Maximum Likelihood Estimation of Utility Functions Using Stata

Abstract

Economists in a wide range of fields are now developing customized likelihood functions to correspond to specific models of decision-making processes. The demand for customization derives partly from the need to consider a variety of parametric functional forms to account for experimental behavior under uncertainty. It is also generated by the fact that these models often specify decision rules that have to be written out by hand. Thus it is becoming common to see user-written maximum likelihood estimates in behavioral econometrics, and less use of pre- packaged model specifications. These pedagogic notes document the manner in which one can estimate maximum likelihood models of functions within Stata. We can quickly go beyond utility functions, in the narrow sense, and consider a wide range of decision-making processes.

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