LA BONDAD Y LA CLARIVIDENCIA DE A. REINACH

Before proceeding with the full structural model, we first constructed a measurement model inclusive of the two latent constructs—fiscal distress and economy—described earlier.

Individual factor loadings for each construct were examined (four for fiscal distress and three for economy) and the overall fit of the model was assessed using common goodness of fit statistics.

As shown in Table 3, all fit statistics (χ2=10.387, df=13, p=0.662, RMSEA=0.000, CFI=1.000, TLI=1.008) are well within the acceptable range suggesting that the hypothesized measurement model fits the data well. Although factor loadings are lower (<0.40) for two of the four fiscal distress measures (hiring freezes and layoffs), we decided to retain all four indicators due to their theoretical relationship to the underlying concept and the overall model fit statistics.⁶

[Insert Table 3 About Here]

Structural Model

The next step involved testing the full structural model shown in Figure 1.⁷ Results are displayed as Model 1 in Table 4. The model (inclusive of both measurement and structural

components) fits the data according to goodness-of-fit statistics (χ²=73.898, df=55, p=0.045, RMSEA=0.029, CFI=0.963, TLI=0.953). A review of individual parameters shows only partial support for Levine’s (1978) arguments. As expected, the local economy (β= -0.544, p<0.001) and crime rate change (β= -0.129, p<0.05) are both negatively related to fiscal distress within large local municipal police agencies. Organizations are less likely to experience the detrimental effects of the great recession if they operate within stronger local economic environments

characterized by higher employment rates, rising home values, and a stronger GDP. Similarly, community need inoculates organizations from fiscal distress, even after accounting for the local context. Large increases in serious crime rates between 2007 and 2011 also buffered

departments from major cutbacks. In contrast, drops in crime are associated with greater fiscal distress. Among the four indicators of political vulnerability and two indicators of organizational atrophy, only organizational size is significantly related to fiscal distress. Larger organizations are more likely to experience some combination of salary reductions, furloughs, hiring freezes, and layoffs. Overall, Model 1 accounts for approximately 45 percent of the variation in the fiscal distress latent construct.

[Insert Figure 1 About Here]

[Insert Table 4 About Here]

We estimated a second model (see Model 2 in Table 4) based on software-produced modification indices, suggestions for additional paths or constraints designed to improve overall model fit (see Gau, 2010; Schumacker & Lomax, 2010). Adjusting models based on empirical data should be done cautiously and with relevant theory in mind to avoid producing a

strong-fitting model unable to be reproduced with different samples. Although Model 1 fit the data, we added a single path based on the suggested modification index—a pathway connecting

government form with the unobserved latent economy construct. This allows us to estimate the same parameters as in Model 1 but also examine the indirect relationship between government form and police department fiscal distress through the local economy. The results in Table 4 show that there is only a slight improvement in overall model fit from Model 1 (χ²=60.811, df=54, p=0.244, RMSEA=0.017, CFI=0.987, TLI=0.983) with the addition of the new direct path (government form>economy) and indirect path specification. Interestingly, while a council-manager form of government is typically associated with “sound budgeting and accounting practices” (Levine, Ruin, & Wolohojian, 1981, p. 620), the results here suggest that the government form is linked to weaker local economic conditions (β= -0.180, p<0.01) and, indirectly, local police agency fiscal distress (β= 0.100, p<0.01).

A final model was estimated to further explore Levine’s (1978) notion of problem depletion. In the present study, problem depletion is operationalized as the percent change in UCR Part I crime rates between 2007 and 2011. We operate under the assumption that police departments increase their exposure to cutbacks during times of fiscal austerity when the problems they are designed to handle become less pressing. By accounting for percent change, we can measure the fluctuations in the magnitude of a jurisdiction’s crime problem over a relatively short period. Indeed, the results in Models 1 and 2 indicate that departmental distress is more common in agencies experiencing the greatest drops in crime during the period. Note, however, that the operationalization only considers the change in crime rates, not the absolute magnitude of the problem. We estimated the indirect path model a second time (reproducing Model 2), substituting 2011 crime rates for the percent change in crime rates from 2007-2011.

As predicted by Levine’s (1978) theory, the absolute magnitude of the problem is less important than its change over time. The revised model (not shown) does not fit the data as well as Model 1 or 2 (χ²=77.711, df=54, p=0.019, RMSEA=0.032, CFI=0.944, TLI=0.957) and the 2011 crime rate variable is not a significant predictor of fiscal distress (β= -0.061, p>0.05).

DISCUSSION & CONCLUSION

Our goal in this study was to examine the relationship between environmental indicators of financial turbulence, structural arrangements of police departments, and fiscal responses by those agencies to economic hardship. Using Levine’s (1978) organizational decline typology, we found that both environmental and size variables affect agency responses.

First and foremost, we found that police departments operating within areas where the economy remained strong were the least likely to experience decline during the Great Recession.

This is intuitive, and on the surface, not something that police agencies have much control over, however, there are steps that police departments can take to prepare for these inevitable

fluctuations in economic conditions. For example, agencies with more slack resources may be able to withstand economic turbulence for longer periods of time before actively making cutbacks. Ironically, this can penalize the most efficient organizations, who tend to use all of their resources efficiently. Perhaps agencies that are best able to come in under budget can use some of these slack resources to prepare for potential hardships.

We also found that police departments operating in contexts with rising crime rates were less likely to make cuts. Where crime rates are high, more officers are needed to address this problem, both proactively and reactively. With falling crime rates, agencies may be able to survive with smaller numbers of officers, and some of these agencies may even be absorbed into

larger agencies (Brunet, 2015). Thus, the response to financial hardship may be influenced by the demand for the services that the organization provides.

With the exception of organizational size, we did not find evidence of any direct

relationships between our measures of political vulnerability and fiscal distress; however, we did find that council-manager government forms are less likely to appear in places where the

economy is doing well. This finding was unexpected, but is explainable in that our measure of economic well-being is linked more closely to individual economics (e.g., housing values, employment rates) than government resources. It could be that while the economy has improved broadly, more resources are not necessarily available at local government levels. Alternatively, the role of city managers may be overstated. Perhaps council-manager governments are not enough to prevent local economic downturns. However, the presence of a city manager may allow for “quick and effective retrenchment action” in the face of a recession, adapting more quickly than other jurisdictions (Levine, Rubin, & Wolohojian, 1981, p. 626).

Finally, we found that larger agencies, employing more officers were more likely to experience fiscal distress. These larger departments may be better able to withstand some belt-tightening by simply asking some of their remaining officers to do more. It is less likely that larger departments disappear altogether, so in order to remain functional, they might have to look to measures such as hiring freezes, layoffs, or salary reductions. Larger agencies may be better situated to survive economic challenges, but that doesn’t mean that they won’t be forced to adapt (see King, 2014).

Our study was not without limitations. While we merged multiple iterations of the LEMAS survey together, we were only able to examine our variables cross-sectionally. This is because the items that appear in the different waves of the LEMAS are not necessarily

consistent. For example, the 2007 LEMAS survey includes a measure of the number of

substations, which allows for measurement of spatial complexity. The 2013 LEMAS contains no such measure, so it is not possible to examine changes in this construct across the waves. As such, a longitudinal examination of police agencies (see King, 2009) using data from the LEMAS series is quite challenging. Ideally, we could examine whether agencies that have become more complex experience more financial distress. The answer to this question is not possible given the data at hand.

We were also lacking some measures that could help us apply Levine’s typology to police agencies (see Brunet, 2015). Measures of the age of the organizations in our sample, and whether there was some type of political changeover would help us further develop the political vulnerability concept, which received only indirect support in our study. Moreover,

organizational-level information regarding retirements, turnover, misconduct, or slack resources would help examine organizational atrophy more effectively. Even when economic

circumstances are challenging, a large number of retirements and voluntary resignations may prevent the organization from taking more formal measures such as layoffs or salary reductions.

It is also possible that police departments begin to mirror each other in attempts to successful address organizational decline and economic turbulence. The literature on

isomorphism among organizations suggests that this process can be coercive when organizations change due to pressures from larger, more powerful organizations, or it can be mimetic if it results from one organization imitating another (see Burruss & Giblin, 2014; DiMaggio &

Powell, 1983). In both cases, police organizations experiencing decline are likely to follow the lead of those agencies which have provided an effective blue-print for addressing such decline.

We did not have any measures of this potential process.

In addition to examining the relationship between organizational decline and police organizational structure longitudinally, future researchers may examine whether a reciprocal relationship exists between fiscal distress and organizational structure. That is, do agencies that experience fiscal distress become less complex in the future? Moreover, what long-term effects might fiscal distress have on police effectiveness and/or police legitimacy? We believe that a number of policing outcomes may be influenced by the economic stability of the police agency.

To conclude, our study examined how both police organizational structure and

environmental economic conditions affect fiscal decisions by police departments. We found that both economic conditions, and factors linked to the organizations themselves predict responses.

In a social reality where economic conditions will continuously ebb and flow, it is important that police agencies have plans in place to adapt to economic turbulence.

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Table 1. Descriptive statistics for endogenous and exogenous variables

Table 2. Correlation matrix and collinearity statistics for study variables

1 2 3 4 5 6 7 8 9 10

1

Median home value

change 1.000

2 GDP change 0.629 1.000

3 Employment rate 0.529 0.445 1.000

4 Crime rate change 0.034 0.038 0.063 1.000

5 Government form -0.156 -0.196 -0.114 -0.104 1.000

6 Funding variety -0.091 -0.044 -0.065 -0.030 0.048 1.000

7 Community policing -0.110 -0.078 -0.017 -0.008 0.172 0.024 1.000

8 Organizational size (logged) 0.005 -0.033 -0.028 -0.030 -0.180 0.111 0.153 1.000

9 Horizontal complexity -0.102 -0.135 -0.103 -0.004 0.076 0.160 0.292 0.639 1.000

10 Formalization -0.086 -0.032 -0.050 0.006 0.027 0.000 0.166 0.262 0.289 1.000

VIF¹ 1.94 1.78 1.42 1.02 1.16 1.04 1.13 1.91 1.99 1.11

1 VIF based on sample of n=391 after listwise deletion.

Figure 1. Theoretical model of fiscal distress and hypothesized relationships

Table 3. Fiscal distress and economy measurement model estimates

Fiscal distress Economy

Indicator Item loading Indicator Item loading

Salary reductions 0.828

Median home value

change 0.877

Furloughs 0.759 GDP change 0.712

Hiring freezes 0.399 Employment rate 0.623

Layoffs 0.355

χ²=10.387, df=13, p=0.662, RMSEA=0.000, CFI=1.000, TLI=1.008

Fiscal distress/Economy R = -0.552

Table 4. Estimates and fit indices for fiscal distress structural model¹

Model 1 Model 2

β S.E. β S.E.

Government form>economy -0.180** 0.061

Government form>economy>fiscal distress 0.100** 0.036

(indirect)

1 Measurement model parameters omitted.

1 As an anonymous reviewer pointed out, it is possible that certain agencies (e.g., more complex agencies) may be more likely to utilize non-sworn personnel, who may serve as specialists or experts. Cutting these employees would likely have a different effect than cutting other officers who may lack this level of expertise. Unfortunately,

1 As an anonymous reviewer pointed out, it is possible that certain agencies (e.g., more complex agencies) may be more likely to utilize non-sworn personnel, who may serve as specialists or experts. Cutting these employees would likely have a different effect than cutting other officers who may lack this level of expertise. Unfortunately,

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