‘Work-study’, Internship and Educational Mismatch among Youths: Evidence from Zambia

RESEARCH PROPOSAL Presented to

Partnership for Economic Policy (PEP)

By

CHITALU MIRIAM CHAMA-CHILIBA

HILARY CHILALA HAZELE

MWIIMBA CHEWE

KELVIN CHILESHE

ZAMBIA

May 2018

SECTION I – PROJECT OVERVIEW & OBJECTIVES

1.1. Abstract (max 100 to 250 words)

In this paper, we seek to estimate the effect of working while studying in college and

university and internships on educational mismatch in the Zambian labour market using an

instrumental variable approach. We broadly define ‘work-study’ experience as pre-

graduation exposure to a working environment during college or university study. The study

will use two rounds of the School to Work Transition Surveys conducted by the ILO in 2012

and 2014. We will estimate a range of ordered probit regression models taking into account

self-selection and sample-selection bias to assess the effects of ‘work-study’ and internship

experience on educational mismatch among the employed youths. We also examine the

heterogeneous effects of ‘work-study and internship experience on educational mismatch

due to gender. The data allows us to generate objective, empirical and subjective

measures of educational mismatch. Rigorous evidence showing the causal relationship

between ‘work-study’ and internship experience and educational mismatch is important for

the creation of effective strategies for enhancing youth employability in developing

countries.

1.2. Main research questions and contributions (max 500 to 700 words)

Youth unemployment even among the educated youths in developing countries is

particularly high (World Bank, 2014). A key challenge faced by youths is that employers often

require work experience, which is impossible to get without being hired. Experience in the

job market, particularly in the form of internships and apprenticeships has the potential to

provide students with a smooth school to work transition by allowing them to acquire

specific labour market skills as well as guidance in terms of career goals and aspirations

(Brooks, et al., 1995). The basic benefits associated with internships are related to the career,

job and job market or networking (Maertz, et al., 2014). Interns gain career related benefits

by having a realistic view of their future profession, developing a better understanding of

their abilities and preferences, and assessing their fit within an industry (Burke & Carton,

2013). More broadly, student’s exposure to work enables them to align their career interests

with their goals at a much earlier stage in life, promoting career planning and alignment

(Maertz, et al., 2014). Indeed, internships and pre-graduation work experience can link

graduates to professional networks or enhance these relationships, which ultimately

improves the quality of the match between the graduates and employers (Holford, 2017).

In Zambia, the government recognises that a mismatch exists in the skills offered by training

institutions and those demanded by the industry and is committed to eliminating this gap

through supporting apprenticeships/internship programs, as stipulated in the 7th National

Development Plan 2017-2021 (7NDP) ( MNDP, 2017). With such internship programs, it is

expected that students will develop relevant skills for work, which are general and

transferable (Busby, 2003). Although about 55% of the employed youths in Zambia have jobs

that match their level of education, a substantial share (26%) is overeducated for the

positions that they hold (Chingunta et al., 2013). The mismatch between level of education

and type of job results in youths not contributing to their full productive potential. More so,

the lower positions taken up by more educated youths tend to crowd out the youths with

lower qualifications that match the positions. Despite the growing evidence on the role of

internships and working while studying on labour market outcomes in the developed

countries (Holford, 2017; Saniter and Siedler, 2014; Jewell, 2014), there has been little work

done in the developing country context. With the gradual increases in the supply of college

and university graduates and low absorption rate in the labour market, youths tend to take

up jobs for which they are more than qualified (Chigunta et al., 2013).

This study seeks to examine the causal effect of working while studying and internships on

educational mismatch in Zambia. Formally, educational mismatch is defined as the gap

between the educational level of an individual and the occupational position that he or

she holds. Educational mismatch is also referred to as vertical mismatch and is often

classified as over education (educational qualifications are higher than those required at

the job), under education (educational qualifications are lower than those required at the

job) and matched for the type of job (Sloan, 2014, Proctor and Dutta, 1995).

To the best of the authors’ knowledge, this will be the first paper in Zambia to examine the

causal relationship between pre-graduation work experience including internships and

educational mismatch. The study intends to control for sample-selection bias into

employment for the (mis) matched youths and self-selection into pre-graduation work. In

the literature, differences in labour market outcomes, based on gender have been

observed (Croson and Gneezy, 2009; Blau et al., 2000). For instance, it has been found that

women are generally more risk averse than men, and such gender differences in

preferences partly explains the differences in labour force participation rates. Similar to

Saniter and Siedler (2014), the study will also examine the heterogeneous effects of pre-

graduation work experience on educational mismatch due to gender. The analysis

proposes to use two rounds of the School to Work Transition Surveys conducted in 2012 and

2014. This evidence is key as the country implements the various programs in support of

internships and apprenticeships as part of the 7NDP strategies in Zambia. Rigorous evidence

is important for the creation of effective strategies for enhancing youth employability.

A historical Perspective of Youth Unemployment and Educational Mismatch In Zambia

The problem of unemployment in Zambia started escalating in the 1990s during the

economic restructuring program, which was accompanied by employee retrenchments as

the job market shrunk considerably (Nyirenda and Shikwe, 2003). The Zambian economy

continued in its depressed state for most of the decade and this resulted in an increase in

the informal sector as retrenchees sought survival means. At the same time, it continuously

became more difficult for young people entering the labour market to find employment.

By the turn of the decade, the economy began to perform much better, largely due to

private sector participation and upswing of copper metal prices, the mainstay of the

Zambian economy. However, the dominance of the private sector and profit-seeking

motive, meant entry into the job market was stricter with emphasis on skilled labour. At the

same time, the employers required instant employee productivity, thus opting to recruit self-

starter and individuals with some form of work experience. More so, increased private sector

participation in the economy led to rapid advancement of production technology, way

ahead of the training institutions’ adaptation of the technology in training. This

technological gap began to create a mismatch between the type of skills set and

qualifications required by industry and those being imparted in the trainees. Chigunta, et

al., (2013) finds that the education and skills mismatch in Zambia continues to greatly

contribute to youth unemployment and long job searching periods even among young

university and college graduates.

In Zambia, youth unemployment rates are 5 times higher than for adults (ZIPAR, 2015). The

youth aged 15-19 having the highest unemployment rate at 17.1 percent , 13.8 percent for

20 - 24 years, 9 percent for 25 -29 years, and 5.7 percent for 30 - 34 year compared to the

national average of 7.4 percent (Central Statistics Office, 2014 LFS). More so, youth aged 15

to 24 are more likely to be unemployed than fellow youths of 25 to 34 year (Bhorat et al.,

2015). In Zambia, employers argue that there is skills mismatch between what they require

in their workforce and what training institutions are imparting in would be workers graduating

from both universities and colleges, including Technical Education, Vocational and

Entrepreneur Training (TEVET) colleges. The deficiency is partly due to skills and education

mismatch coupled with lack of experience. To this effect, employers often use years of

experience as a proxy for someone having employable skills necessary for quick adaptation

and productivity. Bhorat et.al (2015) and Chingunta et al., (2013) also note that the

education and skills gap needs to be addressed in order to remedy the growing youth

unemployment and recognise the gap in rigorous evidence around identifying the

mechanisms to bridge the gap.

In response to recommendations made to develop labour market mechanisms or programs

that would address the gaps in education and skills between the labour market and training

institutions output, the Government of Zambia has over the years developed and planned

various interventions. The National Youth Employment and Job Creation Strategy provided

for in the 2013 national budget, was meant to provide instruments for addressing challenges

of youth employment and empowerment, including skills gap. Two years later, a National

Youth Policy 2015 was launched with an accompanying Action Plan for Youth

Empowerment and Employment, as an implementation tool for the policy. The action plan

had a distinct focus area to address the issues of mismatch (the focus area 2, Capacitating

Youths). This focus area had various themes including skills development and employability,

which then had various strategies. One of the key strategy was developing a national skills

development plan and designing and implementing programs that improve employability

of youths. Central to this was promotion of apprenticeships, internships, attachments and

mentorship programs. Government’s commitment to eliminating skills gap is magnified

through the inclusion of a development outcome dedicated to education and skills

development, outcome number two under enhancing human development in the 7th

National Development Plan (7NDP). The 7NDP education and skills outcome stipulates

various strategies, which are linked to supporting the development of skills at national level,

including emphasis on private sector or industry participation in the training system (Ministry

of National Planning, 2017).

Furthermore, various stakeholders have over the last three to four years been working on

developing the national skills development program. In 2015, various stakeholders that

included Employers, Workers, ILO, Ministry of Labour, Ministry of Higher Education, TEVETA

and others, signed a Memorandum of Understanding (MOU) committing to finding a

solution to skills development in the country and to address skills gap. Key stakeholders

formulated a task team, which identified apprenticeships and internships as a way to

develop skills. In 2017, a National Work based Learning Framework to help with operations

of the apprenticeships and internships while the legislation was finalised and modalities of

how to operationalise it are still under discussion. This study would not only be insightful for

the policy makers and stakeholders to understand the relationship of these programs and

skills mismatch but would be very timely as the country sets to embark on rolling out these

programs under the comprehensive National Skills Development Framework. As such, the

study seeks to investigate the effect of youth participation in an internship or work while

studying and being employed in a job for which they are vertically matched (or

unmatched).

SECTION III – RESEARCH 3.1. Literature review (max 1000 to 1500 words)

Work-based experience or working while studying offers students an opportunity to gain

additional human capital such as skills and experience that could have a bearing on future

labour market outcomes (Ruhm, 1997). Similarly, internships provide invaluable labor market

skills and on the job training to students while signaling to prospective employers about the

quality or ability of the potential employees (Holford, 2017, Saniter and Siedler, 2014). An

internship can be broadly defined as an employment opportunity offered by an employer

to potential employees to work at a firm or organization for a fixed, limited period of time.

Internships can be paid or unpaid, part-time or full time and undertaken during study or

post-graduation ((Frenette, 2013: Heyler and Lee, 2014)). In essence, internships tend to help

prepare youths with necessary skills to thrive in the job market, this could result in better skills

matching for a given occupation (Hora and Thompson, 2017). The study focuses on

analysing the effects of engaging in pre-graduation work and internships on educational or

vertical skills mismatch.

The theoretical relationship between educational mismatch and work experience while

studying can be best explained using the human capital, screening and signaling theories.

The human capital theory postulates that internships increase the skill level of the employee

and thus lead to higher chances of getting employed and earning higher wages (Mincer

(1975), Becker, (1975)). Internships lead to a rise in specific human capital skills, which are

likely to enable interns to find a job for which they are both horizontally and vertically

matched (Simon and Warner (1992): Negrut et al, (2015); WEF, 2014). This is because

internships provide hands-on work experience that not only reduces skill gaps but also

facilitates training relevant to labour market demand (WEF, 2014).

Screening theory also provides useful insight into the relationship between skills mismatch

and internships. Internships can function as a screening device for employers to determine

the interns best suited for particular positions (Stiglitz, 1975). They also reduce selection and

allocation costs, while also enabling the firms to provide firm-specific training to prospective

employees (Wolbers, 2003). Once individuals that are eligible have been identified, they

would then be assigned to a job for which they are matched after they graduate. That is,

having access to temporary employment in a firm or establishment increases the chances

that an individual will have access to employment that fits their training both in terms of field

and level of education (Wolbers, 2003).

Signalling theory as developed by Spence (1973) might also provide some insight into the

relationship between skills mismatch and internships. A major concern with recent

graduates and school leavers is that they do not have the relevant experience to apply for

and acquire the jobs for which they are trained (IYF, 2013). Additionally, for higher levels of

education, credentialism theory questions whether postsecondary education provides the

necessary skills used in employment. The theory asserts that skills are largely acquired on the

job, and employers see education only as a predictor of the future productivity and

trainability of employees (Boudarbat and Chernoff, 2009). Therefore, the combination of

academic and practical skills might signal higher ability and potential productivity to

prospective employers thus making it more likely that an individual will get a job for which

they are vertically matched.

Most studies in empirical literatre have been done in a developing country context and

focus on labour market outcomes such as job satisfaction, future wages and employability

(Saout and Coudin, 2015; Withanawasam and Lalaine, 2012; Samman and Fakhro, 2017).

However, very few studies have examined the relationship between working while studying

or internships and job match (Jewell, 2014; Saniter and Sieldler, 2014), particularly in the

developing country context. The existing evidence suggests that internships enhance

students’ job and social skills and aid their career path decisions. In a study to determine the

wage outcomes resulting from mandatory internships in Germany, Saniter and Siedler (2014)

found that doing an internship had a positive and significant impact on wage returns. The

study however found little evidence that internships improved job matching or had an

impact on graduates’ occupational choices. Similarly, studies by Saout and Coudin (2015),

Withanawasam and Lalaine (2012) and Samman and Fakhro (2017) found that internships

enabled students to find work faster in France, Sri Lanka and Bahrain respectively. Di Paolo

and Matano (2016) find that job quality was improved by pre-graduation work experience

in the field of study for students in the Spanish region of Catalonia. However, Wolbers (2003)

finds that individuals that acquire specific human capital in the form of school or work-based

vocational training are less likely to end up in an unmatched job.

Some studies find that participating in an internship during study reduces the time spent

looking for employment (Vélez and Giner (2015); Saout and Coudin (2015), Withanawasam

and Lalaine (2012); Samman and Fakhro (2017). Cameroon et al., (2013) find that work

integrated learning in Economics, which incorporates formal learning and workplace

experience, had a positive effect on labour market outcomes. Similarly, Weiss et. al (2014)

find that only field related and voluntary work experience had positive effects on labour

market integration in Germany. However, not all studies find a positive relationship between

internships and temporary work and employment outcomes. Using German data, Harms

(2017) finds that internships have negative transitory effects, which die out within five years

of entering the job market. Similarly, Klein and Weiss (2011) found no evidence that

compulsory internships in Germany had a positive impact on wages, employment history

complexity and duration before first significant job. The authors find that internships did not

alleviate disadvantages in labour market integration for graduates from lower education

backgrounds. Despite these findings, there is still a lot of advocacy and support by

universities in developed countries for policies and interventions aimed at providing

internships for students (Teichler, 2011).

Importantly, individual labour supply characteristics are correlated with other factors such

as ability and motivation, which also affect the labour outcomes. For instance, unemployed

youth are different from the employed in observable characteristics such as education, and

unobservable characteristics such as ability, motivation and eagerness to find a job. Studies

in literature have proposed various approaches to deal with the differences in observable

characteristics (propensity score matching or coarsened exact matching), other

approaches have use instrumental variables to deal sample selection bias ( Ghignomi and

Veraschchagina, 2014; Kim and Park, 20 16).

Although there is vast evidence relating to pre-graduation work experience, internships and

educational mismatch from developed countries, there is a paucity of literature in the

developing country context, especially in Sub Saharan Africa. In most developing countries,

the labor force is engaged in the informal sector and it remains unclear to what extent

working while studying and internships will influence educational mismatch in such a

context. In this study, we will examine the effect of the pre-graduation work experience

and internship experience on the educational mismatch in Zambia, using a unique survey

that collected data among the youths aged 15 to 29 in 2012 and 2014. We account for

self-selection and sample-selection bias using instrumental variables in a structural equation

framework (Roodman, 2011).

3.2. Methodology (max 1200 to 1600 words)

The analytical approach for examining the casual effect of internship on educational

mismatch is based on a structure, which assumes that a youth is either employed or

unemployed. In the next stage, educational mismatch is then determined for the employed

youth based on three categories as: overeducated, undereducated and matched.

Intuitively, the modelling approach is sequential: the first stage is a binary model for

employment and the second stage categorical model for the educational mismatch. The

fact that educational mismatch is observed only for the employed sample, leads to a

sample selection bias given the non-random allocation of the sample (Cameroon and

Trivedi, 2005). The unemployed youth may be different from the employed youth in

observable characteristics such as education. More so, employment status is correlated

with other unobservable factors such as ability, motivation and eagerness to find a job,

which also affect the employment status. As such, this proposed specification potentially

implies a selection bias due to the exclusion of the unemployed sample. Further, there is a

bias generated by the endogeneity or self-selection of youths in undertaking internships or

working while studying.

In examining the effect of causal effect of participation in pre-graduation work on

educational mismatch, three important econometric issues need to be dealt with: 1) the

sample selection bias given that educational mismatch is not observed for the entire

sample; 2) endogeneity given that the motivated youth may decide to take up internships;

3) the nature of the ordered categorical nature of the dependent variable. Given that the

dependent variable takes the form of an ordered categorical variable, it can modelled

using an ordered probit or logit (Long, 1997). Secondly, there is potential endogeneity for

the decision to take up pre-graduation work, as more able and motivated students can do

so. This ability or motivation is not fully observed through survey data and analysis that

examines the relationship between internships and educational mismatch, without

accounting for such missing variables, do suffer from selection bias. In equation (1), we

specify working while studying (𝑊𝑜𝑟𝑘_𝑆), which encompasses various forms of work that the

youth is engaged in during college/university and equation (2) focuses only on participation

in mandatory internships (𝑁𝑇) undertaken as part of the study program requirements:

𝑀𝐼𝑆, = 𝛽/𝑊𝑜𝑟𝑘_𝑆, + 𝛽1𝑋, + 𝛽3𝜆, + 𝜀,(1)

𝑀𝐼𝑆, = 𝛽/𝐼𝑁𝑇, + 𝛽1𝑋, + 𝛽3𝜆, + 𝜀,(2)

Where 𝑀𝐼𝑆, represents the ordered categorical outcome of interest, educational mismatch

coded as 0 for the undereducated youth, 1 for the exactly matched youth and 2 for the

over educated youth. This categorisation of the dependent variable justifies the use of the

ordered probit regression. 𝐼𝑁𝑇, is a dummy variable for internship and 𝑊𝑜𝑟𝑘_𝑆, is a dummy

variable for working while studying, while 𝛽/ and 𝛽1 measures the effect of internships and

working while studying on educational mismatch, respectively; 𝑋, is a vector of control

variables, which includes the constant term and 𝛽1 is the corresponding parameter vector

and 𝜀, is the random error term.

Given that internship and working while studying are endogenous to educational mismatch,

we use an instrumental variable to address the selection problem. Similar to Saniter and

Siedler (2014), we propose to use instrumental variable techniques to identify the causal

effect of internships on educational mismatch among the youth in Zambia. We use the

poverty status of the neighbourhood, proxied by the enumeration area, as an instrument for

pre-graduation work. The poverty headcount estimates are obtained from the subnational

poverty mapping undertaken in 2015 (CSO and Worldbank, 2015). Poverty deprivation of

the districts, will determine whether the individuals resides in an environment where they can

get access to work and internships. The poverty incidence is expected to be negatively

correlated to with access to work while studying. Another possible exclusion restriction is the

number of children that a youth has, which is related to the educational mismatch, only

through internships. It can be argued that the number of children that one has can directly

influence the decision to engage in work while studying but not necessarily influence the

job match. However, this argument may only hold for women and possibly suggests that the

instrument could be weak.

To deal with the selection bias generated by excluding the unemployed youths from the

sample and self-selection into pre-graduation work, we will model the ordered probit

equations using two recursive equations with the “cmp” package in STATA , an approach

similar to the Heckman procedure (Roodman, 2010). The study will consider different models

including: 1) ordered probit to be estimated with and without controls; 2) instrumental

variables ordered probit estimated with and without controls; 3) separate models for males

and females with and without controls.

In literature, there are three main alternative approaches to measuring the education

mismatch: 1) the objective method compares the required level and type of employment

with the actual education obtained by an individual 2) the subjective method compares

the workers own assessment of the level of education required with the actual level of

education acquired and 3) the empirical method compares either the mean or modal

educational level of all individuals in that occupation to the actual education level.

We propose to use the objective and empirical method to determine the level of

educational mismatch. In the objective method, we use the ISCO occupational group

classification by education level, the actual education level attained and the actual

occupation category to generate three mismatch categories for the employed youth. An

employed youth is classified as overeducated if the actual occupational position requires

a lower educational level, matched if the occupational position requires the same

educational levels and undereducated if the position requires higher education levels.

Alternatively, the empirical approach, which uses the distribution of schooling in a given

occupation, requires that the mode or mean within a group is compared to the individuals

schooling level. As such, an individual with the schooling level more than one standard

deviation above the mean is defined as overeducated and one standard deviation below

as undereducated. For the empirical approach, we use the mode as it is less sensitive to the

outliers and often provides a more accurate measure of the educational gap (Mendes de

Oliveira et al., (2000). We generate a dependent variable coded as 1 representing under

education, if the highest level of education attained, measured in categories, is lower than

the mode. Matched education is coded as 2, when the level of education attained is the

same as the mode, and overeducation is coded as 3, for the level of education that is higher

than the modal education of all individuals within the occupation category. The other

choice is the subjective criteria, which is constructed based on the self- reported evaluation

by the respondents about how they perceive themselves in the work place. Similar to

Davalos et al., (2016) and Ghignoni and Veraschagina (2011), we will focus on using the

objective and empirical methods due to the limitations of subjective data.

3.3. Data requirements and sources (max 400 to 700 words)

The analysis will be based on two rounds of the School To Work Transition Survey (SWTS). The two

rounds of the SWTS data were designed by ILO Work4Youth project and implemented by Ipsos in

the late 2012 and 2014. These unique nationally representative surveys provide in-depth cross-

sectional data of the youth population aged 15 to 29 that may not be available in the Labour

Force Surveys. The SWTS contains five modules with detailed information on the following: personal,

family and household information; the formal education/training and aspirations; activity history;

and specific sections for the young workers and non-working youth.

The 2012 and 2014 SWTS used the sampling frame of the 2010 census conducted by the Central

Statistical Office in Zambia. In each survey, a multistage cluster sampling technique was used,

where the sampling unit was a cluster or standard enumeration area. The clusters numbers in each

of the 10 provinces in Zambia were sampled proportional to the total youth aged 15-29 in the

province. The total number of youths per province was calculated using the 2010 census single

age projections.

The 2014 SWTS included a sample of 3225 youths aged 15-29 and the 2012 survey included 3206

respondents. The surveys are nationally representative. In our analysis, we use sample weights

available in the datasets for each survey year to account for possible biases. The key variables of

interest are constructed based on the following questions from the survey: Work_study; Did you

ever work while you studied?: Internship; “Did you have 1 (or more) internship(s)/apprenticeship(s)

with an employer as part of your education”.

In general, the proportion of males employed (56% in 2012 and 58% in 2014) is higher than that of

females (44% in 2012 and 42% in 2014). Some reasons for the gender gap include access to

education and other socio-economic barriers to female employment. Interestingly, there are

variations in proportion of youths employed by region of residence in 2012 and 2014. There is a

higher proportion of youths working in the urban areas (58%) compared to the rural areas (41%) in

2012 while the reverse is true for 2014, with 62% employed in rural areas and only 38% in urban

areas. In Figure 1 and 2, we present the educational mismatch among the employed youth using

the objective and empirical method, respectively. A detailed description of the variables to be

included in the analysis is presented in Table 1 and preliminary results using the 2014 STWTS are

presented in Table 2.

Figure 1: Educational mismatch among the employed youth using the ISCO educational

categories

Figure 2: Comparison of educational mismatch among the employed youth using the modal education level for occupation categories, 2012 and 2014

30.01

38.51

31.4833.47

40.19

26.34

0

5

10

15

20

25

30

35

40

45

Undereducated' Matched' Overeducated'

2012 2014

19.04

44.38

36.58

20.68

37.4641.86

05101520253035404550

Undereducated' Matched' Overeducated'

2012 2014

Table 1: Description of the variables

Variable Description Employment Status Dummy variable coded as 1 if youth is employed and 0 otherwise Educational mismatch for employed youth

Variable coded as 1, undereducated, if the actual educational level is below the modal education category for the occupation based on the ISCO classification, coded as 2 if the education level is an exact match and coded as 3 if the education level is higher than the modal education level in the ISCO occupational category

Employed Dummy variable coded as 1 if youth is employed, 0 otherwise Gender Dummy variable coded as 1 if youth is male, 0 otherwise age: 15-19 Dummy variable coded as 1 if youth is aged between 15-19 years, 0 otherwise

age: 20-24 Dummy variable coded as 1 if youth is aged between 20-24 years, 0 otherwise

age: 25-29 Dummy variable coded as 1 if youth is aged between 25-29 years, 0 otherwise

Married Dummy variable coded as 1 if youth is married, 0 otherwise Youth Education Primary Dummy variable coded as 1 if youth is attending primary school, 0 otherwise

Secondary Dummy variable coded as 1 if youth is attending secondary school or other skills training, 0 otherwise

Tertiary Dummy variable coded as 1 if youth is attending tertiary school, 0 otherwise Parents Education Continuous variable denoting the highest level of education for both parents Household Financial Situation

Dummy variable coded as 1 respondent comes from a household that is reported to be poor or fairly poor

Region

Variable denoting the 10 regions in the country namely: Central, Copperbelt, Eastern, Luapula, Lusaka, Muchinga, North Western, Northern, Southern and Western. Lusaka province is the reference category

Migrate Dummy variable coded as 1 if youth migrated and 0 otherwise Rural Dummy variable coded as 1 if the youth resides in a rural area and 0 otherwise Instruments Young children Number of children the respondent has

Environment Continuous variable ranging from 0 to 1 indicating the poverty status of the neighbourhood the youth resides in

Variable of interest Work-study 1 if the youth worked while studying in college or university, 0 otherwise

Internship 1 if internship with an employer was a mandatory part of the youths education and 0 otherwise

SECTION IV – POLICY ENGAGEMENT 4.1. Policy relevance

4.1.1. Describe policy context and needs

The research can be justified from a number of fronts. Firstly, in the Labour market there has always been a question of employer demanding a number of years of experience when recruiting, something that has always been viewed by young graduate as unnecessary and discriminating them away from the job market. Employers have on the other hand justified it as a proxy for accessing potential employees with the relevant or requisite skills for the job specifications, which they argue usually lack in fresh graduate. However, there has been to date scanty evidence to establish the extent to which either the claim by young graduates that the ‘years of experience’ blocks them from being employed or the claim by employers that there is a lack of requisite skills among young graduates in Zambia. Although there is a dearth of literature in this field in the Zambian context, there seems to be a consensus that there is a skills mismatch in the country, without full understanding of the extent and nature of the gap. Various stakeholders have been putting their heads together to try and address the mismatch with the Zambia Business in Development Facility brokering a partnership for skills development in July 2016 which was signed under the office of the Secretary to Cabinet. Efforts of the partnership led to the identification of some inadequacies in legislation governing certain aspects of skills development in the country which do not support formation of apprenticeships, internships and attachments for skills enhancement in young professionals. To this end, a program to develop a framework for national skills development has since started under the Ministry of higher education with support from the International Labour Organisation. Findings from this study will provide critical information for operationalisation of the skills development framework that will be developed. Secondly, the Government has long acknowledged the growing problem of youth unemployment in Zambia. Relying largely on international studies pointing out that the problem of unemployment among youths is being fueled by lack of skills, the government has prioritised skills development among youths and for the last few years this has been in the President’s annual address to Parliament but little tangible progress in practice. The 7Th National Development Plan has pointed out skills development as a key priority and the findings of this research will be timely in informing targeting for programs aimed at skills development under the development plan which has just been finalised and is yet to be fully implemented. Thirdly, In 2015, the Ministry of Youth and Sport developed a youth policy seeking to enhance youth empowerment. The policy and its implementation plan recognise that central to success of any empowerment program is skills development. With little understanding of which the gaps are or what are the preferences of the target group in terms of economic activities, most programs have achieved little success. Findings of this research will give direction as to where the gaps are in the skills among the youth and thus help in formulating more efficient and effective empowerment programs. At the same time, the research findings will help identify the preferences among youths in terms of economic involvement and thus help in targeting the empowerment programs to maximise impact.

Fourthly, the Zambian Government at the beginning of 2017 introduced a skills development levy meant to foster skills development in the country. The levy has thus far been surrounded by lack of clarity of direction and purpose. Nine months after the collection of the levy started, its effect or utilisation is yet to manifest. Clearly low understanding of the extent of the skills gap and lack of clear understanding of the priority areas with dare need has contributed to the delays in clarity among stakeholders over the use of the levy. The findings from this study will help point the authorities utilising this fund to the direction that can best be saved by the fund. Identification of which profession, skill set and the preferences by the young persons will help design and redesign skills development policies that will efficiently and effectively utilise the fund thus collected for the benefit of the economy.

4.1.2. Consultations to date

Name of institution/organization #1 Technical Education, Vocational and

Entrepreneurship Training Authority (TEVETA) List the key representative involved in consultations (names and titles/positions)

- Mr. David Chakonta, Director General - Mr. Orphan Hachinene, Director Development Division

Describe main outcomes of consultation – feedback or inputs received Having a mandate to contribute to skills development in the country, TEVETA has in all engagements indicated willingness and openness to any partnerships that add value to skills development in the country. The institution has been tasked to be the administering institution for the newly introduced skills levy and so any further insights into the nature and dynamics of the skills needs and gaps would only add to their better delivering on their mandate. The Director General chairs a task team that has been constituted under Ministry of higher Education for developing of a skills development framework and TEVETA is party to the MoU signed under the office of the Secretary to Cabinet on skills development and thus see great value in the research.

Name of institution/organization #2 Cabinet Office List the key representative involved in consultations (names and titles/positions)

- Mushuma Mulenga, Permanent Secretary- Private Sector Development, Industrialisation and Job Creation

Describe main outcomes of consultation – feedback or inputs received Such a study is welcome because there is a gap in evidence and information around skills mismatch in the country. The survey would be enlightening on what is currently happening empirically. The study would provide basis for evidence based policies by informing processes such as the work based learnership programme currently being drafted. Skills development is key in achieving the aspirations of the seventh national development plan as the plan is anchored on agriculture sector to help diversification, a sector in which skills are very important.

Name of institution/organization #3 Ministry of Higher Education List the key representative involved in consultations (names and titles/positions)

- Succeed Mubanga, Senior Planner

Describe main outcomes of consultation – feedback or inputs received The Ministry always welcomes any efforts to enhance knowledge and understanding of issues concerning skills. Once the MoU on skills development was signed, the Ministry has led the way. Nevertheless, the limitations in existing empirical evidence of the nature and magnitude of skills mismatch or gaps is of concern to them. They have even constituted a task team to look at developing a framework for work based learner ship in a quest to get insights of what would work best. In this regard this study would add to the information for use in formulating evidence based policies and programmes.

4.2. Engagement strategy

4.2.1. Identify target audiences

Identify potential users of your research findings – institutions/organizations that may use your findings to inform, advise or influence policy or other relevant decision-making processes. Please explain why you believe these institutions/organizations are the most important potential users of your research, to inform relevant development/policy decisions.

Name of institution/organization #1 Private Sector Development, Industrialisation and Job Creation

Explain relevance of this user to inform key decisions As a division under Cabinet Office that has been mandated to facilitate private sector development, industrialisation and job creation, the findings on skills gap, youth preferences and other such issues are key inputs into formulating policies and programs that will help achieve their objectives as a division. With the high interest in skills development emanating from the head of state and the resulting interest from the Secretary to Cabinet, the Permanent Secretary for the division in already on board and a ready user of the findings.

Name of institution/organization #2 Ministry of National Development Planning Explain relevance of this user to inform key decisions As the direct overseer of development planning, the Ministry is the custodian of the 7th National Development Plan which has skills as an integral component of achieving set goals.

The ministry is therefore an eager user of the findings. Initial engagement has already been done with Mr. Ndiyoi Muyatwa, Principal Economist Multilateral Development Cooperation who has indicated the survey findings can be a key input into the implementation of the 7NDP

Name of institution/organization #3 Zambia Federation of Employers Explain relevance of this user to inform key decisions As a representative of private sector in the labour and industrial relations sphere, ZFE has a huge influence on labour and other developmental policies. ZFE has a keen interest in skills development as a deliverable to their members who have been complaining of skills mismatch in the country. As a matter of fact the Federation is part of the MoU and has been central to the lobbying and advocating for the national skills development program. In this light, the findings of this research will an extremely useful input to their advocacy. Additionally, the introduction of skills levy has added a dimension of the Federation needing to ensure the levy is efficiently and effectively utilised to the benefit of its members. Again findings from this research will help them in this quest by highlighting where the gaps are that need to be filled thus ensuring better use of the skills levy, which was recently introduced.

4.2.2. Define outreach and engagement strategy

How, from proposal design to the dissemination of your research results, will you consult and communicate with these users to both gather their inputs and keep them informed of your project, in order to increase chances of research uptake?

INCEPTION/ BEGINNING STAGE Key stakeholders will be engaged right at the start of the project to make them aware and get buy in for enhanced collaboration and relevance. For this, a summary of the project detailing rationale, methodology, expected outcomes and link or relevance to policy will be drawn. The initial engagements shall be one on one to encourage full interaction and exchange of ideas to further enrich the project and enhance its relevance.

INTERMEDIATE STAGE

Once preliminary findings are ready, a stakeholders’ workshop will be convened comprising of relevant ministries and policy bodies, civil society organisations, private sector players, media, academia and other policy influencers.

At the same preliminary findings dissemination workshop, names and email addresses for all attendees will be collected and a mailing list will be created for continuous communication throughout the research and for update and feedback. This will ensuring that there is constant interaction at every stage of the research with the target users and stakeholders to enhance relevance.

At the same time, the advent of social media such as WhatsApp will not be forgotten for certain groups of stakeholders needed for urgent and regular engagement. The social media such as Facebook and Twitter together with some electronic and print media will be used to generate awareness of the project, disseminate some of the relevant preliminary findings and also solicit for feedback on the project from the wider populace.

FINAL STAGE Once the final results are ready, there will be a final dissemination workshop with all relevant stakeholders. In addition, advocacy and policy pressure groups will be engaged and assisted to develop policy briefs and advocacy papers using the main findings of the research which they can use in lobbying and advocating. The resulting policy briefs will also be distributed among relevant government ministries, appropriate international development partners and the media.

In addition to these efforts for policy influence, there will be efforts to have the research findings peer reviewed for possible publication and further sharing with both local and international audiences.

4.2.3. Outline your preliminary dissemination strategy Outline your preliminary dissemination strategy (channels, tools, events, audiences, etc.). Note that PEP expects grantees to disseminate information about their research work and (expected) outcomes throughout the project cycle, and not only after publication.

For preliminary engagement or dissemination, the primary targets will be the relevant ministries and other policy bodies involved in skills development, as well as advocacy and lobbying bodies such as the Federation of Employers. In terms of policy bodies, the primary target will be Technical Education, Vocational and Entrepreneurship Training Authority (TEVETA), Higher education Authority (HEA), Ministry of Higher Education, Ministry of Labour, Ministry of Youth and Sport, Ministry of National Development Planning, and Private Sector Development, industrialisation and Job creation unity of Cabinet Office. On the other hand, Zambia Federation of Employers (ZFA), Sector Associations, Zambia Congress of Trade Unions (ZCTU), Zambia Institute for Policy Analysis and Research (ZIPAR), and other civil society organisations will be

targeted. The major channels for engagement will be one on one meetings with the concerned institutions for detailed explanation of the research and in-depth idea exchange. At the same time, there is the skills development task team meetings that will be used to engage about the research. TV and Radio will also be used and channels for dissemination.

SECTION V – OTHER CONSIDERATIONS 5.1. Describe any ethical, social, gender or environmental issues or risks that should

be noted in relation to your proposed research project.

There are no associated ethical, social, gender or environmental issues or risks associated with this project as the study will use existing secondary data

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