Urban Fiscal Crisis and Local Emergency Management: Tracking the Color Line in Michigan

Nate Breznau and L. Owen Kirkpatrick
Additional contact information
Nate Breznau: University of Bremen

No k9ve7, OSF Preprints from Center for Open Science

Abstract: Increasingly, U.S. state governments deploy emergency management techniques to re-solve troubled municipal finances. Layoffs, school closings, pension renegotiations, and sale of public assets results. These costs unevenly affect black residents. Recent legal de-cisions argue this is an innocent byproduct of black concentration in fiscally distressed cities. Thus, targeted emergency intervention is colorblind. We investigate this assertion, asking if racially inequitable outcomes signal differential impact on, or differential treat-ment of black people. We investigate Michigan, the country’s most intensive emergency management site. Using all politically incorporated units in Michigan, 2007-2013, we ap-ply causal logic and maximum likelihood estimation with covariates of fiscal distress, per-centage black and median household income. We find a net effect of the percentage of black residents on the likelihood of emergency management after adjusting for the other covariates. If correctly specified, our model gives evidence that racial bias was a factor in the application of emergency management.

Date: 2018-04-30
New Economics Papers: this item is included in nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://osf.io/download/5ae707c830777c000fde170a/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:k9ve7

DOI: 10.31219/osf.io/k9ve7

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().