Description Usage Arguments Details Value References Examples

`drdid_rc1`

is used to compute the doubly robust estimators for the ATT
in difference-in-differences (DiD) setups with stationary repeated cross-sectional data. The resulting estimator is
not locally efficient; see Section 3.2 of Sant'Anna and Zhao (2020).

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`y` |
An |

`post` |
An |

`D` |
An |

`covariates` |
An |

`i.weights` |
An |

`boot` |
Logical argument to whether bootstrap should be used for inference. Default is FALSE. |

`boot.type` |
Type of bootstrap to be performed (not relevant if |

`nboot` |
Number of bootstrap repetitions (not relevant if |

`inffunc` |
Logical argument to whether influence function should be returned. Default is FALSE. |

The `drdid_rc1`

function implements the doubly robust difference-in-differences (DID)
estimator for the average treatment effect on the treated (ATT) defined in equation (3.3)
in Sant'Anna and Zhao (2020). This estimator makes use of a logistic propensity score model for the probability
of being in the treated group, and of (separate) linear regression models for the outcome among the comparison units in both pre and
post-treatment time periods. Importantly, this estimator is not locally efficient for the ATT.

The propensity score parameters are estimated using maximum likelihood, and the outcome regression coefficients are estimated using ordinary least squares.

The resulting estimator is not not locally efficient; see Sant'Anna and Zhao (2020) for details.

A list containing the following components:

`ATT` |
The DR DID point estimate |

`se` |
The DR DID standard error |

`uci` |
Estimate of the upper bound of a 95% CI for the ATT |

`lci` |
Estimate of the lower bound of a 95% CI for the ATT |

`boots` |
All Bootstrap draws of the ATT, in case bootstrap was used to conduct inference. Default is NULL |

`att.inf.func` |
Estimate of the influence function. Default is NULL |

`call.param` |
The matched call. |

`argu` |
Some arguments used (explicitly or not) in the call (panel = FALSE, estMethod = "trad2", boot, boot.type, nboot, type="dr") |

Sant'Anna, Pedro H. C. and Zhao, Jun. (2020), "Doubly Robust Difference-in-Differences Estimators." Journal of Econometrics, Vol. 219 (1), pp. 101-122, doi: 10.1016/j.jeconom.2020.06.003

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