Policing Effects on Black Entrepreneurs’ Financial Performance: The Moderating Impact of Formal and Informal Institutions

Abstract

The purpose of this study is to provide a context-based empirical investigation of the racialized effect of policing on the financial performance of Black entrepreneurs. Given the historical role of race in policing in the United States, we expect that the degree of the policing of the Black population in a state will be negatively associated with the financial performance of Black entrepreneurs in the state. The sample for this study is drawn from quarterly police stop data across 14 states from the Stanford Open Policing Project, which is matched with state-level data from the Merchant Maverick ranking of best states for Black entrepreneurs. The sample size is 164 observations over 2013–2015 pertaining to police search rates of Blacks. Findings from the moderated, multivariate regression analysis reveals that the adverse effect of the policing of Black Americans on Black entrepreneurs’ financial performance can be relieved by state-level religiosity and the legalization of marijuana (or cannabis; a mind-altering drug produced from the hemp plant). This research demonstrates the important role of religious and legal institutional mechanisms in countering the economically destructive effects of policing on Black entrepreneurship in the United States.

1. Introduction

Police and law enforcement institutions around the world are intended to protect and serve the public. As a result, formal institutions such as the police are assumed to be beneficial to formally registered businesses that are owned by members of the residential population (G. Bruton et al., 2021) because they can facilitate the entrepreneurs’ perception and access to requisite institutional support and social capital. The entrepreneurial and organizational activity in a society are governed by an amalgam of formal and informal institutions, considered as the “rules of the game” (Harrington & Gelfand, 2014; Vallejo-Imbaquingo & Robalino-Lopez, 2025); wherein formal institutions are associated with constitutions, laws, government policy, and property rights in a context, and informal institutions are linked to cultural factors, norms, traditions, codes of conduct, and sanctions (Brieger et al., 2021; North, 1991; Pacheco et al., 2010). Indeed, policing support of the safety of business owners, employees, and their patrons implies an enlargement of the entrepreneur’s social capital through increasing the entrepreneur’s willingness to engage with formal and informal institutions that can facilitate social connections.

Notwithstanding the potential benefits of policing on entrepreneurial activity, it is possible that the police discriminate based on race, leading to adverse effects for entrepreneurs who are members of Black or Brown racial groups. In the United States, where the problem of unequal policing is rife, the Federal Bureau of Investigation (FBI)’s Uniform Crime Reporting (UCR) program statistics show that though Black people constitute 13% of the U.S. population, they are overrepresented among individuals arrested for non-fatal violent crime arrests (33%) and for serious non-fatal violent crime arrests (36%) (Beck, 2021). This evidence of significant racial differences in policing was substantiated in a recent study of 100 million traffic stops across the United States. In this study, Pierson et al. (2020) demonstrate that there is a 20 percent difference in the likelihood of being stopped by the police between Black and White drivers relative to their share of the residential population. Furthermore, the GBD 2019 Police Violence US Subnational Collaborators (2021) demonstrate that existing police violence statistics often mis-classify and under-report race data covering civilian deaths from police violence. Their study shows that the mortality rate of police violence over the 1980–2018 period was highest for non-Hispanic Black people when compared to other races.

The problem of the unequal policing of Black people relative to White people and other races contributes to comparatively higher levels of distrust for societal institutions (including the police) within Black communities (M. N. Ogbolu, 2025; Singh & Miller, 2024; Singh & Nurse, 2024) and has recently spawned the Black Lives Matter movement (see Fryer, 2019, 2020). Despite the overwhelming evidence of racial differences in policing, it remains unclear how the policing of Black people can affect entrepreneurial activity and success among the Black population. Specifically, what are the effects of policing on Black entrepreneurs’ performance?

This study confronts the above question in the context of police stop and search patterns of Black drivers across 14 US states, examining its relationship with Black financial success from entrepreneurial activity using US state-level data. As shown in prior research, police stop and search patterns can provide useful information about whether the police are discriminating against a particular racial group (see Fryer, 2019). In this study, we theorize that the rate of police searches of Black drivers is associated with lower levels of Black entrepreneurs’ financial performance. Furthermore, we examine the moderating effects of state religiosity. We also evaluate the moderating impact of marijuana legalization, which prior studies suggest might attenuate the policing rates of Black people (Pierson et al., 2020). Marijuana (also cannabis) refers to a mind-altering drug that is derived from the hemp plant.

This paper contributes to the current state of knowledge in the entrepreneurship field in the following ways. First, this study responds to recent calls for more studies that incorporate existing racialized structures into the study of entrepreneurship (G. D. Bruton et al., 2023). Importantly, there is need for more research on Black entrepreneurship, as it relates to gaining a better understanding of ecosystems and structures that can support Black entrepreneurs in a manner that closes the historic wealth gap between White and Black households in the United States (M. N. Ogbolu et al., 2015; Singh & Nurse, 2024). This study provides initial insights into mechanisms that undergird the relationship between the policing of Black people and Black entrepreneurs’ financial success. Accordingly, the study findings reveal two institutional levers that help alleviate the adverse effects of policing on Black entrepreneurship, namely religiosity and legal changes that decriminalize marijuana.

Second, institutional theory scholars often portray the positive effects of the police in supporting entrepreneurs (G. Bruton et al., 2021), especially considering how crime can undermine entrepreneurial activity (Churchill et al., 2023). Moreover, when studies have tackled the adverse effects of formal institutions on Black entrepreneurs, the focus is often on the lack of financial institutional support (e.g., Alshebami, 2025; Ebewo et al., 2025; M. Ogbolu et al., 2023; Singh & Miller, 2024). By contrast, the current study shows new evidence, which highlights the adverse consequences of extra-financial formal institutions (i.e., police institutions) on Black entrepreneurship in the U.S. context. The research findings point to useful avenues for future research that focuses on the unequal impact of institutions in entrepreneurship. They also highlight promising directions for future cross-cultural research that evaluates racial inequalities in policing across cultures such as the United States, United Kingdom, and South Africa.

The rest of this paper proceeds as follows. In the next section, we highlight the relevant theoretical background and offer a set of testable hypotheses. Then, we outline the methodology of this paper, including the data sources, measurement, and variables. Following the methodology, we report the study findings. Finally, we conclude with a discussion of the results, study limitations, and implications for future research and practice.

2. Theoretical Background

The literature has established that race is a germane factor in entrepreneurship in the U.S. context (Fairlie, 2020; Fairlie & Robb, 2008; M. N. Ogbolu, 2025; M. N. Ogbolu & Singh, 2013; M. Ogbolu et al., 2023; Singh & Nurse, 2024). Entrepreneurship offers a promising avenue for creating wealth for Black (and minority) entrepreneurs and their communities (Fairlie, 2020; Reid et al., 2024). Yet, few empirical studies have adopted a racialized structural view in evaluating the effects of formal institutions on entrepreneurs even though “marginalized racial groups experience a fundamentally different entrepreneurial environment from their majority counterparts” (G. D. Bruton et al., 2023, p. 492). This notion from G. D. Bruton et al. (2023) is consistent with arguments from critical race theorists, who argue that enhancing Black entrepreneurial outcomes requires acknowledging the prevailing racist structures and institutions in society (e.g., Gold, 2016). The dearth of empirical work acknowledging these racist structures has caused a deficit in our understanding of the reasons why Black entrepreneurs might underperform their White counterparts, or even more broadly why the racial wealth gap has persisted in the United States.

Responding to the call for a more racialized view in entrepreneurship research (Bratsis, 2023; G. D. Bruton et al., 2023) and in an effort to offer more insight into how structural racism affects Black entrepreneurs’ financial performance (see Singh & Nurse, 2024), we focus our attention on policing effects in this paper. Historically, the relationship between the police and Black Americans has been fraught with incidents of discrimination, often manifesting in disproportionately higher levels of police stops, searches, the excessive use of force, and the arrest of Black citizens. Examples of the earliest reported racially charged police incidents against Black people include the police capture of runaway slaves, the breaking up of labor strikes, and stopping protests or riots (GBD 2019 Police Violence US Subnational Collaborators, 2021). Some of these incidents have unfortunately resulted in the death of Black people at the hands of the police (M. N. Ogbolu, 2025). In recent years, these incidents have generated protests across the U.S. in places such as Ferguson, Missouri; New York City; Washington, D.C.; Chicago, Illinois; and Oakland, California, culminating into the Black Lives Matter movement (Fryer, 2019). These incidents of police discrimination against the Black population are likely to have a profound impact on Black entrepreneurship. In the following, we offer two critical arguments that delineate how the policing of Black people might adversely affect Black entrepreneurs’ financial performance.

3. Study Hypotheses

We expect that discriminatory or perceived discriminatory police incidents against African Americans will directly fuel Black people’s general distrust for the criminal justice systems and government institutions (M. N. Ogbolu, 2025; Singh & Miller, 2024; Singh & Nurse, 2024). Therefore, as the level of policing increases in a municipality or state, the general trust for police among the Black population in that area will decline. This shortage of trust in institutions arises from the increase in adverse events from police interactions with Black people, which reinforces beliefs in the associated municipalities that government institutions are structurally wired to work in opposition to Black people. For example, McDaniel et al. (2021) noted that the trauma and tensions in the aftermath of the police killing of Freddie Gray (a 25-year-old African American) in Baltimore, Maryland, contributed to distrust and broken lines of communication between the city government and the citizenry. The impact of Black entrepreneurs distrusting the police is that they may undertake suboptimal strategic choices in their business to minimize their interactions with police and government institutions. For instance, Black entrepreneurs may eschew incorporating their venture as an employer business or may avoid government funding opportunities, such as the recent paycheck protection program (PPP) loans. This could make them over-reliant on personal and family resources for their business funding. One report indicates that 71% of Black entrepreneurs used their personal or family savings (compared to 66% of White entrepreneurs) to fund their business, although Black households have comparably less wealth and assets than their White counterparts (Singh & Miller, 2024). Such constraints on the entrepreneurial agency and strategy among Black entrepreneurs would likely lead to suboptimal decision making and consequently lower financial success from entrepreneurial activity.

Furthermore, trust in institutions is inextricably connected with the social capital of entrepreneurs (M. N. Ogbolu, 2025). If Black entrepreneurs distrust government institutions such as the police, they will become less likely to expand their social capital in an optimal manner because they may perceive more risk in seeking to expand their social capital beyond their existing ties. According to Price (2012), “as a form of social capital, trust can be defined as the willingness to permit the future decisions of others to influence your welfare” (p. 171). Thus, increases in policing in a state tends to constrain the social capital of Black entrepreneurs by limiting the physical movement or entrepreneurial activities of Black people. This limitation in movements and networking activities implies that Black entrepreneurs would be more likely to gravitate toward their neighborhoods and communities for business support. That is, they will become more embedded within their existing network of family and friends for business support. There are possible benefits that stem from entrepreneurs drawing from their communities for resources. However, their communities also experience similar disadvantages that accrue from policing. As a result, the overall costs of this constrained social capital will more likely outweigh the overall benefits for Black entrepreneurs. Based on the foregoing arguments, we present the hypothesis below.

Hypothesis 1: 

The police search rate of Black drivers is negatively related to Black entrepreneurs’ financial performance.

The above theorizing suggests that the distrust in police and constraints on their social capital reduce the financial performance of Black entrepreneurs and Black communities by extension. Below, we consider institutional-based mechanisms that might reconfigure the primary relationship, thereby limiting the adverse effects of policing on Black entrepreneurs.

First, we consider the moderating role of religiosity, which is an informal institutional mechanism that provides regulatory, emotional, and social support to citizens. The tightness of religious societies often leads to highly predictable social structures, which are built around a shared set of beliefs and actions (Harrington & Gelfand, 2014; Uzuegbunam et al., 2023). These tight social structures in highly religious societies exhibit the potential to enhance institutional (or generalized) trust in entrepreneurial environments where entrepreneurs need to negotiate deals with resource providers such as investors (Chircop et al., 2020). Specifically, religious social structures in the form of historically Black Protestant churches in the United States have the potential to reconfigure trust in institutions, thereby acting as enablers that facilitate equal access to institutional resources for Black people in the United States. According to Pew Research, three-quarters of Black adults surveyed stated that Black churches have helped increase the racial equality in America (Pew Research Center, 2021).

In addition, given the historical antecedents of Black churches in the United States—wherein these churches emerged to serve not just as worship communities but as resource communities—Black churches play a pivotal role in developing social capital for their community members (Chatters et al., 2009). Thus, we expect that state-level religiosity in the form of historically Black churches will have a positive moderating effect on the primary hypothesis.

Hypothesis 2: 

The negative association between the police search rate and Black entrepreneurs’ financial performance is weaker at higher levels of state-level religiosity.

Second, we consider the potential moderating impact of marijuana legalization. For decades, the criminalization of marijuana possession, distribution, and usage had been at the core of police discrimination against Black individuals (Pierson et al., 2020; Reid et al., 2024). The fact that marijuana was considered illegal contributed significantly to the distrust that Black people have for the police. Importantly, M. N. Ogbolu (2025) notes that distrust is a two-way street between Black people and the police, such that Black people may not trust the police to be racially unbiased and the police may not trust members of the Black community when they receive information from them during the investigation of a crime. Thus, the past criminalization of marijuana tended to heighten encounters that catalyze distrust between both parties.

Consistent with expectations, the recent legalization of marijuana in the states of Colorado and Washington led to a lower proportion of police stops and searches in these two states that resulted in a drug related charge (Pierson et al., 2020). Thus, we expect that states that legalized marijuana will experience some restoration of trust between their police institutions and the individuals in the Black communities by reducing encounters or interactions where distrust might occur between both parties. As this trust gradually gets restored, it would also help enlarge the social capital of Black entrepreneurs in these states with the legalization of marijuana, which in turn will increase entrepreneurial access to a wider range of opportunities and resources. Thus, we propose the following moderating effect.

Hypothesis 3: 

The negative association between the police search rate and Black entrepreneurs’ financial performance is weaker with marijuana legalization at the state-level.

4. Research Methodology

4.1. Data Sources and Empirical Context

Data was collected from the following archival sources. The first source is the Stanford Open Policing Project https://openpolicing.stanford.edu/ (accessed on 30 June 2025), which documents the rate at which people of different races are stopped by the police on a quarterly basis (Pierson et al., 2020). This quarterly data on 14 US states is aggregated at the state level. We focused on the portion of the data that captured the post-legalization of recreational marijuana in two states, Colorado and Washington, which occurred at the end of 2012 (Pierson et al., 2020). We extract these quarterly search rate data for Blacks in the corresponding quarters ranging from 2013 to 2015. There are two benefits of focusing on this period. First, it allows for a more precise accounting of the changing external environmental influences that shape the police stop and search rates of vehicles (especially in the two states, Colorado and Washington). We include dummy variable controls for these two states in the multivariate regressions and exploit this variation in the data in our moderated regressions. Second, this period provides a reasonable time lag to the period of measurement of the dependent variables, described below.

The second source of data is Merchant Maverick “Best States for Black Entrepreneurs” ranking, which includes data and ranking on different metrics of Black entrepreneurship https://www.merchantmaverick.com/2023-best-states-for-black-entrepreneurs/ (accessed on 30 June 2025). Merchant Maverick is a website that provides reviews for small business software and services. Merchant Maverick data is drawn from different sources such as US Census Bureau’s 2020 Annual Business Survey, the US Census Bureau’s 2021 American Community Survey, Tax Foundation, and the US Bureau of Labor Statistics. This data source provides data on the different metrics of Black entrepreneurship/business ownership aggregated at the state level. It also provides some of the control measures used in the multivariate regressions. We note that our arguments imply that policing the Black population in a state context is associated with the financial performance of Black entrepreneurs in the state. As such, this data on the metrics of Black entrepreneurial performance at the state level fits well with our theoretical reasoning.

The third source of data is the 2014 Pew Research religious landscape study (https://www.pewresearch.org/religious-landscape-study/database/state/ (accessed on 30 June 2025)). This data surveys 35,000 Americans from all 50 US states about their religious affiliations, beliefs, and practices. This allows for a capture of overall religiosity at the state level, while also offering a breakdown of religiosity by different religious groups (see Uzuegbunam et al., 2023). Among other variables in this data, we were able to identify the proportion of historically Black Protestants in every state.

4.2. Measures of the Study

Our primary interest is to understand the effect of policing of Black population on Black financial performance in entrepreneurship. Accordingly, we employ a state-level measure of annual income of Black-owned businesses as a proxy for the dependent variable, Black entrepreneurs’ financial performance in the state. In supplemental analysis, we also use a measure of Black-owned employer businesses per 1 million people as an indirect proxy of Black wealth creation. Previous research shows that Black employer businesses are more likely to employ Blacks because they receive more Black applicants and hire them at a higher rate than White employers (Stoll et al., 2001).

The independent variable is based on Pierson et al. (2020) measure of police search rates of Black people in a state measured at the quarter level. This represents a good proxy of the extent to which Black people are policed in a state, given the central role of traffic stops and searches in policing in the United States. Unlike survey methods for compiling traffic stops, this dataset offers a more comprehensive capture of the phenomenon because it is developed from public record requests that were filed in all US states.

The first moderating variable measures the percent of historically Black Protestants at the state level. This measure captures state-level religiosity, which has an impact on the social capital of Black businesspeople. In the Pew Research data, some state observations on this measure are indicated as <1%. We apply the following rule to these observations. When <1%, measure approximated to 0.1%. In robustness checks (not reported in the paper for brevity), using alternative religiosity variables such as mainline Protestants and evangelical Protestants produced similar results.

We also evaluate the moderating effect of legalization of marijuana on the policing of Blacks and Black entrepreneurial financial performance relationship. The institutional changes in Colorado and Washington at the end of 2012 pertaining to the legalization of marijuana provide good measures for evaluating this moderation (Pierson et al., 2020). Of the 14 states covered in this study data, dummy variables were generated for these two states: (Colorado = 1) and (Washington = 1). The interaction of these dummy variables and police search rate of Black people provided a meaningful test for the evaluation of the moderating effect of legalization.

The multivariate analysis takes into account other variables that might also impact the financial standing of Black entrepreneurs. Specifically, we control for the unemployment rate, state income tax, and gross state product (a measure of state gross domestic product).

5. Findings

We include a scatter plot that describes the relationship between the police search rates of Black people and Black entrepreneurs’ financial performance. The plot is shown in Figure 1 below.

Table 1. Summary statistics and bivariate correlations.

	Mean	S.D.	Min	Max	1	2	3	4	5	6	7	8
1. Black business owner income	52,154.83	13,622.16	29,067	87,815
2. Black-run employer businesses per 1 M	342.64	176.01	107.76	681.01	0.10
					−0.22
3. Police search rate (Black people)	0.03	0.03	0	0.09	−0.59	−0.27
					0.00	0.00
4. Percent of historically Black Protestants	0.03	0.03	0	0.08	0.37	0.71	−0.25
					0.00	0.00	0.00
5. Unemployment rate	4.49	1.12	2.6	6.9	0.71	0.20	−0.25	0.29
					0.00	−0.01	0.00	0.00
6. State income tax	5.21	3.55	0	13.3	0.23	−0.20	0.10	−0.30	0.02
					0.00	−0.01	−0.20	0.00	−0.83
7. Gross state product	788,220.9	881,797.5	36,170.1	3.36 × 106	0.80	0.22	−0.33	0.64	0.72	0.17
					0.00	0.00	0.00	0.00	0.00	−0.03
8. Colorado dummy	0.07	0.26	0	1	0.13	−0.21	−0.23	−0.25	0.15	−0.05	−0.12
					−0.10	−0.01	0.00	0.00	−0.05	−0.56	−0.14
9. Washington dummy	0.07	0.26	0	1	−0.07	−0.22	−0.27	−0.17	0.05	−0.41	−0.04	−0.08
					−0.38	−0.01	0.00	−0.03	−0.51	0.00	−0.62	−0.31

p-values associated with correlations are below correlation coefficients in the table. Black business owner income and gross state product are in United States dollars.

shows the summary statistics and bivariate correlations among the study variables. For the sample of 14 states, the average Black business owner’s annual income is USD 52,154.83. Yet, we note some significant variance in the data as indicated by the range from a minimum of USD 29,067 (Vermont) to a maximum of USD 87,815 (California). We also note that the range of the search rate variable is from 0 to 0.09. The bivariate correlation between the police search rate of Black people and the Black business owner income is negative (as expected) and statistically significant (r = −0.59, p < 0.01). Similarly, the bivariate correlation between the police search rate of Black people and Black-owned employer businesses per 1 million residents is negative (as expected) and statistically significant (r = −0.27, p < 0.01). Prima facie, these bivariate correlations indicate preliminary support for the key hypothesis that the police search rate of Black people is adversely related to the income of Black entrepreneurs.

Table 2. OLS regression analysis (effect of Black policing on Black entrepreneurial financial performance).

DV = Black Entrepreneurs Financial Performance	Model 1	Model 2	Model 3	Model 4	Model 5
Search rate (Black people)		−213,303.164 ***	−357,494.049 ***	−236,952.691 **	−236,879.254 **
		[66,629.130]	[82,675.807]	[81,868.666]	[81,832.563]
Search rate × Black Protestants			5,156,628.629 **
			[1,926,744.341]
Search rate × Colorado dummy				236,952.691 **
				[81,868.666]
Search rate × Washington dummy					236,879.254 **
					[81,832.563]
Black Protestants			−311,668.510 **	−169,666.618	−169,634.965
			[134,727.603]	[125,457.202]	[125,452.898]
Colorado dummy (Y = 1)	9417.592 **	1976.982	−4597.824	−2572.470	−1467.407
	[3773.219]	[3984.378]	[3911.940]	[5117.051]	[4783.358]
Washington dummy (Y = 1)	662.560	−5934.671	−17,582.546 **	−13,861.341 *	−14,156.208 *
	[2693.864]	[3583.505]	[5846.732]	[7220.635]	[7316.116]
Unemployment rate	2567.037	3578.687	1258.383	2030.555	2030.517
	[3712.720]	[2714.746]	[2642.490]	[3211.087]	[3211.311]
State income tax	500.096	572.368	−448.478	−297.789	−297.651
	[354.692]	[367.019]	[509.162]	[545.487]	[545.458]
Gross state product	0.010 ***	0.007 **	0.014 ***	0.012 **	0.012 **
	[0.003]	[0.003]	[0.004]	[0.004]	[0.004]
Constant	29,393.057 *	33,752.831 **	54,936.894 ***	47,209.011 **	47,205.090 **
	[14,355.759]	[11,628.971]	[15,323.443]	[18,490.244]	[18,490.498]
Observations	164	164	164	164	164
R-squared	0.721	0.839	0.899	0.862	0.861

*** p < 0.01, ** p < 0.05, and * p < 0.1 indicate statistical significance, using two-tailed tests. Table reports OLS coefficients. Robust standard errors (clustered by states) are in brackets.

presents the multivariate regression results testing the study hypotheses. Hypothesis 1 predicts a negative relationship between the police search rate of Black people and the Black business owner income in a state. The findings reported in Table 2 and Models 2–5 provide supporting evidence for this thesis. In the full Model 5, the coefficient of the police search rate is negative and statistically significant (β = −236,879.254; p < 0.05). The results also indicate support for Hypothesis 2, which proposes that religiosity (measured by the rate of Black Protestants in state) will positively moderate the relationship in Hypothesis 1. The interaction effect shown in Model 3 of Table 2 is positive and statistically significant (β = 5,156,628.629; p < 0.05). We plot this interaction effect in Figure 2 and show how the slope of the Black business owner income = f (police search rate) changes for low, moderate, and high levels of religiosity at the state level. We observe that the slope becomes more positive compared to the low through high levels of religiosity. This supports our claim in Hypothesis 2.

Hypothesis 3 proposes a positive moderating effect from the legalization of marijuana in Colorado and Washington. We note that the interaction effect in Models 4 and 5 of Table 2 indicate a positive and statistically significant effect (Model 4, Colorado: β = 236,952.691; p < 0.05; Model 5, Washington: β = 236,879.254; p < 0.05). The interaction plots shown in Figure 3a,b clearly document this effect, showing the effects of legalization in Colorado and Washington. These figures both show that Colorado and Washington (post-legalization) demonstrate a relatively zero slope relationship between the policing rates of Blacks and Black entrepreneurs’ financial performance. Figure 3a shows this moderating effect in Colorado and Figure 3b shows this moderating effect in Washington. Thus, we claim support for Hypothesis 3.

In

Table 3. OLS regression analysis (effect of Black policing on Black employer businesses).

DV = Black Employer Businesses per 1 M	Model 6	Model 7	Model 8	Model 9	Model 10
Search rate (Black people)		−3031.936 *	−328.470	−1646.150 *	−1645.640 *
		[1567.009]	[350.216]	[866.916]	[866.756]
Search rate × Black Protestants			−56,307.676 **
			[21,838.225]
Search rate × Colorado dummy				1646.150 *
				[866.916]
Search rate × Washington dummy					1645.640 *
					[866.756]
Black Protestants			11,528.657 ***	9977.453 ***	9977.673 ***
			[1843.201]	[1628.269]	[1628.206]
Colorado dummy (Y = 1)	−183.972 ***	−289.735 ***	−52.968 **	−94.833 **	−87.156 **
	[58.661]	[78.478]	[22.080]	[35.388]	[32.217]
Washington dummy (Y = 1)	−279.317 **	−373.091 ***	133.597 *	92.893	90.845
	[93.865]	[94.593]	[63.969]	[80.498]	[81.151]
Unemployment rate	29.533	43.913	143.407 ***	134.976 ***	134.976 ***
	[44.197]	[41.974]	[15.493]	[20.062]	[20.061]
State income tax	−20.301	−19.273	33.547 ***	31.899 ***	31.900 ***
	[13.271]	[10.951]	[9.232]	[9.673]	[9.673]
Gross state product	0.000	−0.000	−0.000 ***	−0.000 ***	−0.000 ***
	[0.000]	[0.000]	[0.000]	[0.000]	[0.000]
Constant	332.612	394.582 *	−481.084 ***	−396.624 **	−396.651 **
	[212.128]	[222.281]	[111.376]	[153.458]	[153.450]
Observations	164	164	164	164	164
R-squared	0.290	0.433	0.929	0.902	0.902

*** p < 0.01, ** p < 0.05, and * p < 0.1 indicate statistical significance, using two-tailed tests. Table reports OLS coefficients. Robust standard errors (clustered by states) are in brackets.

, we present results using an alternate dependent variable, the number of Black employer businesses per 1 million people in the state. In addition to creating more financial wealth opportunities for their owners, Black employer businesses tend to employ more Black people than White employer businesses (Stoll et al., 2001). Therefore, the results presented in Table 3 demonstrate implications for Black communities in the associated states. Overall, the results in Table 3 are broadly consistent with our main findings, showing a negative and statistically significant main effect of police search rates and a positive moderating effect of the legalization of marijuana in Colorado and Washington.

In the sensitivity analysis, we considered the potential effects of Historically Black Colleges and Universities (HBCUs) in developing entrepreneurial ecosystems for Black entrepreneurs (Price & Toney, 2024).1 Thus, we included HBCUs’ fixed effects pertaining to NC, SC, TX, and OH (states in our sample with HBCUs). The results reported in

Table 4. The sensitivity analysis controlling for the fixed effects of HBCU States.

DV = Black Entrepreneurs Financial Performance	Model 11	Model 12	Model 13	Model 14	Model 15
Search rate (Black people)		−287,725.245 **	−400,853.355 ***	−389,347.319 ***	−389,115.217 ***
		[108,739.286]	[53,899.768]	[53,835.034]	[53,852.310]
Search rate × Black Protestants			4,656,837.282
			[4,196,586.515]
Search rate × Colorado dummy				389,347.319 ***
				[53,835.034]
Search rate × Washington dummy					389,115.217 ***
					[53,852.310]
Black Protestants			−823,628.358 ***	−783,779.319 ***	−783,516.804 ***
			[133,568.327]	[132,312.339]	[132,456.541]
Colorado dummy (Y = 1)	8515.509 *	376.418	−10,364.861 ***	−11,960.075 ***	−10,140.183 ***
	[4213.791]	[4704.321]	[2812.409]	[2955.428]	[2726.439]
Washington dummy (Y = 1)	−116.193	−5844.103	−40,368.653 ***	−40,460.937 ***	−40,935.705 ***
	[3976.206]	[4176.171]	[6710.465]	[6594.971]	[6657.767]
Unemployment rate	3026.154	3538.032	−3727.134 *	−3817.990 *	−3815.879 *
	[3900.356]	[2854.447]	[2075.172]	[2000.302]	[2002.166]
State income tax	465.456	905.566	−3646.002 ***	−3659.291 ***	−3658.065 ***
	[575.687]	[625.477]	[707.314]	[715.612]	[716.550]
Gross state product	0.010 ***	0.005	0.033 ***	0.032 ***	0.032 ***
	[0.003]	[0.004]	[0.005]	[0.005]	[0.005]
Constant	28,285.915 *	35,080.502 **	93,603.003 ***	93,965.438 ***	93,941.038 ***
	[15,832.879]	[13,101.937]	[14,655.645]	[14,234.305]	[14,247.782]
HBCU state dummies	Included	Included	Included	Included	Included
Observations	164	164	164	164	164
R-squared	0.736	0.859	0.951	0.949	0.948

*** p < 0.01, ** p < 0.05, and * p < 0.1 indicate statistical significance, using two-tailed tests. Table reports OLS coefficients. Robust standard errors (clustered by states) are in brackets.

broadly indicate consistency with the main results, even with the inclusion of these additional fixed effect controls. Hypotheses 1 and 3 are supported. But Hypothesis 2 loses support with the inclusion of these additional fixed effects. However, we note that the interaction effects in Table 4 may suffer from multicollinearity due to their high variance inflation factors (VIFs, exceed 10).

6. Discussion and Implications

Despite the potential of police to serve and protect all citizens equally, the evidence in prior studies unfortunately demonstrates a history of systemic discriminatory police practices and incidents against Black people (Pierson et al., 2020). Until now, empirical studies of the policing effects on Black entrepreneurship have been limited. This is surprising given the promise that entrepreneurship holds for closing the historic wealth gap between Black and White people in the United States (Singh & Miller, 2024). Moreover, when previous empirical work has investigated the racial disparities in entrepreneurial settings, the focus has largely been on financial institutional support for Black entrepreneurs (e.g., Ebewo et al., 2025; M. Ogbolu et al., 2023). Our race-based perspective in this paper offers fresh insights into the role of extra-financial institutions such as the police. By investigating this at the U.S. state level using quarterly police stop and search data across 14 U.S. states, this study substantiates the thesis that the police search rates in a state are negatively associated with the subsequent income of Black entrepreneurs in that state. By extension and given the role of Black employer businesses in Black communities, we also show that this may also partly explain the persistent wealth gap between Black and White households in the United States.

Furthermore, this study offers empirical evidence to support the proposition that formal and informal institutional support can alleviate the adverse effects of policing on Black entrepreneurs’ financial performance. This is consistent with existing institutional entrepreneurship insights, which highlight that institutional change can positively impact historically disadvantaged populations, such as Black communities in America. This study contributes to the literature by demonstrating the role of historical Black churches and legal change in limiting adverse effects on Black entrepreneurs.

6.1. Limitations and Research Implications

There are limitations with the current study, partly due to the state-level data, which present opportunities for future research. First, our measure of policing is focused on aggregated state-level police stop and search patterns. Future research can take advantage of a wider range of police interactions with Black people to offer a more nuanced study of the effects of different forms of policing on Black entrepreneurship. Moreover, empirical studies in the future can employ more fine-grained data to consider intersectionality in factors such as gender, geography, and industry types in the proposed framework. Such data can be sourced through surveys or interviews.

Furthermore, we conduct the current study in the United States context. Yet, we expect that this sort of discriminatory policing against minorities may have a range of other impacts in other countries’ cultural contexts, such as United Kingdom and South Africa. We believe that extending the study of this topic across countries will offer more institutionally relevant and culturally sensitive insights for the entrepreneurship literature.

Two moderating effect findings highlight promising avenues for future research and policy. We demonstrate that religiosity has a significant moderating impact on the effect of policing on Black entrepreneurship. Though we focused our attention specifically on Black churches, our post hoc analysis suggests that the religiosity effects may transcend religious affiliations. Therefore, we believe that opportunities exist for future research to more closely study the impact of religiosity in institutional realignments that affect Black entrepreneurship.

The second moderating effect shows the impact of marijuana legalization in reconfiguring the adverse effects of policing on Black entrepreneurship. Our research is in line with recent work that highlights the importance of programs that facilitate the development and growth of Black entrepreneurs in the burgeoning (and legalized) marijuana industry (i.e., Reid et al., 2024). Our findings suggest that the legalization of this substance that was once at the core of Black incarceration may have the dual benefit of the reduced incarceration of Black people and subsequently the increased financial performance of Black entrepreneurs.

6.2. Practical Implications

The practical implications of this study are twofold. First, the findings pertaining to the role of historically Black churches in alleviating the negative effects of policing on Black entrepreneurs suggest that religious leaders can help facilitate conditions that support Black entrepreneurs. For entrepreneurs, this finding suggests that growth-oriented entrepreneurs should engage with the religious institutions in their community as they seek to build instrumental social ties that can help expand their business. This also highlights opportunities for social entrepreneurs and entrepreneurial ecosystem builders who are focused on social justice. These social entrepreneurs should consider innovative business models that can bridge cross-sectoral partnerships that leverage religious institutions and public institutions toward building trust and enabling laws that serve the interests of entrepreneurs in overpoliced minority communities. Thus, this finding reinforces the recommendation to practitioners and policy makers to engage more with religious leaders in policy discussions that affect the Black community (see Uzuegbunam et al., 2023).

Second, the findings of this research reinforce the point that history matters in the consideration of effective strategies that can address racial inequality in policing and income. The past criminalization of marijuana offenses in many US communities has been shown to impact racial inequality in policing (Reid et al., 2024). Thus, by decriminalizing this substance, certain states like Colorado and Washington have shown the virtue of taking history into account in efforts to address the friction between the police and Black communities. Thus, this research suggests the need for stakeholders to engage in wider inquiries that highlight legal changes that can ameliorate the historical sources of tension that exist between the police and Black communities.

7. Conclusions

In closing, this study has demonstrated the importance of racialized policing structures on the financial performance of Black entrepreneurs. Indeed, the evidence is consistent with the thesis that the historically tense relationship between the police in the United States and Black communities is adversely related to the financial success of Black entrepreneurs (M. N. Ogbolu, 2025). Since entrepreneurship is one of the most viable pathways to closing to the racial wealth gap (Reid et al., 2024; Singh & Miller, 2024), this finding pinpoints a significant institutional constraint on achieving this closure of the racial wealth gap. Yet, this study equally reveals possible institutional pathways to alleviating the negative effect of policing on Black entrepreneurship. Overall, this research affirms the central role of institutions in shaping and reshaping racial disparities in entrepreneurship.