Table 7.
On the Origins of Contemporary Ethnic Inequality Inequality in Geographic Endowments across Ethnic Homelands and Contemporary Ethnic Inequality
| Atlas Narodov Mira (GREG)
|
Ethnologue
|
|||||||
|---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
| Land Quality [Gini Coeff.] | 0.3035** (0.1348) | −0.0077 (0.2191) | −0.0918 (0.1864) | 0.184 (0.1414) | 0.4042*** (0.1132) | 0.1913 (0.1784) | 0.4271** (0.1924) | 0.3930*** (0.1230) |
| Temperature [Gini Coeff.] | 1.651 (7.2462) | −9.1956 (11.1686) | 7.3784 (10.7068) | 3.0874 (8.0507) | 19.5600*** (6.8608) | 47.6529*** (12.3794) | 39.7024*** (10.6988) | 36.8859*** (10.1117) |
| Precipitation [Gini Coeff.] | 0.3421* (0.2034) | 0.7845* (0.4227) | 0.7969** (0.3445) | 0.2916 (0.2259) | 0.1884 (0.2636) | 0.5606 (0.4862) | 0.3762 (0.4119) | 0.2878 (0.2620) |
| Distance to the Coast [Gini Coeff.] | 0.2852** (0.1123) | 0.3954** (0.1801) | 0.1589 (0.1631) | 0.4640*** (0.1458) | 0.1433 (0.1388) | 0.1819 (0.1659) | 0.0012 (0.1994) | 0.3462** (0.1332) |
| Elevation [Gini Coeff.] | 0.5002* (0.2674) | 0.6844** (0.3255) | 0.9012*** (0.3064) | 0.3019 (0.2772) | 0.4413*** (0.1584) | 0.3449 (0.2232) | 0.6396*** (0.2013) | −0.0356 (0.1601) |
| Adjusted R-square | 0.450 | 0.467 | 0.493 | 0.491 | 0.583 | 0.611 | 0.617 | 0.667 |
| Observations | 164 | 164 | 164 | 164 | 164 | 164 | 164 | 164 |
| Region Fixed Effect | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Controls | No | Spatial | Admin Unit | Levels | No | Spatial | Admin Unit | Levels |
The table reports cross-country OLS estimates, associating contemporary ethnic inequality with inequality in geographic endowments across ethnic homelands. The dependent variable is the ethnic Gini coefficient that reflects inequality in lights per capita across ethnic-linguistic homelands, using the digitized version of Atlas Narodov Mira (GREG) in (1)–(4) and Ethnologue in (5)–(8). To construct the inequality measures in geographic endowments across ethnic homelands we first estimate the distance from the centroid of each ethnic homeland to the closest sea coast, average elevation, precipitation, temperature, and land quality for agriculture and then construct Gini coefficients capturing inequality across ethnic homelands in each of these geographic features for each country. In columns (2) and (6) we control for the overall degree of spatial inequality in geographic endowments using the Gini coefficient of each of these features (distance to the closest sea-coast, elevation, precipitation, temperature and land quality for agriculture) estimated across 2.5 by 2.5 decimal degree boxes/pixels in each country (boxes intersected by national boundaries and the coastline are of smaller size). In columns (3) and (7) we control for the regional inequality across administrative units in geographic endowments using the Gini coefficient of each of these features (distance to the coast, elevation, precipitation, temperature and land quality for agriculture) estimated across first-level administrative units in each country. Columns (4) and (8) include as controls the mean values (for each country) of distance to sea coast, elevation, precipitation, temperature, and land quality for agriculture. All specifications include regional fixed effects (constants not reported). The Data Appendix gives detailed variable definitions and data sources. Robust standard errors are reported in parentheses below the estimates.
***, **, and * indicate statistical significance at the 1%, 5%, and 10% level, respectively.