Weathering the Storm: The Impact of Cutbacks on Public Employees

Abstract

The United States saw mass layoffs and unemployment during the Great Recession, where jobs have been slow to recover especially in the government sector. Research on cutback management became widespread in the late 1970s into the 1980s and several researchers have called for attention to be reignited to determine what lessons can be applied to the Great Recession and beyond. However, little attention is paid to the influence of cutbacks on employees. How do layoffs impact public personnel? Using nationally representative employment data, this study examines sector differences in job loss, advance notice, job mobility, and sector switching. In addition to distinctions across job sectors, differences within the government sector across federal, state, and local employees are explored. Findings raise several questions for research and practice regarding the ability to recover staff in a timely manner, the diversity of the organization, and the capacity to cope with future crises.

Keywords

layoffs job loss staffing recession sector switching

The Great Recession was the longest and largest recession in the United States since the 1980s. During this time, December 2007 to June 2009, the United States saw mass layoffs and high levels of unemployment. Despite the Great Recession officially ending in June 2009, unemployment rates peaked at 10% in October 2009 (U.S. Bureau of Labor Statistics, 2012b). During the Great Recession and throughout the jobless recovery, organizations face cutback management decisions similar to those faced during the late 1970s and 1980s during the time of retrenchment and organizational decline. Scholars (i.e., Bozeman, 2010; McKinley, Latham, & Braun, 2014; Pandey, 2010; Raudla, Savi, & Randma-Liiv, 2015; Schmidt, Groeneveld, & Van de Walle, 2017) have called for a renewed interest in cutback management to see what lessons from the past can help guide managers through the recent economic downturn, but little attention has been given to the impact of such decisions on public personnel. The environment of cutback management during the Great Recession differs from the context of the studies of the 1970s and 1980s. Today’s public managers operate in a more complex context with an increasing use of networks and contracts to deliver public services. Employees now have less job security, both in the public sector as states and localities move toward at-will employment and in the private sector as states legislatures pass right-to-work laws.

The influence of job loss and employee mobility has implications beyond the Great Recession as employment in the government sector—across all levels of government—has yet to return to prerecession levels, as shown in Table 1. Cutback management decisions have grave consequences for displaced employees, but may matter even more in the government sector when employment has not bounced back as quickly as the private sector.

Table 1.

Employment Trends by Job Sector 2008-2015, in Thousands.

	2008	2009	2010	2011	2012	2013	2014	2015	Percent change
	2008	2009	2010	2011	2012	2013	2014	2015	2008-2015
Unemployment rate	5.0%	7.6%	9.8%	9.2%	8.3%	8.0%	6.6%	5.7%
Private sector employment	115,977	111,398	107,226	108,562	111,262	113,416	115,831	118,892	2.51
Government employment	22,388	22,579	22,491	22,264	21,949	21,877	21,811	21,901	−2.18
Federal	2,738	2,786	2,860	2,874	2,832	2,807	2,731	2,728	−0.37
State	5,148	5,206	5,145	5,139	5,047	5,033	5,081	5,081	−1.30
State (excl. education)	2,817	28,22.8	27,85.5	27,36.4	26,75.1	26,62.6	26,51.6	26,46.4	−6.06
Local	14,502	14,587	14,486	14,251	14,070	14,037	14,027	14,092	−2.83
Local (excl. education)	64,48.3	65,02.5	64,17.9	63,02.5	62,68.8	62,61.5	62,62.3	62,94.3	−2.39

Source. Bureau of Labor Statistics (2008-2015) Current Population Survey, January, and Current Employment Statistics Survey, January, Seasonally Adjusted.

This study focuses on one cutback method following the Great Recession: layoffs. How did employees in the government—federal, state, and local—and nonprofit sectors fare during the Great Recession compared with those in the for-profit sector? To answer this question, this study first examines the incidence of job loss and whether advance notice was given across sectors and levels of government. Second, employee decisions following job loss are examined across sectors and levels of government, including worker mobility and future job sector choice.

Findings have implications for research and practice on losing and recovering human capital. First, are government agencies and nonprofit organizations better able to protect their employees from job loss than for-profit organizations? Second, the social and political consequences of downsizing are different in the government and nonprofit sectors compared with the for-profit sector. For-profit sector downsizing is about economics, whereas public sector downsizing focuses on waste and inefficiency. For example, shortly after the inauguration, President Trump issued a memo placing a hiring freeze on the federal government (White House, 2017). Cutback management actions in the government may be more about politics than economics, which can have grave repercussions. Government positions tend to be more difficult to recover, yet the public is reliant on the same level of public services. Third, loss of government employees may reduce the ability of the government to cope with future crises. Finally, layoffs may inhibit valuable diversity efforts, as past work (Holzer, 1986; Levine, 1978; Rubin, 1985) and these findings suggest. The next section provides an overview of the context and use of layoffs during times of recession and is followed by a discussion of the hypotheses, methods, and results, concluding with implications and issues for the consideration of both scholars and public managers.

Cutback Management and Organizational Decline

Despite calls to reignite and further develop the scholarship on cutback management from the late 1970s into the 1980s (i.e., Bozeman, 2010; McKinley, Latham, & Braun, 2014; Pandey, 2010; Raudla, Savi, & Randma-Liiv, 2015; Schmidt et al., 2017), little empirical work has been done to examine cutback management strategies and their influence on organizations and employees, especially in the United States. This study examines layoffs, one cutback management decision, and the influence of layoffs on displaced workers, but first, what do we mean when we talk about cutback management? Here, Levine (1979) defines it, stating

Cutback management means managing organizational change towards lower levels of resource consumption and organizational activity. Cutting back an organization involves making hard decisions about who will be let go, what programs will be scaled down or terminated, and what clients will be asked to make sacrifices. (p. 180)

The recent recession and the retrenchment era of the 1970s and 1980s are examples of environmental entropy of the external, economic environment causing public organization decline (Levine, 1978). Similarly, Cameron, Kim, and Whetten (1987) define organizational decline as “a condition in which a substantial, absolute decrease in an organization’s resource base occurs over a specified period of time” (p. 224). McKinley, Latham, & Braun (2014) build upon this definition to include at least 2 years of successive decreases to allow sufficient time for the decline to be noticed by managers and to trigger a response.

Both the organizational decline and cutback management literature draw upon organization-environment and uncertainty theories. Cameron et al. (1987) find that organizational members are affected by times of decline, but not turbulence, whereas top-managers are affected by turbulence rather than decline. During times of decline, organizational member responses illustrate several negative influences of decline, such as low morale, resistance to change, and fragmented pluralism. The negative reaction of organizational members to decline may be the result of members feeling vulnerable to cutback management and decline strategies as they disproportionately absorb the costs of decline and resource scarcity. Levine’s (1979) participation paradox may also help explain this discrepancy as during times of decline, managers involved in cutback decision-making will fight to keep their positions, whereas organizational members have little say in such decisions. Meanwhile, during times of turbulence, top-managers have negative responses, such as centralization, absence of long-term planning, nonselective cuts, turnover of top administrators, and loss of leadership credibility. This is perhaps to be expected as turbulent times require management action and activate the buffering function of management (Thompson, 1967).

Most of the recent studies of cutback management have been outside the United States. Examining decision-making following the Great Recession across 17 European countries, Raudla, Douglas, and colleagues (2015) find organizations with many goals and clear sanctions have greater centralization. Kickert and Randma-Liiv (2017) find politics plays a role in fiscal consolidation across 13 European countries. Examining the Dutch public sector, Van der Voet and Vermeeren (2017) find that cutbacks reduce organizational commitment, but not work engagement. In a study of Estonia, Savi and Randma-Liiv (2015) find that short-term cuts remain in place longer than initially planned, illustrating that cutback management decisions can have lasting effects on public administration. Similarly, the case of Ireland illustrates that “most attention has been on budgetary reductions, with consequent decreases in organizational capacity” (Robbins & Lapsley, 2014, p. 95). The Great Recession sparked centralization and cutbacks that can have lasting effects for the government capacity. Yet we know little about the impact of the recession on public personnel in the United States.

Layoffs in the Public and Nonprofit Sectors in Times of Recession

Layoffs are an appealing management tool to cope with times of resource scarcity and decline. Levine (1978) offers five cutback management strategies: seniority, hiring freeze, even-percentage-cuts-across-the-board, productivity criteria, and zero-based budgeting. Seniority systems cut the newest employees to the organization, where this “first in, last out” rule tends to disproportionately harm women and minorities (Levine, 1978). Hiring freezes rely on natural attrition to reduce the size of an organizations workforce but lacks long-range planning, may leave skill gaps, and could also influence diversity efforts. Across the board cuts have fewer decision-making costs, but passing decision-making to lower levels of the organization lacks strategic planning. Productivity criteria cut low performers but are “insensitive to differences in clients served, unit capacity, effort, and need” (Levine, 1978, p. 322). Zero-based budgeting is future-directed and considers both the intensity of need and activity levels. Perhaps not surprisingly, employees are one of the first targets for reducing costs across cutback management strategies.

Strategic management of human resources should factor into any cutback management decision. Public and nonprofit organizations are labor intensive with 50% to 80% of their budgets dedicated to employees (Pynes, 2013). Employers often prefer to use layoffs rather than changing wages or hours of employees (Bewley, 1999). In addition, “wages on most jobs are sticky—they are adjusted infrequently and so do not respond quickly to changing demand and supply conditions” (Diamond, 2011, p. 1058). Layoffs or large reductions in force are a fast, visible, and seemingly equitable way to cut an organization’s budget. Such characteristics are beneficial to public organizations with political concerns in handling the situation with speed, apparent equity, and in a way that is visible to constituents.

However, layoffs come at a cost. Organizations not only spend immediate resources administering the cuts and paying unemployment compensation, but also face several incremental costs such as greater resistance to change, increases in grievances or even lawsuits contesting layoffs, and higher voluntary employee exits as result of job insecurity (Greenhalgh & McKersie, 1980). Social costs may also result from damage to the employer’s image (Greenhalgh & McKersie, 1980). Layoffs lead to drops in employee morale and productivity as employees question their self-worth and become uncertain about their futures (Behn, 1980; Cayer, 1986; Greenhalgh & McKersie, 1980; Levine, 1979). The diminished opportunities for advancement and the lack of job security reduce organizational trust (Ingraham & Barrilleaux, 1983) and commitment (Van der Voet & Vermeeren, 2017). Layoffs cost organizations time, money, and employees leading to a loss of employee morale, trust, and productivity.

In addition, while layoffs may appear equitable by employing across the board cuts, such cuts disproportionately affect women and minorities. The first employees let go are typically probationary personnel, nonveterans, and those with less seniority (Holzer, 1986; Levine, 1978; Rubin, 1985). Similarly, granting managers the flexibility to lay off employees using criteria based on the needs and interests of the organization seems quite fair on the surface, but could be manipulated by managers to get rid of unpopular employees (Cayer, 1986). Along the lines of equity theory (Adams, 1965), the perceived fairness of workforce adjustment practices influences the job insecurity of employees that can lead to reduced productivity, increased turnover, and resistance to change (Greenhalgh, 1983). If employees perceive the discharge of coworkers to be unfair, the loss of organizational truth, employee morale, and productivity worsens. This leads one to wonder, “How did employees in the government and nonprofit sectors fare during the Great Recession compared to those in the for-profit sector?”

Research Questions

To examine how employees fared across job sectors, this study first examines job loss. Second, sector differences in the implementation of layoffs are examined by whether employees were given advance notice. Finally, this study focuses on how job loss following the Great Recession impacted employees by examining mobility, both relocation and sector switching. Because government employees at the federal, state, and local level operate in distinct contexts, this study explores potential differences across levels of government.

Job Loss

Employees have different levels of job security and protections across job sectors, and even levels of government. At the federal level, four factors must be considered in determining which employees should be let go for a reduction in force: tenure of employment, veterans’ preference, length of service, and performance ratings (5 CFR 351). Public organizations also face greater resistance to layoffs than private organizations as interest groups, the agencies, clientele, and unions will resist reductions in force that affect their interests (Cayer, 1986). Public agencies are less likely to adopt severe workforce reduction strategies than for-profit firms because inequitable personnel policies may threaten tax holder support, the relative job security of civil service regulations, and the comparatively less competitive environment (Greenhalgh, Lawrence, & Sutton, 1988). Considering job security and resistance to layoffs, government employees may be less likely to face job loss than those in the for-profit and nonprofit sectors.

However, public managers at the federal, state, and local level have different tools available to address budget shortfalls, face distinct budget requirements, and each have their own civil service systems. Although some government employees may be shielded from layoffs to cope with times of scarcity thanks to the protections of civil service and merit systems, state government employees in Florida, Georgia, and Texas are subject to at-will employment as well as many local government employees. Employment law varies across states, where there are now 28 right-to-work states that prohibit union security agreements. In addition, many states and localities have balanced budget provisions. Public managers faced with the requirement to balance the budget may be left with no choice but to cut some employees. Cities are more likely to turn to employment cuts rather than salary cuts during times of fiscal stress (Lewis, 1988). In addition, participatory cities, those where citizens participate in budgetary decision-making, are more likely to adopt contentious budget strategies, including laying off employees, compared with nonparticipatory cities (Jimenez, 2014). State and local governments, during the Great Recession and recession of the early 2000s, favored budget cuts and restructuring over tax increases compared with earlier recessions (Scorsone & Plerhoples, 2010). Meanwhile, the U.S. Office of Personnel Management (2009) recommends a number of means for the federal government to avoid layoffs, including detailing employees to other agencies, encouraging employees to change to a lower pay grade voluntarily, promoting early retirement, and encouraging a voluntary reduction of hours. Within the government sector, perhaps local government and state government employees were more vulnerable to being let go due to balanced budget requirements and greater flexibility in their civil service systems.

Research Question 1: Are government employees less likely to face job loss and does job loss vary across levels of government?

Cutback management studies of the past warned about the negative impacts layoffs could have on diversity efforts. The logic being that because women and minorities tend to be the most recently hired, they are most vulnerable to layoffs (Holzer, 1986; Levine, 1978; Rubin, 1985), but does this hold true today? Diversity brings numerous benefits and many workplaces have evolved from a focus on nondiscrimination to fostering inclusion.

Research Question 2: How does the job loss of women and minorities compare across job sectors?

Advance Notice

Advance notice is a means to help displaced workers cope with job loss and find a new job in a timely manner. Notice reduces the amount of time displaced workers are unemployed and increases the chances of finding a job (Ruhm, 1992, 1994) and longer written notice may help employees avoid unemployment altogether by moving directly into a new job (Addison & Portugal, 1992). Employers who provide advance notice not only give the displaced worker time, but also often provide services, such as job counseling or skill retraining. Aside from the benefits to the individual displaced workers, procedural justice, like advance notice, is positively related to trust in the organization (Brockner et al., 1994).

Federal regulations dictate the requirements for advance notice for employers. The Worker Adjustment and Retraining Notification (WARN) Act of 1988 requires employers with 100 or more employees to provide notice 60 days in advance for plant closures or massive layoffs (Employment and Training Administration, 2003). Upon receiving a WARN notice, the State Rapid Response Dislocated Worker Unit works with the employer to provide information to affected employees about employment and training services, such as job search and placement assistance. WARN provides employees who will soon be displaced with access to state services to aid with the transition. Workers, representatives, and local government agencies may file individual or class action lawsuits for violations of WARN requirements to the U.S. district courts. Some states have their own WARN legislation that may require advance notice for smaller employers, such as those with 75 or more employees in California or those with 50 or more employees in New York, but a majority of states do not have their own policies so defer to the federal WARN Act. While the Act requires private sector organizations, both for-profit and nonprofit, to provide notice and services to a large number of displaced workers, federal, state, and local government employees are not covered. Because of the legal requirements to provide advance notice when foreseeable for the private sector, both for-profit and nonprofit, perhaps these employees are more likely to receive advance notice than government employees.

Research Question 3: Does advance notice vary across job sectors?

Relocation

Historically, labor mobility has helped the United States recover from economic downturns. Because the dominant adjustment mechanism for recessions is labor mobility, rather than job creation or job migration, the United States has been able to recover faster than European nations, with less mobile workforces (Blanchard & Katz, 1992). However, U.S. worker mobility has declined in recent decades, especially following the recent recession. According to Frey (2009), overall migration in the United States reached its lowest point since World War II in 2008 where only about 12% of Americans changed residence annually compared with 17% in the 1990s and nearly 20% in the 1950s. The decline in relocation is likely tied to several recent factors that have only been exacerbated by the Great Recession. First, the housing market crisis has led homeowners to be less mobile because homeowners with negative equity are hesitant to sell their houses and move elsewhere. Second, the market crisis created economic distress in areas that typically see growth, such as Florida, Nevada, and Arizona (Frey, 2009). Finally, the recession reduced job opportunities across the country. Therefore, the traditional geographic mobility option for displaced workers now faced the triple threat for homeowners to find financing in a tough credit market, sellers to get a good value for their home in a depressed housing market, and individuals to find jobs in a less than plentiful job market. In addition, people living in different areas of the country may have varying levels of mobility available to them, where there may not be sufficient incentives for workers to relocate in search of a new job (Diamond, 1982). Labor mobility seems to have decreased across all sectors in light of the housing crises, where no differences are expected across sectors or levels of government.

Research Question 4: Does labor mobility vary across job sectors?

Sector Switching

While people may be more hesitant to relocate for a job, they may be more willing to look for a job in a different job sector. For example, Frederiksen and Hansen (2017) find sector switching accounts for a growing percent of all job mobility in Denmark. Although government employees tend to stay in the government sector to help others (Georgellis, Iossa, & Tabvuma, 2011; Hansen, 2014), how does job loss influence sector dedication? Nonprofit employees tend to work in the sector because they find the work meaningful (Leete, 2006; Mirvis & Hackett, 1983) and those who work in the nonprofit sector tend to stay there (Tschirhart, Reed, Freeman, & Anker, 2008). However, Johnson and Ng (2016) find nonprofit managers intend to leave the sector in search of higher compensation. Job loss may lead employees to look elsewhere. Piatak (2017) finds federal government and nonprofit employees to be more likely to change job sectors during the Great Recession. Perhaps employees in the government and nonprofit sectors are more likely to search for a job in a different sector after losing their intrinsically satisfying position.

Research Question 5: Are government and nonprofit employees more likely to change job sectors?

Method

This study focuses on the January 2012 Displaced Worker, Employee Tenure, and Occupational Mobility Supplement of the Current Population Survey to see how the employment situations of nonprofit, government, and for-profit employees compared during the recent recession. The Current Population Survey is a monthly household survey of about 60,000 households conducted by the U.S. Census Bureau for the Bureau of Labor Statistics that provides nationally representative information on employment and labor characteristics of the population of the United States (U.S. Bureau of Labor Statistics, 2012a). A multistage probability sample based on the results of the decennial census covering all 50 states and the District of Columbia is used for the Current Population Survey. For the January 2012 basic Current Population Survey, the household-level response rate was 90% and the person-level response rate for the Displaced Worker, Employee Tenure, and Occupational Mobility Supplement was 95%.

These analyses are based on the responses of 51,964 respondents, who are adults 20 years of age and older who were asked both the monthly employment questions and the January 2012 Displaced Worker, Employee Tenure, and Occupational Mobility Supplement survey questions. The sample excludes individuals who are self-employed and those who work without pay because sector of employment is the key variable of interest. The sample consists of 4,106 nonprofit employees, 9,044 government employees, and 38,814 for-profit employees. Among government employees, 18% work at the federal level, 32% at the state level, and nearly half work at the local level. The key independent variables are sector indicators, which take on a 1 if the individual works in that sector and a 0 otherwise. Sector indicators are included for the nonprofit sector and government sector compared with the for-profit sector as well as for each level of government—federal, state, and local.

Several employment situations are examined in this study to explore whether employees in the government and nonprofit sectors fared differently than for-profit sector employees during the recent recession and jobless recovery. First, job loss is examined. Here respondents were asked,

During the last 3 calendar years, that is, January 2009 through December 2011, did you lose a job, or leave one because: your plant or company closed or moved, your position or shift was abolished, insufficient work or another similar reason?

Job loss is examined for the entire sample to see whether managers in certain sectors were more likely to resort to closures and massive layoffs.

Next, the process of being displaced and the characteristics of displaced workers are examined. This study explores whether displaced workers in different sectors are more or less likely to receive advance notice, where respondents were asked: “Had you been given written advance notice informing you that (fill: the plant or business would be closed / you would lose your job)?” Job mobility is also examined where displaced workers relocate in pursuit of a new job. Here respondents were asked, “Was the reason for the move to look for work or to take a different job?”

Finally, this study examines the sector dedication of those displaced workers who were able to find another job and reported being employed in January 2011. Sector switching is examined by comparing the original job sector of the respondent to the job held a year ago in January 2011. Sector switching is measured as an indicator variable that takes on a 1 if the sector of the first job differs from the January 2011 job sector and a 0 otherwise. Table 2 shows the differences in job loss, advance notice, job mobility, and sector switching across sectors and levels of government.

Table 2.

Dependent Variables by Sector and Level of Government.

Sector employment	Lost job	Advance notice	Moved	Sector switcher
Sector employment	n = 51,964	n = 5,986	n = 5,986	n = 1,421
Local government	6%	24%	5%	79%
State government	7%	29%	9%	62%
Federal government	7%	22%	7%	71%
Nonprofit	8%	20%	4%	73%
For-profit	13%	21%	6%	14%

Several control variables are used in the analyses to isolate the impact of employment sector on job loss, advance notice, job mobility, and sector switching. The sociodemographic controls to account for individual worker characteristics are age, marital status, gender, whether the respondent has a child below the age of 18, race/ethnicity, education level, and a metropolitan area indicator. Descriptive information on each of these variables is shown in Table 3. State fixed effects are also included to account for any political or cultural impacts, which is especially relevant as some areas of the United States were hit harder than others or at least at different times during the recent recession and recovery period. States also have their own employment laws, where state fixed effects controls for differences in right-to-work laws and at-will employment, for example. Finally, in response to calls to account for other factors, such as industry, in examining sector differences (i.e., Rainey, 2009), this study includes both industry¹ and occupation² indicators using the major group Bureau of Labor Statistics classifications. This controls for other factors, such as the nature of the position, that may influence job outcomes rather than job sector.

Table 3.

Descriptive Statistics (N = 51,964).

Variable	M	SD	Minimum	Maximum
Job loss	.115	.319	0	1
Advance notice	.025	.155	0	1
Relocated	.006	.079	0	1
Sector switcher	.980	.140	0	1
Nonprofit sector	.079	.270	0	1
Local government	.086	.281	0	1
State government	.056	.230	0	1
Federal government	.032	.176	0	1
Female	.495	.500	0	1
Married	.573	.495	0	1
Has own child below 18 years	.351	.477	0	1
Hispanic origin	.118	.323	0	1
White	.826	.379	0	1
Black	.096	.295	0	1
Less than high school	.073	.261	0	1
High school graduate	.073	.261	0	1
Bachelor’s degree	.225	.418	0	1
Graduate school	.122	.327	0	1
Age²	2003.72	1186.77	400	7,225
Age	42.72	13.35	20	85
City/metropolitan	.802	.399	0	1

Because each of the dependent variables are binary variables, logistic regression is used to examine how employment sector and level of government relate to job loss and characteristics of displaced workers. A logistic regression is used for each of the outcome variables: job loss for the entire sample, advance notice among displaced workers, job mobility for displaced workers, and sector switching among displaced workers who are reemployed. The model includes the sociodemographic controls, industry and occupation indicators, and state fixed effects to examine how the outcomes vary for nonprofit and government employees compared with the for-profit sector. This model is examined for each of the dependent variables with the exception of sector switching, where state fixed effects are not included due to the reduced sample size of only those displaced workers who were reemployed. The tables show the odds ratio results of the logistic regression with robust standard errors clustered at the state level. Marginal effects for the job sector results are shown in Figures 1 to 4.

Figure 1.

Job loss logistic regression results, marginal effects.

Figure 2.

Advance notice logistic regression results, marginal effects.

Figure 3.

Relocated logistic regression results, marginal effects.

Figure 4.

Sector switcher logistic regression results, marginal effects.

Results

Table 4 shows the results of the logistic regression of job loss on employment sector for the entire sample and the logistic regression of advance notice on the subsample of respondents who lost their jobs.

Table 4.

Job Loss and Advance Notice Logistic Regression Results.

	Job loss			Advance notice
	Odds ratio	Robust SE		Odds ratio	Robust SE
Nonprofit sector	0.789	0.048	***	0.801	0.113
Local government	0.588	0.043	***	1.085	0.212
State government	0.732	0.062	***	1.554	0.374	^†
Federal government	0.718	0.095	*	1.058	0.325
Female	0.877	0.027	***	1.138	0.079	^†
Married	0.753	0.031	***	1.010	0.070
Has own child below 18 years	1.064	0.047		0.968	0.066
Hispanic origin	0.984	0.050		0.957	0.145
White	1.084	0.072		0.850	0.129
Black	1.213	0.100	*	0.846	0.119
Less than high school	0.970	0.056		0.985	0.169
High school graduate	0.899	0.028	**	1.034	0.080
Bachelor’s degree	0.923	0.033	*	1.117	0.094
Graduate school	0.803	0.049	***	0.870	0.105
Age²	0.999	0.000	***	0.999	0.000	***
Age	1.045	0.006	***	1.084	0.021	***
City/metropolitan	1.090	0.055	^†	0.962	0.103
Constant	0.051	0.009	***	0.035	0.020	***
State fixed effects	Included			Included
Industry and occupation	Included			Included
Observations	51,964 (all)			5,986 (lost job)
Pseudo R²	.035			.033

Note. Across levels of government, local and state are significantly different for job loss (χ² = 4.64, p = .031).

†

p < .10, *p < .05, **p < .01, ***p < .001

Both nonprofit sector and government employees across all levels of government—federal, state, and local—were less likely to lose their jobs during the jobless recovery period from January 2009 to December 2011. Nonprofit employees are 2% less likely to lose their jobs compared with the for-profit sector. For levels of government, local government employees are 5% less likely and both state and federal government employees are about 3% less likely to experience job loss.

Women and married individuals are less likely to experience job loss, but Black employees are more likely to lose their jobs as are those living in a metropolitan area. As for age, younger employees are more likely to be let go, but this decreases over time as individuals likely near retirement or have seniority so are less likely to be let go. For education, employees with a high school degree are less likely to lose their jobs than those with only some college education and employees with a graduate degree or higher are also less likely to lose their jobs compared with those who have had just some college.

To answer the first question posed, government and nonprofit employees appear to have more job security than the for-profit sector as they were less likely to lose their jobs during the Great Recession. Across levels of government, significant differences were found between the state government and local government.

Table 5 shows the logistic regression results for job loss with interaction terms added for female and job sector as well as nonminority (White) and job sector. Although no significant differences were found for the nonminority interactions, the odds of women in state government losing their jobs are 1.36 times the odds of men losing their jobs. Regarding the impact of layoffs on diversity efforts, women are less likely to experience job loss overall, but women in state government are more likely to lose their jobs. Although no significant results were found for the nonminority interactions, Black employees are more likely to lose their jobs. Layoffs may continue to impede diversity efforts.

Table 5.

Job Loss and Diversity Logistic Regression Results.

	Odds ratio	Robust SE
Female × Nonprofit	0.889	0.103
Female × Local Government	1.093	0.209
Female × State Government	1.358	0.230	^†
Female × Federal Government	0.854	0.188
Nonminority × Nonprofit	1.001	0.171
Nonminority × Local Government	0.923	0.182
Nonminority × State Government	1.106	0.186
Nonminority × Federal Government	1.132	0.241
Nonprofit sector	0.854	0.136
Local government	0.595	0.129	*
State government	0.562	0.117	**
Federal government	0.696	0.185
Female	0.873	0.031	***
Married	0.753	0.031	***
Has own child below 18 years	1.065	0.047
Hispanic origin	0.984	0.050
White	1.079	0.069
Black	1.211	0.099	*
Less than high school	0.969	0.056
High school graduate	0.897	0.028	***
Bachelor’s degree	0.922	0.033	*
Graduate school	0.801	0.048	***
Age²	0.999	0.000	***
Age	1.045	0.006	***
City/metropolitan	1.090	0.054	^†
Constant	0.052	0.010	***
State fixed effects	Included
Industry and occupation	Included
Observations	51,964 (all)
Pseudo R²	.035

†

p < .10, *p < .05, **p < .01, ***p < .001

In examining advance notice among respondents who lost their jobs, only state government employment has a nearly statistically significant influence over the probability of an employee receiving written advance notice for the layoff or closure. State government employees are 7% more likely to receive advance notice than for-profit employees. In response to the third question posed, only state government employees are more likely to receive written advance notice prior to being displaced compared with the for-profit sector.

Table 6 shows the logistic regression results for job mobility for the subsample of respondents who lost their jobs and sector switching for a subsample of those respondents who were reemployed. The relocation decision of displaced workers in search of a new job seems to have little to do with employment sector as no significant differences across employment sectors or levels of government were found.

Table 6.

Mobility and Sector Switching Logistic Regression Results.

	Relocated			Sector switcher
	Odds ratio	Robust SE		Odds ratio	Robust SE
Nonprofit sector	0.852	0.286		23.262	7.173	***
Local government	0.820	0.285		38.059	12.976	***
State government	1.543	0.440		14.448	3.826	***
Federal government	1.191	0.494		22.342	12.781	***
Female	0.706	0.089	**	1.223	0.170
Married	0.609	0.093	**	1.496	0.234	*
Has own child below 18 years	0.728	0.111	*	1.070	0.209
Hispanic origin	0.818	0.190		0.653	0.167	^†
White	0.694	0.147	^†	1.010	0.273
Black	0.370	0.120	**	0.993	0.385
Less than high school	1.137	0.242		0.431	0.221
High school graduate	0.921	0.161		0.919	0.162
Bachelor’s degree	1.801	0.271	***	0.930	0.198
Graduate school	2.421	0.525	***	0.980	0.287
Age²	0.998	0.000	***	1.001	0.001
Age	1.142	0.045	**	0.951	0.042
City/metropolitan	0.646	0.109	*	1.129	0.170
Constant	0.017	0.016	***	0.110	0.102	*
State fixed effects	Included			Not Included
Industry and occupation	Included			Included
Observations	5,986 (lost job)			1,421 (re-employed)
Pseudo R²	.092			.261

Note. Across levels of government, local and state are significantly different for sector switching (χ²=9.67, p=.002).

†

p < .10, *p < .05, **p < .01, ***p < .001

However, a number of sociodemographic variables have a significant relationship with job mobility. Females, married individuals, individuals with children below the age of 18 years, and those in a city are less likely to relocate in search of a job. It seems as though those who have established or are in the process of establishing a family will be less willing to relocate than those who have fewer dependents in their lives. In terms of education, displaced workers with a college or graduate degree are significantly more likely to relocate compared with those who only have some college experience, which is the comparison group. In terms of age, younger individuals are more likely to relocate, likely due to their increased mobility overall, and this decreases over time, which is likely. In response to the fourth question, job mobility does not significantly vary across job sectors or levels of government.

In terms of sector switching, nonprofit and government employees, across all levels of government, are more likely to change job sectors compared with their for-profit counterparts. Nonprofit sector employees who become displaced workers are 43% more likely to move into a sector other than the nonprofit sector compared with for-profit sector employees finding employment outside the for-profit sector. Among government employees, local government employees are 49% more likely, state government employees are 36% more likely, and federal government employees are 42% more likely to sector switch compared with the for-profit sector. The only other significant finding is for married individuals who are also more likely to sector switch. In response to the final question posed, government and nonprofit employees are less likely to change job sectors and there are significant differences between the state and local government levels.

Discussion and Conclusion

This study provides insights into the aftermath of cutback management during the Great Recession by examining the impact of layoffs of public personnel. By examining job loss, the implementation of layoffs, and the future actions of displaced employees by job sector and levels of government, this study sheds light on the longer term effects layoffs have on public sector employment. For-profit employees were the most likely to be displaced, indicating that for-profit firms are most likely to use layoffs in times of fiscal stress. Although women are less likely to lose their jobs, women in state government are more likely to experience job loss as are Black employees across job sectors. State government employees, however, were most likely to receive advance notice of layoffs. In terms of the influence of job loss on displaced workers, no sector differences were found for geographic mobility, but individuals displaced from the government and nonprofit sectors are more likely to change job sectors than individuals displaced from the for-profit sector. This may be due to the rise of contracting, where people carrying out the same work may change job sectors as needed, or due to the greater number of jobs available in the for-profit sector.

Several implications and areas for future study can be drawn from these findings. First, during the end of the Great Recession and the jobless recovery, both nonprofit and government employees were less likely to lose their jobs compared with the for-profit sector. The government and nonprofit sectors seem to be better able to buffer employees from economic downturns. Because both public and nonprofit managers are less likely to resort to layoffs, these managers likely look for other ways to make ends meet during times of scarcity. This may reflect the prominence of employees in government and nonprofit organizations. Employees tend to comprise the majority of government and nonprofit organizations’ budgets (Pynes, 2013), so they may be a prime target for budget cuts. However, employees are likely part of the technical core of government and nonprofit organizations (Thompson, 1967), explaining why public and nonprofit managers strive harder to buffer employees from cutback management decisions. Government employees also tend to have civil service protections, although this varies across states and localities.

Second, while layoffs have social and political consequences regardless of sector setting, the meanings are different. The conversation about for-profit sector downsizing focuses on economics, but retrenchment in the public sector focuses on waste and inefficiency. Blame and resentment are more likely in government downsizing than downsizing in for-profit firms because first, businesses do not have guaranteed employment or job security as the government sector does, and second, impersonal competition is apparent for private firms, whereas government decisions to downsize seem to be more personal, policy decisions (Kelman, 2006). Historically, job security has been one of the benefits of government work and an added incentive for public sector employees (Frank & Lewis, 2004). Layoffs negatively influence employee morale, productivity, trust, and organizational commitment (Behn, 1980; Cayer, 1986; Greenhalgh & McKersie, 1980; Ingraham & Barrilleaux, 1983; Levine, 1979; Van der Voet & Vermeeren, 2017). However, Van der Voet and Vermeeren (2017) find change management helps alleviate the negative influence of cutbacks on organizational commitment.

Public and nonprofit managers should be transparent and communicate throughout the cutback management process as well as incorporate employee participation into decision-making.

The negative influence of furlough days on job satisfaction, financial burden, workload, and career stability can be reduced by clear communication (Lee & Sanders, 2013). In addition, Pollitt (2010) highlights how leaders should consider timing, communication, ethics, and legitimacy in cutback management decisions. When cutback management decisions are needed, communication and employee input can help reduce the negative impacts they have on employees.

Private sector employment has returned to prerecession levels, but government employment continues to lag behind. Yet President Trump issued a January 2017 memo placing a hiring freeze on the federal government (White House, 2017) until the Office of Personnel Management submitted a plan to reduce the size of government. Policy makers should proceed with caution in implementing severe cutback management strategies such as layoffs. Positions may be difficult to recoup and government underemployment affects the delivery of public services. For example, the media has reported layoffs across local government from firefighters leading to increased response times to teachers leading to increased class sizes (Dewan & Rich, 2012). Short-term cuts stay in place longer than anticipated, where crises open the window for deeper changes that have lasting effects (Savi & Randma-Liiv, 2015). Focusing on budget reductions often neglects consideration of organizational capacity (Robbins & Lapsley, 2014). As Feldheim (2007) states, “when economic values take precedence over these [public service values] the public interest is downsized, not just the employee” (p. 262). Organizations should consider capacity in their budget decisions, especially government agencies and nonprofit organizations, as demand for public and social services also increases in times of recession.

Third, reducing levels of public employees may also compromise the ability of the public sector to cope with future crises. Cepiku and Savignon (2012) found that several countries raised this concern over the pressure to reduce staff and services. As Levine, Rubin, and Wolohojian (1982) asserted decades ago, “Over the long run, retrenchment may make public organizations even less effective and less capable of dealing with their problems than the alleged fat, redundant and overextended institutions that proponents of cutbacks have criticized so vehemently” (p. 130). As many scholars of the 1980s warned against short-term or patchwork actions to instead focus on long-term strategies (i.e., Behn, 1980; Levine, 1978), public managers need to consider the future in evaluating their options and choosing a direction in times of economic crises.

Finally, the influence of cutback management on representative bureaucracy is an area worthy of future research. Representative bureaucracy suggests that bureaucracies should reflect the populations they serve and the population at large (Kingsley, 1944; Krislov, 1974) and research has found government to be more representative compared with the general economy (i.e., Naff, 2001). However, cutback management decisions, such as layoffs, can inhibit diversity efforts (Holzer, 1986; Levine, 1978; Rubin, 1985) as this study found African Americans were more likely to experience job loss as well as women in state government. Research looking into intersectionality and the potential influence of the shrinking public sector on representativeness and diversity efforts are needed.

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.

Notes

ORCID iD

Jaclyn S. Piatak

Author Biography

Jaclyn S. Piatak is an assistant professor in the Department of Political Science and Public Administration at the University of North Carolina at Charlotte. Her research centers around understanding and managing public service, both at an organizational and individual level.

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