Growth in human societies is an inherently multiscale phenomenon, emerging from socioeconomic and demographic changes across nested spatial units. Yet standard macroeconomic indicators obscure these dynamics by averaging over heterogeneity in both place and population. This talk introduces a framework based on the Price equation that decomposes aggregate growth exactly into two components: endogenous income growth and selection effects across spatial scales. These selection effects capture how residential sorting, driven by preference and opportunity, interact with the economic structure of the city to affect aggregate growth. Using population and income data from the Chicago metropolitan area (2014–2019), we show that both growth and selection are highly localized, fat-tailed, and spatially correlated. Selection, defined as the covariance between income and population change, is concentrated in a small number of places and exhibits systematic scaling across counties. Despite intense local sorting, selection effects largely cancel in the aggregate, revealing how volatile and unequal micro-dynamics can produce stable macroeconomic trends. By treating neighborhoods as evolving subpopulations under selection, this framework furthermore connects methods from complex systems to urban sociology, providing a new way to identify processes such as gentrification and abandonment. More broadly, it offers a general approach to understanding compositional change in any nested economic system, from cities to innovation and production networks.