The average wage per person in Vietnam is around 3. Like many other economies in the world, the type of jobs firstly divides the salary level in Vietnam.
The top professions that pay the highest salary are Mineral and Metallurgy 9. There is also a significant gap in salary between different positions in work; for example, the salary for the administrative staff is often between 5 million to 6. Additionally, the wage is distinguished between private and state-owned companies.
The headline figures of median and mean earnings for the public and private sectors are published in Employee earnings in the UK: As a result, the figures presented in this article are not directly comparable with the headline figures. The comparative analysis of private and public sector earnings is complex because of the different structural characteristics of the sectors.
Therefore, in this analysis we use regression modelling to account for some employee and employer characteristics that impact on earnings.
The first step to this modelling exercise is choosing the appropriate earnings dependent variable. This is important because apart from variations in gross hourly earnings in the private and public sectors, there are other payments that constitute earnings that also vary between the sectors.
Bonuses are a large component of the remuneration package in the private sector. Our analysis considers employer and employee pension contributions, which makes some statistics in the analysis different from those published in the main ASHE publication. We consider two dependent variables for the regression analysis: the log of total remuneration consisting of gross hourly pay, overtime, bonuses and employer pension contributions and the log of total remuneration including employee pension contributions that is, total remuneration including employee pension contributions made under salary sacrifice schemes.
Employee pension contributions can take different forms, including additional voluntary contributions AVCs and workplace schemes. We treat employee pension contributions made under salary sacrifice schemes separately in calculating the total remuneration variable for our analysis.
This helps us to check if such contributions have a significant impact on the analysis. Employee pension contributions made under salary sacrifice can reduce the overall taxable earnings of an employee, resulting in greater take-home pay , depending on individual circumstances.
In addition, there is less clarity on the treatment of the employee pension contributions made under salary sacrifice schemes, raising potential double-counting problems. Where workers participate in salary sacrifice schemes, it is not clear whether the employee contribution in a salary sacrifice scheme, which is paid to the pension scheme by the employer, is recorded as an employee or an employer contribution. For instance, the People's Pension , a pension administrator and provider organisation, says any contribution paid to them under a salary sacrifice arrangement will be treated as employer-only contributions.
This would bias the earnings upwards. This analysis of public and private sector earnings includes both descriptive and regression analysis of earnings in the period to For more information on regression analysis and its limitations, see our publication's Quality and methodology section.
The ASHE dataset does not include all employee characteristics that affect pay such as education, experience and employee ability or motivation. It only covers the earnings of paid employees in the UK and does not include data on self-employed workers who can be found on both the high and low ends of the earnings spectrum.
This section briefly summarises the main factors used in analysing private and public sector earnings. The detailed analyses of the variables are provided in Section 6: Detailed analysis of main factors affecting earnings. We include employer pension contributions in our analysis because pensions are a significant proportion on employee remuneration, especially in the public sector.
Employees can contribute to pensions through salary sacrifice arrangements. Under these schemes, employees give up a portion of their gross salaries for additional pension-related benefits; as explained in Section 3, this can lead to greater take-home pay, depending on individual circumstances.
Age is an important determinant of earnings that is used as a proxy for experience. Young workers tend to be paid less than older workers.
Age is also highly correlated with experience and the build-up of human capital over time. In , the mean age of private sector employees was 40 years, while in the public sector it was 44 years. The age distribution shows that employee jobs in the private sector are skewed towards the younger age groups, while in the public sector employee jobs are skewed towards the older age groups see Figure 6 in Section 6. Average hourly earnings increased sharply at younger age groups and then peaked in both public and private sectors in the age range 40 to 44 years.
Sex is an important determinant of earnings. Women, on average, earn less than men per hour, as explored in the ONS's gender pay gap article. Our results show that in the median hourly earnings for men were higher than those for women in both the public and private sectors. The groups consider the qualification levels, training, skills and the type of tasks undertaken. These occupations include scientists, IT engineers, health, educational professionals and solicitors.
In , higher-skilled occupations in the private sector, on average, earned more than similar occupations in the public sector. Another job-related characteristic associated with different levels of earnings are organisation size, location and type of industry.
The size of the organisation is important for various reasons such as economies of scale, access to finance and productivity that can affect earnings. Full-time or part-time status of the job can also affect the earnings of an employee for reasons such as different accumulation of human capital and employers' fixed labour costs.
In the three months to June , the Labour Force Survey shows that there were more men There are several other factors that influence earnings determination. Local labour market conditions and cost of living can be among the geographic factors affecting earnings. Job tenure, often used as a proxy for organisation-specific experience, is also an important factor that influences earnings.
People with higher organisation-specific work experience tend to get paid more than those with less such experience. Permanent staff tend to be paid more than temporary staff, and full-time workers tend to be paid more than part-time workers. Firms also pay benefits-in-kind to workers.
Benefits-in-kind may affect the level of earnings when, for example, employees agree to forgo a part of their salary in exchange for a benefit such as a company car or company-paid health insurance. The econometric modelling of the relationship between private and public sector earnings involves estimating an earnings equation with conventional explanatory variables for example, age, years of schooling, experience and other demographic and job-specific variables , including one that identifies private and public sector employment.
For a detailed discussion of the methodology, refer to the paper discussing the application of Mincer-type earnings functions PDF, KB. The estimation of an earnings equation makes it possible to account and control for some differences between people in employment before calculating the public sector earnings premium when the average public sector worker earns more than the average private sector worker or penalty when the average public sector worker earns less than the average private sector worker.
We alternatively call the premium or penalty that is, the difference between public and private sector earnings the earnings difference.
We estimate the model with the following independent variables: age, age-squared, sex, working pattern full-time or part-time , tenure, occupational classification, organisational size, benefits-in-kind, whether the employment is permanent or temporary, region and various interactive terms of some variables, to capture the joint impact of some variables on earnings.
The Annual Survey of Hours and Earnings ASHE data do not have variables for individual characteristics, which are related to earnings such as experience, qualifications or marital status. We use age to proxy experience, and occupation to proxy qualifications. A full description of the methodology and variables is covered in our publication's Quality and methodology section.
An important variable also included in the model is the dummy variable indicating the individual works in the public sector and not in the private sector. The coefficient to this variable indicates the average earnings difference for working in the public sector. The variable of interest in our model is the one that captures the earnings difference. The coefficient representing the earnings difference is an average figure representing the average public sector worker compared with average private sector worker.
The average worker in the private sector is more likely to differ across industries than the average public sector worker. Our analysis with total remuneration and total remuneration including employee pension contributions under salary sacrifice schemes as dependent variables show that the premiums from the two models are not significantly different. Therefore, and because of the limitations of the salary sacrifice variable highlighted in section 2, we base our analysis on total remuneration rather than on total remuneration including employee pension contributions.
In Figure 1 we show two econometrically modelled average public sector earnings premiums and three raw public sector earnings premiums for the period to The modelled premiums are based on total remuneration and total remuneration including employee pension contributions.
The raw premiums are based on unmodelled private and public sector earnings. They are based on three earnings variables, namely:. The raw premiums show average earnings and are not controlled for the effect of the dependent variables in the regression modelling. As such, they disregard possible heterogeneity in the premium because of variables such as occupation and organisation size.
Positive values represent public sector earnings premiums and negative values represent private sector earnings premiums. Figure 1: The public sector earnings premium declined between and Regression-based and raw average percentage of the public sector earnings premium, to Source: Office for National Statistics — Annual Survey of Hours and Earnings Download this chart Figure 1: The public sector earnings premium declined between and Image.
Figure 1 shows that the modelled average public sector earnings premiums are lower than the raw premiums. For example, total remuneration raw premium is higher than total remuneration modelled premium.
The difference between the raw and modelled average premiums is explained by differences across individual jobs and businesses in the different sectors.
The difference between modelled average premiums based on total remuneration and on total remuneration including employee pension contributions is very small. From now on, we base our analysis on the total remuneration earnings variable. Figure 1 shows that the raw premiums have similar trends. They peaked in , declined between and , and increased in even though the data for are still provisional. Comparing the two raw premiums shows that bonus payments are an important source of earnings in the private sector, and they reduce the earnings gap between the average workers in the private and public sectors.
Bonus payments reduce the public sector earnings premium. Comparing the total remuneration-based raw premium with the raw premium based on gross earnings including overtime and bonus payments shows that employer pension contributions are an important component of the earnings package in the public sector. Taking employer pension contributions into account increased the raw public sector earnings premium by 10 percentage points in The average worker in the public sector continued to earn a premium over the average worker in the private sector over the period, even after controlling for personal and job characteristics.
However, the modelled average premium declined between and The modelled average premium is lower than the raw premium because some of the difference between public and private sector earnings is spread across the different control variables and interaction effects in the model. The modelled average premium is lower than the raw premium because some of the difference between public and private sector earnings depend on the different control variables and interaction effects in the model.
The auto-enrolment regulations were phased in between October and April and over the period, the private sector membership of pension schemes increased fast. The impact of pension contributions therefore declined over time as more private sector employers contributed to pensions.
The Office for National Statistics' publication on employee workplace pensions in the UK states that the pension contribution rates in ASHE are different from the automatic enrolment minimum contribution legal definitions hence they are not directly comparable. Ditch a broad ESG approach to funds for these two focused investment trusts. Skip to Content Skip to Footer. London's City Hall: nice little earner? Pandemics, politicians and gold-plated pensions. Central banks may keep telling us that inflation is transitory, but the reality is that we're in for a period of structurally higher inflation.
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