Small-Area Analyses Using Public American Community Survey Data: A Tree-Based Spatial Microsimulation Technique

2020 ◽  
Author(s):  
Nick Graetz ◽  
Kevin Ummel ◽  
Daniel Aldana Cohen
Keyword(s):  
Survey Data ◽  
Small Area ◽  
Community Survey ◽  
American Community Survey ◽  
Spatial Microsimulation

Small-Area Analyses Using Public American Community Survey Data: A Tree-Based Spatial Microsimulation Technique

2021 ◽  
pp. 008117502110575
Author(s):  
Nick Graetz ◽  
Kevin Ummel ◽  
Daniel Aldana Cohen
Keyword(s):  
Census Tract ◽  
Small Area ◽  
Household Survey ◽  
The United States ◽  
Community Survey ◽  
Local Context ◽  
Primary Data ◽  
American Community Survey ◽  
Public Data ◽  
Spatial Microsimulation

Quantitative sociologists and social policymakers are increasingly interested in local context. Some city-specific studies have developed new primary data collection efforts to analyze inequality at the neighborhood level, but methods from spatial microsimulation have yet to be broadly used in sociology to take better advantage of existing public data sets. The American Community Survey (ACS) is the largest household survey in the United States and indispensable for detailed analysis of specific places and populations. The authors propose a technique, tree-based spatial microsimulation, to produce “small-area” (census-tract) estimates of any person- or household-level phenomenon that can be derived from ACS microdata variables. The approach is straightforward and computationally efficient, based only on publicly available data, and it provides more reliable estimates than do prevailing methods of microsimulation. The authors demonstrate the technique’s capabilities by producing tract-level estimates, stratified by race/ethnicity, of (1) the proportion of people in the census-tract population who have children and work in an essential occupation and (2) the proportion of people in the census-tract population living below the federal poverty threshold and in a household that spends greater than 50 percent of monthly income on rent or owner costs. These examples are relevant to understanding the sociospatial inequalities dramatized by the coronavirus disease 2019 pandemic. The authors discuss potential extensions of the technique to derive small-area estimates of variables observed in surveys other than the ACS.

Examining the Interstate Mobility of Recent College Graduates

2018 ◽  
Vol 47 (3) ◽  
pp. 213-215
Author(s):  
Robert Kelchen ◽  
Douglas A. Webber
Keyword(s):  
Survey Data ◽  
Brain Drain ◽  
College Graduates ◽  
State Level ◽  
Community Survey ◽  
Policy Implications ◽  
American Community Survey ◽  
Important Goal ◽  
The Past ◽  
Important Policy

An increasingly important goal of state policymakers is to keep young, well-educated adults to remain in that state instead of moving elsewhere after college, as evidenced by New York’s recent move to tie state grant aid to staying in state after graduation. We used American Community Survey data from 2005–2015 to examine the prevalence of interstate mobility over the past decade as well as provide state-level rates of “brain drain.” We found substantial variations in interstate mobility across states, which has important policy implications.

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