speccurvieR (version 0.4.2)

se_compare: Compare different kinds of standard errors

Description

se_compare() takes in a regression formula (with or without fixed effects), data, and the types of standard errors desired, including clustered, heteroskedasticity-consistent, and bootstrapped. It then returns a data frame with coefficient and standard error estimates for easy comparison and plotting.

Usage

se_compare(
  formula,
  data,
  weights = NULL,
  types = "all",
  cluster = NULL,
  clusteredOnly = FALSE,
  fixedEffectsOnly = FALSE,
  bootSamples = NULL,
  bootSampleSize = NULL
)

Value

A data frame where row represents an independent variable in the model and each column a type of standard error. Coefficient estimates for each variable are also included (column `"estimate"` for non-fixed effects model and column `"estimate_FE"` for fixed effects models). Columns are automatically named to specify the standard error type.

Some examples:

"iid" = normal standard errors, i.e. assuming homoskedasticity

"CL_FE" = standard errors clustered by fixed effects

"bootstrap_k8n300_FE" = bootstrapped standard errors for a fixed effects model where `bootSamples = 8` and `bootSampleSize = 300`

"CL_Depth_ID_FE" = standard errors clustered by the variable "Depth_ID" for a model with fixed effects

"HC0_Sta_ID" = HC0 standard errors clustered by the variable "Sta_ID"

Note: for fixed effects models the "(Intercept)" row will be all `NA` because the intercept is not reported by `feols()` when fixed effects are present.

Arguments

formula

A string containing a regression formula, with or without fixed effects.

data

A data frame containing the variables provided in `formula` and any clustering variables passed to `cluster`.

weights

Optional string with the column name in `data` that contains weights.

types

A string or vector of strings specifying what types of standard errors are desired. Defaults to "all".

The following types are supported for non-fixed effects models:

With clustering: "HC0, "HC1", "HC2", "HC3".

Without clustering: "iid" (i.e. normal standard errors), "HC0, "HC1", "HC2", "HC3", "HC4", "HC4m", "HC5", "bootstrapped".

The following types are supported for fixed effects models:

With clustering: "CL_FE" (clustered by fixed effects, i.e. the default standard errors reported by `feols()` if no clusters are supplied), if clusters are supplied then the conventional clustered standard errors from `feols()` are estimated for each clustering variable. Two- way clustered standard errors are not supported at this time.

Without clustering: "HC0, "HC1", "HC2", "HC3", "HC4", "HC4m", "HC5", "bootstrapped".

cluster

A string or vector of strings specifying variables present in `data` to be used for clustering standard errors.

clusteredOnly

A boolean indicating whether only standard errors with clustering should be estimated, defaults to `FALSE`.

fixedEffectsOnly

A boolean indicating whether only standard errors for fixed effects models should be estimated, defaults to `FALSE`.

bootSamples

An integer or vector of integers indicating how many times the model should be estimated with a random subset of the data. If a vector then every combination of `bootSamples` and `bootSampleSize` are estimated.

bootSampleSize

An integer or vector of integers indicating how many observations are in each random subset of the data. If a vector then every combination of `bootSamples` and `bootSampleSize` are estimated.

Examples

se_compare(formula = "Salnty ~ T_degC + ChlorA + O2Sat | Sta_ID",
           data = bottles, types = "all", cluster = c("Depth_ID", "Sta_ID"),
           fixedEffectsOnly = FALSE, bootSamples=c(4, 8, 10),
           bootSampleSize=c(300, 500))

se_compare(formula = "Salnty ~ T_degC + ChlorA + O2Sat", data = bottles,
           types = "bootstrapped", bootSamples = c(8, 10),
           bootSampleSize = c(300, 500))

se_compare(formula = "Salnty ~ T_degC + ChlorA", data = bottles,
           types = c("HC0", "HC1", "HC3"))