@article{Davidson:273508,
      recid = {273508},
      author = {Davidson, Russell },
      title = {Artificial Regressions},
      address = {2001-01},
      number = {2110-2018-4157},
      series = {Working Paper No. 1038},
      pages = {26},
      year = {2001},
      abstract = {Associated with every popular nonlinear estimation method  is at least one “artificial” linear regression. We define  an artificial regression in terms of three conditions that  it must satisfy. Then we show how artificial regressions  can be useful for numerical optimization, testing  hypotheses, and computing parameter estimates. Several  existing artificial regressions are discussed and are shown  to satisfy the defining conditions, and a new artificial  regression for regression models with heteroskedasticity of  unknown form is introduced.},
      url = {http://ageconsearch.umn.edu/record/273508},
      doi = {https://doi.org/10.22004/ag.econ.273508},
}