‘Educated youth should be given priority in national development’ | Daily News

‘Educated youth should be given priority in national development’

Unemploment of educated youth (UEY) having minimum of GCE (OL) withing the age group of (15-24) should be given high priority in the national development plan, said Senior Professor, in Applied Statistics, University of Moratuwa, T.S.G. Peiris.

He suggested that it is necessary to consider a separate age category 18-24 rather than 15-24. in the labour force surveys conducted by Department of Census and Statics.

“According to the job market requirements, the secondary level and the tertiary level education system needs to be updated and the skills needs to be developed so that it would not be difficult for the females to find suitable jobs and contribute to the labour force.”

Pro. T.S.G. Peiris

Further, in order to increase the women involvement in labour force, it’s essential to initiate flexible working hours in companies either on shift basis or as part time work, so that it would be a support for the females in balancing their personal life and work life simultaneously.

With the use of technological advancements, it is high time to create job opportunities for youth to work from home as in developed countries.

The government can promote the concept of ‘Entrepreneurship’ as it would be more useful for both males and females to balance their life while earning a reasonable income and creating more employment opportunities for others as well.

Government should get service of applied statisticians for many decision making process.

Following are the views on Youth unemployment by Professor T S G Peiris…

Youth unemployment is the situation where young people of age 15-25 who are looking for a job, but cannot find a job. It is considered as key measure of economic health of a country. Unemployment is a powerful statistic that shapes government policies and decisions. The Department of Census and Statistics (DCS) in Sri Lanka conducts labour force survey (LF) annually (quarterly basis within a year). For the survey, the primarily sampling units (PSUs) are the census blocks prepared at the Census of Population and Housing in 2012 conducted by the DCS and secondary sampling units (SSUs) are housing units within census blocks, selected from systematic random sampling method. The sample size is over 25000.

Large amount of data is collected in such surveys. Based on survey data, The DCS produces summary tables, graphs etc. in books as well as in the website of the DCS. These data have very valuable information which can be effectively used for better planning and development of the country. However, most of the data collected by the DCS are not been investigated deeply to derive useful inferences. The objective of this analysis is to highlight some of the important points on youth unemployment rates (YUR) and educated unemployed youth (EUY) which would be useful for policy makers in the government.

Youth unemployment rate (YUR)

YUR is defined as the percentage of the unemployed population in the age group 15 – 24 years to the current labour force in the age group of 15 – 24 years.

YUR by Provinces…

The results in Table 1 indicate:

The YUR has been fluctuating around 20% during 2013 to 2018 though there is an increasing trend since 2013 in all the provinces with exceptional in 2017. In 2017 there was decrease in YUR in all provinces except Northern province. A sharp drop (26.6% to 19.8%) in 2018 compared with other provinces.

According to the values available in 2019, YUR in Sri Lanka decreased to 20.0% in the second quarter of 2019 from 21.6% in the first quarter of 2019. Thus YUR in Sri Lanka can be taken as 20% irrespective years. According to the YUR statistics in 2018 in all countries, the highest YUR is 53.2% in South Africa and the lowest value is 2.3% in Switzerland.

The rate of increase of YUR in 2018 with respect to YUR in 2013 is the highest (87.9%) in UVA province as it has increased from 14.9% in 2013 to 28.0% in 2018. The rate of increase in North central province is 61.2%. The lowest increase rate was 11.9% in North province. Of the nine provinces when the YUR has increased in seven provinces, only in Western and Sabaragamuwa provinces UYR has decreased by 23.7% and 22.7% respectively.

The reasons of such variation among provinces needs to studied for better planning of the government. However, the above statistics can effectively be used when employment policies are implemented by the government. This suggest that in additional to the common policies in Sri Lanka, province based job markets should be created within provinces.

YUR by Gender

The YUR has been increasing over the years in both gender category. The rate of increase of females is higher than that of men in all years. Furthermore, YURs among females are significantly higher than the national averages of the corresponding years and YURs among men are significantly lower than the corresponding annual national average. This is a serious issue of which policy makers should concentrate. This clearly shows that there is gender discrimination in youth unemployment.

YUR by Level of Education

Table 2:

YUR by level of second category as the age limit is 24.

YUR is significantly higher among the youth having G.C.E. (A/L) and above than the YUR among youth having G.C.E.(O/L). The reason for this gap is not known, but it would very useful to know the reasons from the national policy point of view. The impact of this due to provinces also can be analyzed. Also it is useful to have a breakdown among different stream of G.C.E. (A/L). Nevertheless, there can have some graduates in the category of G.C.E.(A/L) and above as the upper age limit is 24 years.

Unemployment of Educated Youth (UEY)

In LF surveys data are collected under four educational categories such as (a) Grade 5 and below, (b) Grade 6-10, (c) GCE (OL) and (d) GCE (AL) & above and four age categories such as (a) 15-24., (b) 25 -29, (c) 30-39 and (d) over 40. All persons above 15 years of either gender are identified as working age population for this survey. This population consists with two groups: (i) economically active (labour force) and (ii) economically inactive. The labor force comprises all persons of working age who are either “employed” or “unemployed” during a week before the survey period. Thus, labour force = Employed + Unemployed. The unemployment of educated youth (UEY) is considered as those who are unemployed having minimum of GCE(OL) with age between15-24.

I use data of UEY data from the labour force (LF) survey conducted by the DCS in 2016 and analyzed using binary logistic regression procedure. The identified factors which significantly associated with UEY are gender, education attainment, knowledge of English and residential sector.

Influential Factors on UEY

The results found that gender is significantly associated with the UEY and percentage of UEY for females (81.0%) is significantly higher than the percentage of UEY for males (68.9%). The odds of UEY are 0.552 times higher for women than they are men.

Educational Level

The education attainment is also found as a significantly influential factor on EYU and the percentage of EYU among those who passed G.C.E. (O/L) examination (82.0%) is significantly higher than that of those who passed G.C.E. (A/L) examination (69.7%). The odds of UEY are 1.984 times higher for G.C.E.(O/L) category than they are for G..C. E (A/L) category.

English

It was found that the education attainment of the youth is significant associated with EUY. Among the educated youth who have the ability to read and write English, 74.3% are not in the labor force and the corresponding figure for the youth who are unable to read and write English is 77.2%. The odds of UEY are 0.855 times higher for category of able to write and read English than they are for the category of unable to write and read English.

Residential Sector

The analysis found that that there is a significant influence of the living area on EUY. The percentages of EUY are 70.4%, 77.4% and 78.0% for urban sector, rural sector and estate sector respectively. The odds of UEY are 0.670 times higher in Urban sector than they are in Estate sector and the odds of UEY are 0.983 times higher in Rural sector than they are in Estate sector.

Summary of the Data analysis

·Annual youth unemployment rate (YUR) in Sri Lanka has been around 20% since 2013. That is, one out of every five economically active youth are unemployed since 2013.

·Of the provinces, YUR in Sabaragamuwa, UVA and Southern provinces have been higher than the national average of YUR since 2013.

·The YUR has been lower than the national average only in Western and North Western provinces.

·Gender, education attainment, literacy level in English and residential sector are the significant factors associated with the UEY in Sri Lanka.


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