class_docstr: Wrapper class for estimators from the EconML library.
  
  Supports additional parameters as listed below. For init and fit
  parameters of each estimator, refer to the EconML docs.
code: def construct_symbolic_estimator(self, estimand):
      expr = "b: " + ", ".join(estimand.outcome_variable) + "~"
      # TODO -- fix: we are actually conditioning on positive treatment (d=1)
      if self.estimator.__module__.endswith("metalearners"):
          var_list = (
              estimand.treatment_variable + self._effect_modifier_names
          )
          expr += "+".join(var_list)
      else:
          var_list = (
              estimand.treatment_variable
              + self._observed_common_causes_names
          )
          expr += "+".join(var_list)
          expr += " | " + ",".join(self._effect_modifier_names)
      return expr
  
imports: import inspect
  from importlib import import_module
  from typing import Any, Callable, List, Optional, Protocol, Union
  from warnings import warn
  import numpy
  import pandas
  from numpy.distutils.misc_util import is_sequence
  from dowhy.causal_estimator import CausalEstimate, CausalEstimator
  from dowhy.causal_identifier import IdentifiedEstimand
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 7 for calling the Econml obj's underlying member method code with example usage: obj.construct_symbolic_estimator(estimand) and returns: expr