Field of Research
Urban, Regional, and Spatial Economics
I study minority’s welfare from the viewpoint of spatial economics.
Especially, I try to analyze how spatially uneven distributions of the minority population affects their welfare levels, both theoretically and empirically.
Overview of Research
I study minority welfare from the spatial economics viewpoint. Especially, I try to analyze how spatially uneven distributions of the minority population affect their welfare levels, both theoretically and empirically.
One of the key concepts that distinguish spatial economics from other subfields in economics is the existence of “distance.” Individuals or agents located close to each other may interact more than those located far apart, causing them to be mutually beneficial (or sometimes mutually disadvantageous). For example, people in a neighborhood may communicate easily and are more likely to share informal information, leading to more efficient activities. Additionally, being close enables them to help each other occasionally and reduce each other’s daily difficulties. Such benefits that (minority) individuals enjoy may be induced by geographic proximity and spatial agglomeration.
I study topics relating to benefits and costs associated with spatial agglomeration, and below, I briefly explain one of my recent studies about the residential agglomeration of the homeless and their living standards.
“Residential Agglomeration of the Homeless and Its Effects on Their Living Standards” with Kotaro Iizuka (CSIS DP No. 167)
One may expect that people living in the clustered informal settlements (Fig. 1) at the bank of the Tama River, enjoy some benefits from living near other homeless persons.
For instance, they may stabilize their unstable earnings by mutually helping each other. Also, they may get higher earnings if they share and exchange information about informal jobs or income sources with other homeless persons living close. To verify the hypothesis that homeless persons in a larger cluster enjoy higher living standards than those in a smaller cluster, we collected two data types; the house location data and the house temperature data in winter, a proxy variable of the living standard level of a homeless person living in that house. Our empirical analysis indicated that there is a possibility that homeless persons in a larger cluster, with geographic proximity, enjoy higher living standards through a channel of greater social interaction (Fig. 2).
Degree: Ph. D. in Economics (University of Tokyo)