INTRODUCTION
Research goals and objectives
This research aims to analyze the extent to which education and family background influence wage correlation Key factors considered include employment characteristics such as age, marital status, ethnicity, educational attainment, work experience, and urban versus regional location Additionally, family background elements like parental education levels and the number of siblings are examined to provide a comprehensive understanding of their impact on wage disparities.
This thesis develops a model to analyze the influence of employment and family background on wage relationships The findings indicate that education has a direct effect on wages and highlights the significant role of family in shaping individual outcomes Based on these results, the study provides policy recommendations to address these disparities.
Research questions o • • • • • • o o o o o o o o 0 3
This research aims to explore how employment characteristics and family background influence wage levels Specifically, it seeks to answer two key questions: first, the impact of employment characteristics on wages, and second, the role of family background in determining wage outcomes.
Specially, the thesis aims to answer questions below: i Is the educational attainment level a key factor of wage? ii.Does family background affect an employee's wage?
LITERATURE REVIEW
Previous empirical studies 0 • • • • • • • • • • • • • • • • 6
The skills of workers significantly influence their wages, as supported by numerous empirical studies Buchinsky and Leslie (2009) developed a dynamic model of educational investments to predict future wage distributions, utilizing data from male individuals aged 14 to 65 who were either employed or in school, based on the March Current Population Surveys from 1964 to 2004 Their research aims to create a realistic forecasting model that analyzes individual schooling decisions while accounting for uncertainty in aggregate parameters like future wage distributions, while assuming certainty in individual parameters, such as the agent's utility function This study introduces a crucial innovation by integrating parameter uncertainty into the decision-making process, enhancing the understanding of educational investments and wage outcomes.
In our framework, a risk-averse individual considers not only the uncertainty of future wage outcomes based on education and experience but also the variability in the underlying wage distribution parameters.
The VAR-Gibbs model is selected for regression analysis due to its effectiveness in addressing two key issues Firstly, it explores how varying levels of risk aversion influence educational choices, revealing that higher risk aversion correlates with reduced educational investment, as education is perceived as a riskier investment compared to experience during the study period Secondly, the research highlights the significance of financial resources in higher education decisions by assessing how changes in initial wealth affect individuals' educational choices.
This study reveals significant variations in forecasting methods regarding school attendance rates, average educational attainment, and the duration required to earn a college degree It concludes that individuals with greater initial wealth tend to accumulate education more rapidly.
Hamilton et al (2000) investigated the impact of worker and employer heterogeneity on the distribution of output, focusing on the relationship between firm profits and wages Unlike Sattinger (1993), their study addresses a labor market with vertically differentiated workers and firms, where all workers possess a common level of general human capital, yet their skills vary This innovative approach allows for the consideration of unique characteristics that render equally educated individuals differently suitable from the firms' perspectives Additionally, the study assumes a diverse workforce suited for various job types, alongside firms with distinct job requirements, ultimately proposing a non-hierarchical assignment model that complements existing hierarchical models.
In a labor market where firms struggle to identify individual worker skills, those receiving less training may still earn higher net wages due to better job matches This occurs despite workers having similar levels of general human capital and productivity, as varying training costs arise from different matches As the number of firms increases, competition for well-matched workers drives equilibrium wages higher In a scenario with an infinite number of firms, wages align with the competitive level of general human capital, while profits diminish to zero Additionally, an increase in the common level of general human capital boosts gross productivity and reduces training costs, leading to higher net wages, as supported by empirical studies However, profits decline as firms lose monopsony power, counteracting productivity gains.
When firms are fully aware of the quality of individual job matches prior to hiring, they can tailor their offers based on the specific skill types of workers This allows employers to concentrate on the overall wage and training costs, while employees focus on their net wages after accounting for any training expenses The responsibility for training costs becomes a part of the negotiation process, making it less significant who actually pays Consequently, workers who undergo more training may receive higher net wages, not necessarily due to increased productivity, but because their training costs at alternative firms are lower This dynamic creates a situation where poorly matched workers have better outside options compared to well-matched counterparts, thereby enhancing their bargaining power.
Economists find wage and education to be compelling topics, as demonstrated by Meghir's (2005) analysis of a reform's impact on educational attainment and earnings using data from the Swedish Level of Living Survey and national education records from 1985 to 1996 The study divided participants into two cohorts: 10,309 individuals born in 1948 and 9,007 born in 1953 A logit model assessed the relationship between years of education and educational levels, revealing an overall increase of 0.298 years in education due to the reform, with significant effects noted Low-ability students tended to attain the new compulsory education level, while high-ability students showed greater increases beyond this level Although the overall impact on earnings was modest at 1.42 percent, it masked considerable variability, particularly benefiting individuals with unskilled fathers, whose earnings increased by 3.4 percent.
Older studies have explored the relationship between education and wages, notably the research by Harmon and Walker (1995), which analyzed the rate of return on schooling using data from the U.K Family Expenditure Survey (FES) This study focused on a sample of 34,336 employed males aged 18-64, gathered from nine consecutive annual FES cross sections between 1978 and 1986 To address the endogenous issues, the researchers employed an instrumental variable approach, leveraging exogenous changes in the educational distribution resulting from the increases in the minimum school-leaving age in the U.K., which occurred twice during the studied period.
- - - - - - - of the working-age individuals in our data) to provide instruments for schooling By choosing this way, this research has a little bit different to previous studies such as
A study by Grist and Krueger (1991) utilized natural variations in data from external influences on schooling decisions, reinforcing the conclusions of Ashenfelter and Krueger (1994) that an additional year of education can lead to a wage increase of over 15% Additionally, the research revealed that residents in large cities tend to earn higher wages compared to those in other regions.
Social scientists across various fields have extensively researched the link between family background and an individual's economic and social status in adulthood Numerous studies have analyzed how family factors, including parental income, parental education, and the number of siblings, influence wages Levin et al have contributed to this body of work, highlighting the significance of these family dynamics on economic outcomes.
A study conducted in 2007 introduced a novel method to measure sibling correlation in earnings across two distinct time periods, utilizing data from the National Longitudinal Surveys (NLS) This analysis revealed a significant increase in the correlation of annual earnings, family income, and hourly wages among brothers born between 1957 and 1965, compared to those born between 1944 and 1952 Specifically, the correlation for annual earnings rose from 0.26 to 0.45, indicating a statistically significant change The findings suggest that nearly half of the variance in earnings and wages for the more recent cohorts can be attributed to family and community influences, pointing to a decline in intergenerational mobility Interestingly, there was no change in the correlation of years of schooling between these cohorts, indicating that the stronger association between family influences and educational attainment does not account for the observed increase in earnings correlation.
The returns to education have significantly increased between the two cohorts; however, this factor accounts for only a small fraction of the overall rise in the correlation of earnings among brothers.
Betts (2001) utilizes data from the National Longitudinal Survey (NLS) to investigate how school resources influence the labor market outcomes of women This study focuses on the correlation between high school resources and women's educational attainment and earnings in the United States The research analyzes data from a survey of young women aged 37 to 50, covering the period from 1991 to 2001.
2000 There are totally 2,551 the whites and 801 the blacks participating this study
First stage, Betts fitted an ordered probit model to investigate education attainment
The model interprets coefficients as marginal impacts on years of schooling, revealing that additional school inputs significantly affect educational attainment for black women Notably, a 10% increase in the starting salary of teachers with a bachelor's degree, equating to $605, is predicted to enhance black women's education by approximately 0.1 years, while a 10% reduction in class size is associated with a 0.07-year increase In contrast, similar changes yield smaller educational impacts for white women, with only teachers' salaries and books per student showing a positive correlation, and those effects are less pronounced The analysis indicates no significant relationship between school resources and wages for white women, while school inputs positively influence black women's wages, potentially due to a smaller sample size A subsequent probit model assesses the determinants of women's earnings, confirming that years of schooling are an endogenous function of personal background, with wage elasticities regarding school inputs being consistently higher for black women Furthermore, the influence of school resources on earnings remains stable or diminishes as workers age.
OVERVIEW OF VIETNAM LABOUR MARKET
Employment by age and gender 0 0 0 0 0 0 0 ° 0 0
The employment-to-population ratio is a crucial indicator of economic activity in Vietnam, reflecting the percentage of the relevant population groups that are employed This ratio has shown a steady increase over the years, rising from 62.73% in 2006 to 69.18% in 2008 Additionally, the youth population is nearly evenly split between genders, highlighting the demographic structure of the workforce.
In 2008, the labor force participation rate for women was slightly higher at 50.33% compared to men's 49.67%, despite an overall increase in male ratios but a decline in quantity While women experienced decreases in their ratios, they still represented a larger proportion of the labor force than men This trend contrasts with the findings from the Population and Housing surveys conducted between 1997 and 2008, indicating a concerning shift in labor dynamics.
Recent surveys indicate a decline in labor force participation across all age and gender groups, with women representing a smaller percentage than men In the previous year's survey, the employment-to-population ratio was 53.3%, with men at 52% and women at 48% The VHLSS data shows a decrease in observations from 39,071 in 2006 to 35,154 in 2008, despite a slight increase in the labor force, leading to a higher workforce ratio relative to total samples Notably, the VHLSS emphasizes rural areas, where female employment constitutes a significant portion, as many women engage in agricultural activities and serve as primary earners for their families, often working as unpaid family members or self-employed individuals This demographic significantly influences the sample size.
The Population and Housing survey encompasses the entire population of a country, revealing comprehensive labor force trends rather than relying on samples Notably, the youth aged 15 to 24 years represented 27.99% of the workforce in 2006 and 26.45% in 2008, indicating a significant share of labor force growth among young individuals This decline in participation can be attributed to young people's tendency to extend their education, resulting in reduced workforce engagement Additionally, male participation in the labor force tends to be higher than that of females, suggesting that men often enter the workforce earlier Between 2006 and 2008, the youth labor force decreased by over 400 individuals, or 1.54% Despite this decline, the gap between male and female labor force participation rates is relatively small compared to many other countries Overall, both male and female participation rates saw a decline from 1997 to 2007, with the most significant drop observed among young women.
Similar to the labour force participation rate, the employment-to-population ratio in
From a regional standpoint, Vietnam's workforce participation is notable, although it falls short compared to East Asia As of 2009, women comprised 48% of the labor force, while men accounted for 52%, reflecting a trend of gender disparity that persisted over the previous 30 years (Population and Housing Survey 2009).
Vietnam's labor force has seen a gradual decline compared to the labor forces in East Asia and Southeast Asia during this period However, Vietnam is experiencing changes at a faster pace than its regional counterparts Notably, the participation of males in the workforce has decreased significantly.
East Asia, Vietnam is conversely The same trend is found for the South East Asia and Pacific which female's percentages participate in labour force reducing highest
According to the ILO (May 2009), Vietnam has a significantly higher percentage of women in the workforce compared to other countries in the region While women in Vietnam represent 79.5% of the workforce, countries like the Philippines, Indonesia, and Korea have a participation rate of approximately 50% (ILO, 1997-1998).
Figure 3.2: Workforce classified by age-bands (person) i 2,500
The participation of women and men in the labor force shows a gradual decline starting from the age of 15-19, with noticeable differences in participation rates emerging at this age These differences continue to decrease until they reach their lowest point between the ages of 40-44, where the gap is minimal Notably, women remain active in the workforce beyond the age of 55, often contributing more than their male counterparts The Vietnam Household Living Standards Survey (VHLSS) focuses on rural living conditions, highlighting that rural areas represent a significant portion of the sample In these regions, women are frequently the primary earners in agricultural activities and often engage in unpaid family work, remaining active in their roles without the same retirement patterns seen in wage earners.
Table 3.2: Labour force divided by sex, regions(%) rããã ããã2aa6ããã ããã2ao8ããã1
' ' i Regions ã"ATC~exe~ ããMale -Fe~a1e _ ãA:ifsexes -M~1e ã:pe~a!eã -~
-N~rth E-asi -T5:sã4 ãã::20Ấ:20::5s -ã5a-.-42- -isã.-~faãã -ã-sajj- -49j~ 1ã1
-N~-rth-westã - -ãã-s-:7"3 -49:"35 -ããs(Y_-6ã5- -6.-"1"6 -49-:8T -sãa:T9
-N~-rth-ãce~1~a:rc0a-5T -To:2r -49:ã55 -ã5o-.-4ã5- -9.-6"6"- -49-."73-o;~- -ã-ã-sãa:-27 solithã - -ããs:7ã4 -ããsãa:ãiãsãã -49-.-82- -ããs-.-82 -ããsãa:ãs6ão;~- -49:ã44
Central Coast ããcefii~a:rt~rgili~n:a~ - -ã6:73 -4-9:-78 -5a::20:é20:: -6-:94 ãã-ã-s-T.-s?ão;~- -48:-43
- -ããã -ããã -ããã-ãã -ããã -~ -4
Mekong-~i"~e~-cieita:ãã - ãã2o-Đsã - 49:2"3" ããs-o:??" _ ããia-."74ã - 49-.-:290/~ - ãsãa:-7To/~ - ãu;ban _ -23".-74 4&-:6ã5ã ããsT3ãsãã - ã23j~6 - -48-:6T ãs-1:"39
Rli~arãã - -7"6:26ã - 49.-?ãaãã- ããs-o:3ãaãã - 76-:14ã - ããsaã:aK ã49-:94ã -j i
According to Table 3.2, the North West region has the lowest labor force participation, while the Mekong River Delta shows contrasting trends Interestingly, the South East and Red River Delta regions have even lower percentages despite their significant urban centers, including Hanoi, Ho Chi Minh City, and Haiphong, which collectively have populations estimated at 11 to 12 million Nonetheless, urban areas in Vietnam represent less than 24% of the total population aged 15 and over.
Since 1997, the urban population's share of the labor force has been steadily increasing, driven by a gradual shift of people from rural areas to cities This trend reflects not only a rise in the number of urban residents but also the expansion of urban geographic boundaries, highlighting the ongoing transformation of demographics in favor of urbanization.
We also find that women take part in workforce higher both in rural and urban areas.
Employment with education and training 0 0 0
Vietnamese youth exhibit impressive literacy rates, exceeding 90%, with a consistent high level maintained over the past 25 years, despite reductions in state education subsidies following the Doi Moi reforms In 2006, 86.3% of surveyed individuals were found to be literate, contributing significantly to the workforce The literacy rate has shown a steady increase, rising from 93.2% in 2008 to 93.5% in subsequent years.
The 2009 Population and Housing survey indicates that the implementation of compulsory primary education and the policy to eliminate illiteracy have effectively increased the literacy rate While the workforce's literacy rate saw a modest rise from 94.7% in 2006 to 94.8% in 2008, Table 3.3 provides further details on the education levels within the labor force.
Table 3.3 highlights significant disparities in educational attainment across various regions The Mekong River Delta, a leading rice-exporting area, has the highest number of individuals without any educational certificates and those who have only completed primary school In contrast, the Red River Delta ranks first in the number of high school graduates, encompassing both lower and upper secondary education.
Table 3.3: Labour force classified by education (%)
Region No Primary Lower Upper College University Master certificate secondary school and higher
The South East region boasts the highest university graduation rate in the country, while the South Central Coast excels in master's degree attainment In urban areas, individuals with upper secondary school diplomas represent the largest demographic, whereas in rural regions, primary school graduates dominate This disparity highlights that a significant portion of the population lacks education beyond upper secondary level, adversely impacting the skill quality of the workforce in rural areas, which constitutes 76.26% of the total Overall, these educational trends suggest a need for targeted initiatives to enhance workforce skills across the country.
The percentage of individuals with a college degree or higher stands at nearly 6%, with 873 people achieving a university-level education, equivalent to 4.4% This trend highlights a concerning issue within our workforce; while the quantity of workers is abundant, there is a significant shortage of skilled labor Consequently, this deficiency in high-skilled workers is contributing to low productivity across various industries.
According to Figure 3.3, over 95% of the working-age population in Vietnam lacks vocational training, resulting in a significant number of unskilled workers This situation presents challenges for the youth, as highlighted in the Vietnam Youth Development Strategy 2010, which emphasizes the need for job creation Millions of young people in urban areas are actively seeking employment, with many working approximately 75% of their time throughout the year The increase in unskilled workers from 2006 to 2008 can be attributed to the global crisis, which negatively impacted household earnings, forcing many students to drop out of school and enter the workforce without proper training.
According to a survey by VCCI, ILO with observations from FDI companies, Young enterprise associations, VCCI's members and Human and Personnel
This year, a management club survey revealed that up to 50% of enterprises frequently retrain new recruits due to a mismatch between employment skills and company requirements The surveyed companies span various sectors, including printing, aquatic processing, textiles, electronics, and tourism There is a significant shortage of highly skilled workers, particularly in manufacturing, where 67% of positions remain unfilled Consequently, a large proportion of jobs are of a subsistence nature, with manual laborers constituting 67.31% of total employment as reported in the 2008 VHLSS.
Between 2006 and 2008, the percentage of employed workers receiving vocational training significantly declined, dropping from 4.26% in 2006 to just 1.81% in 2008 This decrease can be attributed to the global crisis, which prompted many students to leave school and enter the labor market As a result, a large number of untrained individuals began filling jobs, primarily in manual labor roles such as laborers and agricultural workers Consequently, manual occupations now represent the majority of employment, yet these positions often offer limited duration and low wages, frequently resulting in short-term or seasonal work.
Employment status data categorizes workers into four groups: wage earners who work for others, self-employed individuals who may hire employees or operate independently, and unpaid family workers, also known as contributing family workers The latter group assists in family businesses or farms without receiving payment, often comprising spouses, children, or extended family members like grandparents and cousins, thereby contributing to the business's profitability.
According to the VHLSS data, employment status can be categorized into four groups: wage and salaried workers, employers, own-account workers, and unpaid family workers In 2006, the number of individuals identified in these employment categories was notably low.
In recent years, the percentage of employers has decreased slightly from 0.43% to 0.34%, while wages and salaries workers have consistently represented the largest segment of total employment, ranging from 44.72% to 45.33% Unpaid family workers also showed a minor increase, moving from 44.11% to 44.38% Conversely, the proportion of self-employed individuals declined from 10.83% to 9.85% Collectively, vulnerable employment—comprising self-employed and unpaid family workers—dropped from 54.94% to 54.23% in 2008 Despite this decline, self-employment and unpaid family work remain significant, with over half of all employed women engaged as unpaid workers in family businesses, highlighting a stark contrast to their male counterparts.
Table 3.4: Distributions of status in employment by sex
waies an-cr -~ -3-s-~s4 ; _ 6-ci-6+ -39:Trj_ _ 6_o~-s9- salaries workers (%)
According to data from the VHLSS 2006-2008, an alarming statistic reveals that over half of all employed women in Vietnam are not compensated for their work, highlighting significant gender disparities in earnings For more details, refer to Appendix table AS.
We can say that women suffer more than men in terms of vulnerability in Vietnam because of 78% of their total employment was in the own-account and unpaid
In Vietnam, a significant portion of employed women are engaged as unpaid family workers, reflecting a stark contrast to the 75 percent employment rate among men (ILO, 2007) This concentration in unpaid roles, along with the prevalence of own-account workers, results in a diminished likelihood of formal employment arrangements for women Consequently, they often lack essential elements of decent work, such as adequate social security and a voice in the workplace The high rates of vulnerable employment among women are indicative of widespread poverty within the country.
Unemployment
Age-bands Number of worker Percent
The VHLSS 2008 report reveals that 4,269 individuals aged 15 to under 60 are unemployed, accounting for 21.29% of the total labor force This significant figure is largely influenced by the inclusion of rural residents, where unemployment rates are the highest Additionally, the report highlights that the age group of 15 to 29 is particularly affected by this issue.
In 2009, individuals aged 15-19 represented the highest unemployment rates, accounting for nearly 75% of the total unemployed population, which was 4,269, or 1.76% of the labor force The Population and Housing survey recorded 1,504,888 unemployed individuals, constituting 3.05% of the total labor force, marking the highest unemployment ratio from 1997 to 2009 Notably, those aged 15-29 made up nearly 50% of the unemployed demographic There is a significant disparity in unemployment rates based on technical training and geographical location; urban residents without specific training face higher joblessness compared to their rural counterparts Conversely, individuals with technical training in urban areas have better employment opportunities.
Figure 3.4: Workforce vs employed workers (thousand of person) c 30,000
Source: MOLISA labour and employment surveys
We can conclude that unemployment is not a senous issue of Vietnam economy The challenges are type of jobs and skills of employment
THE MODEL
Before 1992, empirical studies on intergenerational income correlations faced biases, particularly due to OLS estimation methods Solon's 1992 research marked a significant advancement in understanding the impact of family background on employment earnings Previous studies often relied on sibling or father-son correlations, which inadequately addressed the distinction between permanent and transitory income variations, overlooked life-cycle stages, and utilized overly homogeneous samples Additionally, the work of Bielby and Hauser (1977) highlighted the errors-in-variables bias stemming from parental income measurements based on sons' recollections, with their adjustments for response error relying on the unrealistic assumption of no correlation between response errors over time.
Behrman and Taubman (1985) analyzed a sample of white male twins born between 1917 and 1927, encountering downward bias due to two significant limitations Firstly, the absence of direct measures of long-term status, as many studies only considered single-year earnings or income Secondly, the samples were not randomly selected While some studies from this period employed Instrument Variable (IV) estimation, research by Solon (1992) and Card (1998) demonstrated that using family background variables as instruments could exacerbate the bias in Ordinary Least Squares (OLS) results, particularly if these variables are correlated with unobserved factors.
- - - - - - ability If one uses the family background variables solely as instruments, the bias is worse than OLS
Harm (1995) highlights the importance of careful instrument selection, as John Bound et al (1993) warn that weak correlations between instruments and wages can lead to significant bias in Instrument Variable (IV) estimates To mitigate this bias, Card recommends controlling for family background variables, asserting that Ordinary Least Squares (OLS) estimates of education returns are less biased when these variables are included compared to OLS results that do not account for them.
In this study, I aim to analyze the impact of educational and family background determinants on employment wages using Ordinary Least Squares (OLS) methodology A key strength of my research is the utilization of cross-sectional data from two different years, which helps to mitigate bias associated with single-year estimates The samples are drawn from the Vietnam Household Living Standards Survey (VHLSS), ensuring a sufficiently large and randomly selected dataset Additionally, I incorporate parental education and the number of siblings as control variables to account for background influences.
A A A f3JXlf'eniS _ educatim+ ~sibilings+ f3sDcan _irdex+8 4 urlxTn+u; with ui is residual The dependent variable is natural logarithm of nominal hourly wage Betts
(200 1) used the log of nominal wages as the dependent variable in calculating determinants of wage
1 Age is one of characteristic belonging to demographic factors of a person Age increases respectively wage ( Harmon, 1995) A year is added, an employee's wage will increase 13.38% (Betts, 2001)
Ethnicity is a crucial variable in studying employment behavior, as it falls under demographic characteristics In my research, I utilize ethnicity as a dummy variable to examine whether Kinh workers receive higher wages compared to other workers.
3 Married: this is an important variable belongs to demographic characteristics (Dang et al 2005) A married worker will be got higher salary than others ( Betts, 200 1)
4 Educational attainment: employment's education directly affects skills of labour Empirical studies show that employment is skilled or higher education attainment will get higher wage (Hamilton et al 2000; Betts,
5 South east: residences live in center or big city often tendency to be paid higher wage (Dang et al, 20005; Harmon, 1995)
6 Parents' education: education of mother is important directly effect on children's knowledge as well as job selection decision at adulthood It results in positive relation to wage (Betts, 2001)
7 Siblings: number of siblings will negative affect employees' wages (Betts,
Research indicates that individuals with multiple siblings are more likely to seek employment and start working earlier than those with fewer siblings (Dang et al., 2005) This trend suggests that having many brothers or sisters may influence a person's motivation to enter the workforce sooner.
8 Urban: allocation residence also impacts differently on wage Betts, 2001 found that workers who live in central areas are paid higher wage
The Duncan index is a crucial variable representing family background, specifically the socioeconomic status associated with the job held by the head of the household Scored using the Duncan index from 1961 and the Social Occupation Index from 1992, this variable is anticipated to have a positive correlation with wage increases (Betts, 2001).
Determinant Variable Definition Expected I sign
Age Age The age of the employee (over 15 + to under 60)
Ethnicity Ethnicity ã The ethnicity of employee
rvia~Ieltl [95% Conf Interval]
Employment can be categorized into three main forms: (1) paid employment, which includes compensation in cash, kind, or through mutual assistance; (2) self-employment, where individuals generate income for themselves; and (3) family-based activities involving production, business, and services, where no wages or salaries are earned (MOLISA)
Employed individuals are defined as those who have worked for at least one hour during a specified reference period, either for a wage or salary in paid employment or for profit in self-employment and contributing family work This definition also includes individuals who possess a job but were temporarily absent from work during the reference period Employment encompasses all persons aged 15 and over within the labor force who engaged in these forms of work within the last seven days Specifically, employed youth refers to individuals aged 15-24 who are active in the labor market (MOLISA)
A job is defined as a paid position of regular employment, typically encompassing wage and salaried workers However, the term has evolved to include any work-related task, allowing for a broader interpretation Consequently, anyone engaged in work—whether as a paid employee, self-employed individual, or unpaid family worker—can be considered as having a "job."
The labour force, or economically-active population, comprises individuals aged 15 and older who are either employed or actively seeking employment Conversely, those outside the labour force are considered economically inactive, including individuals aged 15 and above who are neither employed nor seeking work.
The labour market is a virtual space where job seekers and employers engage in competition Analysts evaluate its effectiveness using key statistics like the employment-to-population ratio and unemployment rate, which help assess the dynamics between labour supply and demand Understanding these metrics reveals why the labour market often fails to achieve perfect equilibrium.
Own-account workers: persons who are self-employed, with no employees working for them
An unemployed individual is defined as someone who, during a specific short reference period, is without work, available for work, and actively seeking employment through various methods Additionally, a person is classified as unemployed if they are not currently working but have arranged to begin paid or self-employment after the reference period, according to the International Labour Organization (ILO).
Unemployment: a measure of the total number of unemployed persons
An unpaid family worker, or contributing family worker, is an individual who contributes to a family-owned business without receiving any payment This type of worker typically assists in the operations of the business, which is managed by a family member who is classified as an own-account worker, according to the International Labour Organization (ILO).
Vulnerable employment: for purposes of this report, the sum of own-account workers and contributing family workers (unpaid family workers) (ILO)
Work, as a verb, refers to engaging in economic activity by supplying labor for the production of goods and services As a noun, "work" is often synonymous with "job" and "employment," indicating that an individual may express having "work," "a job," or "employment" when referring to their labor contributions.
Individuals of working age who are not part of the labor force include men aged 15 to 60 and women aged 15 to 55 This group consists of those who are neither employed nor classified as unemployed, highlighting a significant demographic outside the active workforce.
' Table Al: Construction of Duncan index variable
Group of occupation Score Occupation codes in
~ Table A2: Youth labour force participation rates(%)
Source: MOLISA labour and employment surveys and GSO population estimates
Table A3 :Labour force classified by sexes and regions
Total I Male I I Total I Male I Female
Regions Peo le) Peo le) %) Peo le %) Peo le) Peo le % Peo le) %)
~~~~~~! ~~-~~-! -r -2~-2o-6r -~Jo-;;-r -5oisr -To99r -49~sir -2-:23-7T ciiiT_s_o36T _ TTa6r49-.-44
~3~+=:~::::::::=~:~:~r=~:~~~~;~F~~~~n:r=~~~~ffo~~ delta river u;b:~ - -655_6_ -fos-9 -4-8:6_5_ -:,-:26-i -5T3_5_ -6-:4-f9- -3-:-i-io -48~-6-i- -f299 51 3 9
' Table A4: Unemployed workers by age-bands (person)
-fio-use;o~r -r -s9-r i2sT -;ys r -7o-r -6ifr -s:n -s-cr iTo-r -9-7T _ 76-s-
-nTs~bie~eil1 -r -~Kt _ 22l f4-r -T7-r -2o-r -i3_T _ 17T ioT _ Ti r f4o-