Description Usage Arguments Details Value References See Also Examples
BVU
estimates gravity models via Bonus
vetus OLS with simple averages.
1 |
y |
name (type: character) of the dependent variable in the dataset
|
dist |
name (type: character) of the distance variable in the dataset
|
x |
vector of names (type: character) of those bilateral variables in
the dataset |
inc_o |
variable name (type: character) of the income of the country of
origin in the dataset |
inc_d |
variable name (type: character) of the income of the country of
destination in the dataset |
vce_robust |
robust (type: logic) determines whether a robust
variance-covariance matrix should be used. The default is set to |
data |
name of the dataset to be used (type: character).
To estimate gravity equations, a square gravity dataset including bilateral
flows defined by the argument |
... |
additional arguments to be passed to |
Bonus vetus OLS
is an estimation method for gravity models
developed by Baier and Bergstrand (2009, 2010) using simple averages to center a
Taylor-series (see the references for more information).
To execute the function a square gravity dataset with all pairs of
countries, ISO-codes for the country of origin and destination, a measure of
distance between the bilateral partners as well as all
information that should be considered as dependent an independent
variables is needed.
Make sure the ISO-codes are of type "character".
Missing bilateral flows as well as incomplete rows should be
excluded from the dataset.
Furthermore, flows equal to zero should be excluded as the gravity equation
is estimated in its additive form.
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 inc_o
and inc_d
cannot be included in the estimation.
BVU
is designed to be consistent with the Stata code provided at
the website
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.
The function returns the summary of the estimated gravity model as an
lm
-object.
For estimating gravity equations via Bonus Vetus OLS see
Baier, S. L. and Bergstrand, J. H. (2009) <DOI:10.1016/j.jinteco.2008.10.004>
Baier, S. L. and Bergstrand, J. H. (2010) in Van Bergeijk, P. A., & Brakman, S. (Eds.) (2010) chapter 4 <DOI:10.1111/j.1467-9396.2011.01000.x>
For more information on gravity models, theoretical foundations and estimation methods in general see
Anderson, J. E. (1979) <DOI:10.12691/wjssh-2-2-5>
Anderson, J. E. (2010) <DOI:10.3386/w16576>
Anderson, J. E. and van Wincoop, E. (2003) <DOI:10.3386/w8079>
Head, K., Mayer, T., & Ries, J. (2010) <DOI:10.1016/j.jinteco.2010.01.002>
Head, K. and Mayer, T. (2014) <DOI:10.1016/B978-0-444-54314-1.00003-3>
Santos-Silva, J. M. C. and Tenreyro, S. (2006) <DOI:10.1162/rest.88.4.641>
and the citations therein.
See Gravity Equations: Workhorse, Toolkit, and Cookbook for gravity datasets and Stata code for estimating gravity models.
1 2 3 4 5 6 7 8 9 10 | ## Not run:
data(Gravity_no_zeros)
BVU(y="flow", dist="distw", x=c("rta"),
inc_o="gdp_o", inc_d="gdp_d", vce_robust=TRUE, data=Gravity_no_zeros)
BVU(y="flow", dist="distw", x=c("rta", "contig", "comcur"),
inc_o="gdp_o", inc_d="gdp_d", vce_robust=TRUE, data=Gravity_no_zeros)
## End(Not run)
|
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