def METHOD_NAME(request):
    result = HOUSING_RESULTS[request.param]
    keys = request.param.split("-")
    mod = MODELS[keys[0]]
    data = HOUSING_DATA
    endog = data.rent
    exog = add_constant(data.pcturban)
    instd = data.hsngval
    instr = data[["faminc", "region"]]
    cov_opts = deepcopy(COV_OPTIONS[keys[1]])
    cov_opts["debiased"] = keys[2] == "small"
    if keys[0] == "gmm":
        weight_opts = deepcopy(COV_OPTIONS[keys[1]])
        weight_opts["weight_type"] = weight_opts["cov_type"]
        del weight_opts["cov_type"]
    else:
        weight_opts = {}
    model_result = mod(endog, exog, instd, instr, **weight_opts).fit(**cov_opts)
    return model_result, result