Demand-side Constraints to Youth Employment in Zambia : Evidence from the Third Enterprise Survey Follow Up Round EVIDENCE FROM THE THIRD ENTERPRISE SURVEY FOLLOW UP ROUND MARIA GABRIELA FARFAN BETRAN 1 Introduction and Context Introduction: What are the key demand-side constraints to youth employment in the formal sector in Zambia? This note seeks to answer this question by providing evidence from a recent follow-up round of data from the Zambia Enterprise Survey (ES). Around 375 000 young people expected to enter the Zambian labor force per year by 20301 (Merotto 2017). Historically, however, only around 137 000 productive jobs have been created annually,2 meaning that the scale of youth unemployment will become an increasing problem unless there are bold steps taken to address it. While there is a great deal of evidence on the supply-side constraints to youth employment in Zambia (see for example Bhorat et al. 2015; Koyi et al. 2012; Ali and Jabeen 2016), there is far less known about what the main reasons are for why formal sector firms in urban areas do not employ more youth. We use data from a module on youth employment that was included as a special topic in the third follow-up round of the Zambia ES. This data covers around 600 formal sector firms which have been part of a longitudinal study which began before the start of the COVID-19 and has run through 2020 and 2021. The international literature on demand-side constraints to youth employment yields several stylized facts about the what the most salient barriers generally are. These include, but not limited to, financial constraints; lack of skills; low education; mismatch of skills to jobs; and coordination failures with respect to youth jobs programming (Figure 1). Figure 1: Concept map: Demand-side constraints for youth employment (Kluve et al. 2016) Demand-side constraints of youth employment (Informal and formal enterprises/firms/farms with current or future jobs) Insufficient access to FINANCE: high costs of financing, lack of suitable collateral; lack of national government coordination on a youth jobs program (of which fiscal incentives is one part) CAPACITY AND INFORMATION GAPS: Lack of financial/business/managerial skills, lack of information on market opportunities and existing skills in the market SKILLS AND QUALIFICATION: skills and wage expectation mismatches; qualifications earned are not commensurate with the demands of industry; employers unwilling to take on risk of hiring someone with little experience COORDINATION failures and learning spillovers; lack of quality standards LIMITED MARKET ACCESS AND STRINGENT MARKET REGULATIONS: lack of access to value chains 1 As per UN’s mid-range population projections (Merotto 2017) 2 For the time period (2008-2012) (Harasty et al. 2015; Ina-Marlene Ruthenberg 2017) The rest of this report proceeds as follows. Section 2 presents a broad overview of the literature on demand-side constraints in sub-Saharan Africa in general, while Section 3 does the same for Zambia in particular. Section 4 describes the dataset used in the analysis and provides some descriptive statistics of key variables. Section 5 presents the main descriptive results of the analysis, and Section 6 presents some concluding remarks and reflects on policy options. 2 Youth Unemployment and Demand-side constraints in Sub-Saharan Africa Youth unemployment is a pressing issue in Sub-Saharan Africa (SSA). By 2100, almost half of the world’s youth population will live in Africa. These youth will be entering labor market in increasing numbers, putting intense pressure on already burdened systems. Presently in SSA, 10 to 12 million youth enter the workforce each year, but only 3.1 million jobs are created, leaving vast numbers of youth unemployed.3 Similarly, atleast 375,000 young people on average are entering the Zambian labor force each year to 2030 (Merotto 2017), but historically only around a third of the mandatory productive jobs have been created annually. Whether these young people will be able to successfully join the labor market will have ramifications not only for their individual wellbeing but also for the welfare of broader society across the entire African continent (Bhorat et al. 2015). In SSA, both unemployment and underemployment are among the myriad labor market constraints facing the youth. Although the unemployment rate is low for many low-income countries in SSA, jobs are often precarious and there is a high degree of vulnerability to unemployment. This implies that increasing the security and quality of jobs is often a priority, rather than simply creating more jobs more generally. Highlighting this point is the fact that SSA has the highest youth working poverty rates in the world at approximately 70% of employed youth. Close to 38% of the youth are working in ‘extreme’ poverty4 and living on less than $1.90 a day (ILO 2016). Amongst those who are employed, an overwhelming majority are employed in informal sector. While most work in the agriculture sector, an increasing number are employed in construction and manufacturing. When disaggregated by gender, young women are disproportionately excluded from labor markets, facing additional constraints such as childcare and unpaid care work. Due to lack of opportunities and barriers to labor market entry, despite seeing high graduate numbers, SSA has the highest brain-drain of skills required to create productive economies, relative to any other region in world (ILO 2016). The demand-side of labor is overall affected by economic growth, incoming investments, and market access. Low levels of public and private investments in areas, including agriculture, have led to limited enterprise growth and job creation, contributing to high levels of underemployment, and presenting youth with a few viable employment opportunities. Rural youth have limited access to land due to unclear and insecure land rights, inheritance laws and social customs. Those involved in entrepreneurship also face challenges in accessing markets for their products and integrating into value chains (Mueller and Thurlow 2019). Access to finance, in particular, remains a chief barrier to business creation and job growth in SSA (Chakravarty et al. 2017). Being young makes it harder to access funds for self-employment as youth have 3 AfDB (2016). https://www.afdb.org/fileadmin/uploads/afdb/Images/high_5s/Job_youth_Africa_Job_youth_Africa.pdf 4 Extreme poverty is defined as living on less than US$1.90 per capita per day and moderate poverty on between US$1.90 and US$3.10, measured in 2011 purchasing power parity (PPP) terms (ILO 2016). lower rates of financial inclusion compared to adults, and they also have less time to accumulate savings/assets for collateral use. According to World Bank’s 2014 financial inclusion statistics (Demirguc- Kunt, A. & Klapper, L. 2015), young adults (15-24 years old), in comparison to 25+ adults, are almost 15% points less likely to have saved money in the past year and 6.1% points less likely to have borrowed capital to start, operate or expand their business. Additionally, in cases of emergency, young adults are also less likely to come up with required funds. The differential for young people may be partially ascribed to constrained informal borrowing due to smaller and more capital-poor networks (Chakravarty et al. 2017). Human capital of labor affects labor demand. As countries get richer, they produce more wage job opportunities relative to the supply of labor, and households have more resources to finance a job search (Fox and Gandhi 2021). Education levels and job aspirations also rise, however. This creates the situation of higher unemployment among educated youth, especially those with secondary school but no further education, regularly found in SSA urban areas. One reason for the pattern of higher unemployment among more educated youth is that the demand for labor with intermediate skills (e.g., completed secondary education) has not grown as fast as the supply of this labor—educational attainment has risen faster than labor demand. Additionally, as African countries grow their economies and expand education, skills mismatch underemployment seems to be becoming more important. An individual is not being able to find a job that utilizes the training or skills that a person has acquired. African Development Bank (2019) found that reported overskilling increases with education level completed. They also find that education is poorly correlated with labor productivity, which may be one reason why employers are less likely to hire well-educated job entrants, in addition to high reservation wage (Fox and Gandhi 2021). SSA region also tends to have more protective job security rules than other regions, especially Francophone countries, where labor market rules are particularly rigid (Betcherman and Khan 2015). In light of protective and restrictive regulations, prime-age workers are favored over youth. Hiring processes are cumbersome; employers would rather hire an individual with experience who will fit better over someone who is inexperienced and may not be a good fit. However, the overall impact of labor regulations in SSA is minimized by the region’s high degree of informality. 3 Focus on Zambia In Zambia youth unemployment rates are higher than non-youth unemployment rates, and this gap has been fairly consistent over the last 20 years. Based on data from the World Bank's World Development Indicators (WDI) database, when comparing general unemployment rates with youth unemployment, and considering the ratio of unemployment to youth employment among countries in Sub-Saharan Africa, Zambia's ratio does not differ from the regional average (Figure 2). The country's general unemployment rate and youth unemployment rate have tended to move in tandem, thus keeping this ratio relatively stable. Young women have a slightly higher probability of being unemployed at 20 percent compared to young men at 18 percent. Figure 2: Youth unemployment vs overall Figure 3: Trends in youth and overall unemployment unemployment in Zambia and Sub-Saharan in Zambia Africa 30 30 Overall unemployment rate Unemployment rate 25 (% of labor force) (% of labor force) 25 20 20 15 15 10 10 Zambia 5 5 0 0 0 20 40 60 Youth unemployment rate (%) Youth unemployment Unemployment Source: Adapted from World Development Indicators data 2000-2020. Zambia needs to address youth that are not in Education, Employment or Training (NEET) to reap the benefit of demographic dividend. About 42 percent of the population is under the age of 15, and 79 percent of the population is under the age of 35 years. Productively engaging youth can, therefore, help Zambia reap a huge demographic dividend. Yet, the share of youth Not in Education, Employment or Training (NEET) in Zambia is high at 43 percent. In comparison, in 2019 the NEET rate for youth globally was 22.2 percent, and 20.7 percent for Africa. Young people classed as being NEET are often faced with challenges including discouragement with respect to job opportunities and limited access to education. Remaining in this situation for an extended period can have a significant impact on their long- term employment prospects by preventing them from developing skills and experience. The Zambian labor market faces a range of different demand-side constraints to productive youth employment.5 These include lack of information about returns on education and jobs, distorting labor regulations, employers lacking information about available workers, and lack of voice. Other constraints pertaining to business and job creation may also exist. For instance, entrepreneurship aspirations, when they exist, clash with lack of capital and a lack of entrepreneurial training. Similarly, while at the aggregate level, legislated severance benefits did not greatly constrain firms’ demand for youth labor, it proved significant for manufacturing sector where relatively more establishments indicated that the system of benefits and other non-wage costs did affect their demand for youth labor to a great extent (Koyi et al. 2012). Zambia’s labor markets are devoid of functional information systems and skills mismatch is prevalent. Most firms felt unable to attain any information on the skills available in the labor market. For instance, the lack of information on training outputs in different fields means that the right signals are not being transmitted from the supply side to the demand side and vice versa. New youth entrants in the labor market are transitioning from the schooling system to labor market with skills mismatched to industry demand (Koyi et al. 2012). Weaknesses include basic, noncognitive, and vocational skills. Therefore, while education indicators are improving in the region, many young individuals remain ill-equipped for the labor 5 Solutions for Youth Employment 2015. market (Betcherman and Khan 2015). Highly educated people may also have high reservation wages, contributing further towards higher youth unemployment. Additionally, graduates at all levels, without technical training and limited experience, face an overcrowded and highly competitive job market, reflecting an ‘aspirational’ mismatch as much as ‘skills’ mismatch. Lastly, employers Many firms reported financing issues as a major stumbling block when it came to hiring youth. Majority of firms had problems in accessing domestic credit, which in turn impaired their ability to grow. Over 80% of wholly Zambian-owned firms cited this as the chief constraint in hiring youth workers (Koyi et al. 2012). High operational costs, especially energy costs, were also an important constriction with regards to job and operations’ expansion. Additionally, there was lack of fiscal incentives to support youth employment creation. Only 10% of surveyed firms reported receiving some form of government fiscal support to enable firms to create additional opportunities for young people. The bulk of establishments surveyed were not aware of fiscal incentives provided by the government; 50% of them thought that they had received no such support at all (Koyi et al. 2012). Agriculture is a critical sector for the Zambian economy, but youth face specific barriers to becoming farm owners. In SSA, longer life spans have meant that many parents continue to farm rather than transfer their land to their children as they enter the labor force.6 The problem of land scarcity for smallholder farmers has also been exacerbated by the rapid growth of medium-scale farms controlled by urban-based investors and rural elites. Land scarcity and lack of capital have forced many young workers to continue farming within households headed by older family members, and thus find themselves outside of the targeting criteria of some of Zambia’s agricultural support programs.7 For example, in Bwacha village in Zambia’s Northern Province, to join a cooperative and have access to the Farmer Input Support Programme (FISP) subsidies, farmers had to pay a one-off membership fee of K 50,000 and buy at least one share worth between K 100,000 and K 150,000, which represents a considerable capital outlay for most households especially the young.8 Even outside of the agricultural sector, young people in Zambia face a number of challenges in the labor market. Access to capital is critical for starting a small business or investing in education, and youth tend to be worse off in this regard, often having less access to financial services, credit, and social networks.9 A 2016 study in the informal settlement (“compound�) of Chawama outside Lusaka found that young entrepreneurs faced many challenges including lack of capital, limited profits, fierce competition, and accusations of witchcraft following financial successes.10 4 The World Bank’s 2021 Enterprise Survey Follow-up on with a focus on youth unemployment in Zambia 6 IFAD (2019). Creating Opportunities for Rural Youth: Rural Development Report 2019. 7 Djurfeldt, A. A., Kalindi, A., Lindsjö, K., & Wamulume, M. (2019). Yearning to farm—Youth, agricultural intensification and land in Mkushi, Zambia. J Rural Stud, 71: 85-93. 8 Birch-Thomsen, T. (2016). “Rural youth in northern Zambia: Straddling the rural–urban divide.� Young Entrepreneurs in Sub- Saharan Africa. 9 IFAD (2019). Creating Opportunities for Rural Youth: Rural Development Report 2019. 10 Chigunta, F., Gough, K. V., & Langevang, T. (2016). “Overcoming constraints through ingenuity and social entrepreneurship.� Young entrepreneurs in sub-Saharan Africa. 4.1 Survey description and background As part of the efforts of the World Bank Group to understand and investigate the impact of COVID-19 on the private sector, the Enterprise Analysis unit conducted follow-up surveys on recently completed Enterprise Surveys (ESI) in several countries, including Zambia. These short surveys re-contact all establishments interviewed as part of the standard World Bank Group Enterprise Surveys (ES) and are designed to provide rapid information on the impact and adjustments that COVID-19 has brought about in the private sector. For Zambia the most recent ES was conducted from September 2019 through March 2020. The latest Zambia ES interviewed a total of 601 establishments covering four regions – Kitwe, Livingstone, Lusaka, and Ndola. Firms are selected following a stratified random sampling approach, where sample is stratified along three variables – firm size, region, and sector. The universe of inference is all formally registered establishments with five or more employees that are in one of the following activities defined using ISIC Rev. 3.1: manufacturing (group D), construction sector (group F), services sector (groups G and H), transport, storage, and communications sector (group I) and information technology (division 72 of group K) (see annex table 1 for distribution of the sample). So far three rounds of COVID-focused follow up surveys have been completed.11 The round 3 follow-up survey includes set of questions designed to elicit demand side issues to firms in Zambia constraining youth employment. The survey re-contacted all 601 formal businesses with 5 or more employees interviewed as part of the baseline 2019 Zambia ES. A total of 522 (of the 601) establishments were interviewed in round 3 survey, conducted from July 28 to September 8 2021.12 Data was collected via Computer Assisted Telephone Interviews (CATI). The reference for last completed month in the dataset is June/July/August. 5 Findings Employment of youths and layoffs during the pandemic The World Bank’s 2021 Enterprise follow-up Survey lends further support to the existing research and literature on youth unemployment and challenges in Zambia. Respondents were asked about the total number of people, aged 15-35, employed and let go during the COVID-19 pandemic by their respective establishments (Figure 4). At the end of the last completed month before survey (i.e., June/July/August 2021), a median establishment in the sample employed 12 permanent, full-time employees, including all employees and managers. Amongst those employed, only 11% of the employees fell in the age bracket of 15-24 years, whereas 66% of employees were between 25 and 35 years. Aside from being overlooked for employment in favor of older-aged individuals, especially amongst the 15-24 years age group, of the workers that have been laid off due to the COVID-19 pandemic, 43% were 25-35 years old.13 11 Round 1 survey was conducted from June 16 to July 14 2020; Round 2 was conducted from December 19 2020 through February 18 2021; Round 3 survey was conducted from July 28 to September 8 2021. Anonymized micro data for the three rounds of follow-up surveys and the baseline ES data is available for download from the ES website (https://www.enterprisesurveys.org/en/survey-datasets). 12 59 of these 522 completed interviews were conducted with firms that were permanently closed. 13 This statistic comes from only those firms that reported laying workers off i.e., 115 firms in the sample. The proportion increases to 61% when we restrict the sample size to large firms, and 58% and 46% when we look exclusively at Livingstone and Lusaka respectively. Livingstone and Ndola cities also employ the fewest 15-24 years old as part of permanent, full-time workforce. Figure 4: Percentage of employees who are classified as youth at the end of last completed month and percentage of youth, 15-35 years old, laid off due to the COVID-19 pandemic 80% 70% 61.4% 67.0% 58.0% 67.3% 60% 65.5% 66.5% 65.0% 45.6% Percentage (%) 50% 42.9% 43.0% 55.1% 40.6% 59.7% 51.7% 40% 33.0% 30% 20.5% 20% 15.4% 11.3% 11.8% 12.8% 8.9% 6.9% 10% 5.9% 6.0% 0% Overall avg. Small Medium Large Kitwe Livingstone Lusaka Ndola Zambia Firm size Region Workers between 15-24 years (N=426) Workers between 25-35 years (N=426) Workers laid off since last round (N=115) Main reasons for not hiring young workers Lack of experience and a skills mismatch are the primary reasons cited by firms for their reluctance to employ young Zambians. Employers were asked to choose the main constraint to hiring young workers from the options a) lack of experience, b) skills mismatch, c) reliability issues, d) high reservation wages, and d) problems with retaining young workers. Amongst these constraints, skill-set mismatch (30%), experience (19%) and high reservation wages (14.5%) were listed as the top three constraints to hiring of young people aged 15-35 years. While the overall average for constraints did not change significantly by firm size or type (manufacturing or retail), small and large firms pointed towards reliability (10%) and difficulty in retaining of youth employees (12%) respectively, as secondary constraints to youth hire. The relative importance of these constraints also vary by region: In Kitwe and Ndola inexperience of youth (27% and 32% respectively) was offered as the chief constraint to hire; in Livingstone unreliability (23% - almost four times the overall sample average) and high reservation wages (24% - close to 10 percentage points higher than the sample average) were cited as the two biggest constraints. These latter findings help in partial understanding the reasoning behind employing the fewest young people as part of permanent, full-time workforce in Livingstone and Ndola. Figure 5: Main constraints to hiring more young people aged between 15 and 35 Overall constraints for hiring young people aged 15-35 years Other 2.4% Less reliable 5.7% Difficult to retain 7.9% Expect higher wages 14.5% Not experienced enough 19.4% Do not know (No constraints to hire) 19.9% Not the right skill-set 30.2% 0% 5% 10% 15% 20% 25% 30% 35% Top 3 constraints to hiring young people aged 15-35 years old - by firm size and region (N=463) 40% 34% 34% 35% 30% 31% 32% 30% 27% Percentage (%) 24% 23% 24% 24% 25% 23% 19% 20% 21% 20% 16% 17% 15% 14% 13% 15% 13% 10% 9% 10% 8% 8% 5% 0% Overall avg. Small Medium Large Kitwe Livingstone Lusaka Ndola Zambia Firm size Region Not the right skill-set Not experienced enough Expect higher wages Which kinds of workers are preferred in different roles? Firms are more reluctant to hire young workers for production or administrative roles. In response to businesses’ preference for hiring someone to fill a professional/administrative role, only 1% of sampled firms would prefer hiring 15-24 years old. The same age-group would be preferred slightly higher (4%) when filling a production (manual) position. Large firms and firms in Ndola report a strong preference not to hire workers in this youngest age category, presumably because of expectations around experience required for such a role. The situation improves increasingly, 42% and 70%, when we observe preference for 25-35 years old for production and professional positions. In Livingstone for instance, workers aged 25-35 years are highly preferred for professional (administrative) and production (manual) roles (52% and 73%), relative to the other 3 cities. On the other hand, in Kitwe, workers between 25-35 years are lowly preferred to fill production (manual) roles (59%). Figure 7: Firms’ preference to hire someone to fill a position for administrative or professional role Firms’ preferences by industry type Firms’ preferences by firm size (N=463) (N=463) 50% 42% 42% 45% 43% 45% 42% 43% 50% 42% 45% 40% 42% 42% 42% 40% 37% 41% 40% 35% 30% 30% 25% 20% 20% 17% 14% 20% 15% 10% 14% 13% 14% 10% 10% 5% 1% 1% 1% 0% 1% 1% 1% 0% 0% Overall Small Medium Large Overall average Manufacturing Retail average Workers (15-24) Workers (25-35) Workers (15-24) Workers (25-35) Workers 35+ No preference Workers 35+ No preference Firms’ preferences by region (N=463) 60% 52% 42% 48% 50% 44% 42% 42% 40% 40% 36% 36% 31% 30% 24% 20% 20% 14% 14% 8% 10% 1% 1% 1% 1% 0% 0% Overall Kitwe Livingstone Lusaka Ndola average Workers (15-24) Workers (25-35) Workers 35+ No preference Young workers, particularly those aged between 25 and 35, are strongly preferred by firms for manufacturing/production roles. For example, relative to workers aged 15-35, individuals aged 35+ are preferred more for professional (administrative) roles (42%). Manufacturing firms (45%), large firms (43%) and Lusaka (48%) region, in particular, prefer employees 35 years and above. On the flip side, probably due to the nature of the work, workers aged 35+ are not favored for production (manual) roles, 12% vs. 25-35 years old’s 70%. Despite lower preference for individuals 35 years old and over, the pattern remains same: amongst firms favoring older-aged employees, manufacturing firms (23%), large firms (18%) and Lusaka (16%) region prefer employees 35 years and above. Figure 8: Firm preferences for hiring to fill a position for manual or production role Firms' preferences by industry type Firms’ preferences by firm size (N=463) (N=463) 90% 77% 80% 72% 80% 70% 70% 70% 70% 63% 60% 60% 60% 50% 45% 50% 40% 29% 40% 13% 30% 12% 19% 30% 23% 18% 20% 14% 11% 12% 14% 15% 10% 8% 20% 14% 10% 4% 5% 10% 2% 10% 4% 4% 4% 0% 0% Overall Small Medium Large Overall average Manufacturing Retail average Workers (15-24) Workers (25-35) Workers (15-24) Workers (25-35) Workers 35+ No preference Workers 35+ No preference Firms’ preferences by region (N=463) 80% 73% 73% 70% 70% 60% 59% 60% 50% 36% 40% 30% 22% 20% 14% 14% 16% 12% 10% 9% 10% 7% 10% 4% 3% 1% 2% 3% 0% Overall Kitwe Livingstone Lusaka Ndola average Workers (15-24) Workers (25-35) Workers 35+ No preference Training and skills upgrading – pre-COVID and during the pandemic Although skills mismatches and inexperience are cited as major constraints by firms, less than one third of firms offered training to young workers even before the pandemic. Relative to retail firms, manufacturing firms offered less training (37% vs. 33%). Large firms also offered 9 percentage point more training than overall sample average; small firms, however, provided 9 percentage point lower training than the overall average. Amongst the 4 cities, 41% of firms based in Lusaka offered training to young workers. In other cities, only 21% firms on average offered similar trainings. When asked about the duration of training completion, 83% of respondents replied with a time period of 3 months or less. Significantly longer trainings i.e., 3 to 6 months and 6 months and above, were observed only in Livingstone (53%) and Kitwe (17%) respectively. Businesses were also asked about training instances post COVID-19. Since the onset of COVID-19, only 26% firms conducted any training for young workers. Retail, large firms, and firms based in Lusaka offered the highest number of trainings during this time period (28%, 36% and 29% respectively). Figure 9: Training offered to young workers pre and post COVID-19 Training offered to young workers pre Training offered to young workers pre and post COVID-19 - by industry and post COVID-19 - by firm size (N=463) (N=463) Training offered to young workers (%) Training offered to young workers (%) 40% 36.4% 37.3% 50% 44.8% 33.4% 39.5% 40% 36.4% 30% 30% 27.0% 20% 20% 10% 10% 0% 0% Overall Manufacturing Retail -10% Overall Small Medium Large average -10% -4.0% -10.5% -9.8% average -8.9% -13.1% -10.5% -20% -20% -13.9% Pre COVID-19 % change Post COVID-19 Pre COVID-19 % change Post COVID-19 Training offered to young workers pre and post COVID-19 - by region (N=463) Training offered to young workers (%) 50% 41.3% 40% 36.4% 30% 23.6% 24.7% 20% 14.7% 10% 0% Overall Kitwe -2.3% Livingstone Lusaka Ndola -10% average -10.5% -9.5% -8.6% -20% -12.5% Pre COVID-19 % change Post COVID-19 6 Recommendations and some thoughts on the way forward There are several stylized facts about demand side constraints to youth employment that can be drawn from the latest round of the Enterprise Survey follow up survey in Zambia. • Young workers make up a relatively small share of the overall formal sector workforce in Zambia, and these workers have been laid off at a higher rate than other workers since the start of the COVID-19 pandemic. • The key constraints preventing firms from hiring more young workers are a) firms are hesitant to hire young workers because of fears about lack of experience, b) firms are worried about skills mismatches between what is required and the skills that young workers possess, and c) worries that wage expectations from potential young workers are too high. This last point is true particularly of small firms, and firms based in Livingstone. • Manufacturing firms in general express a strong preference for hiring older workers for administrative of professional roles, while the opposite is true for retail firms. • There is an interesting dynamic when looking at age-based hiring preference by firm size. Large firms very strongly prefer to hire non-youth workers (aged 35 and above), while for small and medium firms the same cannot be said. • One area in which young workers are consistently preferred to non-youth workers is in manufacturing roles. This result holds true across industries, firm size and over each of the cities covered in the data. • Despite skills mismatches being a central concern of a large share of firms, overall, there is relatively little training being offered to young workers. Even before the start of the pandemic, only around one in three firms was offering training to youth. In particular, large firms and firms in Lusaka were most likely to support upskilling their young workers through dedicated work- based trainings. Since the onset of the pandemic, however, this training has been cut significantly, across all sectors, firm sizes and cities. These stylized facts suggest that there a few potential policy avenues that could be explored to help bridge the gap between the number of young people entering the Zambia labor force each year, and the number of productive jobs being created. i) Foster labor-intensive growth that targets youth. Youth in most low-income countries struggle to find their first job and are more likely to be in unpaid family work or the informal sector. In such circumstances, development of labor-intensive growth and fostering of youth schemes and employment incentives can help smooth the transition from school to work and/or encourage orderly emigration. ii) Address financial constraints for youth. Measures such as subsidized dual apprenticeships have the potential to address financial constraints for youth as well as employers’ inability to commit to provide general training. The dual approach combines wage subsidies with a dual training approach; on-the-job training in firms is complemented by theoretical training in vocational training centers. In Cote d'Ivoire, the program’s direct effects for youth and indirect effects for firms were documented. In the short run, youths increased their human capital investments and a net entry of apprentices into firms was observed. While the subsidized apprenticeships were substituted for traditional apprenticeships, the effect was limited. The subsidy offered offset forgone labor earnings. In four years, the treated youth started performing complex tasks and were able to increase their earnings by 15 percent. Therefore, dual apprenticeships can be instrumental in expanding access to training, upgradation of skills, and improving earnings for youth without crowding out traditional apprentices. iii) Enhancing the role of technical and vocational training. The government should not only ensure availability of quality education, it must augment further the role of technical education and vocational training. This may entail: a. Improving links between education, training and professional work settings. Standardizing qualifications in response to evolving labor market needs through an institutional mechanism for dialogue between training providers and industry; b. Introducing a youth training tax rebate to incentivize substantial increase in private sector expenditure on work-based learning; c. Expanding the reach of formal education and training through use of distance learning setups and strategies. iv) Consolidate programs and reduce the fragmentation of programs across ministries. Job programs are managed by several ministries. Many programs within and across ministries address similar demand side issues, creating overlaps. Efficiency gains can be attained by redistributing responsibilities for job programs and merging programs. Implementation processes for institutional arrangements outlined in the 2014 Social Protection Policy could also be improved. Furthermore, strengthening coordination and communication between programs can contribute to achieving common goals more effectively. This could be done through the creation of an inter-ministerial coordinating body to oversee all JEI programs within Zambia. v) Designing and implementing a comprehensive labor market information system. This could entail provision of clear labor market signals and facilitate firms’ decision-making on wages and employment. For instance, one avenue to reduce information asymmetries between rural youth and the urban labor market, and for those that have relatively less social capital, is the creation of job-search platforms that use modern communication technology to reach a wider set of youth audience. vi) Incorporating gender dimensions and lens in youth employment strategy. Given that the construction sector employs a predominantly male-based youth workforce, the government should consider more employment-intensive long-term infrastructure projects in this sector. In addition, it should target interventions in manufacturing and other value added industries with equal absorptive potential for both male and female youths. 7 Annex Annex Table-1: Distribution of completed interviews by Size, Sector and Region Other Wholesale Agri Other Grand Food Manufacturing Retail and Equip Services Unknown Total Kitwe Small (5-19) 5 13 6 0 13 2 100 Medium (20-99) 6 14 14 0 4 2 Large (100 or more) 1 6 3 0 4 4 Small, Medium and Large (5+) 0 0 0 3 0 0 Livingstone Small (5-19) 6 2 15 1 12 14 105 Medium (20-99) 3 3 5 0 25 15 Large (100 or more) 0 1 0 0 1 2 Lusaka Small (5-19) 10 7 33 10 33 15 294 Medium (20-99) 17 40 9 15 17 10 Large (100 or more) 22 11 18 1 19 7 Ndola Small (5-19) 1 9 10 0 4 3 102 Medium (20-99) 9 0 9 0 15 3 Large (100 or more) 3 0 1 0 13 3 Medium and Large (20+) 0 15 0 0 0 0 Small and Medium (5-99) 0 0 0 4 0 0 83 121 123 34 160 80 601 8 References Ali, Syed, and Urooj Afshan Jabeen. 2016. “Determinants of Youth Unemployment - A Supply Side Analysis.� European Journal of Business, Economics and Accountancy 4, no. 1 (2016): 9. 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