Geography

Caloric Suitability Index dataset

Caloric Suitability Index dataset

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“The Caloric Suitability Indices” (CSI) capture the variation in potential crop yield across the globe, as measured in calories per hectare per year. Moreover, in light of the expansion in the set of crops that are available for cultivation in the course of the Columbian Exchange, the CSI indices provide a distinct measure for caloric suitability for the pre-1500 and the post-1500 era.

The CSI indices provide four estimates of caloric suitability for each cell of size 5′× 5 in the world:

The maximum potential caloric yield attainable given the set of crops that are suitable for cultivation in the pre-1500 period.
The maximum potential caloric yield attainable, given the set of crops that are suitable for cultivation in the post-1500 period.
The average potential yields within each cell, attainable given the set of crops that are suitable for cultivation in the pre-1500 period.
The average potential yields within each cell, attainable given the set of crops that are suitable for cultivation in the post-1500 period.
The Caloric Suitability Indices (Galor and Özak, 2016) captures the potential agricultural output (measured in calories) based on crops that were available for cultivation in the Pre-1500CE and Post-1500CE eras. It is available for 5’ by 5’ grid cells and at the country level. The data can be used to assess or account for the exogenous effect of agricultural potential on various economic and social outcomes. The data can be used to assess or account for the exogenous effect of agricultural potential on various economic and social outcomes. An IPython notebook is included to show how it can be used and also compares it with another measure of agricultural suitability. The data is provided as a service to the academic research community (see license for permitted uses).

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Human Mobility Index dataset

Human Mobility Index dataset

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“The Human Mobility Index (HMI)” that estimates the potential minimum travel time across the globe (measured in hours) accounting for human biological constraints, as well as geographical and technological factors that determined travel time before the widespread use of steam power. In particular, the HMI indices provide a distinct measure of human mobility potential in different eras:

Human Mobility Index (HMI): Mobility on land without seafaring technology. Shows mobility potential on land before the widespread use of steam power.
Human Mobility Index with Seafaring: HMI expanded to allow mobility on a select set of seas for which historical data was available. Shows potential mobility on land and seas before the introduction of ocean-faring ships.
Human Mobility Index with Ocean: HMI expanded to allow mobility on all seas based on CLIWOC (interpolated). Shows potential mobility on land and seas after the introduction of ocean-faring ships, but before the widespread use of steamships.
Based on these cost surfaces, researchers can find the minimum travel times between locations or construct more sophisticated statistics based on these. For example, Ashraf, Galor and Özak (2010) construct measures of pre-historic geographical isolation to study the effect of isolation on development. Similarly, Özak (2010), Depetris-Chauvin and Özak (2016, 2020) and Michalopoulus and Özak (2019) construct potential trade and information flow networks among countries, ethnic groups, cities, and artificial geographical units, to study the origins of the division of labor, and the effect of technological change on isolation and development. Likewise, Depetris-Chauvin and Özak (2019) use these measures to construct artificial states based on Voronoi partitions.

This strategy overcomes the potential mismeasurement of distances generated by using geodesic distances (Özak 2010), for a period when travel time was the most important determinant of transportation costs. Additionally, it removes the potential concern that travel time to the frontier reflects a country’s stage of development, mitigating further possible endogeneity concerns. The research validates these measures by (i) analyzing their association with actual historical travel time; (ii) examining their explanatory power for the location of historical trade routes in the Old World; and (iii) analyzing their association with genetic and cultural distances.

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