Race, representation, and assets forfeiture

Abstract

Under forfeiture laws, law enforcement organizations seize billions of dollars a year from U.S. citizens based on demonstrated or suspected connections between the assets and criminal activity. Interest groups have argued that taking of assets through forfeiture intentionally and disproportionately targets communities of color, but scholars have not sufficiently explored this relationship. In order to address this gap, we draw on racial threat theory to develop the expectation that the growth of black and Hispanic populations within a community will correlate positively with the amount of asset forfeiture, and representative bureaucracy theory to develop the hypothesis that greater representation of a particular minority group on the police force will negatively moderate that relationship. We test these hypotheses in an analysis of 2,278 municipal police departments between 1993 and 2007, finding evidence of a significant relationship between minority population share and reported forfeiture revenue. Furthermore, we find that increasing the proportion of black and Hispanic officers negatively moderates that relationship. We believe the results have implications not only for the U.S., but also for other nations with asset forfeiture regimes and more broadly for our understanding of the ways in which law enforcement organizations respond to diverse populations and the moderating impact of representation on those responses.

Notes

1 Based on data from the Federal Equitable Sharing Program, where civil and criminal forfeitures can be distinguished.

2 Advocates dispute the existence or importance of those incentives (The US Attorney’s Office 2009).

3 In terms of the first, the most important standards are 1) whether the state or the property owner must demonstrate that seized property was not related to criminal activity and 2) what standard of proof is necessary to do so. Two thirds of states place the burden on the owner in some or all cases and, in most cases, these standards have not changed for decades (Carpenter et al. 2015).

4 It is often employed in processing forfeited revenue seized by multijurisdictional or intergovernmental task forces, rather than having different entities that may be operating under different forfeiture laws try to divvy up the proceeds (Edgeworth 2008).

5 Note that the work by Piven and Cloward (1971) where they argue that in order to exercise social control and maintain legitimacy, modern capitalist state responds to massive racial insurgence through expanding the welfare program, is one of the most controversial explanations for welfare expansion around 1960s in the U.S. See Albritton (1979) for critics of it.

6 To explain individual caseworker behavior, Soss and his colleagues develop a Racial Classification Model (RCM), which states that decision making by frontline workers are unconsciously subject to socially constructed assumptions about the welfare recipients, even though they are legally bound to treat recipients equally, regardless of differences in demographic characteristics (Soss, Fording, and Schram 2008; Fording, Soss, and Schram 2011).

7 Note that they use the representativeness index developed by (Pitts 2005), instead of presentation of a certain minority group, as the moderate, and thus 100 on the index would mean perfectly representative staff composition.

8 Available data make it impossible to see the race of the original owners of forfeited property.

9 The most recent wave of LEMAS survey in 2013 was not included in our analytic window because it did not include questions about asset forfeiture.

10 The data are published annually by the U.S. Census Bureau for all types of local governments.

11 Equitable sharing data were collected and complied by the Institute for Justice (available at http://ij.org/report/policing-for-profit/). These data are reported by the federal government annually at the agency level and include every state and local agency that participated in the Program in a given year.

12 In current analysis, we limit the sample to municipal police departments, given that the head of police departments and county sheriff’s offices are generated through different mechanisms. The former one is appointed, and the latter one is mostly through democratic election. In another forthcoming paper, Mughan, Li, and Nicholson-Crotty (2019) examine the motivational difference between the two and probe its implications for seizure behavior. The findings point to a fundamental difference between elected and appointed administrators. Therefore, to rule out the impact from electoral motivation, we separate the two types of police organizations and perform a set of analyses on police departments only.

13 It is also possible that agencies may underreport the forfeiture values given the controversies and unpopular nature of this practice. In that case, our estimations would be conservative approximations and true effects might be even larger.

14 For example, in New Mexico and Washington DC 100 percent of forfeited funds must be deposited in the state’s general fund and the Indiana Constitution mandates all forfeiture proceeds go to the State School Fund.

15 The variable is obtained from the Survey of State and Local Government Finances.

16 The within variation for black population share is very limited, with a standard deviation of 0.015. The standard deviation for the Hispanic population share is larger but still is a small number, 0.023.

Additional information

Notes on contributors

Sean Nicholson-Crotty

Sean Nicholson-Crotty is a Professor of Public Affairs at the O’Neill School of Public and Environmental Affairs, Indiana University. His research focuses on the performance of public organizations, particularly law enforcement organizations, decision making by public administrators, and the diffusion of innovations across governments and organizations.

Jill Nicholson-Crotty

Jill Nicholson-Crotty is an Associate Professor at the School of Public and Environmental Affairs at Indiana University. Her research on public sector agencies focuses on how the demographic compositions of organizations affects services for clients.

Danyao Li

Danyao Li is a PhD Candidate at The O’Neill School of Public and Environmental Affairs, Indiana University. Her research centers on representation, diversity, government accountability and performance of public organizations, with a specific application to law enforcement.

Siân Mughan

Siân Mughan is an Assistant Professor in the School of Public Affairs at Arizona State University. Her research focuses on the equity effects of state and local tax policy, emphasizing the role of institutions in shaping the behavior of actors in fiscally federated systems.