{
  "context": "This criteria evaluates how well the engineer uses spreg's ThreeSLS class to estimate a system of equations with endogenous variables and cross-equation error correlation. The focus is on correct usage of the package API for three-stage least squares estimation.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "ThreeSLS class usage",
      "description": "Uses spreg.ThreeSLS class (or equivalent 3SLS implementation from spreg) to estimate the system of equations",
      "max_score": 30
    },
    {
      "name": "System data structure",
      "description": "Correctly structures the input data using dictionary-based format with 'bigy' for dependent variables and 'bigX' for independent variables across equations, as required by spreg's SUR/3SLS classes",
      "max_score": 20
    },
    {
      "name": "Endogenous variables specification",
      "description": "Properly specifies endogenous variables using the 'bigyend' parameter to handle cross-equation endogeneity where each equation's dependent variable appears as an endogenous regressor in the other",
      "max_score": 20
    },
    {
      "name": "Instruments specification",
      "description": "Correctly provides instrumental variables using the 'bigq' parameter (or equivalent) with appropriate external instruments for the endogenous variables in each equation",
      "max_score": 15
    },
    {
      "name": "Spatial weights integration",
      "description": "Passes the spatial weights matrix using the 'w' parameter to account for spatial dependencies in the system",
      "max_score": 10
    },
    {
      "name": "Results extraction",
      "description": "Extracts coefficient estimates and standard errors from the model results object using appropriate attributes (e.g., 'betas', 'std_err', or similar from the results object)",
      "max_score": 5
    }
  ]
}