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Home Events Implementing an Estimation Command in Stata/Mata

Implementing an Estimation Command in Stata/Mata

David Drukker the Executive Director of Econometrics at Stata will deliver a course on Implementing an estimation command in Stata/Mata.

Writing a Stata command for methods that you use or develop disseminates your research to a huge audience.  This short course shows how to write a Stata estimation command.  No Stata or Mata programming experience is required, but it does help.  After providing an introduction to basic Stata do-file programming, the course covers basic and advanced ado-file programming.  Next, it provides an introduction to Mata, the byte-compiled matrix language that is part of Stata. Then the course shows how to implement linear and nonlinear statistical methods in Stata/Mata programs.  Finally, the course discusses using Monte Carlo simulations to test the implementation.


o How does Stata work?
   o Estimation-postestimation framework
   o Estimation followed by test, predict, and margins

o A quick introduction to Stata do-file programming

o An introduction to Stata ado-file programming and to syntax

o A Stata program that implements the ordinary least-squares (OLS) estimator

o  Writing a certification script

o  An introduction to basic Mata programming

o  Making our OLS program use Mata

o  More Mata programming examples

o  Mata programming for nonlinear statistical estimation

o  A Stata/Mata program for Poisson regression

o  Making predict and margins work with our command

o  Monte Carlo simulations in Stata


10:00 - 10:30: Registration and refreshments

10:30 - 11:30:  The syntax of Stata estimation commands and\\ basic Stata programming 

11:30 - 12:30:  Programming an estimation command in Stata (Basics)

12:30 - 13:15:  Lunch

13:15 - 14:30:  An introduction to the Mata matrix language 14:30 - 15:15:  An introduction to Mata/Stata programming

15:15 - 15:30:  Coffee Break

15:30 - 16:30:  Using optimize() to implement nonlinear statistical estimators in Stata/Mata programs

16:30 - 17:15:  Testing a command by Monte Carlo simulation

17:15: Close