Student Name: Iusupova Farangizbegim Assignment: Week 9 - Monte Carlo OLS & Numerical Integration

Overall Assessment

Grade: ✅ (Pass)

The submission is correct and well-executed. The Monte Carlo simulation provides a clear analysis of the OLS estimator’s properties. The numerical integration section correctly handles the parity requirement for Simpson’s rule (checking for even grid sizes and adjusting accordingly), which is a key technical detail often missed.

Task-by-Task Check

  1. Function Definition: ✅ montecarlo_ols is correctly defined.
  2. DGP Logic: ✅ Correct generation of data.
  3. OLS Logic: ✅ Correct OLS implementation.
  4. Execution: ✅ loops over sample sizes correctly.
  5. Visuals: ✅ Histograms with theoretical overlays are well done.
  6. Statistics: ✅ Mean and variance calculated and interpreted.
  7. Interpretation: ✅ Good discussion of consistency and unbiasedness.
  8. Utility Function: ✅ Correct CRRA definition.
  9. Trapezoidal Rule: ✅ Correct implementation.
  10. Simpson’s Rule: ✅ Correct. You explicitly check mod(N, 2) == 0 and adjust the grid. This is the correct numerical approach.
  11. Grid Loop: ✅ Loops over grid sizes.
  12. Visuals: ✅ Convergence plot included.
  13. Interpretation: ✅ Good comparison of convergence rates.

Technical Implementation

  • Organization: The code is clear and well-structured.
  • Robustness: The Simpson’s rule implementation is robust to grid size choices.

Suggestions for Improvement

  • None significant. The work demonstrates a solid understanding of the concepts.

Summary

13/13 tasks correct. A strong submission.