Employee Turnover and Organizational Performance in U.S. Federal Agencies

Abstract

Contrary to received wisdom, could turnover actually be good for an organization? Traditional research on turnover in the public management field treats turnover as a dependent variable, emphasizing its negative role on organizational performance without sufficient theoretical or empirical support. With an emphasis on the type of employee turnover as a situational factor, this research establishes the hypothesized relationships between different employee turnovers—employee transfers, quits, and involuntary turnover—and organizational performance, and tests them using panel data from 2010 to 2014 in agencies of the U.S. federal government. Empirical results challenge the accepted belief about the harmful effects of turnover on organizational performance: Turnover can be beneficial for an organization. The results confirm the relationship differs across the type of turnover involved: Employee transfers have an inverted U-shaped relationship with organizational performance, and involuntary turnovers have a linear and positive relationship with organizational performance. Given the use of a perceptual measure of organizational performance by remaining employees, these results imply that a low-to-moderate level of employee transfers is likely to increase organizational performance and that involuntary turnovers—an elimination of employees who presented poor performance or were involved in misconducts—contribute to improving organizational performance.

Keywords

employee turnovers organizational performance quits employee transfers involuntary turnovers

Retaining employees has been an ongoing concern among scholars and practitioners in the public sector since the early 1900s (Merit System Protection Board, 1989; White, 1948). Beginning in 1990, scholars in the public management field (e.g., Cho & Lewis, 2012; Cohen, Blake, & Goodman, 2016; Jeon & Robertson, 2013; Jung, 2010; Kim, 2005; Kim & Fernandez, 2017; Lewis, 1991; Pitts, Marvel, & Fernandez, 2011; Whitford & Lee, 2015) have extensively explored employees’ turnover behavior in public organizations. The literature has contributed to the identification of the critical determinants of employees’ turnover decisions and has suggested managerial solutions to resolve this ongoing concern. However, the literature’s approach that treats turnover as a dependent variable emphasizes only the negative role of employee turnover on organizational performance without sufficient theoretical or empirical support.

Does employee turnover necessarily have a negative impact on organizational performance? The traditional belief among scholars and practitioners in both the public and private sector holds that employee turnover typically generates both pecuniary (e.g., recruiting and training costs for new employees) and nonpecuniary costs (e.g., low employee morale) and thus entails negative consequences in lowering organizational performance (Dalton & Todor, 1979; Staw, 1980). Theoretical perspectives on the relationship between employee turnover and organizational performance, however, present a different story: Turnover may in fact be beneficial for an organization by improving organizational performance (Abelson & Baysinger, 1984; Dalton & Todor, 1979). On the basis of these different theoretical perspectives, over 100 studies have offered empirical tests for the actual effects of employee turnover on organizational performance in the generic management field. While empirical evidence from the literature is mixed due to methodological challenges (Hancock, Allen, Bosco, McDaniel, & Pierce, 2013), a major portion of the findings supports the dysfunctional effects of employee turnover on organizational performance in private organizations.

In contrast, the question of the potential effects of employee turnover on organizational performance has been neglected in the public management field: A single publication by Meier and Hicklin (2008) is the only available source for public sector organizations. The current research emphasizes that employee turnover in public sector organizations, in particular the federal government, deserves more attention from scholars due to its distinctive personnel management practices (Appleby, 1945; Rainey & Bozeman, 2000; Truss, 2013). Foremost, public sector organizations are operated rigidly in terminating their employees for poor performance or wrongdoings: Federal agencies must deal with the due process that involves unions, the formal grievance process, and internal administrative processes (Truss, 2013). This distinctive aspect may contribute to identifying unpredicted or unconfirmed results which differ from those in the private sector. In addition, the federal government offers the opportunity for an empirical analysis of the effects of employee transfers that has been neglected in the private sector due to data limitations, and this will contribute to satisfying with the need for empirical evidence on their potential effects on organizational performance in both public and generic management (Dalton, 1997; Valcour & Tolbert, 2003; Wynen, Op de Beeck, & Hondeghem, 2013).

This research aims to investigate whether employee turnover is harmful for governmental organizations and thus contributes to the literature on employee turnover and organizational performance in public management. First, through a critical review of traditional theoretical perspectives, this research develops hypotheses on varying relationships between employee turnover and organizational performance in accordance with the type of employee turnover (employee transfers, quits, and involuntary turnovers). Second, this research tests a set of hypothesized relationships between employee turnover and organizational performance using panel data from federal subagencies from 2010 to 2014. A panel data approach with both unit and year fixed effect estimators offers numerous benefits over a cross-sectional data approach in addressing reverse causality and endogeneity issues. Empirical results challenge the wide-spread but untested belief among public management scholars that employee turnover has harmful effects on organizational performance perceived by remaining employees: Employee turnover can be beneficial for an organization. While a low-to-moderate level of employee transfers is likely to increase organizational performance, involuntary turnovers (for poor performers and misconduct)—regardless of rate—contribute to improving organizational performance. The results confirm the key role of turnover types as a situational factor in the employee turnover–organizational performance relationship.

This research begins with a review of the theoretical perspectives on the relationship between employee turnover and organizational performance, and develops hypotheses on the relationship. The discussion then turns to the data and methods used to test the relationship, followed by the findings of the empirical models. Finally, this research discusses both theoretical and practical implications concluding with a discussion of the limitations of this research.

Employee Turnover and Organizational Performance

Traditional Theoretical Perspectives

Theoretical perspectives on the relationship between employee turnover and organizational performance are rooted in multiple disciplines, including psychology, sociology, economics, and generic management (Hancock et al., 2013; Park & Shaw, 2013). The most dominant perspective on the employee turnover–organizational performance relationship emphasizes the dysfunctional effects of employee turnover and predicts a linear negative relationship between employee turnover and organizational performance. That is, “turnover rates at any levels hurt organizational performance” (Park & Shaw, 2013, p. 269). With a recognition that modern organizations need to survive in a knowledge-based economy, scholars predict the potential negative consequences of employee turnover in organizational performance with three different orientations (Hancock et al., 2013). First, employee turnover incurs monetary costs to organizations: Organizations need to spend additional expenditures to hire and train new employees to replace former employees (Allen, Bryant, & Verdaman, 2010; Dalton & Todor, 1979; Staw, 1980). Second, human capital theory suggests that employees’ accumulated knowledge and skills are of great significance in maintaining organizational performance (Becker, 1993; Strober, 1990). For this reason, losing employees who have more experience in their job will lead to a negative outcome in organizational performance. Third, as social capital theory suggests, employee turnover may disrupt the social relations that employees typically use in sharing knowledge and information and these relations are essential in pursuing organizational goals more effectively (Szreter, 2000). Organizations that experience the loss of employees are thus thought to suffer a decreasing performance. In addition, turnover decisions may involve additional socialization costs for newly hired employees to obtain the equivalent level of social relations which existing employees have (Park & Shaw, 2013). Social capital often acts as a club good by excluding new members in existing social relationships in organizations (Aldridge, Halpern, & Fitzpatrick, 2002; Szreter, 2000).

While holding a belief in the significance of accumulated human capital and social capital among employees affecting organizational performance (Price, 1977; Shaw, Gupta, & Delery, 2005), another theoretical perspective predicts a nonlinear negative relationship between employee turnover and organizational performance. Grounded on learning curve theory, this perspective suggests that the negative effect of employee turnover on organizational performance decreases as turnover increases: A low to moderate level of employee turnover is more disruptive to organizational performance than a moderate to high level of employee turnover (Park & Shaw, 2013; Shaw et al., 2005). Scholars working with this theoretical perspective focus on the probable difficulty for newly hired people to build a comparable or equivalent level of human capital with current employees. In particular, they predict that organizations with a high turnover rate have a lower level of accumulated human capital, which in turn suggests that newcomers will more quickly attain the same level of human capital as current employees. As Shaw, Gupta, and Delery (2005) point out, “when voluntary turnover rates are high, an organization typically replaces a short-tenured employee with a new employee who soon represents the same level of human capital accumulation and shows equivalent performance” (p. 52). On the contrary, when turnover is low or moderate, “it is quite time-consuming for a new employee to build specific human capital that is equivalent to the average stayer’s” (Shaw, Gupta, & Delery, 2005, p. 52).

The previous two hypothesized relationships are solely built upon negative impacts (or costs) involved in turnover behavior, but “there may be potential benefits associated with turnover that mitigate or in some cases outweigh the costs” (Hancock et al., 2013, p. 577). Those benefits, for examples, include lower compensation costs (Abelson & Baysinger, 1984), facilitating innovation through an influx of new blood, new technology, and new ideas (Abelson & Baysinger, 1984; Dalton & Todor, 1979; Schneider, Goldstein, & Smith, 1995), increasing mobility that positively affects employees’ work attitudes and motivation (Dalton & Todor, 1979; Staw, 1980). Moreover, turnover can benefit an organization through the elimination of poor performers and replacement with more competent new employees (Abelson & Baysinger, 1984; Dalton & Todor, 1979).

While the idea of the positive effects of turnover is regarded as new or radical among scholars in the generic management field, “the idea has its roots in classic public sector personnel administration” (Meier & Hicklin, 2008, p. 575). For example, Mosher and Kingsley (1941) suggest that turnover can be beneficial if it can increase the possibilities of promotion through increased mobility. Public organizations with high mobility can attract more future employees. Furthermore, they imply that an optimal level of turnover should be “sufficiently large to prevent the stagnation of the service and sufficiently small to reflect healthy working conditions” (Mosher & Kingsley, 1941, p. 341). Stahl (1976, p. 391) emphasizes the modification of the traditional view of turnover as “an unmitigated evil.” He lists the probable advantages that an organization will receive from employee turnover, such as “representativeness, freshness of viewpoint, and breadth of experience on the part of key workers” (Stahl, 1976, p. 391).

Scholars with this viewpoint, thus, argue that turnover may be beneficial to an organization if the benefits listed above exceed the costs related to the selection, retention, and training process: They predict an inverted U-shaped relationship between employee turnover and organizational performance. That is,

an optimal turnover rate is found at the point where benefits maximally exceed the costs. Specifically, at low to moderate levels where benefits are greater than costs, increased turnover rates can contribute to organizational performance, but as rates rise beyond moderate levels, they have negative effects. (Park & Shaw, 2013, p. 269)

Developing Hypotheses

While previous traditional theoretical perspectives set up a framework of predicting the employee turnover–organizational performance relationship for empirical investigations, the findings fail to offer coherent and convergent evidence. One significant reason for this divergence among empirical findings comes from developing theoretical perspectives without paying attention to the distinction between turnover types (for exceptions, see Batt & Colvin, 2011; McElory, Morrow, & Rude, 2001; Simon, 2012; Subramony & Holtom, 2011, 2012): Previous theoretical perspectives focus on total turnover and its potential effects on organizational performance, but such an approach disregards different reasons and contexts for employee turnover.

Recently, scholars have urged an elaboration of previous theoretical perspectives through the incorporation of the idea that the relationship between employee turnover and organizational performance is contingent on the type of employee turnover (e.g., Haucknecht & Trevor, 2011; Shaw, 2011). For example, while some studies (e.g., McElroy, Morrow, & Rude, 2001; Morrow & McElroy, 2007; Shaw, Duffy, Johnson, & Lockhart, 2005) confirm a linear negative relationship between voluntary turnover and organizational performance, other studies (e.g., Meier & Hicklin, 2008; Siebert & Zubanov, 2009) identify an inverted U-shaped relationship between total turnover and organizational performance. As an effort to address this disparity, the current research develops hypotheses with a consideration of the possible role of the type of employee turnover as a situational factor in the employee turnover–organizational performance relationship while predicting that the relationship differs across different types of employee turnover. That is, different types of employee turnover will lead to different consequences in organizational performance. This research considers three different turnover types: (a) employee transfers, (b) quits, and (c) involuntary turnovers (including both termination for misconduct and poor performance). Figure 1 describes the hypothesized relationships between employee turnover and organizational performance by the type of employee turnover.

Figure 1.

Relationships between employee turnover and organizational performance by type.

First, employee transfers are defined as employee movements to another federal agency with no competition to the applicants from outside the federal government. Theoretical arguments suggest that employee transfers to a subdepartment or unit within an organization may have positive aspects. First, an employer expects employee transfers to provide positive outcomes in increasing organizational flexibility and innovation (Dalton, 1997; Dineen, Ling, & Soltis, 2011; Tsui, Pearce, Porter, & Hite, 1995) and correcting misplacements of employees (Yoder, 1958). For these reasons, managers and supervisors often encourage internal transfers to employees (Dalton, 1997; Dineen et al., 2011; Yoder, 1958). Second, employee transfers are initiated by employees for three main reasons: (a) finding more developmental and career advancement opportunities; (b) finding a job or an organization that better fits the employee’s personalities; and (c) personal problems at their current position (to care for their family nearer their home, lack of important facilities such as a hospital, to get closer to their children, and so on). For these reasons, employees who consider internal transfers within the organization may have a lower work motivation and job satisfaction in their current workplace. Replacing them with new employees may offer some benefits to an organization, including an influx of new technologies and new ideas by new employees and a positive change in employees’ work attitudes caused by promotional opportunities.

With these potential benefits to organization, federal employees’ transfers to other federal agencies are expected to bring a positive consequence in organizational performance. After a certain level of employee transfers, however, organizational performance would be worsened because the costs, such as the loss of accumulated human and social capital and the expenses involved in hiring and training new employees, will no longer be compensated by these benefits (Dalton, 1997). The theoretical argument on employee transfers, thus, is identical to the perspective of an inverted U-shaped relationship. Therefore, this research predicts an inverted U-shaped relationship between employee transfers and organizational performance and proposes the following hypothesis:

Hypothesis 1: Employee transfers have an inverted U-shaped relationship with organizational performance such that the relationship is positive at a low-to-moderate level of employee transfers but becomes negative at a moderate-to-high level of employee transfers.

Second, quits, which are often used interchangeably with voluntary turnover, represent federal employees’ voluntary departure from current federal workplace to other sectors. Quits are initiated by employees for personal reasons such as higher salaries, better career opportunities, and dissatisfaction with job, and are distinguished from employee transfers and voluntary retirements (Batt, 2002; Campion, 1991). Employees who voluntarily quit their jobs are considered as holding higher human and social capital than those who are laid off by their employers involuntarily or those who transfer to other subunits within an organization. In addition, quits are typically regarded as more unmanageable than other types of employee turnover due to their unpredictability (Park & Shaw, 2013; Shaw, Delery, Jenkins, & Gupta, 1998). Therefore, employee quits will be detrimental to organizational performance.

The harmful effect of quits, however, will be lowered as quit rates increase because new employees can build up human and social capital equivalent to the level held by current employees (Shaw, Gupta, & Delery, 2005). In addition, as quits keep increasing, an organization begins to commit more resources and efforts to minimizing the adverse effects of quits and to offer new employees training for job skills and knowledge to facilitate their learning process (Shaw, Gupta, & Delery, 2005). These efforts by an organization will result in weakening the negative effects of quits on organizational performance.

In sum, quits are expected to have a negative effect on organizational performance, but the negative effect will be attenuated as quits are moving from low-to-moderate levels to moderate-to-high levels. Therefore, this research predicts an attenuated negative relationship between quits and organizational performance. The following hypothesis is proposed:

Hypothesis 2: Quits have an attenuated negative relationship with organizational performance such that the relationship is more negative at a low-to-moderate level of employee quits.

Third, involuntary turnovers, which are actions that terminate employees from their position, are initiated by an employer for employees’ poor performance or misconduct. Note that involuntary turnover in this research should be distinguished from cutbacks: Cutbacks in general do not entail hiring new employees while pursuing the reduction in the size of workforce of an organization (Behn, 1980; Jones, 1998). In general, involuntary turnovers are assumed to offer benefits for organizational performance (Dalton, Toder, & Krackhardt, 1983; Holtom, Mitchell, Lee, & Eberly, 2008). Such benefits may include a lower level of disruption for remaining employees, which in turn will increase their work performance (Park & Shaw, 2013). In addition, if an organization can eliminate poor performers and replace them with new employees who perform better, the remaining employees will benefit from a lower workload and less work stress (Abelson & Baysinger, 1984). Replacing employees for poor performance or misconduct can also send a warning signal to the remaining employees: It may positively encourage employees who remain in the organization to work better or avoid wrongdoing (Meier & Hicklin, 2008).

Psychological contract theory suggests, on the contrary, that involuntary turnovers may generate adverse effects on organizational performance if the remaining employees perceive the elimination process of involuntary turnovers as unfair (De Meuse, Bergmann, Vanderheiden, & Roraff, 2004; Morrison & Robinson, 1997). While feeling the loss of job security, those remaining employees “withdraw psychologically (e.g., reduced trust and loyalty, withholding of effort, and reduced involvement) or physically (e.g., increased absences or voluntary turnover), with negative economic consequences for the firm” (Datta, Guthrie, Bausil, & Pandey, 2010, p. 308). In the public sector, however, this concern may not matter. As one of the aspects which sharply distinguishes them from private sector organizations, public sector organizations are under strict constraints by external constituencies and internal regulations in terms of eliminating civilian employees (Rainey & Bozeman, 2000). For this reason, managers and supervisors in public sector organizations may take an action to eliminate employees with a consistently poor performance record or employees who commit serious misconduct.

In sum, in the public sector, involuntary turnovers will eventually improve organizational performance through replacing those who present poor performance or are involved in misconduct with new employees who present better performance or personal virtues, even though they incur monetary costs such as hiring and training new employees. Thus, this research sets up the following hypothesis:

Hypothesis 3: Involuntary turnovers have a linear positive relationship with organizational performance.

Method

Data

This research uses two major data sources: the U.S. Office of Personnel Management’s Fedscope and Federal Employee Viewpoint Survey (FEVS). Fedscope offers statistics on employment, accessions, and separations in the federal agencies since 2005. Employee turnover measures in this research, as well as some organizational demographic control variables, are obtained from Fedscope’s quarterly statistics for each federal agency. The FEVS is used to measure organizational performance, which is the dependent variable of this research, and control variables including organizational satisfaction-relevant and managerial practices variables. The unit of analysis in this study is the federal agency (including subagencies of a parent agency/department and independent agencies). For example, the Internal Revenue Service is the subunit or agency of the Department of the Treasury. Both the Internal Revenue Service and the headquarters of Department of Treasury are included as separate units in the sample data set.

By combining data from the Fedscope and the FEVS (excluding agencies with incomplete information for either the dependent or independent variables), this research developed the final sample data set that consists of 595 observations (179 agencies in 2010, 178 agencies in 2011, 86 agencies in 2012, 78 agencies in 2013, and 74 agencies in 2014). During the time frame of this research, four agencies in the sample data set (Tricare Management Activity, Mineral Management Service, Financial Management Service, and Bureau of Public Debt) had experienced organizational changes, and this research treats former and new agencies as separate units.¹ The large reduction in the number of agencies since 2012 is the result of the lower number of agencies which participated in the FEVS than in previous years, and leads to an unbalanced panel data structure.² The agencies in the sample data set do not present much variation in key demographic information—such as employees’ average age, tenure, and salaries—from the excluded agencies. The military agencies under the Department of Air Force, the Department of the Army, the Department of Defense and the Department of Navy are the most represented ones in the sample data set: about half (46%) of total sample observations are from those military agencies.

Dependent Variable

The dependent variable is organizational performance perceived by employees. The measure of organizational performance in this research is based on the following survey item in the FEVS: “My agency is successful at accomplishing its mission.” As the survey item is stated, organizational performance in this research is operationalized as the level of mission achievement of each agency as perceived by employees. This perceptual performance is measured by the proportion of employees who have at least a positive perception of the agency’s mission achievement.

Using a perceptual measure of organizational performance in this research is meaningful. Scholars suggest that organizational performance is conditional on who is evaluating the performance rather than on whether performance is evaluated by objectively verified measures (Connolly, Conlon, & Deutsch, 1980; Tsui, 1990). An organization consists of multiple constituencies with diverse needs, and different constituencies deliver diverse evaluations on organizational performance: Thus, each constituency’s perspective needs an equal attention. In particular, organizational performance perceived by employees, as an “internal” constituency, conveys a critical clue on how current employees—who are obligated to execute tasks and programs for their organizations—perceive changes in achieving their organizations’ missions and goals after former coworkers left their workplace for some reasons.

Furthermore, there is ample evidence that perceptual measures are moderately or highly correlated with objective measures of organizational performance (Boomer, Johnson, Rich, Podsakoff, & MacKenzie, 1995; Brewer, 2005): In particular, a correlation between them becomes higher if both measures of performance gauge the same dimension of performance. Using three different sample data sets, Wall et al. (2004) compared both subjective and objective measures of company performance. While confirming convergent validity, discriminant validity, and construct validity, their findings support the validity of using subjective measures of organizational performance when objective measures are not available. Given this restriction, the use of the perceived performance variable is justified in that it enables scholars to compare different federal agencies (Fernandez & Moldogaziev, 2011; Meier & O’Toole, 2013).

Table 1 presents descriptive statistics for both dependent and independent variables, as well as other control variables. Approximately 80% of respondents in federal agencies presented a positive perception of their agency’s performance in achieving its own mission between 2010 and 2014. The perceived level of organizational performance varies widely across federal agencies, with the lowest level at 49.6% and the highest at 93.4%. Details can be found in Appendix B.

Table 1.

Descriptive Statistics.

Year	2010	2011	2012	2013	2014	Total
	M	M	M	M	M	M
	(SD)	(SD)	(SD)	(SD)	(SD)	(SD)
Performance (%)	79.38	80.30	81.43	79.01	78.68	79.82
Performance (%)	(0.084)	(0.082)	(0.059)	(0.061)	(0.064)	(0.075)
Employee transfer rate (%)	1.99	1.90	1.80	1.68	1.17	1.80
Employee transfer rate (%)	(0.048)	(0.021)	(0.023)	(0.015)	(0.008)	(0.031)
Quit rate (%)	3.4	3.67	3.37	2.98	2.94	3.42
Quit rate (%)	(0.030)	(0.029)	(0.029)	(0.026)	(0.021)	(0.029)
Involuntary turnover rate (%)	2.94	3.33	3.24	1.92	1.32	2.74
Involuntary turnover rate (%)	(0.060)	(0.069)	(0.049)	(0.026)	(0.018)	(0.055)
Job satisfaction (%)	71.29	71.11	70.43	66.85	66.38	69.92
Job satisfaction (%)	(0.057)	(0.055)	(0.044)	(0.060)	(0.055)	(0.057)
Relatedness (%)	85.03	85.00	84.82	76.87	76.19	75.72
Relatedness (%)	(0.040)	(0.041)	(0.029)	(0.032)	(0.031)	(0.037)
Cooperation (%)	77.46	77.77	76.87	76.19	75.72	77.09
Cooperation (%)	(0.055)	(0.051)	(0.047)	(0.054)	(0.054)	(0.053)
Opportunities (%)	68.18	67.54	67.01	63.26	62.63	66.48
Opportunities (%)	(0.087)	(0.081)	(0.073)	(0.081)	(0.084)	(0.085)
Trust in supervisor (%)	68.33	69.32	69.07	68.91	68.58	68.84
Trust in supervisor (%)	(0.055)	(0.051)	(0.048)	(0.055)	(0.054)	(0.053)
Resources (%)	50.73	47.97	49.47	43.9	45.34	48.16
Resources (%)	(0.097)	(0.094)	(0.072)	(0.079)	(0.077)	(0.091)
Physical conditions (%)	70.37	71.32	70.24	69.31	67.94	70.19
Physical conditions (%)	(0.070)	(0.069)	(0.054)	(0.069)	(0.071)	(0.068)
Empowerment (%)	50.41	50.89	50.79	47.54	47.11	49.82
Empowerment (%)	(0.091)	(0.084)	(0.070)	(0.075)	(0.075)	(0.083)
Accomplishment (%)	74.93	74.6	74.59	71.99	71.68	73.99
Accomplishment (%)	(0.047)	(0.044)	(0.041)	(0.048)	(0.043)	(0.047)
Minority (%)	32.85	32.93	30.69	30.68	29.89	31.91
Minority (%)	(0.118)	(0.117)	(0.086)	(0.111)	(0.093)	(0.110)
Age (years)	46.14	46.22	46.04	46.09	46.12	46.18
Age (years)	(2.730)	(2.850)	(2.640)	(2.720)	(2.680)	(2.620)
Total employees	9955.33	10061.56	9868.06	11237.32	11523.93	10337.64
Total employees	(23569.52)	(24137.59)	(12422.49)	(15964.59)	(15814.22)	(20647.42)
Sample size	179	178	86	78	74	595

Independent Variable

The main independent variable in this research is employee turnover rate at each federal agency. Turnover rate is measured in three different categories: employee transfer rate (transfer to other federal department or agency voluntarily), quit rate (leave the federal government voluntarily), and involuntary turnover rate (termination for poor performance or misconduct). Turnover rate for each of these categories is calculated as the proportion of employees who left their agency. This research counts the number of employees who left their agency during a 12-month period starting one year before the administration of the FEVS, and divides that number by the number of total employees in the starting month of the period.

Table 1 shows each turnover rate decreasing over the time period of this research. Both employee transfer rate and quit rate were stable at round 1.9% and 3.5%, respectively, between 2010 and 2012, then decreased to 1.17% and 2.94%, respectively, in 2014. Involuntary turnover rate also presents a similar trend to that observed in both employee transfer rate and quit rate: The involuntary turnover rate was steady at around 3.2% from 2010 to 2012, but it decreased rapidly to 1.92% and 1.32% in 2013 and 2014, respectively. As presented in Appendix B, the data set may include an outlier: A single agency (the Aviation Rulemaking Advisory Committee) reports a dramatically different turnover rate in two categories (63.16% for employee transfer rate and 21.05% for quit rate). Results of empirical models without this observation, however, present consistent findings with the ones from empirical models with it.

Control Variables

This research includes a range of control variables that previous research has confirmed significant effects on organizational performance (e.g., Fernandez & Moldogaziev, 2011; Keenan & Newton, 1984; Meier & O’Toole, 2001; Peters & O’Connor, 1980; Rainey, 2014; Spector & Jex, 1991). First, the level of employees’ overall job satisfaction (Job Satisfaction) is controlled with an expected positive relationship with organizational performance. Because the measure of overall job satisfaction encompasses multiple dimensions, such as pay, benefits, and work environment, other satisfaction-related variables were excluded. Second, a list of variables relevant to managerial practices and relational aspects was also controlled: The level of relatedness between individuals’ work and agency’s goals and priorities (Relatedness), the level of personal accomplishment (Accomplishment), the level of cooperation among coworkers (Cooperation), the level of empowerment (Empowerment), the level of opportunities to improve skills (Opportunities), and the level of trust in supervisor (Trust) were included. Finally, another set of variables of organizational demographics—including the size of organization (Total Employees), the proportion of minority employees (Minority), the proportion of supervisors and managers (Supervisor), and the average age of employees (Age)—was controlled. Appendix A presents data sources to measure dependent, independent, and control variables.³

Model

This research uses a multivariate two-way ordinary least square (OLS) fixed-effects model to analyze a panel of subagencies between 2010 and 2014. A panel data approach offers some advantages over a cross-sectional data approach in this research. First, it can address the reverse causality issue through allowing a time-lagged performance variable and controlling for other potential confounding factors (Park & Shaw, 2013). Recent studies (e.g., Meier & Hicklin, 2008; Siebert & Zubanov, 2009) also provide evidence for the validity of the direction of the relationship between employee turnover and organizational performance assumed in this research. Second, a panel data model can reduce the risk of omitted variable bias: The model includes unit fixed effect estimators to control for unobservable characteristics of federal agencies as well as year fixed effect estimators to parcel out potential effects of unobserved contexts across the time period of this research.

Although a panel data approach offers these advantages, it raises the possibility of serial correlation and heteroscedasticity. A Wooldridge diagnostic test (F = 3.166, prob > F = 0.1954) confirms no serial correlation in the data set of this research. To address the risk of heteroscedasticity, this research estimates the empirical model using clustered robust standard errors: Monte Carlo simulations in Bertrand, Duflio, and Mullainathan (2004) and Petersen (2009) show that this approach can reduce the risk of heteroscedasticity. The parsimonious fixed-effects model for subagency i in year t is

\begin{array}{l} P e r f o r m a n c e_{i t} = α_{i} + β_{1} T u r n o v e r_{i t - 1} + β_{2} T u r n o v e r^{2}_{i t - 1} + \\ γ_{1} A g e n c y_{i} + γ_{2} Y r_{t} + X_{i t} β + ε_{i t} \end{array}

$P e r f o r m a n c e_{i t}$ is subagency i’s performance in year t, and $T u r n o v e r_{i t - 1}$ is subagency i’s turnover rate in year t-₁. Agency_i is a vector of agency dummy variables to control for unobserved heterogeneity. Yr_t is a vector of year dummy variables (with 2010 as the reference year), which can control for yearly unobservable or unmeasurable changes in comparison to 2010. X_it is the vector of control variables mentioned above.

Results

Table 2 presents the results of fixed-effects models for employee turnover and organizational performance. Recall that employee transfer rate, quit rate, and involuntary turnover rate (including termination for misconduct or poor performance) are the key independent variables in the fixed-effects models. The only difference between Model 1 and Model 2 is that the latter includes the squared term of each turnover rate variable: The squared term of the turnover variable in Model 2 is included to test the curvilinear relationship between employee turnover and organizational performance.

Table 2.

Results of Fixed-Effect Model for Employee Turnover and Organizational Performance.

	Model 1	Model 2
	Coefficient/(SE)	Coefficient/(SE)
Employee transfer rate	0.012	0.308
Employee transfer rate	(0.051)	(0.198)
Employee transfer rate (squared)		−2.138*
Employee transfer rate (squared)		(1.127)
Quit rate	0.068	−0.458
Quit rate	(0.177)	(0.335)
Quit rate (squared)		3.931*
Quit rate (squared)		(2.263)
Involuntary turnover rate	0.127***	0.182
Involuntary turnover rate	(0.047)	(0.112)
Involuntary turnover rate(squared)		−0.180
Involuntary turnover rate(squared)		(0.289)
Job satisfaction	0.140	0.159
Job satisfaction	(0.101)	(0.100)
Relatedness	0.273***	0.273***
Relatedness	(0.092)	(0.094)
Cooperation	0.312***	0.300***
Cooperation	(0.082)	(0.082)
Opportunities	0.053	0.052
Opportunities	(0.065)	(0.065)
Trust in supervisor	−0.055	−0.058
Trust in supervisor	(0.079)	(0.079)
Resources	0.187***	0.197***
Resources	(0.064)	(0.063)
Physical conditions	−0.012	−0.028
Physical conditions	(0.057)	(0.057)
Empowerment	0.194***	0.177***
Empowerment	(0.063)	(0.064)
Accomplishment	0.043	0.048
Accomplishment	(0.097)	(0.096)
Minority	−0.097***	−0.105***
Minority	(0.020)	(0.020)
Age	0.017	0.016
Age	(0.012)	(0.012)
Supervisor	−0.011	−0.009
Supervisor	(0.024)	(0.024)
Total employees	0.000	0.000
Total employees	(0.000)	(0.000)
Constant	−0.031	−0.027
Constant	(0.099)	(0.097)
Agency dummies	Y	Y
Year dummies	Y	Y
Number of observations	595	595
R ²	.679	.685
Adjusted R²	.671	.678
F	29.45***	27.38***

Note. Numbers in parentheses are clustered robust standard errors.

p < .10. **p < .05. ***p <.01.

First, Model 1 and Model 2 present the evidence for the curvilinear relationship between employee transfers and organizational performance. The estimated coefficient of employee transfer rate is 0.012 in Model 1, but it is not statistically significant: This result rejects the possibility of observing a negative linear relationship between employee transfers and organizational performance. A linear term of the employee transfer rate variable is still not statistically significant in Model 2 where the quadratic term of the employee transfer rate variable is included. Instead, the estimated coefficient of the quadratic term, −2.138 (p < .10), has a marginally statistically significant impact on organizational performance. A joint significance test confirms that both a linear and a squared term are jointly significant (p = .051): both a positive linear term and negative squared term confirm the inverted U-shaped relationship between employee transfers and organizational performance predicted by Hypothesis 1. That is, as employee transfer rate increases from a low-to-moderate level, more employees perceive that their agency accomplishes its mission successfully.

An inverted U-shaped relationship implies that there is an optimal level of turnover to achieve this highest level of organizational performance: Organizational performance will be highest when the benefits and the costs are balanced. When confirming the inverted U-shaped relationship, the optimal level of the turnover can be estimated by taking the first derivative of the regression equation. Such a process suggests about 7.2% as the optimal level of employee transfer rate. This is much higher than the mean of employee transfer rate of 1.8%.⁴ Most of the federal agencies have their mean employee transfer rate below this level so that their organizational performance—more precisely the level of mission achievement perceived by employees—will be improved as their employee transfer rate increases up to 7.2%; however, less employees will perceive a successful mission achievement of their organizations once employee transfer rate moves beyond 7.2%.

This finding supports theoretical conjectures that internal replacements may generate benefits for an organization that sends those employees to another agency (Corredoira & Rosenkopf, 2010; Dalton, 1997; Somaya, Williamson, & Lorinkova, 2008). As those conjectures predicted, an agency can expect an improvement through holding a certain level of organizational flexibility and amending flawed hiring processes. The current finding provides empirical evidence for the positive aspects of employee transfers in contrast to the received opinion. The finding, however, suggests an opposite direction of the effects of employee transfers which has not been identified. As human capital and social capital theories warn, too many employee transfers will not only involve a dramatic loss of aggregated human capital, but also disrupt the social relations and interactions among employees. This will eventually negatively affect employees’ perception on organizational performance.

Second, the results for quit rate show some evidence on a curvilinear pattern of the relationship between quit rate and organizational performance as in the case of transfer rate. In Model 1, a linear term of the quit rate variable is not statistically significant. In Model 2, the linear term is still not statistically significant, but the estimated coefficient, 3.931 (p<0.10), of the squared term of the quit rate variable is marginally statistically significant. Although a negative slope for the linear term and a positive slope for the squared term may imply an attenuated or a U-shaped relationship, a joint significance test shows that both terms are jointly insignificant which rejects the possibility of having an attenuated negative relationship with organizational performance as predicted by Hypotheses 2.

While previous empirical findings (e.g., Batt & Colvin, 2011; McElroy et al., 2001; Morrow & McElroy, 2007) present evidence for the detrimental effects of quits on organizational performance in private organizations, the current findings do not present statistically significant evidence for the potential relationship between quits and organizational performance in the federal agencies. This result is quite surprising but can be explained by considering tenure length. More than 60% of employees who left the federal government have a service experience of less than 2 years in the sample data set of this research. As human capital theorists suggest, less than 2 years of service experience may not be enough time to obtain the job skills and knowledge that increase an accumulated level of human capital of their organizations. For this reason, remaining employees may not perceive much difference in their agencies’ mission achievement after former employees quit their jobs and leave their organization.

Third, regarding involuntary turnover rate, Model 1 and Model 2 present a different story. The estimated coefficient, .127, of the involuntary turnover rate in Model 1 is statistically significant (p < .05) and implies that an additional 1-percentage point increase in involuntary turnover rate will lead to an increase of about 0.13-percentage points in the proportion of employees who have a positive perception of their agency’s mission accomplishment. On the contrary, in Model 2, both the linear term and the squared term of the involuntary turnover rate fail to have statistical significance. The results thus confirm a linear positive relationship between involuntary turnover rate and organizational performance that is expected from Hypothesis 3.

Contrary to the traditional theoretical perspective that involuntary turnovers are beneficial to organizational performance, recent empirical findings (e.g., Batt & Colvin, 2011; Subramony & Holtom, 2011) have presented evidence supporting the negative effects of involuntary turnovers in the private sector. This study’s findings, on the contrary, imply that decisions to terminate employees for reasons of poor performance or misconduct will be advantageous to organizations. The magnitude of an estimated impact seems not to be substantial. These findings, however, may imply that even though involuntary turnover will incur the costs of hiring and training new employees, an organization will obtain nonpecuniary benefits that better achieve its missions and goals.

In sum, among different possible relationships between employee turnover and organizational performance, the results empirically support the inverted U-shaped relationship between employee transfers and organizational performance and a linear positive relationship between involuntary turnovers and organizational performance. Contrary to Batt and Colvin (2011), the results refute the claim that all different employee turnovers have equivalent relationships with organizational performance. Figure 2 describes both relationships confirmed by the empirical results of this research. Other control variables—Relatedness, Cooperation, Resources, and Empowerment—have a statistically significant and positive relationship with organizational performance as previous studies have confirmed.

Figure 2.

Confirmed relationships between employee turnover and organizational performance.

As a robustness check of the current findings, additional models were tested. First, to address an issue of nonnormal distribution of a dependent variable, the models based on a log-transformed dependent variable were tested. Second, additional models with both linear and squared terms centered on their mean were also tested in case the collinearity between them may lead to a type II error in testing the hypotheses by increasing standard errors. These additional models present consistent findings with the current ones.⁵

Conclusion

Is employee turnover indeed detrimental for an organization? Scholars and practitioners in the public sector have long agreed that employee turnover is not beneficial for organizational performance, but their belief has no ample evidence from either a theoretical or empirical perspective. Based on the idea that the type of employee turnover is a situational factor, this research develops and tests hypotheses predicting differing effects of employee turnover on organizational performance by its three main types (employee transfers, quits, and involuntary turnovers). Using a panel data set from 200 U.S. federal agencies between 2010 and 2014, empirical results present both theoretical and practical implications of the research on employee turnover and its effects on organizational performance in the public sector.

This research presents evidence which supports the theoretical perspective of considering potential benefits employee turnover will bring to an organization: The research confirms an inverted U-shaped relationship between employee transfers to other federal agencies and organizational performance. While some scholars (e.g., Corredoira & Rosenkopf, 2010; Dalton, 1997; Somaya et al., 2008) propose that transfers to other departments or suborganizations within the current workplace may benefit sending organizations, the finding of an inverted U-shaped relationship between employee transfer rate and organizational performance presents empirical evidence which lends support to their conjectural perspective: An organization which experiences an appropriate level of employee transfers will gain a positive outcome in its performance. Furthermore, the research presents evidence for a linear positive impact of involuntary turnovers. These findings ultimately suggest that the relationship between employee turnover and organizational performance differs by turnover types: Therefore, researchers should be encouraged to take a contingent perspective on the relationship between employee turnover and organizational performance in their future research.

Practically speaking, the findings of this research suggest that managers and supervisors in federal agencies should take into account different consequences of turnover behavior in managing human resources. Foremost, managers and supervisors should not be bound by a naive belief that employee turnover is simply a problem that they should attempt to prevent or fix. Zero or low-level employee transfer rates may assure a certain level of positive performance in an organization, but efforts to hold employee transfer rate to a minimum will sacrifice the probable benefits of improving organizational performance through reducing compensation costs, improving innovation, and increasing employees’ work motivation. Collaboration by managers and supervisors between federal agencies seems to be essential in managing employees who plan to transfer to other federal agencies.

Managers and supervisors should also continue to make efforts to observe their employees’ performance and to take actions against employees who generate harmful effects on other employees’ performance or on the organization as a whole. Laying off employees who present poor performance or are involved in misconduct may relieve disruptions or stagnation in the working process, and therefore replacing them with new employees may further generate a substantial and positive effect on organizational performance. When terminating employment contracts of federal employees, federal agencies should comply with a due process that requires sufficient evidence, appropriate procedures, and negotiations with unions. While some lawmakers have argued that due process is extremely burdensome and inefficient, the findings of this research imply that managers and supervisors use the due process efficiently and effectively so that only employees who present significant wrongdoings or poor performance are eliminated. However, the findings on the positive side of involuntary turnover should not be discussed on the potential consequences of cutbacks in organizational performance. As briefly mentioned, employee cutbacks entail hiring freeze that prevents organizations from filling up vacant positions with employees who hold better skill sets. As a result, cutbacks cause organizations to experience deterioration in performance (Jones, 1998).

Although this research provides significant contributions to theory and practice, some limitations should be mentioned. First, different organizational contexts may affect the relationship between employee turnover and organizational performance. For example, different agencies may use different managerial styles in helping new employees to obtain their job-relevant skills and knowledge. And different types of mission across federal agencies may also moderate the impacts of employee turnover on organizational performance. In the sample data set of this research, however, these possibilities were not confirmed: The results of both a between-effect estimator model and intraclass correlation coefficient refuted the possibility that unobservable characteristics across agencies may moderate the relationship between employee turnover and organizational performance. Second, the aggregated data structure employed in the current research typically involves the loss of variation among individual responses. This is unavoidable but an accepted trade-off when using panel data approaches instead of cross-sectional data approaches. A more desirable empirical strategy may be an individual-level analysis, but no repeated observations at the individual-level limit this possibility. Third, effects of employee turnover on organizational performance may differ by the quality and occupational types of employees. Each individual employee certainly varies in analytical skills and knowledge relevant to their work. Federal agencies operate with the combined efforts of many different levels of federal employees including senior executives, supervisors, managers, and street-level employees. Federal employees also can be categorized by their specialization: general administrators, human resource managers, technical experts, and numerous other employee groups. Unfortunately, both the Fedscope and the FEVS do not provide such detailed information on individual employees. Future research to investigate differing effects of employee turnover by employees’ quality and specialization would offer valuable insights. Finally, this research does not present the evidence on whether employee transfers bring any changes in performance to organizations that hire those transferred employees. Future research is warranted regarding the potential consequences of employee transfers in organizational performance for those receiving organizations.

Footnotes

Appendix A

Variables and Measures.

Dependent Variable
Organizational Performance (from FEVS)
• “My agency is successful at accomplishing its mission.”

Independent Variables
Agency-Transfer Rate (from Fedscope)
• Proportion of employees who voluntarily transferred to other federal agencies
• Quit Rate (from Fedscope)
• Proportion of employees who voluntarily left the federal government
Involuntary Turnover Rates (from Fedscope)
• Proportion of employees who involuntarily left their agencies for their misconduct or poor performance.

Control Variables
Job Satisfaction (from FEVS)
• “Considering everything, how satisfied are you with your job?”
• Relatedness (from FEVS)
• “I know how my work relates to the agency’s goals and priorities.”
Cooperation (from FEVS)
• “The people I work with cooperate to get the job done.”
• Opportunities (from FEVS)
• “I am given a real opportunity to improve my skills in my organization.”
Trust in Supervisor (from FEVS)
• “I have trust and confidence in my supervisor.”
Resources (from FEVS)
• “I have sufficient resources to get my job done.”
Physical Conditions (from FEVS)
• “Physical conditions (e.g., noise level…) allow employees to perform their job well.”
Empowerment (from FEVS)
• “Employees have a feeling of personal empowerment with respect to work processes.”
Accomplishment (from FEVS)
• “My work gives me a feeling of personal accomplishment.”
Minority (from Fedscope)
• Proportion of non-White employees
Age (from Fedscope)
• Average age of employees
Supervisor (from Fedscope)
• Proportion of managers and supervisors
• Total Employees (from Fedscope)
• Total number of employees

Note. FEVS = Federal Employee Viewpoint Survey.

Appendix B

Descriptive Statistics on Organizational Performance and Employee Turnover Rates.

Turnover rates	M	N	SD	Minimum	Maximum
Performance	0.798	595	0.075	0.496	0.934
Agency-transfer rates	0.018	595	0.031	0	0.632
Quit rates	0.034	595	0.028	0.003	0.211
Involuntary turnover rates	0.027	595	0.055	0	0.136

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

Author Biography

Shinwoo Lee is a PhD candidate at the School of Public and Environmental Affairs, Indiana University. His research interests include public personnel management, organizational behavior, and administrative reforms, with specific focuses on employee separations, government outsouring.

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