Here I will put examples of abstracts and my rewrites of them.
“Frontier planters, immigrants, and the abolition of slavery in Brazil,” by
François Seylerv and Arthur Silvey.
A protracted legislative battle culminated in the abolition of slavery in Brazil in 1888. In this paper, we unbundle the material interests of individual electoral districts in the persistence of the coercion system. We build a new data set of roll-call votes on 1884-1888 emancipation bills in the legislature, and connect it to local features of the districts. In line with previous works, we find a robust positive association between local levels of slavery and the likelihood that the representative votes against emancipation. We extend this literature by considering two sources of conflict within the enfranchised elite, and thus revisit the influential Nieboer-Domar hypothesis. We find higher support for emancipation laws where slaves could more easily escape, and also where immigrants provided an alternative source of labor for landowners. A two-pronged instrumental variables strategy that leverages historical and topographic determinants of the location of slaves and maroons across space as well as heteroskedasticity with respect to the regressors supports a causal interpretation of our main results.
The legislative battle to abolish slavery in Brazil from 1884 to 1888 had 20 key votes that evolved dramatically. We unpack how the material interests of each of the 122 electoral districts affected this evolution. It is well known that districts with more slaves opposed emancipation. We probe deeper to revisit the Nieboer-Domar hypothesis that viability of serfdom and slavery depends on lack of land inaccessible to the masters that might support escapees. We find more support for emancipation laws where slaves could more easily escape and where immigrants were more available as an alternative source of labor. These are highly endogenous variables, so we use a two-pronged instrumental variables strategy that uses variation in (a) history and geography, and (b) heteroskedasticity of the regressors.