computes annualized growth rates
1.3 Construct Data Matrices ✅ Correct setup of LHS and RHS matrices
1.4 OLS Estimation ✅ Correct equation-by-equation OLS estimation
1.5 Extract A1 Matrix ✅ Correct extraction of the transition matrix
1.6 Residuals & Sigma ✅ Correct calculation of covariance matrix
1.7 Identification (Cholesky) ✅ Correct use of chol(Sigma, 'lower')
1.8 Compute IRFs ✅ Correct computation of IRFs for all shocks
1.9 Plot IRFs ✅ Generates a full 3x3 grid of all IRFs
1.10 Save Figures ✅ Saves figures correctly

📈 Technical Implementation

  • VAR Estimation: Manual equation-by-equation OLS implementation is correct.
  • Identification: Correctly uses Cholesky decomposition.
  • IRF Generation: Robust implementation that calculates responses for all shocks.
  • Visualization: The use of a 3x3 subplot grid to show all interactions in the VAR is excellent.

💬 Style & Clarity

  • Code Structure: Professional coding style with clear sections and headers.
  • Comments: Good comments explaining the logic.
  • Variable Naming: Logical and descriptive names.

📊 Visual Output Assessment

  • Plots: High-quality plots with clear titles and labels.
  • Data Plot: Includes an optional plot of the transformed data, which is good practice.

✅ Suggestions for Improvement

  1. Looping: The plotting section uses hardcoded subplots. Using loops would make the code more compact and easier to maintain for larger systems.

🎯 Summary

Outstanding work. The submission is technically sound, well-documented, and produces complete results. The comprehensive plotting of all IRFs demonstrates a thorough understanding of the VAR model.

Grade Level: ✅ Pass (10/10 tasks correct)