Absorptive capacity facilitates adaptation to novel environmental disasters.

Absorptive capacity-the ability to learn and apply external knowledge and information to acquire material resources-is an essential but overlooked driver in community adaptation to new and unprecedented disasters. We analyzed data from a representative random sample of 603 individuals from 25 coastal communities in Louisiana affected by the Deepwater Horizon oil spill. We used simultaneous equation models to assess the relationship between absorptive capacity and resource acquisition for affected individuals after the disaster. Results show that the diversity of individuals' prior knowledge coupled with the community's external orientation and internal cohesion facilitate resource use. They go beyond simply providing resources and demonstrate individual and community features necessary for absorbing information and knowledge and help devise adaptation strategies to address the dynamics of changing economic, social, and political environment after the disaster.

Modeling the diffusion of complex innovations as a process of opinion formation through social networks.

Complex innovations- ideas, practices, and technologies that hold uncertain benefits for potential adopters-often vary in their ability to diffuse in different communities over time. To explain why, I develop a model of innovation adoption in which agents engage in naïve (DeGroot) learning about the value of an innovation within their social networks. Using simulations on Bernoulli random graphs, I examine how adoption varies with network properties and with the distribution of initial opinions and adoption thresholds. The results show that: (i) low-density and high-asymmetry networks produce polarization in influence to adopt an innovation over time, (ii) increasing network density and asymmetry promote adoption under a variety of opinion and threshold distributions, and (iii) the optimal levels of density and asymmetry in networks depend on the distribution of thresholds: networks with high density (>0.25) and high asymmetry (>0.50) are optimal for maximizing diffusion when adoption thresholds are right-skewed (i.e., barriers to adoption are low), but networks with low density (<0.01) and low asymmetry (<0.25) are optimal when thresholds are left-skewed. I draw on data from a diffusion field experiment to predict adoption over time and compare the results to observed outcomes.

Revisiting the effect of colonial institutions on comparative economic development.

European settler mortality has been proposed as an instrument to predict the causal effect of colonial institutions on differences in economic development. We examine the relationship between mortality, temperature, and economic development in former European colonies in Asia, Africa, and the Americas. We find that (i) European settler mortality rates increased with regional temperatures and (ii) economic output decreased with regional temperatures. Conditioning on the continent of settlement and accounting for colonies that were not independent as of 1900 undermines the causal effect of colonial institutions on comparative economic development. Our findings run counter to the institutions hypothesis of economic development, showing instead that geography affected both historic mortality rates and present-day economic output.