New paper with preliminary results that helps resolve the debate about which agglomeration index works best. This paper “Measuring Agglomeration: Which estimator should we use?” shows that a simple spatial gini coefficient has more desirable size and power properties than the Ellison & Glaeser or Duranton & Overman indices.
Recent working paper “Agglomeration within an Urban Area” develops a new index to measure colocalization and estimates the determinants of agglomeration within the Denver-Boulder-Greeley CMSA. This paper will be presented at the NBER Workshop on Urban Economics in July as well as at the ASSA ARUEUA sessions in Philadelphia.
A number of new projects in the works examining the impacts of schools on a number of outcomes in Charlotte. Check out a new working paper on school segregation and adult labor market outcomes — “School Segregation, Educational Attainment and Crime: Evidence from the end of busing in Charlotte-Mecklenburg”
New research looks into the impact of public school choice under No Child Left Behind on neighborhood gentrification. Results highlight that allowing families to opt out of `failing’ neighborhood schools leads to higher property values, more home renovations and households with more income.
In new research, I am examining the confounding role of single-family housing renovations in using hedonic estimators to value local amenities (e.g. access to transit, school quality, etc.). I formally test and quantify for this potential positive bias in estimated housing appreciation rates.
Recent research into the spatial concentration of crime within the city of Charlotte has led to some interesting figures below. These figures show how many miles a criminal travels from their home to commit a crime. The solid line indicates the density of distances traveled for over 30,000 arrested criminals between 2007 and 2009. The dotted line indicates the general distribution of randomly matched criminals and crimes.
Interesting results. Criminals really do not travel far to commit crimes and this trend is most pronounced for violent crimes.
Check out some of the graphs from my paper with Erik Johnson, A Nonparametric Test for Industrial Specialization. This figure display the concentration of manufacturing and service establishments in the Denver-Boulder-Greeley CMSA. Each grid cell represents our place and we conduct this test for 258 NAICS four digit industries and over 70,000 establishments.
Figure 1) Bivariate Kernel Density of Establishment Concentration in Denver CMSA
The largest peak represents downtown Denver and two secondary commercial centers exist northwest and south of Denver in Boulder and the Denver Technology Center.
In this paper, we develop a nonparametric test to determine in specific places have statistically significant amounts of same industry concentration. Since all of our conclusions are based on data driven counterfactuals of randomly located industries we can overcome a number of issues related to small sample sizes. Our kernel density estimators are used to produce our measure of concentration and mitigate the Modifiable Areal Unit Problem (MAUP). Check out the results for just one of our 258 industries.
1) Establishment Density – NAICS 5411 -Legal Services
The kernel density figure here shows the high concentration of legal establishments in Denver.
2) P-Values of Concentrations – NAICS 5411 -Legal Services
This figure shows how the the concentration of establishments compares to the overall concentration of service industry establishments in this urban area.
3) Global P-Values of Concentrations – NAICS 5411 -Legal Services
This figure incorporates a correction for multiple hypothesis testing to account for the fact that we are conducting 2,601 hypothesis tests for our 51×51 grid shown by the squares in Figure 1. Results highlight 3 areas of statistical significant concentration of legal services establishments – downtown Denver, Boulder and Greeley.