R/EventStudyOLS.R

In eventstudyr: Estimation and Visualization of Linear Panel Event Studies

#' Runs Ordinary Least Squares (OLS) with optional fixed effects and clustering
#'
#' @param prepared_model_formula A formula object created in [PrepareModelFormula()] that is passed to [EventStudy()].
#' @param prepared_data Data frame containing all of the parameters required for [EventStudy()] plus leads and
#' lags of the first differenced policy variable and leads and lags of the policy variable.
#' @param idvar Character indicating column of units.
#' @param timevar Character indicating column of time periods.
#' @param FE Specifies if unit fixed-effects should be included. Defaults to TRUE.
#' @param TFE Specifies if time fixed-effects should be included. Defaults to TRUE.
#' @param cluster Specifies whether to use clustered errors by units. If FALSE, will use unclustered
#' heteroskedasticity-robust standard errors. Defaults to TRUE. Must be TRUE if FE is TRUE.
#'
#' @return A data.frame that contains the estimates for the event study coefficients.
#' @import estimatr
#' @keywords internal
#' @noRd
#'
#' @examples
#' model_formula <-  PrepareModelFormula(
#'    estimator = "OLS",
#'    outcomevar = "y_base",
#'    str_policy_fd = c("z_fd", "z_fd_lead2", "z_fd_lead3", "z_fd_lag1", "z_fd_lag2"),
#'    str_policy_lead = "z_lead3",
#'    str_policy_lag = "z_lag3",
#'    controls = "x_r"
#' )
#'
#' EventStudyOLS(
#'    prepared_model_formula = model_formula,
#'    prepared_data = df_EventStudyOLS_example,
#'    idvar = "id",
#'    timevar = "t",
#'    FE = TRUE,
#'    TFE = TRUE,
#'    cluster = TRUE
#')

EventStudyOLS <- function(prepared_model_formula, prepared_data,
                          idvar, timevar, FE, TFE, cluster) {

    if (! inherits(prepared_model_formula, "formula")) {stop("prepared_model_formula should be a formula")}
    if (! is.data.frame(prepared_data)) {stop("data should be a data frame.")}
    if (! is.character(idvar)) {stop("idvar should be a character.")}
    if (! is.character(timevar)) {stop("timevar should be a character.")}
    if (! is.logical(FE)) {stop("FE should be either TRUE or FALSE.")}
    if (! is.logical(TFE)) {stop("TFE should be either TRUE or FALSE.")}
    if (! is.logical(cluster)) {stop("cluster should be either TRUE or FALSE.")}

    if (FE & TFE & cluster) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(idvar) + get(timevar),
            clusters = get(idvar),
            se_type = "stata"
        )

    } else if ((!FE) & TFE & cluster) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(timevar),
            clusters = get(idvar),
            se_type = "stata"
        )

    } else if (FE & (!TFE) & cluster) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(idvar),
            clusters = get(idvar),
            se_type = "stata"
        )

    } else if ((!FE) & (!TFE) & cluster) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            clusters = get(idvar),
            se_type = "stata"
        )

    } else if (FE & TFE & (!cluster)) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(idvar) + get(timevar),
            se_type = "stata"
        )

    } else if ((!FE) & TFE & (!cluster)) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(timevar),
            se_type = "stata"
        )

    } else if (FE & (!TFE) & (!cluster)) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            fixed_effects = ~ get(idvar),
            se_type = "stata"
        )

    } else if ((!FE) & (!TFE) & (!cluster)) {

        ols_output <- estimatr::lm_robust(
            formula = prepared_model_formula,
            data = prepared_data,
            se_type = "stata"
        )
    }

    return(ols_output)
}