The Long-Term Effects of Africa's Slave Trades - Social Sciences ...

5.2.2 Initial Population Density
The second IV strategy is to use initial population density as an instrument.
As shown in Section 5.1, slaves tended to be exported from areas with high
initial population densities. This suggests that population density is a possible
instrument for slave exports. However, it is unlikely that initial population
density satisfies the necessary exclusion restrictions. There are two
reasons for this. First, past population density will be positively correlated
with good initial characteristics of the country, which may persist, affecting
current income. However, this correlation, as I show in Section B of
the appendix, results in an IV estimate that is biased towards zero. Therefore,
the IV estimate can be taken as a lower bound estimate. Second, past
population density is correlated with current population density, which may
affect income directly. Herbst (2000) argues that low population densities
are responsible for Africa’s poor economic performance. Again, if this relationship
exists, then the IV estimate will be biased towards zero, and can
be taken as a lower bound estimate. I also control for current population
density in the second stage.
The IV results are reported in Table 6. In all specifications, the estimated
coefficient for the log of population density in 1400 is positive, as
expected, and statistically significant. The IV estimates for ln(exports/area)
are negative and larger in magnitude than the OLS estimates. In general,
these IV estimates are lower than the IV estimates when the distance to
slave markets (reported in Table 5) are used. This is consistent with the
population density IV estimates being biased towards zero and therefore
being lower bound estimates.
5.3 Controlling for Additional Country Characteristics
The third strategy is to control for additional country characteristics that
may affect income per capita, and therefore bias OLS estimates, if omitted
from the regression equations. The results are reported in Table 7. In the
first column, I add to the estimating equation five region fixed effects: Central
Africa, Western Africa, Southern Africa, Eastern Africa, and Northern
Africa. The fixed effects control for any country characteristics that differ
by region.
I also include variables that control for differences in countries’ physical
environment, endowments of natural resources, culture, and religion.
In columns 2 to 4, I control for a country’s geographic environment, by
including distance to the equator, natural openness measured by the log
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