Recommendations

Based on the validation test results, here are specific recommendations to address detected issues. Each recommendation includes actionable suggestions to improve your panel data model.

{% for rec in recommendations %}
{% if rec.severity == 'critical' %}⚠️{% elif rec.severity == 'high' %}🔴{% elif rec.severity == 'medium' %}🟡{% else %}🔵{% endif %} {{ rec.category }}
{{ rec.severity|upper }}

{{ rec.issue }}

Failed Tests:
    {% for test in rec.tests %}
  • {{ test }}
    • {% endfor %}
Suggested Actions:
    {% for suggestion in rec.suggestions %}
  1. {{ suggestion }}
    2. {% endfor %}
{% endfor %}

General Best Practices

  • Robust Standard Errors: Always consider using robust standard errors (clustered, HAC, or Driscoll-Kraay) to account for potential violations of i.i.d. assumptions.
  • Specification Testing: Run specification tests (Hausman, Mundlak) to validate your choice between Fixed Effects and Random Effects models.
  • Time Effects: Consider including time fixed effects to control for common shocks and time trends that affect all entities.
  • Model Diagnostics: Examine residual plots and influential observations to identify outliers and potential model misspecification.
  • Theory-Driven Specification: Base your model specification on economic theory and prior research, not just statistical tests.

Further Reading