Poor housing conditions remain a major global public health challenge but direct causal evidence on their health effects is limited. We examine a rare rural housing intervention: the large-scale construction of subsidized high-quality cottages in Ireland 1883-1919. Using annual district-level data on deaths by cause, age and sex, we estimate the program's impact using difference-in-differences and triple-difference designs. Districts that built more cottages experienced mortality reductions of up to one death per thousand, driven by fewer respiratory deaths. The results are consistent with reduced indoor air pollution through improved ventilation. Cost-benefit analysis shows the scheme was highly cost-effective.

Evolutionary growth theories suggest that natural selection on economically beneficial traits set the stage for modern growth (Galor and Moav 2001; Galor and Moav 2002; Clark 2007). This paper assesses whether selection was viable during the Malthusian era under imperfect intergenerational transmission of traits. I describe a simple model of intergenerational transmission in Malthusian equilibrium to quantify how much selection different parameter combinations deliver. I use micro-data from historical Germany to parametrize the model; I estimate the fertility differential across, and the transmission of, latent endowments (proxied by occupational status). High-status couples had ~0.6–1.6 additional surviving children, and endowments were strongly transmitted (λ ≈ 0.59). I find that the degree of selection depends on high intergenerational transmission, and on a dynamic social baseline. With a fixed intercept the German parameters can deliver 0.28 standard deviations cumulative drift, while under an imposed moving intercept (adapting social endowments), which the data do not identify, the model projects 1.78 standard deviations over 20 generations. These projections also imply that even when mean endowment drift is modest, the share of the population in the upper-tail of the endowment distribution increases substantially.

Studying urban development often requires within-city locations. However, the geographic limitations of census data limit historical studies in terms of granularity and coverage. This project proposes a scalable geocoding procedure to obtain within-city locations for households in U.S. cities for the 1880–1950 census. Using inferred street intersections within enumeration districts (EDs), this approach requires minimal data inputs, rather than detailed historical maps and city directories. ED centroids are assigned to households to obtain approximate locations. We geolocate 80% of all EDs across 133 cities across the six census-waves. The 1950 sample includes approximate location for 28% of the US population. When benchmarking this procedure against ED polygons, we successfully assign locations to 78% of all EDs. This compares favourably to 50% coverage for existing address-based approaches. The resulting crosswalk would enable researchers to use within-city variation to study patterns of urban development, as well as to exploit fine-grained geographic variation to answer causal questions.