Job Switch From the Private Sector to the Public Sector: The Characteristics of the Switchers

I. Introduction

In many aspects, the public sector differs from the private sector (Nutt, 1999). Rainey and Bozeman (2000) investigated similarities and differences observed between private and public sector organizations. These differences make jobs in the private sector and public sector different (more or less attractive to workers) in many aspects such as salary, job security, working conditions, and employment relationships (Buelens & Van den Broeck, 2007; Karl & Sutton, 1998; Markovits et al., 2010). Furthermore, a worker makes a decision on turnover based on these aspects of his or her job (Cotton & Tuttle, 1986; Ertas, 2015; Fry, 1973).

Some workers decide to switch jobs, and the others decide to secure the current job even if the two groups of workers have a similar job or work for the same company. What makes this different turnover decision? Various factors can impact the turnover decision, including worker’s characteristics, firm’s characteristics, economic situation, labor market structure, etc. (Doeringer & Piore, 1985; Miller, 1984; Rosenfeld, 1992). Some scholars have tried to answer the question by focusing on workers’ characteristics such as education, race, gender, and ability (Jovanovic, 1979; Muchinsky & Morrow, 1980; Mueller & Price, 1990). This paper focuses on investigating the characteristics of job-switching workers following Anderson et al. (1994, p. 205) argument that workers’ characteristics are a primary source of variance in turnover decisions.

While great attention has been directed to the job switchers from the public sector to the private sector, there has been little analysis of the job switchers of the opposite direction (Su & Bozeman, 2009, p. 1106). Only recent years have seen a few papers about understanding the job switchers from the private sector to the public sector (e.g., see Bozeman & Ponomariov, 2009; De Graaf & van der Wal, 2008; Su & Bozeman, 2009). These recent studies pave the way for further research on the behaviors of sector switchers out of the private sector into the public sector.

The main focus of this paper is on the sector switchers moving from the private to the public sector. The purpose of this paper is to examine whether the characteristics of sector switchers from the private sector into the public sector are different from stayers. Our research is related to a broader set of questions that asks how employees’ characteristics and sector switching are related. Employees would choose to switch sectors (or jobs) for many reasons. It would be reasonable to think that the sector switchers from the public to the private sector probably have systematically different reasons from the sector switchers of the opposite direction.^[1]

Knowing the differences in the characteristics of sector switchers from the private to the public sector and those who stay in the private sector is beneficial. First, the boundary between the two sectors has been blurring (Billis, 2010; Dees & Anderson, 2017). This means that more people can switch sectors with fewer efforts or difficulties. Second, the private sector is believed to be more efficient than the public sector (e.g., Grossman et al., 1999; Hall & Lobina, 2005). Based on this belief, many countries have tried to reform their public sector to increase its efficiency by privatization (e.g., Pack, 1987; Sheshinski & López-Calva, 2003). So, bringing people with work experience in the private sector to the public sector can make the reform successful. In other words, the public sector would be more efficient by hiring workers with knowledge, skills, and experience from the private sector. Third, it may not be easy for the public sector to attract qualified and skillful people from the private sector, mainly because of the wage gap between the two sectors (Borjas, 2002). Therefore, knowing the characteristics of those who are more likely to switch from the private sector to the public sector is beneficial for the public sector to attract more qualified and skillful workers.

This paper is structured as follows. Section II reviews research on switching job sectors and introduces the main hypotheses of this study. Section III explains the empirical methods and data. Section IV empirically examines the characteristics of job switchers from the private sector to the public sector. Section V concludes with a summary of key results, policy implications, avenues for future research.

II. Switching Job Sectors and Relevant Studies

People keep finding better jobs across sectors (Mortensen & Pissarides, 1999). However, switching job sectors is not an easy decision for people because it reflects the change of workplace environment, and it contains some uncertainty for their changes. Job switching between job sectors (private and public) would probably be a more complicated decision than job switching within a sector because of the differences between the two sectors. The differences between the private and public sectors seem to be decreasing over time (Boyne, 2002; Poole et al., 2006). However, it does not mean that there are no significant differences among sectors. The literature clearly shows the differences between the public and private sectors (Allison, 1983; Rainey & Bozeman, 2000).

Some theories explain job sector switch behavior assuming that people decide to change their job sector based on their current job status and expectation for future job expectations. Person-organization fit theory (P-O fit theory) argues that employees’ behavior and attitude can be explained with the relationship between employees and the organizational work environment (Edwards & Cable, 2009; Rynes & Cable, 2003). When employees’ characteristics do fit with organization’s characteristics, they are more satisfied, more productive, and want to stay in their current work environment (Galletta et al., 2011; Kristof, 1996; Kristof-Brown & Guay, 2011; Ostroff & Schulte, 2007; Schneider et al., 2000; Wynen et al., 2013). In the opposite case, employees have less satisfaction with their job and want to switch their jobs.

The characteristics of employees include employees’ personal goals and value on their job (Edwards & Cable, 2009), so it covers various personal attitudes and behaviors on the job such as satisfaction and importance on salary or public service motivation (PSM). Social exchange theory claims that employees determine their attitude and behavior depending on the fulfillment of their self-interest through personal and organizational exchanges (Blau, 1964). Therefore, employees who feel treated fairly and receive what they think are more motivated to perform on a high level and stay with the organization. Conservation of resource theory assumes that people are trying to support, foster, contain, protect the existing resources that they are valuable (Hobfoll, 2011, 2012; Hobfoll & Lilly, 1993). When employees feel that they lack resources, such as low benefits and satisfaction, they tend to leave the organization.

Attraction-Selection-Attrition (ASA) theory also explains the employees’ job sector switch (Schneider, 1987). This theory explains that people look for and tend to be easily attracted toward an organization similar to themselves or goes well with their own interest or personality (Liu et al., 2010). Schneider (2001) argues that workers judge their P-O fit and seek to find jobs in organizations with characteristics similar to their own. Also, the organization selects someone who has a similarity to the organization (Kristof, 1996; Werbel & DeMarie, 2005). People leave the organization if they are not mixed well with the organization. These theories enhance the understanding of why employees decide to switch their job sector under their current employees-organization relationship.

Many other factors affect job sector switch decisions from the private to the public sector (Akerlof et al., 1988). In other words, the job sector switching from the private sector to the public sector can also be understood by various theories. First, a highly competitive organizational environment, job security, and pension issues in the private sector can motivate people to move to the public sector providing greater job security and generous pension (Greenhalgh et al., 1988; Lewis & Frank, 2002; Su & Bozeman, 2009). Second, employees’ desire to increase their satisfaction or expectation on their work leads to change their job sector (Bozeman & Ponomariov, 2009). For example, the workforce environment in pursuit of profit than public interest makes people (especially those who have high publicness) decide to change the job sector to fulfill their interest and expectation to their job (Perry, 1996). Third, institutional factors affect the job sector switch, especially women and minority groups (Llorens et al., 2007). Women and minority groups get more protection against discrimination and wage penalties in the public sector than in the private sector (Lewis & Frank, 2002). Fourth, the decrease in the gap between the private and public sectors makes people easy to switch the job sectors (Boyne, 2002; Poole et al., 2006).

Here are the main hypotheses of this study based on the theories and previous empirical studies. Millard and Machin (2007) describe more women than men working in the public sector. However, the pattern of male and female employment in the private sector was the opposite of the pattern in the public sector. Mayer (2014) also argued that the ratio of female full-time workers in state and local governments is higher than the ratio of female full-time workers in the private sector. Hypothesis 1 [Gender]: If other things are equal, then female employees would be more likely to switch sectors from private to the public sector than male employees.

Deep-rooted African American disadvantages can exist in the private sector (Kamarck, 2007). Wilson et al. (2013) argue that if an employer’s discretion increases, then African Americans are more disadvantaged. Knowing that the private sector allows more discretion than the public sector, I think that minority groups would be more likely to work in the public sector if other things are equal. Lewis and Frank (2002) empirically show that minorities prefer public-sector jobs to private-sector jobs. Hypothesis 2 [Race]: If other things are equal, then non-white employees would be more likely to switch sectors from the private to the public sector than white employees.

Workers with a higher level of human capital have more access to numerous job opportunities (Ng & Feldman, 2009). In general, the level of education of public-sector workers is higher than private-sector workers (Mayer, 2014; Millard & Machin, 2007). Similarly, Blank (1985) finds that the probability of public-sector employment rises significantly with education. Hypothesis 3 [Education]: If other things are equal, then employees with higher education would be more likely to switch sectors from private to public than employees with lower education.

Workers with government-funded projects would be more likely to move from the private to public sectors for two reasons. First, there can be a selection. A person with more interest in the public sector would choose to work for a private firm with public-sector-like attributes and decide to engage in government-funded projects. Second, workers with experience in government-funded projects can develop an interest in working for the public sector. Hypothesis 4 [Experience]: If other things are equal, then employees with experiences of government-funded projects would be more likely to switch sectors from private to public.

People with a high degree of risk aversion would be more likely to want to work in the public sector (Bellante & Link, 1981; Blank, 1985; Pfeifer, 2011). In general, public-sector jobs have a higher level of job security than private-sector jobs (Munnell & Fraenkel, 2013). Mussagulova et al. (2019) find that job security is one of the main motives for working in the public sector. Hypothesis 5-1 [Satisfaction on job security]: If other things are equal, employees with lower job security satisfaction would be more likely to switch sectors from private to public. Hypothesis 6-1 [Importance of job factors: Job security]: If other things are equal, employees who think job security is an important job factor would be more likely to switch sectors from private to public.

Public-sector employees are known to have more prosocial and altruistic proclivity (Mussagulova et al., 2019; Perry & Wise, 1990; Ritz et al., 2016). Wright and Christensen (2010, p. 156) argue that PSM of workers in the public sector was higher than private-sector employees. Carpenter et al. (2012) also find a positive relationship between the level of PSM and attraction to the public sector. Hypothesis 5-2 [Satisfaction on PSM]: If other things are equal, employees with lower satisfaction on PSM would be more likely to switch sectors from the private to the public sectors. Hypothesis 6-2 [Importance of job factors: PSM]: If other things are equal, then employees who think PSM is an important job factor would be more likely to switch sectors from private to public.

In this study, I include both satisfaction and importance on job aspects. Studies found that the relationship between satisfaction and importance is higher for those aspects rated as more important than for those aspects rated as less important (Ewen, 1967; Schaffer, 1953). However, as Locke (1969) pointed out, there exists a discrepancy between satisfaction and importance. The levels of satisfaction and importance are not necessarily the same or proportional for each person. In other words, satisfaction would result from the difference between ‘what is wanted’ and ‘what is obtained.’

Moreover, ‘what is wanted’ is related to the importance of the job aspect. For example, there are two workers, A and B. Suppose A thinks of a salary as an important job factor, while B thinks of a salary as an unimportant job factor. The more important the job factor, the greater the potential range of satisfaction on the job factor (Locke, 1969). Besides the range, A’s satisfaction level on salary should likely be lower than B’s if other things between the two workers are the same (or very similar).

III. Data and Empirical Methods

A. Data

This study uses data from the National Survey of College Graduates (NSCG).^[2] The website of NSCG describes the data as follows:

“What is the NSCG?: The National Survey of College Graduates (NSCG) is a study by the National Science Foundation (NSF), an independent agency of the U.S. government. The U.S. Census Bureau collects and processes the survey data for NSF. The NSCG has been conducted since the early 1970s and is the most important source of information on the education and career paths of the Nation’s college-educated population.”

This survey is conducted once every two or three years and provides the various characteristics of the college graduates of the United States. The characteristics include detailed demographic, education-related information such as education level from bachelor, master, doctoral to professional degree, current and past job-related information including job sector, salary, training, working hours. Using unique individual identifiers in 2003, 2006, 2010, and 2013 survey year, I construct a panel dataset. So, I can track all employees over time and across different employers. I compare two cohorts over the periods from 2003 to 2006 and from 2010 to 2013. Here is the reason why I split the four surveys into two periods: 2003-2006 and 2010-2013 instead of making a single panel data using the four surveys. Eighty-four point five percent of people in 2003 show up in 2006, while 42.5% of people in 2010 show up in 2013 (i.e., 27,448 out of 64,601 in 2010 show up in 2013). However, no one shows up in all four surveys.

This study excludes individuals in the lower 1% quartile or higher 99% quartile of annual salary. I only include people who got an annual salary of more than $14,000 and less than $237,000 from 2003 to 2006 and more than $14,500 and less than $298,000 from 2010 to 2013. With the exclusion of these outliers, I can use a more realistic population of employees. I only consider full-time employees working more than 35 hours per week and 52 weeks per year.^[3]

The dependent variable of the analyses of this paper is switching job sectors (Variable’s name: Sector switching). From NSCG, employees were asked the following survey question: ‘which one of the following best describes your principal employer?’. Respondents choose one job sector among business/industry sector, government, and educational institution. Business/industry sector consists of three subsectors: 1) for-profit, 2) self-employed, not-incorporated, and 3) non-profit. Based on the information on job sector switches over the periods, I make a dummy variable whether employees switch their sector or not: set to 1 if employees who worked for-profit business/industry sector in 2003 or 2010, and employed in government in 2006 or 2013, 0 if respondents are not employed in government in 2006 or 2013. In short, the stayers in the private sector get 0, and sector switchers from the private sector to the public sector get 1 for the dependent variable.

The key explanatory variables are defined as follows. Gender is a dummy variable equal to 1 if the employee is male. Race is a categorical variable with five categories: White, Black, Asian, Hispanic, and Others. Education measures the level of schooling of the employee: Bachelor, Master, and Doctoral/Professional. Job mismatch measures to what extent the employee’s job is related to his/her highest degree: Closely related, Somewhat related, and Not related. The question in the 2013 NSCG survey for this variable is “To what extent was your work on your principal job related to your highest degree?” I use three-point Likert scales: closely related = 1, somewhat related = 2, not related = 3. Whether the employee’s job is related to government projects is measured by Government-funded project variable. The question in the 2013 NSCG survey for this variable is " Thinking back now to 2012, was any of your work during 2012 supported by contracts or grants from the U.S. government?" Satisfaction on principal job: Security is a variable that measures the employee’s satisfaction level on job security. The question in the 2013 NSCG survey for this variable is “Thinking about your principal job held during the week of February 1, please rate your satisfaction with that job’s security.” Similarly, Satisfaction on principal job: PSM is a variable that measures the employee’s satisfaction level on job’s contribution to society. Respondents choose one among four options to each factor: very dissatisfied, somewhat dissatisfied, somewhat satisfied, and very satisfied. I use four-point Likert scales: not important at all = 1, somewhat unimportant = 2, somewhat important = 3, very important = 4. The variables measuring the importance of job factors are Importance of Job factors: Security and PSM. The question in the 2013 NSCG survey for these variables is " When thinking about a job, how important is each of the following factors to you?" Job satisfaction and job importance have additional aspects such as salary, benefits, location, opportunity for advancement, intellectual challenge, level of responsibility, and degree of independence.

I use several independent variables to figure out the factors that affect employees’ sector switching decisions. Employees’ age is categorized into five groups: 20s, 30s, 40s, 50s, and 60s and over (Variable’s name: Age). Marriable is a dummy for whether the employee is married (=1) or not (=0). Work-related training participation status is used in our analysis(Variable’s name: General training). Respondents select yes or no to the survey question: ‘during the past 12 months, did you attend work-related training, such as workshops or seminars?’. Besides these variables, I include Supervisor status and education/job-related variables (Salary, Professional meeting, Size of employer, Location of employer, and Job category). Supervisor is based on the survey question “did you supervise the work of others as part of the principal job you held during the week of [survey reference date]?” Salary is transformed as a log annual salary. Professional meeting is based on the survey question “during the past 12 months, did you attend any professional society or association meetings or professional conferences?” In the survey, employer size is defined as how many people worked for your principal employers, and categorized by eight groups: 1-10, 11-24, 25-99, 100-499, 500-999, 1,000-4,999, 5,000-24,999, and over 25,000 employees (Size of employer). Similarly, employer’s location is categorized by four groups: Northeast, Midwest, South, and West (Location of employer). The National Survey of College Graduates(NSCG) is focused on employees in the science and engineering workforce. Therefore, the survey provides seven categories of jobs: Computer and math science, Life and related science, Physical and related sciences, Social and related sciences, Engineering, S and E related fields, and Non-S and E fields (Job category).

B. Empirical Methods

I employ logit regression to identify the determinants of sector switching decisions because I have a dichotomous dependent variable. The dependent variable Sector switching is 1 if the employee switched sectors from the private to public and is 0 if the employees stayed in the private sector.

$$\begin{align} \log\left\{ \frac{P\left( Sector\ switching = 1 \middle| X \right)}{1 - P\left( Sector\ switching = 1 \middle| X \right)} \right\}& = \\ \beta_{0} + \beta_{1}x_{1} + \ldots + \beta_{k}x_{k}& \tag{1} \\ \\ P\left( Sector\ switching = 1 \middle| X_{1}, \ldots, X_{k} \right)& = \\ \frac{\exp\left( \beta_{0} + \beta_{1}X_{1} + \ldots + \beta_{k}X_{k} \right)}{1 + \exp(\beta_{0} + \beta_{1}X_{1} + \ldots + \beta_{k}X_{k})}& \tag{2} \end{align}$$

Where $P\left( Sector\ switching = 1 \right)$ is the probability of the employee switches his/her job from the private sector to the public sector. The explanatory variables are expressed by the vector X that includes $x_{1}$ though $x_{k}$. The explanatory variables included in logit regressions are Age, Gender, Marriage, Race, Education, Job mismatch, Government funded project, Salary, Supervisor, General training, Professional meeting, Size of employer, Location of employer, Job category, Satisfaction on principal job, and Importance of job factor.

Here are some theoretical and empirical backgrounds of choosing control variables.^[4] Based on the conservation of resource theory, workers should be more likely to leave the organization if they feel they lack resources such as low benefits and satisfaction. I regard Salary, General training, Professional meeting, Satisfaction on principal job, and Importance of job factor as some forms of benefits and satisfaction. Tai et al. (1998) indicate that age, tenure, income, and professional rank have an impact on turnover. Healy et al. (1995) find that age does not show a strong statistical relationship with a decision to leave an organization. However, Ng and Feldman (2009) argue that age–voluntary turnover relationship would be stronger than Healy et al. (1995). Lewis and Frank (2002) find that older Americans prefer public-sector jobs than young Americans. Ahituv and Lerman (2011) find that married workers are more likely to get higher wages and job stability than unmarried workers. On the other hand, Fang (2007) argues that marital status does not significantly impact turnover intention. A skills-job mismatch would harm performance and result in layoffs (Collings & Mellahi, 2009). Chavadi et al. (2021) show that Job mismatch has a positive relationship with turnover intention. Similarly, Ju and Li (2019) argue that education-job mismatch negatively affects job tenure (years). Even and Macpherson (1996) say that the labor turnover of large firms is lower than small firms. Idson (1993) proposes that larger firms’ greater capacity to develop long-term relationships with their workers would lower turnover rates.

IV. Empirical Results

I check whether all variables mentioned above are different between switchers from the private sector to the public sector and the stayers using a series of t-tests. Table 1 (years: 2003-2006) and Table 2 (years: 2010-2013) provide the differences in the mean of the variables between two groups, including t-tests of whether the mean differences are statistically significant.

According to these results, the sector-switching group significantly differs from the stayer group in several factors. Notably, switchers from the private(business/industry profit) sector to the public sector(government) show lower salary, more government funding experience, lower level of satisfaction on job security, benefit, an opportunity for advancement, and intellectual challenge, higher level of satisfaction on PSM(contribution on society) than the stayers. The sector-switching group also puts more importance (and is more satisfied) in PSM on their job than non-switchers.

The results of a series of t-tests of each explanatory variable are drawn, not controlling other explanatory variables. The logit regression results using the NSCG data for 2003-2006 and 2010-2013 are shown in Table 3 and Table 4, respectively. Table 3 and Table 4 present all of the estimates for seven models with different sets of explanatory variables. The coefficient of each explanatory variable represents the change in the log-odds of switching jobs from the private sector into the public sector from a one-unit increase in the explanatory variable, holding the other variables in each model. More generally, a positive coefficient indicates that the probability of the sector switching from the private sector into the public sector rises with an increase in the explanatory variable after accounting for the effects of the other explanatory variables.

The sign of the coefficients of the variables in Table 3 and Table 4 has essential information. However, the magnitude of the coefficients does not have a particular meaning in the context of the logit regression. Therefore, I present the estimates of marginal effects in APPENDIX, Table A and Table B. Table A is based on Model 7 in Table 3, and Table B is based on Model 7 in Table 4. Most of the main variables of interest show statistical significance.

The first hypothesis of this paper (H1: Gender) can be tested using the explanatory variable ‘Gender’. Female workers were more likely to switch their jobs from the private to the public sector than male workers from 2003 to 2006.^[5] This empirical result is consistent with the previous studies. Millard and Machin (2007) showed more women than men working in the public sector, but the pattern of male and female employment in the private sector was the opposite of the pattern in the public sector. Mayer (2014) also argued that female workers held about 57% of full-time jobs in state and local governments, but women accounted for about 42% of all the full-time jobs in the private sector.

The coefficients of ‘Race: Black, Asian, Hispanic, and Others’ suggest that minorities were generally more likely to switch jobs from the private sector to the public sector (H2: Race). Interestingly, the probabilities of switching sectors from the private into the public of black workers were higher than any other race. This empirical result is related to Kamarck (2007) that explained the existence of deep-rooted African American disadvantages in the private sector. Also, Wilson et al. (2013, p. 975) argued, “Study of Income Dynamics sample indicate that the ‘new government business model,’ characterized by increased employer discretion has disproportionately disadvantaged African Americans.”

As expected, more-educated workers were more likely to switch jobs from the private sector into the public sector (H3: Education). More precisely, the workers with a doctor or professional degree had significantly higher chances of switching sectors than the workers with a bachelor’s degree. These findings link to Millard and Machin (2007, p. 47) that showed a higher level of education of public sector workers over private-sector workers. Mayer (2014, p. 11) also presented a statistic that “On average, public sector employees have more years of education than private-sector workers. In 2013, 53.6% of workers in the public sector had a bachelor’s, advanced, or professional degree, compared to 34.9% of private-sector workers”

The coefficients of the explanatory variable ‘Government-funded project’ are positive and statistically significant, which means that employees with experiences of government-funded projects were more likely to switch sectors from the private to the public sector (H4: Experience). I have to be cautious about interpreting these coefficients in terms of causality. There can be two directions. The first one is that workers in the private sector who experienced government-funded projects can develop an interest in the public sector (such as PSM) and human relationships with government workers. This can make the workers in the private sector switch jobs in the public sector. On the other hand, the other direction can be explained by selection. It is reasonably possible that workers in the private sector with a higher interest in government or public sector should be more likely to be involved in government-funded projects. In addition, the workers whose firm and job are close to the public sector would have less difficulty when they switched into the public sector because of the similarity of work environment, job description, etc. Regardless of these concerns of interpreting the coefficients, what is clear is that employees in the private sector with more experience in government-funded projects had a higher chance to move to the public sector.

The workers in the private sector with a lower level of satisfaction on job security were likely to switch into the public sector (H5-1: Satisfaction on job security). The pattern showed a clear increasing trend: the absolute values of the coefficients increased over time. Interestingly, the coefficients of ‘Importance of job factors: Security’ are positive but not statistically significant (H6-1: Importance of job factors: Job security). These empirical findings suggest that employees in the private sector would consider their satisfaction on job security more seriously to decide their turnovers to the public sector. Previous studies showed that the public sector has higher job security. In other words, stability of employment is greater in the public sector than in the private sector. Munnell and Fraenkel (2013, p. 31) emphasized the higher level of job security in the public sector: “public sector worker is less likely to lose a job than a private-sector worker.” Mussagulova et al. (2019, p. 123) also suggested that one of the primary reasons for joining public service is job security. These job choices can be related to the degree of risk aversion of an individual worker. Individuals with a high degree of risk aversion would be more likely to want to work in the public sector (Bellante & Link, 1981; Blank, 1985; Pfeifer, 2011).

As expected, those who place a higher priority on PSM (contribution to society) were more likely to switch jobs from the private to the public sector (H6-2: Importance of job factors: PSM). The pattern was apparent for both periods of 2003-2006 and 2010-2013. Interestingly, workers in the private sector with a higher level of satisfaction on PSM were also likely to join the public sector in the second period (2010-2013) (H5-2: Satisfaction on PSM). PSM appeared to be one of the essential factors workers consider when deciding to switch sectors from private to public. Public servants are known to have more prosocial and altruistic proclivity (Mussagulova et al., 2019; Perry & Wise, 1990; Ritz et al., 2016). Wright and Christensen (2010, p. 156) mentioned that PSM of workers in the public sector was higher than private-sector employees. They also showed that PSM increased the likelihood of choosing a job in the public sector as an employee’s subsequent job, while PSM would not clearly predict the employee’s first job, which is highly consistent with the findings from hypotheses on PSM of this paper. Jeon and Robertson (2013) showed that the workers with a higher level of PSM were less likely to leave the public sector, which suggested PSM could be used as one of the employee-retention strategies of the public sector.

This paper focuses on finding the difference in characteristics between sector-switchers from the private to the public sector and the stayers. However, investigating the difference in characteristics between the sector-switchers from the private to public and the sector-switchers of the opposite direction is worth investigating. Table C and Table D in APPENDIX present logit regression results using the sector-switchers of the opposite direction, from the public sector to the private sector. Comparing the results in Table 3, Table 4, Table C, and Table D gives us valuable information. The coefficients of the main variables related to the hypotheses in Table 3 and Table 4 have mostly a different sign from the coefficients in Table C and Table D. These results reinforce the main empirical results that there are significant difference in characteristics between the sector-switchers from the private to the public sector and stayers.

V. Conclusion

With this study, I aimed to answer the following central research question: "Are the characteristics of sector switchers from the private sector into the public sector are different from stayers?" By addressing this question, I tested eight related hypotheses. The findings confirm that the sector switchers from the private sector to the public sector were different in many aspects: (1) Females and unmarried employees were more likely to switch their jobs from the private to the public sector from 2003 to 2006. (2) Black employees were more likely to move from the private to the public sector for the whole period. (3) The more educated employees seemed to have more freedom to change their private to public careers. (4) Employees with experience in government-funded projects were more likely to switch jobs from the private to the public. (5) Workers who showed a low satisfaction level in job security and considered PSM as an essential job principle were more likely to switch from the private sector to the public sector.

Anderson et al. (1994, p. 205) clearly argued that “Overall, there is no simple story of one factor being the dominant influence on turnover.” Other factors not investigated in this paper that impact sector switches from the private sector to the private sector may exist. However, the empirical findings of this paper can provide valuable and usable knowledge for improving our understanding of employees’ characteristics and motivation to work for the public sector. Taken together, the empirical results of this paper may provide some interesting implications for the literature on public policy and public management.

Most previous studies focus on turnovers from the public sector to the private sector. To the best of my knowledge, this is one of a few papers investigate employees’ turnover from the private sector to the public sector. In terms of data, this paper has advantages over the previous studies. First, the data used in this paper contains information on ‘actual turnover’, not ‘turnover intention.’ Boouckenhooghe et al. (2013) explained that turnover intention is a worker’s desire or willingness to leave an organization. However, ‘actual turnover’ is different from ‘turnover intention’ as Aydogdu and Asikgil (2011, p. 3) described: “Intention to turnover is defined as one’s behavioral attitude to withdraw from the organization whereas turnover is considered to be the actual separation from the organization.” Most of the previous studies on turnover and sector-switching used survey data sets with questions on turnover intention. Even if there is a positive correlation between turnover intention and actual turnover, it is still possible that employees who revealed turnover intention can end up securing the current job. Second, the data of this paper has relatively long periods and a larger number of employees. Related to that, previous empirical studies lack panel data analysis. A partial solution to the previous studies’ problem is to track the same employees for more than one time period. In this paper, I track turnovers of the same workers over the periods: 2003-2006 and 2010-2013.

The public sector would be benefited from hiring employees with work experience in the private sector for many reasons. Put differently, bringing knowledge, skills, experience of the private sector into the public sector is getting more critical. First, despite the differences between the private sector and public sector (Buelens & Van den Broeck, 2007; Karl & Sutton, 1998; Markovits et al., 2010; Rainey & Bozeman, 2000), the boundary between the private and public sectors has been blurring (Billis, 2010; Dees & Anderson, 2017).^[6] This phenonium is related to creating ‘hybrid’ organizations and the combination of multiple logics within organizations (Bromley & Meyer, 2017, p. 942). Second, the public sector is believed to be less efficient than the private sector. Leibenstein (1976) proposed four critical reasons why firms or governments may not be able to produce products or services at the least cost: incomplete labor contracts, unpriced inputs, incomplete production or cost functions, and individual motivation. Public sectors would suffer more from the four reasons because (1) public sector agencies would have fewer incentives to minimize costs and maximize profits, (2) the services produced and offered by public sector agencies are often hard to put prices, (3) public sector employees have a higher degree of job security. The public sector would be expected to be more efficient by bringing more workers with private sector experience.

Nevertheless, it is not easy for the public sector to attract qualified and skillful people from the private sector. Borjas (2002) showed that it was getting more difficult for the public sector to attract and retain high-skill workers. He also argued that the main reasons for the difficulty were the wage gap and wage structure: (1) the mean wage in the private sector was higher than the public sector, and (2) the wage structure of the public sector was more condensed (smaller variation in the wage distribution) than the private sector. It is, however, evident that there should be other factors besides the wage gap and structure to affect employees’ decision to work for the public sector.

How can the public sector attract skillful and qualified workers from the private sector? Before answering the question, we may have to ask this question: “who are attracted to work in the public sector?” or “Who wants to switch from the private sector into the public sector?” The public sector needs to understand the characteristics of workers who prefer to work for the public sector over the private sector. The empirical findings of this paper would open a window into the extent and characteristics of sector switchers from the private sector into the public sector.

The study needs to be interpreted with caution because the economic and cultural situations such as a demographic structure, labor market structure, and relationship between the private and public sectors are different among countries. In other words, evidence from a single country, the United States, may not be representative. Another limitation, albeit one faced by most studies of turnover or sector switch, is that other factors can affect people’s decision on sector switch that are not included in the models of this paper.

The findings in this paper raise issues for academic researchers, policymakers, and managers. First, this study provides empirical evidence that there are significant difference in characteristics between the sector-switchers from the private to the public sector and the stayers. I also show that the difference in characteristics between the sector-switchers from the private to the public sector and the sector-switchers of the opposite direction is clear. Until recent years, there have not been enough studies on turnover from the private sector to the public sector. Therefore, we do not have solid evidence on the individual characteristics of the sector-switchers. Moreover, we do not have much information on what attracts people to the public sector. We need more studies to find out how the public sector attracts (high-skilled) workers.

Second, bring (high-skilled) workers from the private sector to the public sector is one thing, and retaining them is another. Talented and ambitious workers will stay with their current organization only if they are offered development opportunities, motivation, and nurturing (Davis et al., 2007). However, the public sector is often vulnerable to brain drain, particularly in developing countries (Kim, 2008). Therefore, knowing the characteristics of the people more likely to work for the public sector (or switch jobs from the private to the public sector) would be the first step to developing retention strategies for key talent.

Third, In recent years, the literature on Human Resource Management (HRM) emphasis on how employee’s performance contributes toe organization performance (Mudor, 2011). More research is needed to understand what the sector switchers bring into the public sector. In detail, we can measure individual and organizational performance changes caused by hiring workers from the private sector.

To resolve these, one would require very detailed data on turnovers, individual characteristics, performances, etc. More research along these lines is needed. As is always the case in social studies, more work remains to be done.

Appendix