Youth participation in a labour force and in the country’s development outcomes is intertwined. It affects growth, human capital and social norms. Labour force participation rates by youth are just one indicator and do not give the full picture of their impact on the labour market. For a broader picture, youth in the labour market need to be seen through the lens of the demographic dividend and human capital stock. Since 2008’s global financial crisis, young people’s role in the labour market has become a burning issue for researchers and policy-makers.
A decade after that global financial crisis, the 2020 covid-19 pandemic hit the world harder, presenting unprecedented challenges. Youth were among the most vulnerable, cast out from the labour market in droves. For students, their education was interrupted.
As a developing country, Bangladesh faces the challenge to transform its youth bulge into human capital for its labour market. Bangladesh has outperformed many comparator countries in dealing with the covid-19 induced economic crisis. But it is also true that the crisis pushed many young Bangladeshis out of jobs, either temporarily or permanently.
The two drivers
This writeup focuses on two integral features of youth employment in Bangladesh: youth not in education, employment or training (NEET) and returns to education. The NEET rate is basically the share of young people in the whole population who are not in jobs or educational activities. It provides a measure for young entrants into the labour market (or those outside the education system, training and employment). One must note that NEET does not mean youth unemployment, because it also includes young people outside the labour force not in education or training – it doesn’t matter whether they are seeking a job or not.
The ‘returns to education’ feature is measured by a proxy variable: employment outcomes of average years. Education is the key variable for both the quality and the stock of human capital for a country. World Bank economists George Psacharopoulos and Harry Patrinos in 2004 research titled ‘Returns to Investment in Education’ concluded that education was a pivotal investment to generate employability, income and productivity. In other words, education engenders human capital development.
Several comparative studies show that more educated individuals earn higher wages, are less vulnerable to unemployment and feel more dignity of labour than their less-educated counterparts. According to estimates by the United Nations’ specialised labour-standards agency the International Labour Organization (ILO), the youth unemployment rate in 2020 was 14.8% in Bangladesh – nearly three times more than the overall unemployment rate of 5.2%. The share of unemployed youth in total unemployment is 79.6%. More strikingly, according to the country’s main data collection agency, the Bangladesh Bureau of Statistics, the unemployment rate among young college graduates is 13.4%.
… the youth unemployment rate in 2020 was 14.8% in Bangladesh – nearly three times more than the overall unemployment rate of 5.2%.
ILO’s data on South and South East Asian countries from 2017 show that Bangladesh has the second highest share of youth not in education, employment or training (NEET). Only Nepal has a higher share. The share of NEET youth in Cambodia, Malaysia, Myanmar and Viet Nam is less than half that of Bangladesh.
Perhaps the biggest concern for Bangladesh is the share of female NEET youth, which is 44.6%. This is four times the share of the male NEET youth, which is 9.8%. The share of male NEET youth in Bangladesh is actually at optimal level, similar to in Malaysia, Myanmar and Viet Nam. The female NEET youth rate is jacking up the youth NEET problem for Bangladesh.
Education (not equals) jobs
Now, what are the employment outcomes of average schooling years in Bangladesh? Data from the Bangladesh Bureau of Statistics show a positive relationship between education and unemployment. This means that, in Bangladesh, the likelihood of employment reduces with more education. This goes against established human capital development theories. It should severely puzzle Bangladeshi policy-makers!
The marriage between unemployment and education in Bangladesh points to several factors that mean that education is not paying off in terms of its returns in the labour market for individuals.
The average number of years of schooling for an unemployed Bangladeshi male youth is 11. Meanwhile, their employed counterparts have an average of 6.9 years of schooling. Similarly, average number of schooling years for unemployed female youth is 9.6, compared with 6. for their employed counterparts. This is not the case just for youth; disaggregated by geography and economic sector, the data show that, on average, unemployed Bangladeshis are more educated than are employed Bangladeshis.
The marriage between unemployment and education in Bangladesh points to several factors that mean that education is not paying off in terms of its returns in the labour market for individuals. As individuals become more educated, their reservation wage increases; as they expect higher wages in the job market, it becomes increasingly difficult for them to find employment in an economy like Bangladesh, where the labour market is dominated by the informal sector, which employs about 85% of the labour force of the country.
Researchers’ investigations should go beyond ‘unemployment–education match’ analytics. What is the segment-wise relationship between different education levels and employment? This might explain the ‘non-returns’ to education in job outcomes for Bangladeshis. The author’s simulations show some surprising findings in this!
The curious case of Bangladesh
The author’s findings show that females with up to high school education (higher secondary level) are more likely to be unemployed compared with females with no education. This is alarming! For Bangladeshi women, as level of education increases, job opportunity decreases. Meanwhile, for Bangladeshi men, increased education increases their probability of getting a job.
For Bangladeshi women, as level of education increases, job opportunity decreases.
But there is a disclaimer here: all three levels of education have almost the same negligible effect of turning an unemployed male into an employed one. This evidence goes against established theories, which dictate that, with more education, a person’s likelihood of getting a job increases.
The findings suggests that, to build back from the covid-19 aftermath and prepare for graduation from United Nations least developed country status, Bangladeshi policy-makers must look into the two critical impediments in the labour market: 1) youth employment, particularly that of young girls and women; and 2) reforming the education system to match industry skills.
Where to now?
To increase women’s labour force participation, proactive policies such as job search assistance, apprenticeships, small and medium enterprise support and industry-led training programmes are low-hanging fruit. For long-lasting impacts, stronger labour market institutions and decent working conditions are a must.
Macroeconomic factors, such as private investment as a share of gross domestic product (GDP), increase formal job creation and social security for unemployed youth. For Bangladesh, it is clear that women will play a pivotal role in making its national employment policy successful.
Bangladesh’s three big labour sector agencies are the Ministry of Labour and Employment, the Employers’ Federation and the Workers Union. These bodies must strengthen collaboration and coordination among themselves. Only then will different government agencies, development partners and the private sector be able to solve the policy challenges in front of them.
 Years of schooling is a measure for capabilities of a person.
 2017 has been taken as a time benchmark as all the countries have data until 2017, even though some have data until 2019.
 Data inferred from the Bangladesh Bureau of Statistics’ Labour Force Survey 2016–2017.
 The author applied a simple econometric technique by using the probabilistic regression model for Ordinary Least Squares estimations using data from Bangladesh’s Labour Force Survey 2016–2017. Additional information on the modelling is available upon inquiry.
 With level of education from primary to secondary, from secondary to higher secondary, and to tertiary level, the probability of being employed decreases for Bangladeshi females.
Photo ©️ Mahmud Hossain Opu