Private sector jobs: It has been commonly believed in the studies that public sector organizations have a different approach in comparison to private sector organizations. This paper aims to help further develop this question by examining the extent to which the relation between worker efforts differs greatly within the public sector as well as the private sector.
Through the use of information taken from the Monthly Employment Survey (PME), Brazil 2003-2012, and proxy data for work effort (unpaid time off and absences) The study revealed that there were distinct differences in the profiles of workers dependent on the sector in which they work.
Also, the estimates of these dynamic models prove that the degree of effort varies as they transition from one industry to another in the labor market. For instance, employees in the public sector do not tend to engage in non-paid overtime similar to those working in the private sector, and are more likely to be absent from work.
Resume – Private Sector Jobs
Na literatura economica brasileira tem sido amplamente difundido que o setor publico funciona de forma diferente em comparacao com o setor privado. Este artigo pretende contribuir para desenvolver ainda mais este problema, investigando se a relacao entre os esforcos despendidos pelos trabalhadores difere significativamente entre o setor publico e o setor privado.
Tendo como base de dados a Pesquisa Mensal de Emprego (PME), Brasil 2003-2012, e proxies para o esforco de trabalho (horas extras nao pagas e ausencias), observaram-se, inicialmente, diferencas significativas entre os perfis do trabalhador, dependendo do setor em que estao empregados.
Por sua vez, os resultados da estimacao dos modelos de paineis dinamicos confirmam que o nivel de esforco do trabalhador se modifica de acordo com a mudanca ocupacional de um setor para outro no mercado de trabalho.
Resumidamente, os trabalhadores do setor publico nao tendem a trabalhar horas adicionais nao remuneradas comparativamente aos do setor privado, alem de ser mais propenso a faltas no emprego.
Introduction
In the past few years, the dynamics of the labor market are one of the primary subjects of study. The literature on labor economics contains numerous studies on job shifts as well as the similarities and differences between the private and public sectors. But, only a few of these studies focus on sector switching, which highlights the absence of empirical research on the differences between private and public sectors in the mentioned dynamic.
The articles on sector switchers depend on a myriad of issues to present arguments on the shift, for example, the historical and environmental distinctions between the two sectors (Su and Bozeman 2009; Bozeman as well as Ponomariov (2009, Bozeman and Ponomariov) and the differences in motivation and incentive (Rainey and Chun 2005) as well as the level of formalization (Buchanan 1975) as well as the impact of the security of job and salary (Rainey and Bozeman 2000; Boyne 2002, Ichino and Riphahn (2004) Engellandt and Riphahn 2005; Rainey as well as Chun 2005 Bradley and colleagues. 2007).
Based on Bozeman as well as Ponomariov (2009) and Bozeman and Ponomariov (2009), one reason for the lack of systematic study is the small number of databases available. The majority of databases are not focused on sector switchers or work records, and when such variables are considered, it is hard (because of the method by that data are aggregated) to connect sector-switching patterns with motivation or attitude variables.
Sector switchers are people who move from the private sector to the public sector or the reverse. Recent studies have shown that people switch sectors due to various reasons. The reason for this is due to the characteristics of the job (Kaufman and Spiderman 1982 Su and Bozeman, 2009) and also to the desire for a certain industry (Eisenberger and Co. 1986) and individual values (Cohen 1993).).
Despite the obvious importance of knowing the connection between changing sectors to advancement in their career, it is important to recognize that people can change jobs due to a variety of specific reasons. Numerous studies examine the behavior of job seekers and motivation for work, as well as the rate of turnover (Karl and Sutton 1998), and at the end of the day, many factors lead to job change.
Apart from the numerous motives behind job changes and turnover, it is important to remember that sometimes turnover is seen as an independent variable, particularly when it comes to the impact on the performance of the organization (e.g., Kacmar et and. (2006)).
In this article, the primary question is to determine if those employed in the private sector are putting in greater effort than those working in public sector jobs and, if yes examine whether the extra effort is due to non-observable factors that determine the decision to work in the private sector. Thus, the focus is not always on the causes for the reasons for shifts in employment but rather on whether they cause an alteration in the behavior of individuals.
In this way, this study is a good way to offset the absence of empirical research on the distinction between private and public individuals. This is because the majority of studies concentrate on environment and organizational traits instead of individuals.
But, this paper focuses on the work of workers in the workplace of employees in addition to the notion that workers in private or public sectors differ fundamentally in their efforts, the companies will differ as well. As stated by Boyne (2002) in his 2002 article, private and public companies tend to differ in several key aspects most definitely, their workers. According to Kjeldsen as well as Jacobsen (2013), The interaction between employees and the organization is a key element to the success of an organization.
In this regard, this paper attempts to tackle a subject that is not often discussed: the connection between work effort and sector change. The significance of this relationship is closely linked to the degree of productivity and efficiency in companies that are either private or public. While many other aspects can contribute to productivity and efficiency and efficiency, the performance of jobs is considered as the most significant, and the job is thought of as a function of worker effort (Mitchell 1982).
Based on Boyne (2002) that, although in private companies, owners have a direct financial incentive to supervise and regulate workers conduct In the public sector, monitoring is seen as a public good in which managers stand to benefit from putting their efforts into this task, which results in less effectiveness.
With this in mind, and in light of the literature that is cited throughout the Brazilian characteristics of the Brazilian labor market I examine the idea that private sector workers have an increased level of effort when compared to workers in the public sector. I believe this is from a variety of studies (Baldwin 1984, Goulet and Frank, 2002, Lyons et al. (2006), Buelens and Van Den Broeck, 2007; Baarspul and Wilderom 2012) and also on Brazilian characteristics of the Brazilian labor market (Foguel and others. 2000; Gonzaga and co., 2003). 2003).
This is based on previous studies which have demonstrated statistically significant differences between public and private sector workers, which generally indicates less commitment to the organization for employees of the public sector (Lyons and co. 2006.
Buelens as well as Van Den Broeck Buelens and Van Den Broeck, 2007) but, writers such as Perry as well as Wise (1990), as well as Kjeldsen, emphasize the motivations of public sector employees working in the public sector, employees are motivated by the intrinsic value of contributing to social welfare. This is essentially the notion of the public.
A more thorough understanding of work is crucial to define the effectiveness and efficiency of both the private and public sectors. This is why, along with other reasons, I hope to gain insight through the study of people working as “sector switchers,” moving from private to public. To accomplish this I make use of proxies for work like unpaid overtime work (workers who work longer times than what is stated in their contracts) and absence rates.
This article is designed to add to research by providing simple and simple methods for estimating the level of effort that are based on the behavior of workers and using a longitudinal data set (from the Monthly Employment Survey, PME–Pesquisa Mensal de Emprego Brazil 2003-2012) in contrast to most papers, which are focused on psychological theories and employs only cross-sectional information collected from surveys.
While the application of these proxies could have imperfections, they are the most efficient and effective analytical tools available in the literature.1
Job shift and work effort: theories and empirical evidence
Theory: Worker effort
The model of human capital is based on the assumption that the decision to change jobs is determined by its utility value for a person. The decision to leave is guided based on the net discount value of an individual that is, the benefits less the cost of a job change. Thus, employees move when their net gains are positive. Also, as the individuals have different individual discount rates as well as in the costs of personnel as well as benefits may be concluded that certain workers tend to change jobs more than other workers are.
As per Ehrenberg as well as Smith (2012) According to Ehrenberg and Smith (2012), in an environment of competitive employment, the rate of job loss is usually and continues to be the case. This is partly because employees have different skills and capabilities, and the firms differ in their working conditions.
About employees, though the economics of theory generally presumes that benefits are the primary factor that influences the choice of jobs for workers Many scholars who study public administration believe that the importance of money is lower than non-monetary rewards (Karl and Sutton 1998; Rainey 1983) as well as the security of employment (Houston 2000 ), job security (Houston, Lewis Frank, 2002), job security (Houston and Sutton, 2000, Lewis Frank 2003) and the degree of motivation and incentive (Rainey and Chun 2005 Lipset as well as Schneider, 1983).).
The advantages of all the factors mentioned above will result in the degree of the employee’s commitment to the company. But, as per Foster and Rosenzweig (1994), the quantity of the inputs provided by an employee will be contingent directly on the degree to which it is acknowledged and, consequently, the amount of reward will be determined by the extent of monitoring. monitoring.2 This is because of the moral hazard posed by many contractual agreements between employers and employees.
Human resource management is an approach to controlling the relationships between the employer and employee to allow an organization to realize its objectives, the agents, both employers, and employees must be aware of all factors that will enhance their managerial process. The failures that happen within the management process are when the parties who cooperate (the employer and the principal and the employee, who is the agent) diverge in their attitudes.
This is because of agency issues (Fama 1980) that can be quelled by ensuring the effective functioning of the companys governance, which includes the costs associated with organizational structure and coordination (for agency expenses, see Jensen and Meckling 1976) for example recruiting employees and monitoring expenditures, as well as incentives; factors that are directly related to the performance of organizational effectiveness in general and efficiency.
A vast amount of theoretical research has been focusing on the fact that companies utilize a variety of different methods to direct the appropriate behavior of an employee (Prendergas 1999). This is based upon the theories of agency that an employee (agent) is averse to effort and that is why companies (principals) create contracts to motivate employees to work in an effort-based manner.
In the context, of management for human resources workers effort is viewed as the person who is a part of the company (organization dedication). Another important aspect is that companies must make agreements that influence the kind of employees they employ since the degree of the employees commitment to their work environment is contingent on the perception of employees of the company dedicated to their needs.
Within the diverse definitions of commitment to an organization from the research literature Goulet as well as Frank (2002) identify it as a set of behavior an intention to behave and motivating forces or a mindset. This is among the reasons that conclusions about commitment to an organization are so controversial (Buelens and Van Den Broeck, 2007, Goulet and Frank, 2002), and must be careful when concluding (Baarspul and Wilderom 2012).
Sector change: private and public sector
Rainey, as well as Chun (2005), claimed that those working for the government are afflicted with less motivation and incentive than people working who work in the industry. This could be a reason for Lipset and Schneider (1983) claim that government agencies are less efficient and effective than markets.
Perry, as well as Porter (1982), are based on the difficulty public sector agencies to provide their employees with understanding personal importance. According to them, the principal reason for this is the difficulties that public employees face when they are unable to discern any connection between the accomplishments of the agencies and their work.
The discussion of the differences between private and public sector employees has been examined by numerous authors using various methods (Rainey and Chun 2005; Rainey and Bozeman, 2000, Su and Bozeman, 2009). A summary of the main studies that have examined the differences between private and public sector employees has mostly been focused on the organizational characteristics instead of the employees themselves. According to The authors Baarspul as well as Wilderom (2012) there are only a few research findings on the public-private distinction that is dedicated to an individual have been examined to date.
Research on the work of workers has been an ongoing issue for researchers because productivity increases appear to be mostly due to increased effort by workers. Numerous theories and strategies were created to better understand the source of motivational factors for employees as well as other studies were developed to find out if employees in the public sector have different motivations in comparison to employees in private industry. In addition, according to Wright (2001), numerous studies have highlighted the interaction between environmental and personal factors affects the motivation of individuals.
From Ichino as well as Riphahn (2004) as well as Engellandt as well as Riphahn (2005) The variation in the amount of job security across both sectors is greater, indicating that the number of workers who are committed to their duties varies based on the particular sector. According to the authors, the results suggest that the less probability of losing a job, the less effort. The behavior of the worker is in line with the notion of agency theory.
It argues that employees and principal (employers)principalsferent views to risk. Therefore, each employee will choose the approach that will maximize their long-term rewards. Based on Adams (1965) workers evaluate themselves with other employees inside and outside of their organizations and, therefore, when the ratio of their outputs to inputs is perceived to be lower as the proportion of results to inputs of others they may be disappointed.
Balchin as well as Wooden (1995) assert that since employees working who work in the public sector be more confident regarding the future of their careers, they could be less worried about being dismissed due to excessive absences from work, and consequently may have a tendency to miss work more frequently. Based on Baldwin (1984) Baldwin (1984), public sector workers are frequently thought of as lazy, self-serving and misinformed. It is likely that this stereotype is due to the spread of a low commitment to organization that leads to accommodating and risk-averse workers (Bellante and Link 1981).
While it is said that the human resource management within the government sector has transformed to follow the same practices as those employed by private businesses however, in certain countries it takes longer, and the process is more sluggish. Based on Osborne as well as Gaebler (1992) The start of the process begins before the point at the public sector managers are urged to reduce their bureaucratic burdens.
According to Vandenheuvel (1994) in his paper, it is possible that the environment which exists in the public sector is different from that which exists inside the private industry, in terms of regulations. As per the subject of this paper Riphahn and Thalmaier (2001) and Ichino and Riphahn (2004) discovered that workers working in their German government sector which were protected by extremely extensive levels of protection for employment were absent at 6.7 per cent compared to 4.3 percent employed in the public sector that did not have extended protection. Jimeno Cortes and Jimeno Cortes (1996) studied the impact of low coverage of employment on absenteeism.
They discovered that workers without protection from employment show an incredibly higher level of effort than employees with permanent safe contracts. Also, Buelens along with Van Den Broeck (2007) concluded that workers in the public sector had significantly fewer hours of work and also showed that they were less committed to their work when compared to employees in the private sector.
It is widely acknowledged across the world of literature people who work in the sector of switchers differ from other workers in terms of a variety of human capital, attitudinal and life circumstances. Based on Bozeman as well as Ponomariov (2009) switching the sector of work can create barriers (possible specific certification for the public sector, standards, perceptions of different organizational cultures and the importance of different certifications) that tend to hinder sector change.
In addition, those who choose to change sectors are likely to be those who want to be more flexible and also to gain substantial qualifications and there is a market demand for their services.
In a thorough investigation, Engellandt and Riphahn (2005) look at the effects of work absence and overtime as measures of efforts for temporary job holders in Switzerland and conclude that the amount of absence is not different between permanent and temporary workers. However there is a noticeable distinction in the work hours.
Booth et al. (2002) also draw upon using the the hours per week of overtime that are not paid typically used as a proxy of workers’ effort within the UK. The findings show that working overtime increases the likelihood of switching into permanent work for women who work as temporary workers.
Data and methods
A model that is empirical and a hypothesis
To understand the mechanisms that explain different behavior of employees from private and public sectors I use an experiment using the probit model for random effects (RE probit model) as well as the Chamberlain Corresponding random effect (CRE) probe model (Chamberlain model).
The original idea was that the unobserved heterogeneity was an uncorrelated random variable, not related to the regressors. Afterwards, it was decided to use the model of random effects then applied. But, if the unobservable personal traits (such as aptitude or laziness) are associated with regressors (for example, sector selection).
The probit model suggested in the work of Mundlak (1978) as well as Chamberlain (1980) can be considered the best option as it provides an operational form for the non-observed characteristics of individuals which allows for a relaxation of the independency between the unobserved effects and observed covariates.
Chamberlain models include as explanation variables the within-group mean of all covariates, which will capture the relationship between unobserved heterogeneity as well as the covariates, which renders an RE probit model inconsistent.
4 Variables of Interest (Yit) are the measures of a worker effort. To control the effect of composition, control variables designed to record the socioeconomic status of the workers and the characteristics of the labor market are used.
Thus, the first equation can be interpreted in the following manner:
Yit measures the effort of a worker (binary variable to determine the proxies utilized) As are the parameters that reflect both socioeconomics and the characteristics of the labor market. ci refers to an unobservable personal characteristic which are time-bound; I refers to the individual and t indicates the time. The error terms are.
In order to do this, it is examined whether the impact of employment in the sector on workers work is different based on gender and the time of year. So, it is included to the Eq. (1) A dummy interplay between gender, and industry of employment as well as (2) an imaginary interaction between year and sector to test whether behavioral differences between workers in the private and public sectors may change over time.
Then, I will check whether workers alter their intensity levels in the event that their workplace moves from public to private sector. In such a situation, it is important to pay more attention as the estimate could be distorted if unobserved factors interfere with the assessment of the workers group profile. This is the reason the methodology suggested by Mundlak (1978) and Chamberlain (1980) was chosen.
Engellandt and Riphahn (2005) caution about two possible causes of endogeneity. The first is due to the notion that people in the private sector might become “positively selected” because of lack of motivation because they are able to accept the terms which are generally imposed in terms of job security.
The second however is the idea that private sector workers might have been “positively selected” because they are less likely to take on a job that is less secure since they anticipate more job opportunities in the near future. In the event that non-observed variables cause the selection of workers in the private sector, like it is important to determine whether these influences are contributing to endogeneity.
In the event that private sector workers show a shift in the effort of workers this theory must be examined by adding the model variables the measure that determines if the employee employed within the public sector the date was in permanent employment within the private sector over the preceding period (t 1 – t).
The calculated equations will be tested to test the hypothesis (H) which is the basis of this study:
Private sector employees have more effort levels as compared to those in the public sector.
This theory originates from the idea of the fact that Brazil public sector Brazil is known for its lack of commitment. This is why the idea is the apprehension of comparing this stereotype, which is prevalent in Brazil in comparison to the actual situation by suggesting that public service in Brazil is a magnet for people with an “fitting” attitude.
To do this to do this, the importance that the calculated coefficients of a2-a4 are significant enough to be used to determine the possibility that workers alter their work intensity in the event that their job is shifting from public to private. The analysis will be done by comparing the coefficients estimated by workers who switched jobs and those who were in the same sector. If the coefficients were substantial, they would provide strong evidence that workers effort is different in relation to the industry of work.
According to Bradley and colleagues. (2007) It is up to the individual to decide on their level of satisfaction with the job, based on a analysis of the marginal benefits and the marginal cost of a the job (sector) change. So, taking into consideration the argument that the less the likelihood of losing jobs the less work will be.
This is the idea put forth in the work of Ichino Riphahn and Ichino (2004) as well as Engellandt and Riphahn (2005) and Engellandt and Riphahn (2005). It is anticipated that the estimated coefficients will be significant, in order to confirm that the worker is acting strategically. In general, workers who switch to public sector work show less effort when the change takes place.
Data
To conduct my empirical analysis, I rely on information of the Monthly Employment Survey (PME) carried out by the Brazilian Institute of Geography and Statistics (IBGE) between 2003 between 2003 and 2012. The PME offers an accurate representation of the Brazilian workforce above that age 10 and includes six major Brazilian metropolitan areas (RMR–Recife and RMSA–Salvador, RMBH–Belo Horizonte, RMRJ–Rio De Janeiro and RMSP-Sao Paulo. RMPA–Porto alegre). The method of data collection was based on a rotational system and the structure of a monthly household panel with each panel was scrutinized for 4 consecutive months. The panel was then taken out of the sample for 8 months, and then reinserted for a further 4 months before being removed completely removed from the sample. In the context of the article and using a the household identification code I constructed an database that consists of just two interviews from all workers: the first interview with one interview (the first interview) followed by a second interview at t = 2 (12 months after the initial interview). So, any particular worker, based on our model will be present in only two years.
The variables used in our study provide details of socio-demographics, the characteristics of jobs and measures of the workers effort. The method employed in this study was comparable to that employed in Jimeno and Cortes (1996), Booth and colleagues. (2002) as well as Engellandt and Riphahn (2005) that are considered as the most reliable indicators of effort variables frequently used in the literature, and adapted to the actual conditions in the Brazilian labour market database.5 They include: gender, age, education degree, private sector, temporary jobs duration, job tenure, Dummies and proxies of effort to represent each region of metropolitan.
The dummy variables that are employed to gauge the level of effort of workers are designed to provide evidence of the employee conduct on the course of work. Absence and unpaid overtime are common variables employed in studies on work effort. They indicate the level of effort exerted by employees (Jimeno and Cortes 1996. Engellandt as well as Riphahn 2005). According to Booth and colleagues. (2002) it is an positive correlation between worker performance in determining the amount of hours they do not get paid for overtime work. Engellandt as well as Riphahn (2005) highlighted the differences in absences among workers according to their work.
The econometrics model is determined using the respective proxies to effort mentioned in the previous paragraph. Both variables are binary and represent that the employees who work less than 40 hours a week and who would like to work more hours. The second is a reference to absence from work for at minimum one hour in the week that is the reference for the survey. Absence can be a sign of absence and was taken into consideration when an employee absent from work due to reasons that are not explained.
After having completed the steps within the database, taking into account only employees employed, and excluding cases that were not completed and employees who are aged between 15 and 70+ I arrived at the final sampling of 255,122 observation (201,524 from the private sector and 53,598 in the public sector).
Descriptive analysis
This section will provide an analysis of a brief descriptive summary that pertains to this sample. The summary statistics of the sample are provided in Table 1. In the beginning, it is crucial to emphasize that this study is only applicable to people who had jobs at your first meeting, between 18 and 65, and followed up one year later (after one year). When the follow-up period, a portion of the respondents were working in that same field and the other was employed in a different sector. People who went not employed or financially inactive (out of the labour force) were not included.
Variables Unpaid overtime Absence
Empty Cell RE probit Chamberlain RE probit RE probit Chamberlain RE probit
RMR–Metropolitan regions of Recife and RMSA, the metropolitan region of Salvador; RMBH -Metropolitan region located in Belo Horizonte; RMRJ–Metropolitan region of Rio de Janeiro; RMSP–Metropolitan region of Sao Paulo; and RMPA–Metropolitan region of Porto Alegre.
Source: Monthly Employment Survey.
It is crucial to note that these data come of data from the Brazilian labor market that has, of all emerging countries one of the highest rates of worker turnover. While there is a greater degree of regulation in the Brazilian labour market has been more controlled in comparison to other countries in the developing world however, the laws of Brazil contribute to increase rate of turnover, creating the opposite of the purpose it was designed to.
Typically, Brazilian legislation requires that employers provide notice to employees in the event that they are dismissed (one one month before dismissal) and also pay amount of money to employees who is dismissed without reason (50 percent of the amount from the Length of Service Guarantee Fund – FGTS).
These costs could even alter the behavior of the worker, causing them to incite their own dismissal. As per Macedo (1985), Amadeo and Camargo (1996) and Barros and others. (1999) this method is well-established and has led to negative consequences on the part of employees behavior, and has given an incentive for them to force the dismissal of their employees (fake dismissed).
With all the care and methodological requirements the database demands that of the 255,122 people 150,510 (62.5 percent) are men , and 201,524 (75.5 percent) working in the private industry as shown in Table 1. The greatest proportion of workers in the public sector could be explained by the higher stable job security (job safety) in this sector , since I analyzed two interviews in a row (1 1 year time interval). In addition, the high turnover rate within the private industry causes many workers unemployed, which implies that they were not included in the study.
Concerning the gender differences and gender, it has been observed that men participation is greater within the business sector (62.5%)) and less for the public service (45.8) when compared to women. Gornick as well as Jacobs (1988) discussed spoken the fact that women are more likely to work as public servants. The reasons can be attributed to the security of their jobs and income, both of which are greater for females as a result of their double journey to work.
In relation to the age range It is evident that young workers (16-25 years) are more likely to be employed in jobs in the private sector, however, the older workforce (aged 55or older) tend to be employed within the public sector. This is likely because of the unique characteristic of younger and older workers that is connected with their lives on the job market. Younger workers tend to be more likely to change jobs in comparison to older workers, in pursuit of work experience or to get the best job.
In addition, it is widely acknowledged throughout the world that younger people are less expensive. This is the reason why head of households, accountable for the family financial income have a much greater share of working in the government sector.
Regarding the factor of schooling The results appear to suggest the fact that public service has more schooling as compared to private sectors. In both sectors, those who have higher education level of education (schooling at 11+ years) have the highest percentage (61.6 percent in the the private sector, and 85.5 percent in public sector) however, in the latter, it is the government sector which has the highest percentage of workers who are educated.
Another key difference between the public and private sector is the distinction in terms of tenure that is significantly higher in the public sector (70.2 months versus 30.5 in the private sector). This could be due to the distinct characteristics that are common between the private and public sectors of Brazil (Barros and al. 1999; Foguel and. 2000) in particular due to the fact that the public sector employment is more appealing to those who seek security (Gonzaga and. 2003).
Thus, the probability of dismissal in the public sector is less than the private sector and layoffs are rare, which is why the duration of employment is higher in the public sector.
With regard to the variables that are used as an measure of effort – absence and overtime that is not paid – the first (unpaid time off) has a higher proportion of workers working by private companies however, the latter is an increased percentage of workers of workers employed in government.
The reason for this result could be due with the reality that the accounting of absenteeism in private companies is handled in a more thorough manner by businesses than the public sector in which the allowance for absences is the most often. It is therefore possible that the employee absence of the public sector may be not properly accounted for.
To improve the analysis of distinctions between public and private sector workers efforts, it was carried out the two-sample tests to measure the variance of mean the results for each variable are shown on the 3rd column (0.0090 and -0.0226 respectively for non-paid overtime or absence).
For Bradley et al. (2007) The risks of losing employment and promotions has a different magnitude among workers, in accordance with the sector occupancy. Thus, the data in Table 1 is consistent with the hypotheses that were predetermined since private sector employees had efforts indicators (unpaid overtime and absence) in the average more than those in workers in public service.
According to Vandenheuvel (1994) Vandenheuvel (1994), it is widely believed that employees employed for the government sector tend to be more likely not be at work as colleagues in private industry. One explanation could be mentioned in Kriegler and Wooden (1990) who declare that workers at larger workplaces are more likely to miss work, which suggests that the absence of employees in larger workplaces, such as public enterprises, might affect output less and consequently cause less anxiety for managers.
In addition it is true that there is evidence that the Brazilian private sector made up of small and micro businesses (approximately 99percent from the overall) which are responsible for about 70% of the employment within the sector. This could be a further explanation for the low rates of absenteeism for the sector of private.
Results from experiments
The next section is where I discuss the econometrics findings. To compare the intensity of work of workers in the private and public sectors I followed the method employed in Engellandt and Riphahn (2005) by using the probit estimator that has randomly effect (random affect probit) and then add the probit model developed in Mundlak (1978) as well as Chamberlain (1980)–hereafter Chamberlain models.
The study of the empirical strategy starts with estimation for the random effect probit of the variables of effort – Table 2 below. The results show that there are different behavior patterns for workersthat are related to absences caused by proxy in accordance with the sector of employment. The coefficient for overtime that is not paid working was not statistically significant; however the significant and negative calculated value for absenteeism (-0.5141 for the RE probit model and -0.2231 for Chamberlain models) suggests that, in comparison with private sector employees working in the public sector the amount of workers who are who are absent from work is greater. These results are indication that the two sectors differ regarding the behavior of workers.
The standard errors are in brackets. In the RE probit models contain an dummy variable for the years metro zones (RMR, RMBH, RMRJ, RMSP, RMPA) and dymmy interplay for the year and sector. chamberlain RE Probit model includes the same variables that are in that of the RE probit model, but also include an additional explanation within the group variables.
Indicate statistical significance at 10 10%.
Indicate the statistical significance level 5 %.
Indicate statistical significance at 1 %.
Source: Monthly Employment Survey.
The gender-based variable suggests that men are more productive in comparison to women for the two proxy types studied. Furthermore, the degree of education is not a factor when deciding on overtime work unpaid proxy, however it is crucial in the context absent proxy (RE probit model).6
Table 3 outlines the previous analysis. In this analysis, I aim to understand the potential different levels of effort between workers based on gender. The goal was to determine whether the impact of employment sector differs by gender through dummies interactions for gender, industry, kind of contractual (temporary work). The results reveal the significant differences based on gender and sector for non-paid overtime or absences. The statistically significant coefficients show that the effort of men generally more than women.
Table 3. Random effects and Chamberlain probit models of the work of workers by industry and by gender. 2003-2012.
Variables Unpaid Overtime Absence
In the Empty Cell, Chamberlain probit. RE probit Chamberlain probit
Empty Cell Coef. Coef. Coef. Coef.
The private sector 0.0477 0.0234 -0.5474** -0.2550**
(0.0698) (0.0857) (0.0739) (0.0979)
Men 0.2168*** 0.2181*** -0.3769*** -0.3728***
(0.0271) (0.0272) (0.0330) (0.0333)
Private sector men -0.0445 -0.0441 0.07952. 0.0813**
(0.0298) (0.0298) (0.0383) (0.0384)
Temporary contract for Men*Private Sector -0.0412 -0.0510 0.0212 -0.0175
(0.0668) (0.0671) (0.1171) (0.1177)
Rho 0.3342*** 0.3345*** 0.4773*** 0.4795***
(0.0104) (0.0104) (0.0132) (0.0133)
Log likelihood -43,661.248 -43,652.086 -22,581.426 -22,544.827
Total (obs.) 255,122 255,122 255,122 255,122
Notes: 1. Common mistakes in parentheses. 2. These models are controlled to account for the same covariates as Table 2.
Indicate the level of statistical significance 10 10%.
Indicate the statistical significance level at 5%..
Indicate statistical significance at 1 %.
Source: Monthly Employment Survey.
When I looked at the interaction variables private sector and men, the the coefficient of unpaid proxy was insignificant at the 10 percent level of significance. For the absence proxy, this coefficient is significant (5 5 %)) and, most interestingly its sign is reversed. This means that males employed in the private sector are more likely to be absent more often than women.
In order, the potential influence of factors that are not observed in the characteristics of an occupational category is illustrated in Table 4 and Table 5. The concept behind these estimates is to establish whether there is a substantial difference in the behavior of people working in the public or private sector workers when sector changes occur. This was examined by adding a variable that explains the possibility that the worker working by the government sector had previously been employed by a private company prior to.
In the sense that the variables estimated for the characteristics of individuals and their labor markets are as far as the coefficients are concerned, they show that younger women, female workers, those employed within the public sector workers in smaller firms and those who work fewer hours are more likely to put in high-effort. It is also evident that the coefficients of factors related to education did not show statistical significance; this is a fundamental characteristic for a specific segment of employees.
Table 4and Table 5 present the results of random effects models that examine the effects of switching sectors upon the amount of workers surveyed. If the private sector employees as a collective differ from those employed in the public sector then there must be a marked distinction in the behavior of workers in the private sector who have just made the transition to public sector workers as in comparison to those who were employed in the public sector all. It is important to remember that the term “job switcher” I would guess that it refers to people who work within the private industry (t) and have made the switch to the public sector right prior to (t 1) the current job.
In the case of the analysis that is presented in Table 4, which outlines the factors that determine unpaid overtime at the time of t, the findings in column 1 demonstrate that the total private sector work is not affected by extra control, as well as the indicator that is lagged of previous private sector jobs. This means that sector switch work efforts are not different in any way from those of other employees of the public sector. Therefore, this finding provides an argument against the endogenous selection to work in the private sector.
A possible explanation for this result could be the possibility that the level of effort among private sector employees would be driven by a group of “positively/negatively selected” workers. To determine the significance of this “selection”, the estimate of column 2 measured the worker efforts within the private industry to those who remained in the same sector as well as those who changed to the public sector during the following period.
The table in the table 4. (column 2) indicate a low estimated percent of people who were able to get public jobs during the next time (in each model) and for those who remain in the private sector the effort level was not much different in comparison to that of public employees, as per the Chamberlain model.
Similar analysis was conducted to determine absence from work the period t. The results are presented on Table 5, below. The negative coefficients of the private sector show that employees working by the government sector tend to be more likely absent than workers within the private industry. Concerning the additional control the indicator of time lag of prior private sector jobs the index was high (RE probit model) meaning that the effort levels that workers who had previously held private sector positions and then made the switch to the public sector substantially differs from the effort displayed by those working within the public sector for all of the time. This finding suggests an underlying strategy of behavior for those who have switched to public sector employment showing less effort when the change happens, which is indication of negative selection. On the other hand when there is an assumed an unobserved correlation between heterogeneity and variables (Chamberlain model) the amount of effort shown by employees is not significantly different this is a good indication of moral hazard the conduct of those who had previously been employed in private sector positions.
Again, in order to analyze the possibility of existence of a “positively/negatively selected” high performers group, the estimations results of column 2, Table 5, compared workers effort who both do and do not reach public sector in the subsequent period. Results from the model of random effects reveal that those who had worked in private sector positions contribute (significantly) greater work (less absences) than workers in the public sector. In the Chamberlain model, the coefficient, even though it is negative, is not that significant which means that the amount of effort provided by workers who have worked prior to private sector jobs does not differ from those who work within the public sector.
These results merit special focus. For a more thorough analysis, it can be concluded that job changes could alter the way that workers perform their work. Regarding the absence from work (Table 5) the workers who were employed in working in the private sector (where the majority of workers exert more effort as is evident in Table 1, column 1 5) and then moved into public service do not differ in their level in effort (absence) as compared to workers who work within the government sector for all period (Chamberlain Model).
This might be a sign that there is some shift in the effort of workers once they have achieved their goal that is, in this case finding a job in the public sector (adverse selection issue). The results, therefore, suggest that workers in the private sector have an increased level of effort when compared to workers working in public services.
Also, as with Riphahn and Engellandt (2005), I also conducted another test to determine the endogeneity of jobs in the private sector to confirm the analysis presented. To determine the possibility of biasing using as an exogenous “private sector job” indicator on the other coefficients of the model I re-estimated these models with both proxies of work (Table 2) without excluding the private sector indicator.
In the end, marginal impacts of other variables remained nearly identical as a signal it is not the case that employment in the private sector is not exogenous.
In addition, unlike the work of Engellandt and Rippohn (2005) and Riphahn (2005), I used another analysis (Chamberlain model) because the results of probit models with random effects could be biased if non-observable variables affect the selection process into one of two groups that include workers (private industry or the public sector) and are associated to our dependent variables. This is the reason certain results are different between RE probit and Chamberlain.
In the end, it does not suggest that all options have been exhausted. But, the data confirm our theory and indicate an association between work and work effort is not due to the endogeneity of the private sector.
Conclusion remarks
This article was written to analyze and compare how workers behave in the public and private sectors using proxies to measure work and drawing upon information taken from the Monthly Employment Survey (PME) in Brazil from 2003-2012.
The research paper sought to find out the extent to which there are disadvantages in terms of the effort required for jobs in the public sector when compared to private sector positions. To examine this idea I applied the RE probit model as well as the Chamberlain model based on proxy variables, which sought to determine the efforts of workers working in a job. In this case, two variables were chosen unpaid overtime workers (those who work less than 40 hours a week and who would like to work more working hours) or absence (absence rates).
The results are within the expected range however, they do raise certain questions. First, it is crucial to note a small distinction between categories (private sector workers as well as employees of the public sector) with respect to their effort (according to overtime that is not paid and absence from work).
In general, speaking of fewer absences from work, the findings confirmed that employees in the private sector are more productive than those working in the public sector. The reason for this result is based on the premise of the theory of agency, is the most commonly used argument that people working employed in the public sector have greater job security.
In the end, the analysis appears to confirm different behavior between workers. Concerning the non-paid overtime variables the coefficient estimated was not significant. But, when it comes to absences the calculated values (-0.6193 as well as -0.4201) in the private sector suggest that those employed in this industry are less likely to be absent than those employed working in those in the public sector.
The main question is to what degree unknown factors could exert influence on how much effort is required by an occupational group. The results obtained by the random effects probit model appear to suggest that individuals who were working in private industry and switched to public service are more likely to exert greater efforts (less absence) in their work than those employed in the public sector.
But, assuming that non-observable individual characteristics are related to the choice of the sector (private and public sector jobs) the consequences of changing jobs on performance are not significantly statistically relevant (no proof of moral risk).
Thus, our data point to two significant results. It is indicator of the existence of various groups of workers effort and is evident more when working in the private sector because the level of work (absences) is generally more pronounced in this industry. Also, the estimation yield of RE probit and Chamberlains model reveal that the work (absence) of private sector workers who recently become public sector workers is greater than that of those who were employed all.
But, if we only look at Chamberlain models, the difference in the effort among the employees did not appear to be statistically significant. The results suggest that different information about the traits of employees can lead to issues of discriminatory selection in the behavior of employees of the public sector that may have lowered their levels of effort.
In a conclusion, the findings of this research confirm in part, the results regarding the differences in effort between workers as demonstrated by a number of studies. In addition, this study offers more details on the relation between overtime hours that are not paid and absence as well as efforts are measured, as well as sector shifts. This can help in the understanding of the possible causes for the differences between the private and public sectors with respect to worker effort.
With the particulars in this Brazilian labor market, a conceivable assumption is that the security of employment and the consequent reduction of the risk of losing jobs (job security) can influence the worker attitude to accommodation which in turn reduces the amount of organizational commitment within the government sector. The study confirms that private sector workers showed greater commitment to work, both in terms of absence from work, than those who worked in the public sector.
Thus, a reasonable hypothesis is that different levels of work effort may result from different strategies for workers because there are selection processes in play according to the fact that workers who are willing to put in a minimal effort shift into the government sector. Thus, a low level of effort may be the result of the individual personal choice or personal habits or even a lack of it, and not primarily due to the organizational context.
In the end, the results demonstrate that shifts in the job in public sector jobs to the public sector can cause changes in the behavior of individuals. While there are many reservations about the econometric theory, in particular issues with endogeneity which could significantly alter the parameters of the model This empirical analysis indicates that the recruitment and screening process (adverse choice) within the public sector could be in error.
The results reported by this study provide an avenue for further research: the evaluation of the significance of the differences in the security of work, competition pressure, and the cultural identity that is unique to each nation as possible reasons for the different frequency of absences within government.