title: How to estimate probit model with binary endogenous regressor using Stata
body: <p>The theoretical principle behind the estimation is clear to me (as is described on Wooldridge's textbook and  some previous threads]<a href="https://stats.stackexchange.com/questions/48922/estimating-two-stage-selection-model-with-probit-reduced-form-equation-and-ols-s/48957#48957">1</a>)</p>
  
  <p><a href="https://stats.stackexchange.com/questions/48922/estimating-two-stage-selection-model-with-probit-reduced-form-equation-and-ols-s/48957#48957">1</a>: <a href="https://stats.stackexchange.com/questions/94063/probit-two-stage-least-squares/94392#94392">https://stats.stackexchange.com/questions/94063/probit-two-stage-least-squares/94392#94392</a>. However when I check the Stata manual of <code>ivprobit</code>,it writes </p>
  
  <pre><code>"···regressors are continuous and are not appropriate for use with discrete endogenous
  regressors."
  </code></pre>
  
  <p>So I wonder if there is some other (built-in or user-written)command that can be used to implement to estimate such model (<strong>binary</strong> endogenous regressor).</p>
  
  <hr>
  
  <p>Thank you for your useful suggestion. A further question: if I want to estimate Heckman selection model with binary endogenous variable, something like what's discussed in this thread <a href="https://stats.stackexchange.com/questions/48922/estimating-two-stage-selection-model-with-probit-reduced-form-equation-and-ols-s/48957#48957">two-stage selection model</a>, 
  which command can I use? <code>cmp</code>? (the syntax of this command is complicated and confusing to me). Or can I just add inverse Mills ratio to the rhs and use <code>biprobit</code> as suggested by @drstevok? </p>