,
Centre d'études prospectives et d'informations internationales (CEPII)
[dtc]| Title: | CEPII's GeoDist datasets in R |
|---|---|
| Description: | Provides data on countries and their main city or agglomeration and the different distance measures and dummy variables indicating whether two countries are contiguous, share a common language or a colonial relationship. The reference article for these datasets is Mayer and Zignago (2011). |
| Authors: | Mauricio Vargas [aut, cre] ,
Centre d'études prospectives et d'informations internationales (CEPII)
[dtc] |
| Maintainer: | Mauricio Vargas <[email protected]> |
| License: | CC0 |
| Version: | 0.1 |
| Built: | 2024-11-11 06:16:09 UTC |
| Source: | https://github.com/pachadotdev/cepiigeodist |
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.
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.
http://www.cepii.fr/CEPII/en/bdd_modele/download.asp?id=6
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
# filter countries that share borders dist_cepii[dist_cepii$contig == 1, ]# filter countries that share borders dist_cepii[dist_cepii$contig == 1, ]
There are firstly three identification codes of the country according to the ISO classification, the country's area in square kilometers, used to calculate in particular its internal distance. Variables indicating whether the country is landlocked and which continent it is part of are also included.
A data frame with 238 observations on the following 34 variables.
iso2ISO codes in two characters.
iso3ISO codes in three characters.
cnumISO codes in three numbers.
countryName of country in English.
paysName of country in French.
areaCountry's area in km2.
dis_intInternal distance of country i, dii=.67*sqrt(area/pi) (an often used measure of average distance between producers and consumers in a country). See Head and Mayer, 2002 for more on this topic.
landlockedDummy variable set equal to 1 for landlocked countries.
continentContinent to which the country is belonging.
city_enNames of capitals or main cities of the country in English.
city_frNames of capitals or main cities of the country in French.
latLatitude of the city.
lonLongitude of the city.
capVariable equals to 1 if the city is the capital of the country, to 0 if the city is the most populated city (maincity equals to 1) but not the capital, and to 2 in the cases of two capitals, if the city is the most populated but the "second" capital or the previous capital.
maincityVariable coded as 1 when the city is the most populated of the country and as 2 otherwise.
citynumNumber of cities for each country used to calculate the weighted distances described in Mayer and Zignago, 2011.
langoff_1Official or national languages and languages spoken by at least 20% of the population of the country (and spoken in another country of the world) following the same logic than the "open-circuit languages" in Mélitz (2002).
langoff_2Same as langoff_1.
langoff_3Same as langoff_1.
lang20_1Languages (mother tongue, lingua francas or second languages) spoken by at least 20% of the population of the country.
lang20_2Same as lang20_1.
lang20_3Same as lang20_1.
lang20_4Same as lang20_1.
lang9_1Languages (mother tongue, lingua francas or second languages) spoken by between 9% amd 20% of the population of the country.
lang9_2Same as lang9_1.
lang9_3Same as lang9_1.
lang9_4Same as lang9_1.
colonizer1Colonizers of the country for a relatively long period of time and with asubstantial participation in the governance of the colonized country.
colonizer2Same as colonizer1.
colonizer3Same as colonizer1.
colonizer4Same as colonizer1.
short_colonizer1Colonizers of the country for a relatively short period of time orwith only low involvement in the governance of the colonized country.
short_colonizer2Same as short_colonizer1.
short_colonizer3Same as short_colonizer1.
http://www.cepii.fr/CEPII/en/bdd_modele/download.asp?id=6
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
# filter to avoid multiple records for the same country geo_cepii[geo_cepii$cap == 1 & geo_cepii$maincity == 1, ]# filter to avoid multiple records for the same country geo_cepii[geo_cepii$cap == 1 & geo_cepii$maincity == 1, ]