GEODIST TWO DATASETS ISO

Variable coded as 1 when the two countries were or are the same country. Variable coded as 1 when the country in `iso_o` is a colony of the country in `iso_d` after 1945. Variable coded as 1 when the country in `iso_o` is a colony of the country in `iso_d`. Variable coded as 1 when the two country share the same colonizer after 1945. Variable coded as 1 when the country in `iso_o` was ever a colony of the country in `iso_d`. Variable coded as 1 when the two countries have at least 9% of their population speaking the same language. Variable coded as 1 when the two countries share the same official language. The GeoDist webpage provides two distinct files: a country-specific one. Variable coded as 1 when the two countries are next to each other and 0 otherwise. Our first dataset (geocepii), incorporates country-specific geographical.

GEODIST TWO DATASETS ISO

iso_dĬountry of destination as ISO codes in three characters. iso_oĬountry of origin as ISO codes in three characters. ArgumentsĪ data frame with 50176 observations on the following 14 variables. 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. 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 two weighted distance measures use city-level data to assess the geographic distribution of population inside each nation.

These two variables incorporate internal distances based on areas provided in the `geo_cepii` dataset. The output looks like this (Stata generates all the possible IDYear pairs so that the number of observations enormously increase in panel data setting): Code: Example generated by -dataex. 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. and then run the below codes, Code: rename 0 cross using 'test.dta' geodist lat lng lat0 lng0, gen (d) dataex in 1/30. 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. Provides different distance measures and dummy variables indicating whether the two countries are contiguous, share a common language or a colonial relationship. Dist_cepii: Data on pairs of countries including distance measures and dummy variables indicating common attributes Description

Geodist two datasets