Summary of estimates function that, if is used with default options, provides estimation results are consistent with the Stata methods used in Head and Mayer (2014) . This function is adapted from the work of Isidore Beautrelet.

hm_summary(model, robust = FALSE, ...)



(Type: lm) Regression object obtained by using the estimation methods from this package or a generic method such as lm or glm. Some particular classes (gpml, nbpml, negbin and nls) don't return R squared and F statistic.


(Type: logical) Determines whether a robust variance-covariance matrix should be used. By default is set to FALSE.

If set TRUE the estimation results are consistent with the Stata code provided at the website Gravity Equations: Workhorse, Toolkit, and Cookbook when choosing robust estimation.


additional arguments to be passed to tobit.


Summary lm object.


# Example for CRAN checks: # Executable in < 5 sec library(dplyr) data("gravity_no_zeros") # Choose 5 countries for testing countries_chosen <- c("AUS", "CHN", "GBR", "BRA", "CAN") grav_small <- filter(gravity_no_zeros, iso_o %in% countries_chosen) # Using OLS for testing fit <- ols( dependent_variable = "flow", distance = "distw", additional_regressors = c("rta", "contig", "comcur"), income_origin = "gdp_o", income_destination = "gdp_d", code_origin = "iso_o", code_destination = "iso_d", uie = FALSE, robust = FALSE, data = grav_small ) fit2 <- hm_summary(fit, robust = FALSE)