{
  "context": "This evaluation assesses the engineer's ability to use the spreg package's SUR (Seemingly Unrelated Regression) functionality to estimate systems of related equations. The focus is on proper use of SUR-specific classes, correct data preparation for multi-equation systems, and extraction of appropriate model outputs.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "SUR Class Usage",
      "description": "Uses the spreg.SUR class to estimate the system of equations rather than estimating equations separately.",
      "max_score": 30
    },
    {
      "name": "Data Structure Preparation",
      "description": "Correctly prepares the bigy and bigX dictionary structures required by SUR, mapping equation names/indices to their respective dependent and independent variable arrays.",
      "max_score": 25
    },
    {
      "name": "Coefficient Extraction",
      "description": "Properly extracts coefficient estimates from the SUR model object (e.g., using the bSUR attribute or appropriate methods) for all equations in the system.",
      "max_score": 15
    },
    {
      "name": "Standard Error Extraction",
      "description": "Correctly retrieves standard errors for coefficients from the SUR model object (e.g., using std_err or similar attributes) for all equations.",
      "max_score": 10
    },
    {
      "name": "R-squared Access",
      "description": "Accesses equation-specific R-squared values from the SUR model output (e.g., using sur_inf attribute or equation-specific attributes).",
      "max_score": 10
    },
    {
      "name": "Log-likelihood Access",
      "description": "Retrieves the log-likelihood value for the estimated system from the SUR model object (e.g., using logll or similar attribute).",
      "max_score": 10
    }
  ]
}