gravity (version 0.9.8)

bvu: Bonus vetus OLS (BVU)

Description

bvu estimates gravity models via Bonus vetus OLS with simple averages.

Usage

bvu(dependent_variable, distance, additional_regressors = NULL,
  income_origin, income_destination, code_origin, code_destination,
  robust = FALSE, data, ...)

Arguments

dependent_variable

(Type: character) name of the dependent variable. This dependent variable is divided by the product of unilateral incomes such (i.e. income_origin and income_destination) and logged afterwards.

distance

(Type: character) name of the distance variable that should be taken as the key independent variable in the estimation. The distance is logged automatically when the function is executed.

additional_regressors

(Type: character) names of the additional regressors to include in the model (e.g. a dummy variable to indicate contiguity). Unilateral metric variables such as GDP should be inserted via the arguments income_origin and income_destination. As country specific effects are subdued due to demeaning, no further unilateral variables apart from incomes can be added.

Write this argument as c(contiguity, common currency, ...). By default this is set to NULL.

income_origin

(Type: character) origin income variable (e.g. GDP) in the dataset.

income_destination

(Type: character) destination income variable (e.g. GDP) in the dataset.

code_origin

(Type: character) country of origin variable (e.g. ISO-3 country codes). The variables are grouped using this parameter.

code_destination

(Type: character) country of destination variable (e.g. country ISO-3 codes). The variables are grouped using this parameter.

robust

(Type: logical) whether robust fitting should be used. By default this is set to FALSE.

data

(Type: data.frame) the dataset to be used.

...

Additional arguments to be passed to the function.

Value

The function returns the summary of the estimated gravity model as an lm-object.

Details

Bonus vetus OLS is an estimation method for gravity models developed by Baier2009,Baier2010;textualgravity using simple averages to center a Taylor-series.

The bvu function considers Multilateral Resistance terms and allows to conduct comparative statics. Country specific effects are subdued due to demeaning. Hence, unilateral variables apart from incomes cannot be included in the estimation.

bvu is designed to be consistent with the Stata code provided at Gravity Equations: Workhorse, Toolkit, and Cookbook when choosing robust estimation.

As, to our knowledge at the moment, there is no explicit literature covering the estimation of a gravity equation by bvu using panel data, we do not recommend to apply this method in this case.

References

For more information on gravity models, theoretical foundations and estimation methods in general see

Anderson1979gravity

Anderson2001gravity

Anderson2010gravity

Baier2009gravity

Baier2010gravity

Feenstra2002gravity

Head2010gravity

Head2014gravity

Santos2006gravity

and the citations therein.

See Gravity Equations: Workhorse, Toolkit, and Cookbook for gravity datasets and Stata code for estimating gravity models.

For estimating gravity equations using panel data see

Egger2003gravity

Gomez-Herrera2013gravity

and the references therein.

See Also

lm, coeftest, vcovHC

Examples

Run this code
# NOT RUN {
# 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)

fit <- bvu(
  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",
  robust = FALSE,
  data = grav_small
)
# }

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