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TVET Programs in Nepal: Issue of Access and Relevancy
Manoj Sharma Neupane
Labour Market Analysist, TVET Professional
Corresponding Email: nmanojsharma@yahoo.com
Equitable access of market relevant TVET (Technical and Vocational Education and Training)
programs is the first and foremost pre-condition to get the desired outcomes from TVET. The access
and relevancy of TVET programs in Nepal are usually questionable. The major objectives of this
paper is to analyze the access and relevancy of presently available long term TVET programs and
identify its gap with the market demand. The analytical approach adopted for this paper is mainly
quantitative and is based on the analysis of micro data of TVET institutes affiliated with Council
for Technical Education and Vocational Training (CTEVT) and Central for Education and Human
Resource Development (CEHRD) with corresponding information of their location, programs and
enrolment capacity. Likewise, review of various other literatures including, journal articles,
workshops proceedings, research reports etc. are also taken into reference. Significant variation
is found between the ratio of district level enrolment capacity of long-term TVET programs to
corresponding number of SEE graduates of the districts which raises question on the equitable
access of TVET programs in terms of geography. Based on the analysis made in this paper, health
related programs are justified as over accessed programs whereas a clear gap can be observed in
the supply mechanism of TVET regarding tourism and agriculture sector. Attention is therefore
needed to promote TVET programs in agriculture and tourism related sectors both in quality and
quantity in order to mitigate existing mismatch between demand and supply.
Abstract
Keywords: Access, Relevancy, TVET, Productivity, Labour Market
Journal of
Training and Development
2020, Volume 5
ISSN: 2392-456X(Print)
ISSN: 2392-4578(Online)
TITI
DOI: https://doi.org/10.3126/jtd.v5i0.33888
Introduction
Labor productivity is one of the major components
to enhance total factor productivity of the economy.
Similarly, systematic development of TVET sub
sector (sectors concerns with skills, knowledge and
technology) is instrumental in enhancing the
productivity of workforce which ultimately
contributes to increase total factor productivity and
production of a nation (Neupane, 2013). The first
and foremost pre-condition to get the desired
outcomes from TVET is to make equitable access
of market-relevant TVET Programs.
In recent past, lot of efforts have been made to
increase the access of TVET programs throughout
the country and make it affordable to all target groups,
including gender, caste, ethnicity, and economically
poor (CTEVT, 2018). Moreover, the term relevancy
is probably the much used word in literature of
TVET. Skills Development Policy, 2007 was the
first TVET policy of Nepal which had recognized
these issues together with other three priority areas
like quality, integration and sustainable financing
(Ministry of Education (MoE), 2007)1 . The Technical
and Vocational Education and Training (TVET)
Policy, 2012 had also given equal emphasis to all of
these areas (MoE, 2012), which is further continued
in the Integrated Education Policy, 2019 (MoEST,
2019a). Moreover, ensuring inclusive and equitable
access of quality education is one of the major goals
of Sustainable Development Goal (SDG) which aims
to support the efforts of Member States to enhance
the relevance of their TVET systems and to equip
all youth and adults with the skills required for
employment, decent work, entrepreneurship and
lifelong learning {United Nations Educational,
Scientific and Cultural Organization (UNESCO),
2016}.
For a country like Nepal where each and every sector
of economy is facing scarcity of technical human
resources, the effective implementation of TVET
policies to increase the quality and relevancy of
TVET programs is the primary requirement of the
country (Neupane, 2013). The subsequent TVET
policies implemented in Nepal had therefore focused
on all of these aspects of effective TVET system and
management. Expansion of TVET institutions and
programs is essential to increase the equitable access
of TVET, but it is not sufficient in itself. Unless and
until TVET programs devise certain quality standard
and the curricula and training infrastructures which
are relevant with the demand of the labour market,
it will not work properly {UNESCO, International
Labour Organization (ILO), 2002}. During the last
two decades, TVET sub-sector of Nepal has witnessed
remarkable success in increasing the access of its
programs throughout the country. However, progress
towards equity and relevancy of programs is still
debatable.
Scope
The scope of this paper is limited within the analysis
of access and relevancy of presently available long-
term TVET programs regulated by CTEVT and
CEHRD. It only explores and considers the sector
wise data of TVET programs, such as health,
agriculture, engineering, tourism & hospitality etc.
but does not enter into program level analysis.
Likewise, the analysis of equity and relevancy of
short term TVET programs is also beyond the scope
of this paper.
Methodology
Although, the paper is a review based paper, the
quantitative analysis of micro data is also adopted
as a major basis while preparing this paper. Mainly
two data sets are used for the quantitative analysis.
The first data set, which is used to analyze the status
of access of TVET programs incorporates list of
TVET institutes associated with CTEVT and CEHRD
together with their address (Local Level), approved
programs and enrolment capacity of these programs.
In total, corresponding data of 1551 TVET institutes,
including 1067 institutes associated with CTEVT
and 484 institutes associated with CEHRD were
included in the data set. The data obtained from the
administrative record of these corresponding institutes
were then migrated to computerized software named
Statistical Programs for Social Science (SPSS) and
further analysis was made. The long-term TVET
capacity by province, district, local level and trade
was first analyzed with the help of descriptive
statistics.
Likewise, the second data set was also developed
considering 77 districts as an analysis unit. In this
data set, enrolment capacity of long term TVET
programs, population, number of SEE graduates of
2017, economic establishment, persons engaged in
those economic establishment were entered from
different sources. The first variable ‘enrolment
17 JTD 5
TVET Programs in Nepal......
1 The name of then Ministry of Education (MoE) has changed now as Ministry of Education, Science and Technology (MoEST)
Manoj Sharma Neupane
capacity of long-term TVET programs’ is considered
as the indication of supply for the TVET programs
whereas the later four variables are considered as
the proxy of demand-side indicators. The district
level enrolment capacity of long-term TVET
programs is deducted from the first data set. Similarly,
district wise SEE graduates’ number is obtained from
Education in Figure 2017 (MoEST, 2017), data of
population is obtained from National Report of
Population and Housing Census (2011) and district
level economic establishments and corresponding
number of persons engaged in those economic
establishments were obtained from National
Economic Census, 2018 (CBS, 2019a). The second
data set is mainly used to explore and analyze the
situation of relevancy of TVET programs at macro
level.
Beside these two datasets, the literatures which have
been central or pivotal to a particular topic of access
and relevancy of TVET programs in Nepal are
sufficiently reviewed in this paper. These literatures
include journal articles, research reports, workshop
proceedings, informative publications of government
agencies and literatures available on-line regarding
access and relevancy of TVET in general and case
of Nepal in specific. Similarly, other informative
documents were also collected and reviewed to
explore the status of access and relevancy of TVET
programs in Nepal.
Analysis and Discussion
In education, the term access typically refers to the
ways in which educational institutions and policies
ensure or at least strive to ensure that students have
equal and equitable opportunities to take full
advantage of their education (The Glossary of
Education Reform, 2014). Since, TVET is considered
as an integral part of education, the same concept
also applies to TVET. Increasing access generally
requires TVET system to provide additional services
or remove any actual or potential barriers that might
prevent some students to equitably participate in
certain courses or programs (ibid).
Expansion of TVET Programs
At the time when CTEVT was established, there
were only six technical schools throughout the
country. Utterpani Technical School was the only
technical school in the then Eastern Development
Region (EDR) and Seti Technical School was the
only technical school in the Far Western Development
Region (FWDR). Increasing access to TVET
programs for the needy population was the primary
objective of the government. The plan of the then
His Majesty’s Government (HMG) to establish a
technical school in each zone from Mechi to Mahakali
had remained unfulfilled even after one decade
(National Planning Commission (NPC), 1991).
Since the establishment of CTEVT in 1989, the rate
of expansion of TVET institutions has been increasing
uninterruptedly. In 1993, CTEVT had started to
affiliate private technical schools to run TSLC2
programs and also started to grant affiliation to run
diploma programs later in 2001. Similarly, since
2000 it started to run technical education in
community high schools as an Annex Program3
(CTEVT, 2020). The technical stream education in
community school which was started in 1993 under
then Department of Education (DoE)4 , further
contributes on the number of technical schools.
Ultimately, the number of long-term TVET providing
institutes has reached to an all-time high (1551) at
the end of the fiscal year 2019/20 (see chart 1).
The socio-economically backward communities have
not been adequately included in the TVET sub-
sectors for many years. The government had not
sufficiently run the constituent schools which could
provide opportunity to these groups of people under
subsidized cost. Till 1999, there were only 13
constituent institutes to run long-term TVET Program
(CTEVT, 1999). Likewise, the private institutes
were not affordable for the students from lower
economic class, (Dahal, 2020). In the meantime, the
18 JTD 5
2 The Technical School Leaving Certificate (TSLC) programs are now known as Pre-diploma programs.
3 The then ‘Annex Program’ is later known as TECS program.
4 The Department of Education(DoE) is now named Central for Education and Human Resource Development
19 JTD 5
TVET Programs in Nepal......
concept of technical education in community school
(TECS) emerged which was expected to address
both of these challenges. On one hand, TECS
programs were assumed to be cost effective since it
used the physical infrastructures and management
system of community schools that has already been
developed. Because of its social responsibility and
non-profit nature, the target groups are expected to
be subsidized (CTEVT, 2016).
Chart 1
Expansion of long-term TVET providing institute
Source: CTEVT, 2020 ( Report of Skill Mapping Taskforce)
Access of TVET Programs by Local Level
Lamichhane, (2012) pointed out some barriers that
hinders poor and disadvantaged groups to participate
in the TVET programs. Two among the various
barriers he pointed out were: TVET providers are
far away from rural areas and the programs are
unable to show clear linkage with employment.
Likewise, Neupane, (2010) had further explored that
53% of long-term TVET institutes were concentrated
in the Tarai region and 25% in Kathmandu Valley.
Among the rest 22%, 19% were in other hilly region
(excluding Kathmandu Valley) and 3% were in
mountain region. These facts provide enough ground
that till a decade earlier, large share of TVET
providers were concentrated within district
headquarter and other urban areas. Moreover, at the
time when Right Honorable Prime Minister of Nepal,
Mr. KP Sharma Oli, announced the commitment of
his government to expand CTEVT affiliated institutes
to each of the 753 local levels within two years. At
that time, only 232 local levels had TVET institute
to provide long-term TVET programs (MoEST,
2019b). Presently, the situation has changed, the
local levels having TVET institutes has been increased
to 635, which is 84.32% of all 753 local levels (see
Table 1). It is interesting to note that additional 403
local levels have got access to long term TVET
providing institutes within the last two and half years.
Although the backlash effect of that decision in
quality of TVET programs cannot be overlooked,
his announcement brought a paradigm shift in
increasing access of TVET sector in Nepal, and more
specifically in the rural part of the country.
Table 1
Local Level by institutional access of TVET
SN
1
2
3
4
5
6
7
Provinces
Province No. 1
Province No. 2
Bagmati Province
Gandaki Province
Lumbini Province
Karnali Province
Sudurpaschim Province
Total
Total local level*
137
136
119
85
109
79
88
753
Local levels with
TVET institutes
105
103
104
71
98
70
84
635
Coverage rate
76.6
75.7
87.4
83.5
90.0
88.6
95.5
84.32
Source: Analysis of microdata (data set 1); * Source: MoEST, (2017). Education in Figure 2017.
Manoj Sharma Neupane
20 JTD 4
If the proportion of local level with TVET institutes
is compared by province, remarkable variation can
be found. The TVET institutes in Sudurpaschim
Province covers 95.5% of the local level followed
by the Lumbini Province which is at the second
position, where the TVET institutes cover 90% (98
of 109) of the local level. The corresponding
percentage of local level with TVET institutes in
Karnali, Bagmati, Gandaki Provinces and Province
No.1 are 88.6%, 87.4%, 83.5% and 76.6%
respectively. It is unusual to note that among the
seven provinces, Province 2 lies at the bottom with
75.7% local levels with TVET institutes, since this
province is relatively in a comfortable position in
terms of infrastructural development like roads and
electricity. The reasons behind the lower institutional
access of TVET programs in Province No. 2 may
be due to easy access to road transportation making
it easy to move to TVET institutes in the neighboring
local levels and also due to easy access to Indian
institutes because of the open border. Similarly, lower
awareness on the importance of TVET may be
another reason since literacy rate of this province
(50%) is lower in comparison to national standard
(65%) (MoEST, 2017).
The 84.32% coverage of local level does not mean
that TVET programs have been accessed to 84.32%
of citizens of the country. This is only a part of the
story. Neither the area nor the population of these
local levels are equal. Moreover, there may be notable
variations of enrolment capacity, population and area
among these local levels. So, institutional access of
TVET in each of these local levels does not count
the same. As per the population census, 2011,
Kathmandu Metropolitan City is the local level with
highest number of population (975,753) whereas the
population of Dolame Rural Municipality of Mustang
District is the lowest with a population of 1,423 only
(CBS, 2011).
The enrolment capacity of TVET programs among
77 districts gives certain indication regarding its
equitable access. As explained in the methodology,
data set 2 incorporates the enrolment capacity of
TVET Programs, population, number of SEE
graduates in 2017, number of economic
establishments, and persons engaged in those
economic establishments by districts. Descriptive
statistics of some of these variables are presented in
Table 2. As per this statistics, the average enrolment
capacity of TVET in district level is 1,272.5. The
higher value of standard deviation (1125) further
suggests that there is large variation of enrolment
capacity among the 77 districts. This status is further
justified by the difference between the minimum
number of enrolment capacity of district (40) and
maximum number of enrolment capacity, which is
7,239. Such types of variation can also be observed
in other variables like, SEE graduates in 2017,
economic establishment and persons engaged in
those economic establishment. (See table 2).
Table 2
Descriptive statistics of variables regarding demand and supply of TVET
SEE graduates in 2017
Enrolment capacity in TVET
programs
Economic establishment
Persons engaged in economic
establishment
Valid N (list-wise)
N
77
77
77
77
77
Minimum
56.00
40.00
87.00
1695.00
Maximum
35581.00
7239.00
125047.00
590002.00
Mean
6192.6234
1272.5584
11991.6364
41928.0130
Std. deviation
5130.38206
1125.16067
15733.03378
71065.81948
Source: Analysis of micro data (data set 2)
21 JTD 5
TVET Programs in Nepal......
Graduates of Secondary Education Examination
(SEE) are the eligible population who can enroll in
long- term TVET programs. In this line of reasoning,
the ratio of enrolment capacity to SEE graduates
helps to generate broader idea regarding the status
of equitable access of TVET programs. So, another
variable was created as “TVET capacity per 100
SEE graduates” in the same data set. Based on the
analysis of this variable, the minimum ratio obtained
from the analysis is 4.49 and maximum is 203.15.
The mean value of this variable is obtained as 23.94
and standard deviation as 22.89. The higher value
of standard deviation and wider gap between the
minimum and maximum value also suggest that the
opportunity to enroll in TVET programs are not
equitable accessed to all parts of the country. Some
parts of the country have higher access to TVET
than others. (See table 2)
Table 3
Descriptive statistics on TVET capacity per 100 SEE Graduates
SEE graduates/TVET enrolment
capacity
Valid N (list-wise)
N
77
77
Minimum
4.49
Maximum
203.15
Mean
23.9409
Std. Deviation
22.89899
Source: Analysis of Microdata (Data set 2)
Chart 2
Distribution of districts by enrolment opportunity in TVET
Source: Analysis of Microdata (Data set 2)
Manoj Sharma Neupane
22 JTD 5
Regarding the equitable access of TVET programs,
we can broadly say that 24 out of 100 SEE graduates
get an opportunity to enroll in TVET programs. The
Chart 2 further shows the distribution of districts as
per the range of enrolment capacity in TVET in
terms of 100 SEE graduates. Of the total 77 districts,
highest proportion 36.4% (N= 28) of districts falls
under the category of having 15 to 20 enrolment
capacity per 100 SEE graduates followed by 20.8%
districts falling under 20 to 25 enrolment capacity,
13% districts have under 10 to15 enrolment capacity
and so on (See chart 2). Moreover, data shows that
almost 80% of the districts have between 10 to 30
SEE graduates enrolment capacity for every 100
SEE graduates in the TVET programs. It is obvious
that the number of SEE graduates in the districts
may not be constant overtime. Slight fluctuation on
the number can be observed over time, so whether
the variation can be acceptable or not is a million
dollar question and requires further analysis. The
analysis of correlation coefficient between TVET
capacity, SEE graduates, and population can provide
answer of that question to some extent.
Table 4
Correlation analysis on TVET Capacity, Population and SEE Graduates
Population
SEE Graduates of 2017
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Enrollment capacity in
TVET programs
.862**
.000
77
.931**
.000
77
Population
1
77
.950**
.000
77
**. Correlation is significant at the 0.01 level (2-tailed).
Source : Analysis of micro data (data set 2)
Table 4 shows the results of correlation analysis
among enrolment capacity on TVET Programs,
Population and Number of SEE graduates together
with other supplementary statistics. As per the data,
there is significant positive correlation between each
of these variables, however the degree of correlation
is highest (.950) between population and SEE
graduates followed by .931 between TVET capacity
and SEE graduates and lowest 0.862 between TVET
capacity and population.
The obtained correlation coefficient broadly suggest
that the enrolment capacity of TVET programs are
evenly distributed to all the district of the country
to some extent. However, there is still sufficient
room to make the distribution more equitable. If the
correlation coefficient between the population and
SEE graduates (.950) is compared with the population
and TVET enrollment capacity (.862), the significant
difference between the obtained correlation
coefficients suggest that the opportunity to technical
education is not as easy as compared to general
education. This factor should also be taken into
account in the expansion of TVET programs in the
future.
Relevancy of TVET Programs
Relevancy is one of the major factors that influences
the effectiveness of TVET programs. However, it is
not always easy to decide whether a program is
relevant or not. Since in our context, 84.6% share is
of informal employment whether it is in formal sector
or informal sector (CBS, 2019b). It is obvious that
none of the survey or census can perfectly capture
the dynamics and dimensions of informal
employment.
Attempt is made to analyze the relevancy of the
TVET programs delivered in the country in broader
scenario. As mentioned in methodology, enrolment
capacity of long-term TVET program, which is
considered as an indication of supply of TVET
programs, is analyzed by the help of micro data set-
1. The TVET capacity is further categorized under
five broader categories of occupational sectors as
(a) Agriculture (b) Engineering (c) Health (d) Tourism
and Hospitality and (e) Other service sectors.
Similarly, the number of economic establishments
and persons engaged in those economic establishment
are the indication of demand since most of the formal
employments are captured by these figures.
According to Nepal Labour Force Survey 2017-18,
7.08 million workers are currently working in the
labour market. Out of them, 4.7 million are in the
sub-sectors which are mainly related with more
technical activities (CBS, 2019b). Eleven out of
twenty-one sub-sectors can be considered to be under
this category, which are agriculture; forestry and
fishing; mining and quarrying; manufacturing;
electricity, gas, steam and air conditioning supply;
water supply; construction; transportation and storage;
accommodation and food service activities; human
health and social service activities and other services.
Likewise, National Economic Census, 2018 has
presented the disaggregated figure of economic
establishments under the same categories (CBS,
2019a). These sub-sectors are again clustered under
five broader headings of occupational sectors like
agriculture, engineering, health, tourism and other
service sector. For this re-categorization, agriculture,
forestry and fishing is categorized as agriculture,
human health and social service activities is
categorized as health sector, accommodation and
food service activity as tourism, and other service
activities as other services. Similarly, the remaining
six subsectors (Mining and quarrying; manufacturing;
electricity, gas, steam and air conditioning supply,
water supply; construction, and transportation and
storage;) are categorized as engineering sector. The
corresponding figures of existing workers from
National Labour Force Survey, 2017-18 and
economic establishments from National Economic
Census, 2018 are subsumed accordingly under these
five broader categories (CBS, 2019). (See table 5)
Table 5
Economic establishments, currently working labour force and Enrolment capacity by sector
SN
1
2
3
4
5
Occupational sector
Agriculture
Engineering
Health
Tourism
Other services
Total
Economic
establishments ¥ Currently working
Labour Force v Enrolment capacity in
TVET programs #
Number
24,229
116,073
19,990
30,540
57,514
348,346
Persons
7.0
33.3
5.7
37.5
16.5
37.7
Persons
1,523,000
2,567,000
171,000
371,000
156,000
4,788,000
%
31.8
53.6
3.6
7.7
3.3
100.0
Cap.
34,124
41,141
21,432
690
600
97,987
%
34.8
42.0
21.9
0.7
0.6
100.0
Sources: ¥ CBS,(2019a); v CBS, (2019b); # Analysis of microdata (data set 1)
Table 5 shows that the Engineering sector occupies
42% share in the total enrolment capacity of TVET
programs, whereas the share of this sector is 33.3%
in terms of economic establishments and 53.3% in
terms of currently working labour force. The former
proportion is the indication of supply side status and
later two proportions indicate the demand side status
of TVET programs. Similarly, in agriculture sector,
the corresponding share is 34.8% of enrollment
capacity of TVET programs (as supply side) and
TVET Programs in Nepal...... 23 JTD 5
24 JTD 5
7.0% and 31.8% of economic establishment and
currently working labour force (as demand sides)
respectively.
Although slight mismatch can be observed between
the supply and demand side proportions in the
agriculture sector, this mismatch is considerable
since data are taken from different sources and are
not perfectly comparable. Similarly in engineering
sector, the average of demand side proportions of
two different sources, which is 43.45% (average of
33.3% and 53.6%) almost matches with supply side
proportions (42%). Based on the analysis, sufficient
evidences are not available to justify the mismatch
between the demand and supply side of TVET in
engineering and agriculture sector.
Unlike Engineering and Agriculture Sector, the
discrepancy between supply and demand side
proportions is found notably higher in health and
tourism sector. In health sector, the proportion of
supply side is found to be (21.9%) whereas the
proportions of the two demand side variables –
currently working labour force and economic
establishments are 3.6% and 5.7% respectively.
Similarly in tourism sector, the proportion of supply
side variable is found to be (0.7%) and the
corresponding demand side variables are 7.7% and
37.5% respectively. Based on these notable
discrepancies observed in the comparison, it can be
concluded that TVET sector is under-capacitated in
terms of tourism related programs whereas health
sector can be taken as over capacitated sector.
Within the demand side data, the significant
discrepancies is found in both thetourism and
agriculture sector of currently working labour force,
and economic establishments. The most probable
reason behind this discrepancy is the variation of
ratio between formal and informal employment.
According to NLFS 2017/18, the ratio between
formal and informal employment in agriculture and
non-agriculture sector are 6:94 and 47:53 respectively
(CBS, 2019a). This ratio further suggests that the
employment in tourism sector is mainly concentrated
in registered enterprises/establishment whereas
majority of agriculture related employment prevails
outside the registered enterprises or establishments.
Relevancy of Provincial Distribution of TVET
Programs
While analyzing the provincial distribution of
enrolment capacity of TVET programs as per these
occupational sectors, the pattern of distribution is
not found to be as expected. Health related programs
are found to be more concentrated in Province No.
1, Province No. 2, Bagmati Province and Lumbini
Province. These four provinces occupy almost 85.4%
of enrolment capacities of health related programs.
If we analyze the distribution pattern separately for
each province, large majority (43%) of programs of
Province No. 1 is related to engineering trade whereas
significant proportion of programs are also related
to agriculture (29%) and health (27%) trade. On the
contrary, 61% programs of Karnali Province is related
to the agriculture trade, 34% are related to the
engineering trade whereas only 5% programs are
related to the health trade (See table 6)
The trade and province wise distribution of enrollment
capacity further supports the aforementioned analysis.
The dominancy of engineering related programs is
found in Province No. 1, Province No 2, Bagmati
Gandaki and Lumbini Provinces which are
comparatively known as industrialized provinces.
Similarly, dominancy of agriculture related programs
is found in less industrialized provinces like Karnali
and Sudurpaschim Provinces, which are
comparatively known as agriculture based provinces.
The programs under health sector are found relatively
in lower proportion in Karnali and Sudurpaschim
Provinces. While analyzing the distribution patter
of trade and programs by province, it seems rational
on the basis of the economic activities of the
provinces.
Manoj Sharma Neupane
TVET Programs in Nepal......
Table 6
Trade wise and province wise enrolment capacity
SN
1
2
3
4
5
6
7
Province
Province No 1
Province No 2
Bagmati Province
Gandaki Province
Lumbani Province
Karnali Province
Sudurpaschim Province
Total
Agriculture Engineering Health Tourism Others Total
Cap.
13610
13022
23453
9112
17370
9336
12084
97987
Source: Analysis of micro data (data set 1)
Cap.
4000
2600
5640
3680
5844
5680
6680
34124
%
29
20
24
40
34
61
55
35
Cap.
5840
7272
9401
3632
7626
3216
4154
41141
%
43
56
40
40
44
34
34
42
Cap.
3650
3070
7852
1550
3740
440
1130
21432
%
27
24
33
17
22
5
9
22
Cap.
40
40
360
170
40
40
690
%
0.3
0.3
1.5
1.9
0.2
0.0
0.3
0.7
Cap.
80
40
200
80
120
80
600
%
0.6
0.3
0.9
0.9
0.7
0.0
0.7
0.6
Relationship between Demand and Supply
Attempt was made to analyze the relationship
between enrolment capacity of TVET programs with
other demand side variables - number of economic
establishments and persons engaged in those
economic establishment with the help of data set-2.
Significant positive correlations are found in both
case while running correlation analysis. The obtained
correlation coefficient 0.866 between TVET
enrolment capacity and economic establishment and
0.824 between TVET enrolment capacity and persons
engaged in those economic establishment is found
statistically significant at 0.01 level (See table 7).
These correlation coefficients suggest strong positive
correlation between the demand and supply of TVET
programs. However, they are not close to perfectly
correlation. These correlations are found to be weaker
than the correlation between enrolment capacity and
number of SEE graduates (0.931) (see table 7). This
comparison further suggest that the enrolment
capacity of TVET programs are more influenced by
supply of students (Number of SEE graduates) rather
than the demand of market (Establishment and
employment).
Table 7
Correlation coefficients between demand and supply side indicators
Economic
establishments Persons engaged in
economic establishments
Enrolment
Capacity of TVET Pearson Correlation
Sig. (2-tailed)
N
.866**
.000
77
.824**
.000
77
**. Correlation is significant at the 0.01 level (2-tailed).
Source: Analysis of micro data (data Set 2)
Productivity of Workers
According to Nepal Labour Force Survey 2017-18,
the average monthly income of the current working
labour is NRs. 17,809 and considerable variation of
income is found between informality (formal &
informal) and sectors (agriculture-non agriculture)
(CBS, 2019b). The average income of an individual
who are engaged in formal employment in the
agriculture sector earns NRs 14,197 per month
whereas the corresponding income of an individual
engaged in informal employment is NRs. 12,055.
Unlike the considerable variation in agriculture
25 JTD 5
26 JTD 5
sector, average income is found to be almost similar
between informal and formal non agriculture sector.
A person engaged in formal employment of non-
agriculture sector earns (NRs. 18,942) almost same
amount as those engaged in informal employment
of non-agriculture sector (Rs.18,984) (CBS, 2019b).
Table 8
Monthly earning by occupational sector
The income level of existing worker in five major
trade is presented in table 8. The income data was
deducted by the same approach adopted as to generate
table 4. Non-agriculture sector is justified as more
productive sector than agriculture since comparatively
productive workforces are engaged in this sector
and relatively more advanced technologies are used.
Comparatively, among the non-agriculture sector,
more skilled and productive workforce are found in
the health sector since the average income of person
engaged in this sector is highest (NRs. 22,288) among
the five sectors (See table 8). Similarly, other service
sectors and engineering sector is also justified as
productive sector. On the contrary, agriculture and
tourism are the sectors in which productivity of
workers are found to be relatively lower.
According to human capital theory, the income
variation among individuals is the factor of their
investment in human capital. This means persons
who invest more on education and skills have higher
labour market outcome than those who invest less
(Baker, 1962). Although some other factors (e.g.
technological exploration, labour organization,
uniqueness of occupation and wage trend) also
slightly influence the income of individuals (Hasan,
2013), human capital components like skills and
knowledge are the major determinants of individuals’
income. These facts helps to conclude that TVET
related investment in agriculture and tourism is found
to be comparatively lower than others sectors of the
economy. From the productivity point of view, it
could be suggested that TVET programs or
interventions are more required in tourism and
agriculture trades to enhance overall productivity of
country. Tourism and agriculture should therefore
be the needy sector to carry out skill development
activities in the future.
Conclusion
TVET sector of Nepal has achieved remarkable
progress by expand the TVET institutes and programs
after the establishment of CTEVT in 1989. The
annual rate of expansion of TVET institutes since
that date is observed as 43.34%. Moreover,
institutional access of TVET has been expanded to
83.4% of the local level till date. Although expansion
of TVET institutes and program is necessary to
increase the access of TVET Programs, but it is not
sufficient in itself. Equitable access of TVET
programs is crucial to get desired outcomes and
sufficient attention should be paid to make the
expansion equitable in every nook and corner of the
country.
Twenty three out of hundred SEE graduates get the
opportunity to be enrolled in the TVET programs in
the present context of Nepal, however this
opportunity is not found to be fairly distributed to
every parts of the country. This opportunity is limited
to less than 15 for some 15 particular districts but is
higher than 30 for another 12 districts. Proper
attention should therefore be paid towards the
distribution of TVET programs equitably to all parts
of the country.
The most challenging issue of the present TVET
system is to mitigate the mismatch between presently
available training programs and the need of the
labour market. Broadly speaking, health related
programs are justified as over accessed programs
SN
1
2
3
4
5
Sector
Agriculture
Engineering
Health
Tourism
Other service sector
Average
Average income
12,185
17,125
22,411
12,288
19,406
17,809
Source: CBS, (2019b) (Nepal Labour Force Survey, 2017-
18
Manoj Sharma Neupane
TVET Programs in Nepal...... 27 JTD 5
based on the analysis made in this paper whereas
agriculture and tourism sectors are facing scarcity
of skilled human resources as per the actual
requirement. Moreover, tourism sector is revealed
as a completely neglected sector in the aspect of
skilled human resource development. On one hand,
delivery of tourism related programs seems in the
least priority of the TVET sector. On the other hand,
the productivity of workers engaged in this sector
is absolutely low. The lower productivity of workforce
working in tourism and agriculture sectors further
suggest higher need of skills training for the workers
currently working in these sectors.
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