| dist_cepii {cepiigeodist} | R Documentation |
Data on pairs of countries including distance measures and dummy variables indicating common attributes
Description
Provides different distance measures and dummy variables indicating whether the two countries are contiguous, share a common language or a colonial relationship. There are two kinds of distance measures: simple distances, for which only one city is necessary to calculate international distances; and weighted distances, for which we need data on principal cities in each country. The simple distances are calculated following the great circle formula, which uses latitudes and longitudes of the most important city (in terms of population) or of its official capital. These two variables incorporate internal distances based on areas provided in the ‘geo_cepii' dataset. The two weighted distance measures use city-level data to assess the geographic distribution of population inside each nation. The idea is to calculate distance between two countries based on bilateral distances between the largest cities of those two countries, those inter-city distances being weighted by the share of the city in the overall country’s population. The distance formula used is a generalized mean of city-to-city bilateral distances developed by Head and Mayer (2002), which takes the arithmetic mean and the harmonic means as special cases.
Format
A data frame with 50176 observations on the following 14 variables.
iso_oCountry of origin as ISO codes in three characters.
iso_dCountry of destination as ISO codes in three characters.
contigVariable coded as 1 when the two countries are next to each other and 0 otherwise.
comlang_offVariable coded as 1 when the two countries share the same official language.
comlang_ethnoVariable coded as 1 when the two countries have at least 9% of their population speaking the same language.
colonyVariable coded as 1 when the country in 'iso_o' was ever a colony of the country in 'iso_d'.
comcolVariable coded as 1 when the two country share the same colonizer after 1945.
curcolVariable coded as 1 when the country in 'iso_o' is a colony of the country in 'iso_d'.
col45Variable coded as 1 when the country in 'iso_o' is a colony of the country in 'iso_d' after 1945.
smctryVariable coded as 1 when the two countries were or are the same country.
distSimple distance (most populated cities, km)
distcapSimple distance between capitals (capitals, km)
distwWeighted distance (pop-wt, km) with theta=1 (theta measures the sensitivity of trade flows to bilateral distance dkl)
distwcesWeighted distance (pop-wt, km) theta=-1.
Source
http://www.cepii.fr/CEPII/en/bdd_modele/download.asp?id=6
References
Mayer, T. & Zignago, S. (2011) Notes on CEPII's distances measures: the GeoDist Database CEPII Working Paper 2011-25
Head, K. & Mayer, T. (2002) Illusory Border Effects: Distance Mismeasurement In-flates Estimates of Home Bias in Trade CEPII Working Paper 2002-01
Examples
# filter countries that share borders
dist_cepii[dist_cepii$contig == 1, ]