Unequal Cities,Unequal Participation: The Effect of Income Inequality on Civic Engagement

Abstract

Civic participation is a touchstone of American government, yet it has declined steadily over the past 50 years. Alongside changes in the relationship between American citizens and their government has been a stark increase in the levels of income and wealth concentration. While there is strong evidence that income inequality drives down participation at the national level, there have been fewer studies on the effects for local governments. This article studies the relationship between participation in departmental policy making and income inequality at the local level across the United States in a sample of small and mid-sized cities. When accounting for aspects of the government’s structure, local department culture, and community demographics, income inequality has a significant, though mixed, effect on civic participation. While changes in a community’s income inequality diminish the likelihood of citizens participating in government decision making, the present level of income inequality correlates with higher rates of engagement.

Keywords

public participation civic engagement income inequality local government

Introduction

Civic participation has long been a hallmark of American democracy with continued importance to the functioning of local governments throughout the nation. Despite its significance to the character and operation of the United States, researchers have generally found participation at all levels to be declining over the past half-century. Stated most forcefully by Robert Putnam (2001) in Bowling Alone, Americans vote less, exhibit lower levels of trust in government, and take part in fewer communal activities since the 1970s. While Putnam’s theory is well known, researchers have subsequently argued that the growth of new means and forums for individuals to connect create opportunities for individuals to build social capital and become politically engaged (Mossberger, Tolbert, & McNeal, 2007; Warren, Sulaiman, & Jaafar, 2014). Furthermore, as policy increasingly shifts toward higher levels of government, citizens have begun to find a greater voice and increased effectiveness in local participation (Dahl, 1994) and toward more “engaged citizenship” (Dalton, 2008, p. 77).

Running parallel with the steep decline in civic participation has been an increase in economic inequality within the United States. At present, levels of income and wealth concentration are at heights not witnessed since the Gilded Age (Hacker & Pierson, 2010). Increases in income inequality have led to concerns about consequences for economic mobility and civic participation, as a result of diminished shared cultural experiences, the concentration of resources, and reduced bridging social capital (Putnam, 2001). A substantial body of literature, particularly at the cross-national level, confirms these fears and shows a strong negative correlation between measures of economic inequality and rates of voting and other forms of civic participation (Solt, 2008; Stockemer & Scruggs, 2012). However, how income inequality influences civic participation at the local level in the United States is unclear. Owing to the expanding availability of income inequality data at local levels and a survey with a sample of managers in small and mid-sized cities, this article studies how growing income inequality affects whether citizens participate in decision making with local governmental departments.

To do so, this article first reviews the existent literature on civic participation at the local level, with a focus on the importance of public engagement and past research on the impact of economic inequity. From the literature, a model is developed comprising income inequality, community demographics, organization culture, and government structure to test using a national survey of managers in five governmental departments. Income inequality is found to have significant, though mixed, effects on citizen participation. The model reveals that higher levels of income equality in the years studied are positively associated with participation. However, cities where income inequality increased in the past decade observed diminished levels of community engagement.

Literature Review

The importance of citizen participation for American governance is well established, nearly to the point of being unassailable as a positive both for governments and the governed (Day, 1997). Despite the challenge of structuring and integrating citizen participation (Abelson et al., 2003; Innes & Booher, 2003), researchers have shown it to produce numerous benefits to local governments. In particular, it has been demonstrated that the process of policy making drives much of the dissatisfaction with politics, rather than the actual policies that are adopted (Hibbing & Theiss-Morse, 2001). Programs often require support from the governed to ensure stability, because society can much better absorb dissatisfaction with specific policies than with the democratic process (Easton, 1965). To that end, the benefits of civic engagement are often framed in terms of the process’ effects on the citizens involved, because participation is argued to make individuals feel more positively about their community and their government (Bloomfield, Collins, Fry, & Munton, 2001; Nelson & Wright, 1995). Although the effects on citizen attitudes toward government may be short lived, civic engagement can often be self-perpetuating for individuals, as demonstrated through minor, structured experiences such as jury duty (Gastil, Deess, & Weiser, 2002), encouraging more and wider participation (Michels & De Graaf, 2010).

While it should be noted that the effect of participation is far more conclusively known for the participants than democracy as a whole (Michels, 2011), researchers have begun to study how civic engagement alters policy outcomes. Fung (2015) in reviewing the literature on the topic argued that having citizens involved in the policy-making process increases the legitimacy of policies, improves the efficiency of government, and helps to elevate social justice concerns. Scholars have shown citizen participation to improve the effectiveness of governance by bringing new voices to the process, making clear citizen preferences, and bringing new expertise to the policy-making process. For instance, when given a chance to participate in comprehensive planning, the resulting plans have been shown to be both stronger and more likely to be adopted (Burby, 2003). However, far from a panacea, not all processes that open deliberations to citizen input are equally well constructed (Burke, 1968). As Irving and Stansbury (2004) show, when technical knowledge is needed, the population is widely dispersed, or too few voices can be heard; the benefits of opening policy processes may not outweigh the costs.

Despite the widely acknowledged importance of civic engagement, since the 1970s, there have been declining levels of direct participation, eroding confidence in elected officials, and a growing cynicism toward institutions of democracy (Dalton, 2013; Putnam, 2001; Skocpol & Fiorina, 2004). One potential, though partial, explanation for the decline in participation is the rise in income inequality, which has been increasing in the United States since the 1970s and correlates cross-sectionally with the decline in social capital and civic engagement (Alesina & La Ferrara, 2000a; Casey & Christ, 2005; Kahn & Costa, 2003; Rupasingha, Goetz, & Freshwater, 2006).

Researchers have most commonly studied income inequality cross-nationally, where a strong negative association was shown between inequality and measures of democracy and civic participation (Lancee & Van de Werfhorst, 2012; Solt, 2008; Stockemer & Scruggs, 2012). A smaller body of literature has studied the effect of income inequality at more localized levels in the United States. For instance, Flavin (2012) found that income inequality reduced representation for those with lower income at the state level and Solt (2010) found that citizens of states with greater income inequality are less likely to vote. Moving beyond cross-sectional studies, Fairbrother and Martin (2013) found that longitudinally there was not a significant effect of growing inequality on trust at the state level. At a substate level within the United States, Alesina and La Ferrara (2000b) found a negative relationship between participation in civic organizations and income inequality. Thus, there is still a need for greater specificity on income inequality at local levels, particularly on how changing levels of income inequality affect civic engagement.

Along with income inequality, socioeconomic status has been an important predictor in both the rate of participation and the size of the role given to citizens (Haeberle, 1987; Mesch & Schwirian, 1996). However, community wealth can have a nonlinear effect. As Oliver (1999) shows, it is actually middle-income areas that had the highest rates of participation, owning to the greater varied interest within those communities. Along with socioeconomic status, education is a strong predictor of engagement both for individuals and at the community level, owing to its association with social capital and the availability of resources to participate (Hauser, 2000).

More populous areas have been shown to have lower rates of participation, a finding that reaches back modernly to Dahl’s (1967) hypothesis about the ideal-sized democratic polity. Oliver (2000) directly studied the effect of population, finding that across several measures of participation, larger cities had lower levels of participation. He attributed that finding to the difference in local mobilization in larger areas, as well as differing levels of interest and the psychological orientation of residents in more populous areas.

However, the makeup, along with the size, has been found to be a critical component of a community’s engagement but there have been mixed findings on how homogeneity influences civic participation. Oliver (1999) found that diversity increased the rate of participation, though subsequent studies have generally not corroborated that finding. Both Alesina and La Ferrara (2000b) and Hill and Leighley (1999) found lower rates of engagement among more racially diverse communities.

In addition to community demographics, researchers have demonstrated the importance of governments and departments in supporting engagement from their citizens. Government structures are important for determining the availability of opportunities as more centralized, and hierarchical governments and departments that give greater authority to top-level management are less likely to receive input from employees or the public (Andrews, Boyne, Law, & Walker, 2009; Zhang & Yang, 2009). The effect of centralization partially relates to the skepticism among professionals with authority toward changes that may threaten their power (Zhang & Yang, 2009), which is also demonstrated by the unwillingness of centralized institutions to adopt technology changes in service delivery (Damanpour, 1991; Mergel & Bretschneider, 2013).

Governmental structures also influence participation through their role in providing and configuring opportunities for their citizens to participate. From the ease of voting (Norris, 2004), to direct democracy (Bowler & Donovan, 2000; Donovan & Karp, 2006), to deliberative governance (Fischer, 2003), how governments structure opportunities and the number of those opportunities presented will influence the level of civic engagement in their communities (Kirlin & Kirlin, 2002).

The level of centralization and openness of government have been shown to influence whether there are opportunities available (Dalton, 2008), but the attitude of government employees affect how often they are utilized. For instance, Yang and Pandey (2011) found that managers, through their commitment and intention to incorporate citizen views in the process, played a substantial role in encouraging civic engagement, a finding that has been supported in subsequent studies (Liao & Zhang, 2012). In addition, Yang and Callahan (2007) found that favorable attitude toward public participation helped to encourage greater levels of community engagement in policy making.

Relatedly, organizations with a greater appetite for risk may be willing to undertake more civic participation in the hopes for improved policy, despite concerns over the potential for delays (Bovaird, 2007). In addition, structures related to the organization of a department (Rainey, 2009) or a government (Hajnal & Lewis, 2003) have been shown to have an effect on participation rates.

Method

Data sources

To test citizen participation at the city level, I use data from a national survey conducted in 2014 and 2016 by the Center for Science, Technology and Environmental Policy Studies at the Arizona State University. The survey was administered to public managers in small and mid-sized American cities with populations ranging from 25,000 to 250,000. In each city, managers from five departments were selected to participate, specifically City Management, Community Development, Finance, Police, and Parks and Recreation, providing a total sample to be surveyed of 2,500. These five departments have been selected for the biennial survey as its original iteration because they were the only government units present in the full sample of cities.

The response rate was 27% in 2016 and 31% in 2014, providing nearly 1,500 total responses to consider across the two most recent iterations of the survey. Because neither participation nor community demographics changed significantly between 2014 and 2016, I use the most recent response for each city and department to avoid double counting any single observation. There are 830 unique department and city observations that are complete, which further breaks down to 132 from City Management, 196 in Community Development, 126 in Finance, 166 from Police, and 210 Parks and Recreation managers.

The survey asked managers about whether “citizens and external stakeholders take part in agency decisions.” The responses were converted from a Likert-type scale to a dichotomous variable that takes a value of 1 if the respondent said very often or often rather than sometimes, rarely, or never. Any observation where the manager responded they did not know the level of participation was removed from the analysis.

To study how income inequality impacts public participation, supplementary data were gathered from the U.S. Census. Observations of the survey of local governments that are only available for 2014 will be matched with 2014 five-year estimates of the American Community Survey. The most recent version of data from the Census is from 2015, so that will be used to estimate community demographics in 2016. Because the survey is conducted at the city level, all census demographics are collected for that level of aggregation.

Income inequality is measured using the Gini coefficient, a measure that reports the difference between a city’s actual distribution of income against a perfectly equal distribution. Ranging from 0 to 1, higher values indicate a greater concentration of income. Income inequality is included as a cross-sectional measure to observe how levels of income inequality affect levels of local participation as well as with a second variable measuring the change in the Gini coefficient for that city since 2007. The Census first released measurements of the Gini coefficient for cities in 2005, and the 2007 three-year American Community Sample Survey presents the first observation with a large enough sample for practical use in this study. Therefore, the change in the Gini coefficient will run from 2007 through 2014 or 2015, depending on the year of observation for each city. The two measures of income inequality showed low levels of correlation (r = .08), allowing for the inclusion of both measures in the same models. Both measures of income inequality are predicted to lower citizen participation.

The socioeconomics of the community is captured using the city’s education level. The rising concentration of wealth in the United States has occurred simultaneously with the increasing clustering of talent, leading to a strong association between education levels in a community and income (Moretti, 2012). Education is measured specifically with the percentage of residents over the age of 25 with college degrees, which should increase engagement and the ability to participate in local issues; thus, it is expected to be positive in the analysis.

The second demographic variable included is the percentage of the population that works in government. Brewer (2003) found that employment in public service was a significant predictor of one’s level of civic participation at the individual level, arguing such citizens act as catalysts for further engagement in the community. Here, the impact of government employment on participation rates is analyzed to test whether those individual effects identified by Brewer extend outward and spillover across a community.

The racial demographics of the city are captured with two variables. The first is a diversity index modeled after a similar measure developed by Brown University’s Spatial Structures in the Social Sciences (S4) initiative. The index measures the evenness of representation in a community across the various racial groups available from the Census (Lee, Iceland, & Sharpe, 2012). However, the diversity index only measures the magnitude of the diversity, not the structure; for example, the index can indicate that one racial group has a large presence in a city, but not the race of that group. Therefore, to more fully account for the demographics of the region, the percentage of African Americans is also included in the model. Because of the systematic barriers that reduce participation from minorities, communities that are more diverse and have higher shares of African Americans are predicted to have lower rates of citizen participation.

The age of the region is also accounted for in the analysis. Older residents are more likely to have the means and time to actively participate in local government (Nachmias & Palen, 1982). Therefore, as a region grows older, it is expected to have higher rates of citizen participation. To account for any potential nonlinearity in the measure, a squared term is included as well.

The final demographic variable included in the model is the total population in the city. Following past research by Oliver (2000) and others, more populous cities are expected to have lower rates of participation.

The survey of local governments also supplied several independent variables to test how agency culture and governmental structure impact citizen participation. The attitude of managers toward public participation is captured through three variables, which are combined into a single measure using principle components analysis (Abdi & Williams, 2010). The three statements asked specifically whether “citizen participation is necessary even if it dramatically slows down government decisions”; “citizen participation increased government effectiveness”; and “citizen participation is relevant only when citizens have sufficient expertise and knowledge.” The final question was inverted so that all three would indicate a positive attitude toward participation. It is expected that departments with managers who are more positive toward participation should see higher rates of citizen participation.

Regardless of the attitude of managers, a department that does not advertise or simplify opportunities to participate is likely to see lower rates of engagement. The survey asked managers about whether Facebook was used to facilitate participation by citizens, which is included to test the effect of department efforts to encourage public engagement. Departments that use social networks to aid engagement are expected to have higher rates of participation.

Centralization within the department should create less room for participation because of the established tension between openness and efficiency (Dahl, 1994; Kweit & Kweit, 1984). As decision making becomes more concentrated, fear of losing control over the policy process increases, slowing or stopping efforts to engage citizen voices in decision making (Moynihan, 2003). Centralization is measured with a question asking whether top management exerts strong control over the organization. The question has a Likert-type scale, which is transformed to a dichotomous variable to indicate whether the respondent agreed or agreed strongly and should negatively predict citizen participation.

Opening department’s processes introduce new risk to an organization that may disrupt normal routines and challenge existing structures. The tolerance for risk in a department is reported by managers with two questions that ask whether employees were willing to take on risk and whether they feared taking on risk. These questions are combined into an equally weighted index, which should positively predict citizen participation.

In addition, there may be an association between the openness of the department to citizen participation and their general openness to other external actors. The survey also asked whether agencies had participation from other governmental and organized interests. The complete list of other actors, which includes 13 groups other than citizens, was divided into three variables using principle components analysis, generally grouped into two components of government actors and a third of nongovernmental actors. The division within the two groups of government actors, as displayed in the summary statistics in Table 1 below, is driven by how often those groups participate in department decision making. Openness to other actors should indicate a more accessible agency and is predicted to be positive for all three variables. The specific factor loadings for these three variables, along with the variable described above for department attitude toward participation, are listed in the online appendix.

Table 1.

Summary Statistics.

Statistic	M	Minimum	Maximum	Prediction
Dependent variable
Citizen participation	0.58	0	1
Income inequality
Gini coefficient	44.22	33.11	59.19	Negative
Change in Gini coefficient	1.52	−4.26	9.77	Negative
Demographics
% college educated	0.21	0.05	0.46	Positive
% government employment	0.05	0.01	0.21	Positive
Racial Diversity Index	0.49	0.03	0.77	Positive
% African American	0.11	0	0.78	Negative
Age	35.55	21.8	54.1	Positive
Population	95,679	24,739	279,427	Negative
Organization culture
Manager attitude	0	−2.13	0.95	Positive
(Attitude) knowledge not necessary to participate	0.65	0	1
(Attitude) participation increases effectiveness	0.69	0	1
(Attitude) participation is necessary	0.73	0	1
Centralization	0.5	0	1	Negative
Risk taking	0.2	0	1	Positive
(Risk) employees are willing to take on risks	0.3	0	1
(Risk) employees fear risk taking	0.33	0	1
Facebook facilitation	0.59	0	1	Positive
Government Participants 1	0	−1.21	3.47	Positive
(Participation) from Mayors Office	0.72	0	1
(Participation) from Governor’s Office	0.6	0	1
(Participation) from other city departments	0.89	0	1
Government Participants 2	0	−2.63	1.77	Positive
(Participation) from State Legislature	0.04	0	1
(Participation) from Federal Departments	0.3	0	1
(Participation) from Internal Staff	0.25	0	1
Nongovernment participants	0	−2.47	2.06	Positive
(Participation) from neighborhood associations	0.43	0	1
(Participation) from news media	0.24	0	1
(Participation) from interest groups	0.34	0	1
(Participation) from religious groups	0.21	0	1
(Participation) from professional associations	0.42	0	1
(Participation) from nonprofit organizations	0.08	0	1
(Participation) from consultants	0.1	0	1
Community Development Department	0.24	0	1
Finance Department	0.15	0	1
City Management Department	0.16	0	1
Parks and Recreation Department	0.2	0	1
Police Department	0.25	0	1
Government structure
Input	0.44	0	1	Positive
Council-Manager	0.72	0	1	Positive
Year (2016)	0.56	2,014	2,016

External governmental structures are also expected to influence the rate of participation for citizens. Citizen participation has been mandated through state and federal laws, and where those laws are in effect, there should be higher rates of participation as citizens respond to increased opportunities. In addition, the form of government has been shown to be an important predictor of civic engagement, as council-manager systems generally draw greater participation because they are less concentrated and represent professional administration of policy (Zhang & Yang, 2009). In this study, cities with council-managers are expected to have higher rates of citizen participation than those run by mayors.

Summary statistics for all variables used, along with their expected direction in the study are included in Table 1. Where multiple variables were combined, the final index is shown with the separate components listed below. Because the dependent variable is dichotomous, a logit regression is used and odds ratios are reported. In addition to the covariates listed above, the five department types and the year of the observation are included as dichotomous variables in the model.

Results

Table 2 reports the results for all six regression models. The separate components of the regression are tested independently, before a full model with income inequality, community demographics, organization culture, and government structure is reported.

Table 2.

Regression Results.

	Dependent variable
	Citizens participated in department’s decision making
	(1)	(2)	(3)	(4)	(5)	(6)
Income inequality	1.027*		1.034**	1.031*	1.034**	1.040**
Income inequality	(0.011)		(0.013)	(0.013)	(0.012)	(0.015)
Change in income inequality		0.948*	0.970	0.925**	0.925***	0.944*
Change in income inequality		(0.020)	(0.021)	(0.022)	(0.021)	(0.024)
% college educated			1.028***			1.030***
% college educated			(0.006)			(0.008)
% government employment			1.046**			1.066***
% government employment			(0.017)			(0.020)
Racial Diversity Index			1.216			1.265
Racial Diversity Index			(0.390)			(0.487)
% African American			0.327**			0.243**
% African American			(0.134)			(0.118)
Age			0.853+			0.877
Age			(0.074)			(0.089)
Age-squared			1.002+			1.002
Age-squared			(0.001)			(0.001)
Population			1.206*			1.261*
Population			(0.105)			(0.128)
Manager attitude				4.324***		4.517***
Manager attitude				(0.755)		(0.814)
Centralization				0.710**		0.663***
Centralization				(0.075)		(0.073)
Risk taking				1.768***		1.672***
Risk taking				(0.240)		(0.237)
Facebook facilitation				1.376**		1.297*
Facebook facilitation				(0.152)		(0.148)
Government Participants 1				0.870*		0.862*
Government Participants 1				(0.055)		(0.057)
Government Participants 2				1.010		1.001
Government Participants 2				(0.085)		(0.087)
Nongovernment participants				1.037		1.038
Nongovernment participants				(0.081)		(0.085)
Finance				0.232***		0.291***
Finance				(0.039)		(0.052)
City Management				0.749		0.936
City Management				(0.134)		(0.176)
Parks and Recreation				0.464***		0.619**
Parks and Recreation				(0.075)		(0.108)
Police				0.104***		0.167***
Police				(0.017)		(0.031)
Input required					4.045***	2.144***
Input required					(0.406)	(0.267)
Council-Manager					1.040	0.825
Council-Manager					(0.114)	(0.106)
2016			0.739**	0.583***	0.757**	0.599***
2016			(0.070)	(0.064)	(0.074)	(0.068)
Constant	0.393+	1.396***	0.379	0.469	0.217**	0.067
Constant	(0.189)	(0.079)	(0.731)	(0.272)	(0.115)	(0.152)
Observations	830	830	830	830	830	830

⁺p < .1. *p < .05. **p < .01.***p < .001.

Both variables for income inequality are shown to significantly impact civic participation in cities, though in opposite directions. Contrary to predictions, the level of income inequality in a community increases the likelihood that a manger reports that citizens participate often or more in their department’s decision making. While that result is unexpected, the positive effect is shown whether the bivariate relationship is analyzed, or if the changes in equality, community demographics, department culture, and government structure are held constant. In the full regression, the odds that a manager reported that citizens participating regularly increased by 1.04 times for each one unit increase in the Gini coefficient, holding all else constant.

However, changes in the Gini coefficient had the opposite effect on civic participation in communities. For every one unit increase in income inequality since 2007, the odds that citizens participated in department decision making were .944 as high, holding all else constant. While the relationship losses significance in the third model when the other demographics are included, the effect of changes in income inequality is generally consistent across the models.

The other community demographics included also influenced a community’s level of civic participation. As predicted, the share of residents with a college education and that were employed in the public sector increased the likelihood that citizens participated in department decision making.

Only one of the variables used to account for the racial dynamics in a community was significant. While cities with a higher share of African American residents had significantly lower rates of civic participation, the racial heterogeneity in a community does not have an effect. Although it cannot be tested in this model why racial differences affect civic participation, it is an important area requiring study to understand the presence of such disparities.

Finally, the total size of the population in a city has a significant and positive effect on participation, perhaps indicating that larger regions provide more opportunities to participate or a larger pool of potential participants.

Organization culture was also shown to be an important predictor of citizen participation. The attitude of department managers has a significant and positive effect on increasing the rate they reported that citizens participated in the department’s decision making at least often. To some degree the effects here may derive from managers that support participation being overly likely to report they observe participation, but the magnitude of the effect, being over 4 times as likely, is unlikely to derive solely from that effect.

The centralization and culture of risk tolerance within a department also had a significant effect. Holding all else constant, more centralized departments were less likely to often have citizens participate in decision making. In contrast, a department that is more open to risk is roughly 1.7 times as likely to have citizens participate at least often, holding all else constant. Similarly, using a social network, specifically Facebook, to facilitate participation has a significant and positive effect on community engagement.

There is mixed evidence on how input from other participants impacts citizen participation rates. With the 13 other participants loaded onto three factors, there was only one that reached statistical significance. Where there is increased input from mayors, governments, and other city departments, there is a lower rate of citizen participation, providing some evidence that departments have limited capacity to absorb input from different actors. However, the other two groups of actors were insignificant, limiting the strength of that finding.

As predicted, having laws that require citizen input on policy-making activities increased the probability of citizens participating often. These laws provide greater opportunities for engagement, and even if those opportunities are not equally meaningful, such laws do increase the rate of participation. However, the other variable for organization structure, whether the city was run by a council-manager or by a mayor, was insignificant.

Finance, Parks and Recreations, and Police departments are all found to be less likely to engage in citizen participation than Community Development departments, while the differences with City Management offices does not reach statistical significance. The final variable included was the year for the observation, which was significant and negative in the models tested. While there is no theoretical reason to have expected participation to decline between 2014 and 2016, it should not go overlooked and may be worthwhile terrain for future research.

Discussion

This article tested how the level and change in income inequality, along with community demographics, organization culture, and government structure, impacted civic participation at the city level. While there is a substantial body of literature that has tested the association between income inequality at the national and state level, less is known about its effects within cities. Surprisingly, the level of income inequality was found to positively predict the level of civic participation in the community. That was true when a simple correlation between the two variables was studied, or when a full model containing government structure, local department culture, and community demographics was tested, indicating that the relationship is fairly robust to different specifications.

How can that finding be reconciled with the existing body of literature that has consistently found a clear and negative association between inequality and civic engagement? One potential explanation would begin by looking at the dependent variable used to operationalize participation. In this study, the dependent variable asked whether citizens participated “often” or “very often” in departmental decision making but does not specify either what constitutes participation and ignores the number of citizens involved. The relationship between participation and economic inequality has often been measured with voting figures, which requires wider levels of participation than direct input to departmental decision making. To that end, income inequality may leave a limited number of residents with more ability to participate, explaining the positive effect in the study.

If that explanation is correct, it would imply that having more income inequality will not create wider or deeper civic participation; just as income inequality concentrates wealth, it may act to concentrate citizen participation. However, the finding for changes in the Gini coefficient weakens the strength of that explanation. While the level of income inequality had a positive effect, increasing a city’s income inequality dampens civic participation. Thus, there is some evidence that inequality is diminishing participation in government and may pose a long-term risk toward the legitimacy of local institutions. However, the two findings for inequality are difficult to reconcile, so testing the relationship with other definitions of participation and economic equality will add further clarity.

The interpretation posited above to explain the relationship between existing levels of income inequality and participation is further supported by the finding for population. While larger regions have generally been found to have lower rates of public participation, the variable was significant and positive in this study. However, it may be that a larger city provides a larger pool of people that may participate, and though participation rates among the population are lower overall, it is more likely that participation will occur as measured in the dependent variable.

The analysis points toward changes that city and department leaders can make to encourage greater civic engagement among their citizens. In particular, departmental culture was shown to be an important explanation of differences in participation rates. Having managers that support participation and encouraging a healthy attitude toward risk within departments increased the likelihood of citizens participating. In addition, the model shows that centralization within a department has the opposite effect. While culture is generally sticky within organizations, this study highlights opportunities to make changes where officials desire to increase citizen participation.

Although less malleable, government structures can also encourage citizen participation. In particular, the presence of a legal requirement to include the public had a positive effect. While some scholars have highlighted the potential detrimental effects of such requirements (Innes & Booher, 2004), particularly if followed in word rather than spirit, these requirements can have a positive effect by widening the scope of opportunities that citizens perceive.

The analysis provides directions to future research on civic participation and changes in communities. There is a need to study how the demographics of those participating differ based on the levels of income concentrations in cities to identify the complete effect of growing inequality. Research on who participants has generally found that participants are whiter, better educated, and have higher incomes than the general public (Verba, Schlozman, Brady, & Nie, 1993), but we do not know if growing income inequality exacerbates these differences. It may also be that as inequality increased, those with means participate differently, either through formal, official channels or informal opportunities. How these opportunities affect other citizens and are reflected in the public’s trust in government is worth considering in future work.

More broadly, as demographics can shift over time, it will be important for governments to know how changing demographics may affect rates of participation in their communities. How do citizens and governments react when their communities become more diverse, are growing in size, or are going through an economic decline? These questions require study. In addition, other measures of economic inequality can be studied as well, such as gentrification, to understand how processes of urban change affect the opportunity and propensity to engage in the policy-making process. Finally, testing how changes in department culture influence rates of citizen participation would add greater causal weight behind the argument for its importance to encouraging civic engagement. These questions generally point toward the need for increased longitudinal research on civic participation at the local level.

This analysis does not come without limitations. The most significant concern arises from the operationalization of the dependent variable. Citizen participation, which is measured based on managers’ perceptions of the public’s involvement in decision making rather than an observation of such participation occurring, has the potential to not align perfectly with reality. However, by converting the Likert-type scale to a dichotomous variable and including the manager’s perception of participation, it is hoped such error has been minimized. Confirmation of the findings presented here using observed data, potentially from elections or other types of participation, will help to further test how inequality affects community engagement.

In addition, there is still the possibility that reverse causality is present. Specifically, it may be that the wealthy have articulated and led the adoption of policies that further concentrated income, leading to the positive correlation. This analysis has tried to account for this potential, by using the change in income inequality as an effect on the level of participation. However, income inequality has been rising for decades, leaving concerns that the process may be cyclical and began outside the period being studied.

Supplemental Material

Appendices_(1) – Supplemental material for Unequal Cities, Unequal Participation: The Effect of Income Inequality on Civic Engagement

Supplemental material, Appendices_(1) for Unequal Cities, Unequal Participation: The Effect of Income Inequality on Civic Engagement by Eric Joseph van Holm in The American Review of Public Administration

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Eric Joseph van Holm

Author Biography

Eric Joseph van Holm, PhD, is a postdoctoral research fellow in the Center for Science, Technology and Environmental Policy Studies (CSTEPS) at Arizona State University. His primary research interests include urban political economy and issues of regional development driven by science and technology. He received his doctoral degree in public policy from Georgia State University and the Georgia Institute of Technology.

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