Description Usage Arguments Value

Run a hurdle IV regression, either lognormal IV or cragg IV. You should specify the model you want to fit. Currently this does not have a nice summary function for the output.

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`formula` |
the second stage regression: y~exogenous + endogenous |

`inst` |
a vector of your instrument(s): c(inst1,inst2) |

`endog` |
a vector of your endogenous variable(s): c(end1,end2) |

`exog` |
a vector of your exogenous variable(s): c(ex1,ex2) |

`data` |
the dataframe |

`endog_reg` |
a list of endogenous regression formulae. By default will estimate endogenous ~ all exogenous variables + all instruments |

`start_val` |
an optional list of start values. By default the function will find start values using simple linear/probit regressions of the specified formulae |

`type` |
either "lognormal" or "cragg" |

`options:` |
cholesky true or false; maxit = maximal number of iterations; trace = 0; method = "BFGS". Options are similar to those for optim, see optim documentation for more details |

Returns estimated parameters as well as a the hessian and standard deviations

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