Neighborhood effect averaging problem

[1][2] Mei-Po Kwan, a prominent scholar in human geography, highlighted the importance of accounting for spatial processes and interactions within neighborhoods in a 2018 paper.

On the other hand, neighborhood-level data offers a broader perspective on specific areas, encompassing factors like average income, crime rates, or access to amenities.

[2] To address this problem, Kwan proposed utilizing spatial statistical techniques to consider individuals neighborhood contexts at different temporal scales throughout their life.

Factors such as proximity, spatial autocorrelation, and the influence of neighboring areas can be considered, providing a more accurate understanding of the complex dynamics between individuals and their environment.

[1] This approach advances urban and regional studies knowledge, providing insights into the intricate interplay between individuals and their surrounding environment.