Report No. 64 81941 South Asia Human Development Sector An Assessment of Skills in the Formal Sector Labor Market in Bangladesh A Technical Report on the Enterprise-Based Skills Survey 2012 October 2013 Discussion Paper Series Report No. 64 South Asia Human Development Sector An Assessment of Skills in the Formal Sector Labor Market in Bangladesh A Technical Report on the Enterprise-Based Skills Survey 2012 October 2013 Discussion Paper Series Discussion Papers are published to communicate the results of the World Bank’s work to the development community with the least possible delay. The typescript manuscript of this paper therefore has not been prepared in accordance with the procedures appropriate to the formally edited texts. Some sources cited in the paper may be informal documents that are not readily available. The findings, interpretations, and conclusions expressed herein do not necessarily reflect the views of the International Bank for Reconstruction and Development/ The World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Contents Acknowledgements .......................................................................................................................... i  Acronyms and Abbreviations ......................................................................................................... ii  1. Introduction ................................................................................................................................. 1  2. Survey Objectives, Scope, and Methodology ............................................................................ 2  2.1. Objectives ............................................................................................................................ 2  2.2. Scope of the Survey ............................................................................................................. 2  2.3. Survey Instruments .............................................................................................................. 3  2.4. Sampling .............................................................................................................................. 4  2.4.1. Sampling Frame ............................................................................................................ 4  2.4.2. Sampling Methodology................................................................................................. 4  2.5. Survey Non-Response and Replacement ............................................................................. 6  2.6. Characteristics of the Sampled Data .................................................................................... 7  2.7. Survey Weights .................................................................................................................... 8  3. Main Findings of the Survey..................................................................................................... 10  3.1. Composition of Skills in the Formal Sector....................................................................... 10  3.1.1. General characteristics of workers .............................................................................. 10  3.1.2. Participation in Pre-Employment Training ................................................................. 15  3.1.3. Work experience and wages ....................................................................................... 16  3.1.4. Assessment of Cognitive and Non-Cognitive Skills of the Workers.......................... 18  3.1.5. Household and personal backgrounds of workers ...................................................... 23  3.2. Demand for Skills and Skills Mismatches ......................................................................... 25  3.3. Skills Matching Mechanism – Recruitment ....................................................................... 27  3.4. Post-Employment Skills Building Opportunities............................................................... 30  4. Conclusions ............................................................................................................................... 33  4.1. Summary of Key Findings ................................................................................................. 33  4.2. Policy Implications ............................................................................................................ 34  References ..................................................................................................................................... 36  Annex 1: Occupational List .......................................................................................................... 37  Annex 2: Literacy and Numeracy Tests........................................................................................ 39  Figures Figure 1: Proportion of workers by gender and economic sector ................................................. 10  Figure 2: Proportion of workers by age cohort and economic sector ........................................... 10  Figure 3: Proportion of workers by age cohort and education level ............................................. 11  Figure 4: Proportion of workers by education level for each economic sector ............................ 12  Figure 5: Proportion of workers by occupation for each economic sector ................................... 13  Figure 6: Proportion of workers by occupation for each education level ..................................... 14  Figure 7: Proportion of workers by occupation for male and female ........................................... 15  Figure 8: Percent of workers who took short-term training courses ............................................. 15  Figure 9: Participation in apprenticeships by education level ...................................................... 16  Figure 10: Proportion of workers who have changed jobs, by occupation ................................... 17  Figure 11: Literacy and numeracy test score by educational level ............................................... 19  Figure 12: Proportion of workers in professional occupations, by academic performance at each school level ................................................................................................................. 20  Figure 13: Employers’ perceptions of skills’ importance and employees’ skill sufficiency ........ 21  Figure 14: Workers’ perceptions on importance of skills and their self-evaluation ..................... 22  Figure 15: Comparison of skills evaluation (% sufficient) by managers and workers ................. 23  Figure 16: Pattern of domestic migration by education level and reasons ................................... 24  Figure 17: Distribution of workers by their household income and by educational level ............ 24  Figure 18: Share of graduates expected to be recruited the most in the next 3 years (%) ............ 25  Figure 19: University enrollment by academic fields and employers’ skills demand .................. 26  Figure 20: Number of graduates by academic disciplines and proportion of professional workers ....................................................................................................................................................... 27  Figure 21: How workers find jobs and median weeks to find jobs .............................................. 29  Figure 22: Percentage of workers who has family or relatives working in the same establishment ....................................................................................................................................................... 29  Figure 23: Average number of applicants per post by occupation ............................................... 30  Figure 24: Use of post-formal education training opportunities by education level (%) ............. 31  Figure 25: Types of off-the-job training ....................................................................................... 32  Figure 26: Share of training providers .......................................................................................... 32  Tables Table 1: Number of establishments and employees by economic sector in the formal labor market .............................................................................................................................. 4  Table 2: Number of establishments by size in the Sample Frame .................................................. 5  Table 3: Targeted sample number of enterprises and employees by establishment size ................ 6  Table 4: Survey results by economic sector ................................................................................... 7  Table 5: Number of establishments and employees surveyed by size and sector of the establishments .................................................................................................................. 8  Table 6: Number of establishments surveyed by sector and division ............................................. 8  Table 7: Average entry salary of workers who entered the labor market during the last three years ....................................................................................................................................................... 18  Table 8: Proportion of workers who use computer at work.......................................................... 20  Table 9: Criteria for Selecting New Hires in Each Sector (%) ..................................................... 28  Table 10: Two most common modes of advertising vacancies by sector..................................... 28  Table 11: Proportion of firms that provide formal off-the-job/on-the-job training or informal training ........................................................................................................................... 31  Authors Shinsaku Nomura Education Economist The World Bank Seo Yeon Hong Economist The World Bank Christophe Jalil Nordman Research Fellow French Institute of Research for Development (IRD), DIAL and Consultant The World Bank Leopold Remi Sarr Senior Economist The World Bank Ayesha Y. Vawda Senior Education Specialist The World Bank Acknowledgements This study has been conducted as a background paper to the Skills Development Policy Note of the Bangladesh Education Sector Review. The team benefited significantly from consultations with the Advisory Group of Skills Development Policy Note, consisting of representatives from the MoE, the University Grants Commission (UGC), the Ministry of Labor, the National Skills Development Council Secretariat, the Directorate of Technical Education (DTE), Bangladesh Technical Education Board (BTEB), Bangladesh Bureau of Statistics (BBS), the Bureau of Manpower, Employment and Training (BMET) from the Government of Bangladesh; Dhaka University, BRAC University, and Bangladesh Institute of Development Studies (BIDS) from the academia and research institutions; representatives from the private sector; BRAC, Dhaka Ahsania Mission and UCEP from civil society; and ILO, SDC, ADB, DFID, CIDA, and EU from the development community. The team benefited from overall guidance provided by Amit Dar, and useful inputs and feedbacks from the World Bank colleagues, including Syed Rashed Al-Zayed, Md. Mokhlesur Rahman, Yoko Nagashima, Dilip Parajuli, Hiroshi Saeki, Subrata S. Dhar, Muhammad Asahabur Rahman, and Syeda Kashfee Ahmed. SRG Bangladesh Limited conducted the field work of the Enterprise-based Skills Survey and prepared the data, and Md. Mohiuzzaman and Zaima Ahmed helped the field monitoring of the survey. The findings, interpretations, and conclusions expressed in this report are entirely those of the authors. i Acronyms and Abbreviations BBS Bangladesh Bureau of Statistics DPE Directorate of Primary Education ESR Education Sector Review ESS Enterprise-based Skills Survey HIES Household Income and Expenditure Survey HR Human Resources HSC Higher Secondary Certificate ICT Information and Communication Technology JSC Junior Secondary Certificate MDG Millennium Development Goals NSA National Student Assessment OJT On-the-Job Training SSC Secondary School Certificate STEP Skills Toward Employment and Productivity TVET Technical and Vocational Education and Training ii 1. Introduction Education and skill development have played a crucial role in economic growth, poverty reduction and social transformation in Bangladesh, particularly the inclusion of women in the labor force in the last decade. Bangladesh has made impressive gains in improving access to education, reaching the MDG of gender parity at the primary and secondary levels. Increased access to secondary education among girls over the past twenty years appears to have produced a powerful agent of social mobility as it is likely that many of the young girls who benefitted from the female stipends in the early 90s have now entered the labor market and may be enjoying higher earnings than older female cohorts. The widespread entry of women into the labor market has been a leading factor in the rapid expansion of the garment industry. With around USD 15 billion in export value in 2010, the readymade garment industry is currently Bangladesh’s most important industry sector (McKinsey & Company 2011). International studies have shown that education is an important instrument for sorting in South Asian labor markets with the less educated overwhelmingly found in low paying and less secure jobs, mostly in the informal sector (World Bank 2012a). Bangladesh is no exception. Education can improve productivity of workers and, in the long run, contribute to lower levels of vulnerability. With the vast majority of the labor force in Bangladesh still lacking basic primary education competencies, the education and skills challenge is enormous and can only be addressed through concerted efforts of all stakeholders beginning before a child enters school and continuing through a quality formal education system. However, education continues to be offered with mostly theoretical and outdated content that neither sets the stage for a skilled labor force that could propel the economy nor makes them competitive for higher value skills in the globalized economy. Both the general education and the Technical and Vocational Education and Training (TVET) systems are considered not providing the skills required by the labor market today while the transition to an urban industrialized and knowledge based economy will require relevant linkages between education outcomes and the labor market needs. In this context, a Policy Note on the Skills Development is being prepared to discuss the issues of the linkage between education and skills development and the labor market. The Policy Note, together with two other Policy Notes on Access and Equity, and Quality of Education, will be part of the Bangladesh Education Sector Review (ESR). The ESR is developed for diagnosing the current educational situation in Bangladesh and discusses different policy options for the way forward. The Skills Development Policy Note aims to assess the flow and stock of today’s skills demands and supply, in the areas of formal and informal sector labor market, as well as the overseas labor market where a large number of Bangladesh seeks for employment opportunities. It also aims to discuss the skills required for Bangladesh to develop when achieving the status of the middle income country as stipulated in the Vision 2021. As part of the Skills Policy Note, the Enterprise-based Skills Survey (ESS) has been conducted. This background report documents the technical properties of the ESS and discusses the general results of the survey. 1 2. Survey Objectives, Scope, and Methodology 2.1. Objectives The ultimate interest in conducting the ESS is to assess if the education system in Bangladesh is producing graduates with skills that are relevant to and demanded by the labor market in terms of types, quantity, and quality. To assess this, the survey aims to assess the skill composition in the selected industries, to assess the supply and demand of different types of skills education, to understand the practices of recruitment, skill appraisal and training opportunities within the enterprises. The survey informs about strength and weakness of the education system and discusses how the education system and the labor market can increase the efficiency of matching skills demand and supply and effectiveness of the education and training to the labor market. The survey also aims to provide information on various skill building and skill matching processes, including recruitment process, on-the-job training (OJT), and career development opportunities. 2.2. Scope of the Survey The uniqueness of the ESS is two-fold. First, it is an enterprise based skills survey. It is a more common approach to survey households or individuals for collecting information related to skills and education, but this study takes enterprises as the survey unit. It is unique also because it is a skill survey unlike common enterprise surveys that focus on business environment or activities. Second, the survey collects information from both employers and employees. Information collected from employers includes practices of recruitment and training as well as the general assessment of the workforce. Information collected from employees are related to educational background, work experiences, household characteristics and an assessment of literacy and numeracy skills and personalities. Collection of information from both the employers and employees enables a comprehensive review of skills composition in enterprises from different angles. Besides, this methodology thus provides the so-called “linked (or matched) employer- employee” data that are now well known for providing excellent information for the combined analysis of the supply and demand sides of the labor market. The survey does not include the informal sector of the labor market. The Bangladeshi labor market consists of a very large informal sector, which includes businesses run by households, or as domestic workers or day laborers. While the absolute size of employment is much larger in the informal sector, most of these works engage less educated or less trained workers. The informal sector work is assessed for the ESR through different surveys, including Household Income and Expenditure Survey (HIES) 2010. The field work took place between November 2012 and January 2013. 2 2.3. Survey Instruments The enterprise survey consists of two sets of surveys, including: (i) employer survey and (ii) employee survey. Both sets of surveys were conducted by face-to-face interview. The employer survey is responded in principle by business owners or top managers. It allows responses by Human Resources (HR) managers or other high level managers who are more familiar with the workforce in order to collect more information related to skills and HR management. Following modules are found in the employer survey: characteristics of the workforce, recruitment, training, and characteristics of the enterprise. The employee survey is conducted for sub-sample of employees in the sampled establishments. The employees to be interviewed are selected by random sampling. The field team requests a roster and samples are drawn by using prescribed method.1 If a firm does not have a roster, the interviewer listed up all the employees and randomly selected the samples. The employee survey module collects information on: education, work and training experiences, household background, and numeracy and literacy skills and personality assessment. The survey instruments included modules to capture cognitive and non-cognitive skills of workers. The study uses the definition of skills identified by the World Bank’s Skills Toward Employment and Productivity (STEP) framework (see World Bank 2010). There are three types of skills primarily discussed:  Cognitive skills include the ability to understand complex ideas, adapt effectively to the environment, learn from experience, engage in various forms of reasoning, and overcome obstacles using thoughts (via literacy, numeracy, and other abilities) to solve abstract problems.  Non-cognitive skills involve characteristics across multiple domains (including social, emotional, personality, behaviors, and attitudes) not included under cognitive skills—for example, work habits (effort, discipline, and determination), behavioral traits (self- confidence, sociability, and emotional stability), and physical characteristics (strength, dexterity, and endurance).  Technical skills are a combination of cognitive and non-cognitive skills used to accomplish specific tasks (skills used at work and in daily life). For operational definitions, the cognitive skills objectively measured through the Enterprise- based Skills Survey (ESS) are literacy and numeracy. The instruments consist of eight questions for each of literacy and numeracy modules. All the questions assess primary education level of cognitive skills as many of them are taken from National Student Assessment (NSA) conducted in 2011 by Department of Primary Education (DPE). Problem-solving skills, which are sometimes considered cognitive skills, are treated here as non-cognitive skills, because problem solving is not only a cognitive exercise—it also requires various non-cognitive skills. In ESS, technical/vocational, job-specific, and Information and Communication Technology (ICT) skills are considered technical skills. 1 In a small firm, every third person from the roster is interviewed. In a medium and large firm, every fifth and seventh persons are selected. If the employment size exceeds 200, every 30th person is interviewed. 3 2.4. Sampling 2.4.1. Sampling Frame The frame for the enterprise survey was based on the Business Registry of 2009, collected by the Bangladesh Bureau of Statistics (BBS). The Business Registry contains all enterprises that have more than 10 employees in Bangladesh. The data contains 100,1942 enterprises nationwide, and the share of enterprises by divisions is as in Table 1. Table 1: Number of establishments and employees by economic sector in the formal labor market Establishments Employees N % N % Manufacturing 35,993 36% 3,405,629 65% Commerce (wholesale, retail) 4,008 4% 95,616 2% Financial and insurance 8,008 8% 219,609 4% Public administration 8,073 8% 423,571 8% Education 30,984 31% 638,003 12% Sub-total for sampled sector 87,066 87% 4,782,428 91% Agriculture, forestry, fishery 76 0% 3,287 0% Mining and Quarrying 132 0% 8,560 0% Electricity, gas 474 0% 38,436 1% Water and sewage 81 0% 4,850 0% Construction 271 0% 13,815 0% Transportation 1,164 1% 56,476 1% Hotel and restaurants 3,502 3% 69,158 1% Information and communication 864 1% 30,464 1% Real estate 149 0% 5,250 0% Professional 591 1% 24,590 0% Administrative 698 1% 24,739 0% Health 2,930 3% 140,357 3% Entertainment 399 0% 15,170 0% Other service 1,793 2% 61,872 1% International org 1 0% 12 0% Sub-total for non-sampled sector 13,125 13% 497,036 9% Total 100,191 100% 5,279,464 100% Source: Authors’ calculation using Business Registry 2009 Note: The original database has 16,361 establishments with missing industry information but with detailed business activity information. Industries for those establishments are relabeled by the authors. Missing sector information for 3 establishments. 2.4.2. Sampling Methodology The sampling methodology for the ESS is a stratified random sampling. In a simple random sample, all members of the population have the same probability of being selected and no weighting of the observations is necessary. In a stratified random sample, all population units are 2 3 establishments do not have sector information, so Table 1 presents 100,191 establishments. 4 grouped within homogeneous groups and simple random samples are selected within each group. This method allows computing estimates for each of the strata with a specified level of precision while population estimates can also be estimated by properly weighting individual observations. Stratified random sampling was preferred over simple random sampling for the ESS for several reasons. First, it allows obtaining unbiased estimates for selected economic sectors with some known level of precision. The sampling weights take care of the varying probabilities of selection across different strata. Second, Bangladeshi economy is highly concentrated on a few leading sectors and a simple random sampling would not allow making inferences for the small sectors. As shown in Table 1, the top 5 sectors occupy 87 percent of employment and 91 percent of formal sector employment. The strata for ESS are economic sector and firm size. The survey covers five economic sectors, including manufacturing, commerce (wholesale and retail), finance, education, and public administration. The selection of economic sectors was made purposively. First the economic sectors have relatively large proportion of firms in the formal economic sector (i.e. in the sampling frame) as well as large share of employees. Second, the selected economic sectors are considered to have diversity in educational and skills demand. According to the HIES 2010, the shares of workers with higher than university level education are: manufacturing – 4 percent, commerce – 2 percent, finance – 41 percent, public administration – 16 percent, and education – 55 percent (6 percent for the whole labor market). By this, manufacturing and commerce are characterized as relatively low education sectors, finance and education sectors are relatively high education sectors, and the public administration is in the middle. Manufacturing sector represents a larger sample size because of anticipated diversity within the manufacturing sector. The manufacturing sector, the largest economic sector in Bangladeshi labor market, employs 65 percent of formal sector workers, and the activities within the sector is diverse. Some of the large sub-sectors in the manufacturing are: textile, readymade garments, bricks, food processing, and furniture. The survey does not expect specific representation of any subsectors, but key subsectors with high representation can be discussed at subsector levels. Firm size levels are 10-20 (small), 21-70 (medium), and 71+ employees (large-sized firms). The geographical criterion was not introduced to sample stratification because there is not enough number of firms for each cell if geographical quota is introduced. There were no additional requirements, such as on the ownership, exporter status, location or years in operation of the establishment. The number of establishments by size is displayed in Table 2. Table 2: Number of establishments by size in the Sample Frame Small Medium Large Total (a) Manufacturing 18,761 10,413 6,819 35,993 (b) Wholesale and retail 3,037 810 161 4,008 (c) Financial and insurance 5,150 2,493 365 8,008 (d) Public administration 4,162 2,929 982 8,073 (e) Education 23,434 7,084 466 30,984 (f) Total of 5 sampled sectors [sum of (a) through (e)] 54,544 23,729 8,793 87,066 (g) Total of non-sampled sectors [from Table 1] 8,050 3,740 1,335 13,125 (h) Total number of establishments [(f)+(g)] 62,594 27,469 10,128 100,191 (i) Representation of the entire formal sector [(f)/(h)] 87.1% 86.4% 86.8% 86.9% Source: Business Registry 2009 5 In the formal sector, 62 percent of establishments are small, 28 percent are medium sized, and 10 percent of firms are large. Since 90 percent of firms are small and medium-sized, the ESS oversamples large firms. There is a large discrepancy in their representativeness when considering the number of establishment (firm) or the number of employees in each sector. In terms of workforce, 17 percent of employees work in the small size firms (10 to 20), 18 percent in the medium size firms (21 to 70), and 65 percent in the large size firms (71 and more). The survey under-samples small firms in terms of the number of establishment, but it oversamples their number of workers. The targeted numbers of sample employees will be: 6 employees in small firms, 15 employees in medium firms, and 30 employees in large firms. The total number of employees surveyed will be expected 7,254 by this calculation (Table 3). Table 3: Targeted sample number of enterprises and employees by establishment size Enterprise Employee Small Medium Large Total Small Medium Large Total Manufacturing 80 60 60 200 480 900 1,800 3,180 Commerce 45 22 8 75 270 330 240 840 Finance 37 23 15 75 222 345 450 1,017 Public Administration 30 22 23 75 180 330 690 1,200 Education 37 23 15 75 222 345 450 1,017 Total 229 150 121 500 1,374 2,250 3,630 7,254 Source: Prepared by authors 2.5. Survey Non-Response and Replacement Internationally, enterprise-based surveys tend to have relatively high non-traceability or non- response rates. Enterprises may go out of business, change physical location, or change the business sector, all of which result in non-traceability or deviation of the samples from the frame. Survey non-response is also frequent because of refusal to cooperate in the survey because of business confidentiality. For example, Enterprise Surveys from Chile (2010), Peru (2010), and Argentina (2010) reported non-response due to firm ineligibility (including non-traceability) rates of 14 percent, 6 percent and 9 percent and refusal rates (per contacted establishment) of 27 percent, 25 percent, and 40 percent. High ineligibility rates are found in Yemen (2010) and Viet Nam (2009) – 44 percent and 23 percent respectively (Enterprise Survey website). The corresponding rates for Bangladesh ESS were 21 percent of non-traceability and 5 percent of refusal. In the Bangladesh ESS, the problem of non-traceability was particularly important because of imperfections in the sample frame. First, the Business Registry of 2009 is already three years old by the time of ESS, and it was expected that many small and medium size establishments may have gone out of business or changed the business under the difficult economic environment of the past three years. Second, the Business Registry itself contained a lot of missing or incorrect information, especially in the contact phone numbers and detailed physical address. In order to minimize these problems, the following strategies have been adopted in the Bangladeshi ESS. The establishments whose phone numbers exist in the sample frame were contacted by phone calls up to five times prior to interviews for making appointment. Up to three 6 visits were conducted for each establishment to overcome minor inconvenience problems for the interviewees. The local survey firm3 also contacted trade associations and local authorities to obtain their supports. When permissions were necessary from headquarters to survey local branch offices, such permissions were sought. Only after three visits, replacement firm strategy was adopted. Survey non-response did occur in 177 establishments, but substitutions were made in order to potentially achieve strata-specific goals. Among the survey non-responses, 143 cases were due to non-traceability and 34 cases were due to refusal of participation. Table 4: Survey results by economic sector Manu- Public facturing Finance Commerce Education Admin Total Original firm surveyed 88 65 48 60 62 323 Replaced 112 10 27 15 13 177 Firm closed 15 0 1 3 1 20 The firm was nonexistent 79 6 21 9 0 115 Firm changed location 4 0 0 1 0 5 Firm changed industry 3 0 0 0 0 3 Firm refused 11 4 5 2 12 34 Total 200 75 75 75 75 500 % of establishments from original frame 44 87 64 80 83 65 % of establishments replaced due to non- traceability 51 8 29 17 1 29 % of establishments replaced due to refusal 6 5 7 3 16 7 Source: Prepared by authors Replacement firms are identified by the following two strategies. In principle, the local survey team is responsible for identifying a replacement firm in case of non-traceability of the sample firm. The local survey team, after making every effort to trace the sample firm, was allowed to find a substitute firm that belongs to the same economic sector and the same size category as the original sample. The replacement firm must be located in the same geographical area, and if there are multiple firms that satisfy the characteristics, the nearest firm to the original address was to be selected. In case of refusal, the guidelines originally expected resampling of the firms by using the random sampling procedure from the Sample Frame. However, due to logistical difficulties, they were replaced by the same procedure as the non-traceability. There are some cases of item non-response, in which interviewees refuse to answer some specific questions. The item non-response problems is minimized in the survey design by (i) allowing refusals (by adding specific modalities) for sensitive questions that may generate negative reactions from the respondent such as tax or profit of the firms, and (ii) re-contacting the designated respondents in order to complete the survey whenever necessary. 2.6. Characteristics of the Sampled Data The ESS has collected samples from 500 establishments and 6,981 employees (Table 5). The number of employee samples collected is 96 percent of the targeted 7,254 employee samples (see 3 SRG Bangladesh was contracted to conduct this survey. 7 Table 3). This is because the sample contained more small size firms (236) than the original plan (229) and less medium and large size firms. This discrepancy is resulted from time lag between the dates of data collection – it has been three years since the Business Registry was compiled in 2009. Table 5: Number of establishments and employees surveyed by size and sector of the establishments Number of Establishments Number of Employees Small Medium Large Small Medium Large Total Total < 20 21-70 71+ < 20 21-70 71+ Commerce 42 24 9 75 252 336 246 834 Education 39 22 13 75 249 306 420 975 Finance 40 22 12 75 255 312 360 927 Manufacturing 83 54 60 199 528 846 1,770 3,144 Pub Admin 32 20 22 76 204 282 615 1,101 Total 236 142 116 500 1,488 2,082 3,411 6,981 Source: Prepared by authors using ESS 2012 Geographical distribution of the sample establishments shows that 53 percent of the samples are collected from Dhaka, followed by Rajshahi, Chittagong, Rangpur, Khulna, Barisal and Sylhet (Table 6). Table 6: Number of establishments surveyed by sector and division Rajshahi Khulna Dhaka Chittagong Barisal Sylhet Rangpur Total Commerce 4 3 50 9 1 1 7 75 Education 10 5 35 7 9 2 7 75 Finance 11 6 31 10 5 4 8 75 Manufacturing 43 6 120 20 0 3 7 199 Pub Admin 5 10 29 13 7 5 7 76 Total 73 30 265 59 22 15 36 500 Source: Prepared by authors using ESS 2012 2.7. Survey Weights Three types of survey weights were calculated, including: (i) establishment weight, (ii) employee weight for representing the establishment, and (iii) employee weight for representing the five sampled formal economic sectors. The establishment weight is the inverse of the probability that a sampled firm is selected in the formal economic sector. Let be the probability of the firm of size s in sector j to be surveyed. This probability can be calculated as / with X being the total number of firms in the cell sj (e.g. medium size firms in the manufacturing sector) and x being the number of firms actually surveyed in this cell sj. X is obtained from the Business Registry 2009, the Sample Frame of this survey, and the sum of the weights equals to the Business Registry. This weight should be used for assessing the employer module of the survey. Employee weights for representing the establishments are calculated as: 8 / where is the probability of workers to be surveyed in firm f, and is the number of workers surveyed in firms f, which was assigned to be 6, 15 and 30 depending on the firm size. is the total number of workers in firm f. It should be noted that this probability does not vary across workers in the same firm. The probability of the workers to be included in the global sample can simply be written as , which is obtained by: ∗ The weight is the employee weight to represent the employees of the five selected economic sectors in the formal labor market, and it is obtained by taking the inverse of , as 1/ . 9 3. Main Findings of the Survey 3.1. Composition of Skills in the Formal Sector 3.1.1. General characteristics of workers Eighty-four percent of workers in the formal labor market are male. On the other hand, the share of female workers in the five sampled economic sector is 16 percent (figure 1). The largest share of female workers is observed in education sector – 20 percent, followed by manufacturing – 17 percent and finance – 16 percent. Commerce sector, including retail and whole sale, employees the smallest proportion of female workers – 4 percent. Figure 1: Proportion of workers by gender and economic sector Source: Authors’ analysis using ESS 2012 The workers in the formal labor market are relatively young; more than half of workers are aged below 29 years old. In the surveyed five economic sectors, 4 percent of workers are aged below 19, and 49 percent of workers are aged below 29, totaling 53 percent of workers in these age cohorts (figure 2). The youngest economic sector is manufacturing – where 61 percent of workers are aged below 29. Education, on the other hand, consists of relatively older workers. 45 percent of workers are in their thirties. 31 percent of workers are older than 40 years old. Figure 2: Proportion of workers by age cohort and economic sector Source: Authors’ analysis using ESS 2012 10 Young workers, aged below 29, have relatively low levels of education. Among the workers aged between 20 and 29, 30 percent has education of primary or less, and 57 percent has up to secondary level education (figure 3). The share of university degree holders increase rapidly in the 30-39 age cohort. It is most likely that students are in their late twenties or thirties when they finish university, so when they enter the labor market, they are already in their thirties. Figure 3: Proportion of workers by age cohort and education level Proportion (%) Source: Authors’ analysis using ESS 2012 In the sampled five economic sectors, the majority of workers are relatively low-educated. 28 percent of workers have up to primary education and 48 percent of workers has up to secondary education, totaling 76 percent of workers having secondary education or below (Figure 4). The share of university graduates is about 22 percent and about 2 percent of graduates have TVET certificates. The share differs across economic sectors. The public administration is the most highly educated sector, with 58 percent of workers having more than university degree, followed by education and finance, which respectively consist of 49 percent and 40 percent university graduates. Commerce and manufacturing sectors have relatively small shares of university graduates – 21 percent and 8 percent respectively. In manufacturing sector, 39 percent of workers have less than or equal to primary education. 11 Proportion (%) Figure 4: Proportion of workers by education level for each economic sector Source: Authors’ analysis using ESS 2012 In the sampled five economic sectors, 24 percent of workers belong to the professional category and 76 percent of workers to non-professionals.4 The share of professionals is the largest in the education sector (44 percent), followed by finance (31 percent) and commerce (29 percent) (figure 5). In terms of each occupational category, the share of construction and craft workers is the largest, 32 percent, in the sampled five economic sectors. This is attributed to the large share of construction and craft workers in manufacturing sector, 48 percent. Craft worker category includes garment and various handicraft workers, and they are mostly found in the manufacturing. Followed by the construction and craft worker category, clerical support workers is the second largest occupational category. This is by a large attributed to public administration sector, which consists of almost 50 percent of clerical workers. Finance sector also hires relatively large share of clerical support workers, 34 percent. Sales workers and skilled agricultural workers are the two smallest occupational categories. It is natural to consider that skilled agricultural workers are not found in these formal enterprises since the majority of the agricultural workers do not belong to enterprises. A large share of sales workers is found in commerce sector. 4 The survey classifies occupations into 10 major categories following the STEP framework. Three professional level occupations include (i) managers, (ii) professionals, and (iii) technicians and associate professionals. Seven non-professional occupations include (iv) clerical support workers, (v) service workers, (vi) sales workers, (vii) skilled agricultural workers, (viii) construction or craft workers, (ix) plant and machine operators, and (x) elementary occupations. Detailed list of occupations in each occupation categories is included in the Annex 1. 12 Figure 5: Proportion of workers by occupation for each economic sector Occupation Commerce Manufacturing Public Administration Managers 7.3 4.8 0.8 Professionals 14.2 5.8 21.3 Technicians and associate prof.. 7.1 9.0 3.7 Clerical support 8.7 5.5 49.6 Sales workers 18.4 1.4 0.1 Service workers 12.2 6.1 14.9 Skilled agricultural workers 0.8 0.1 1.0 Construction, craft 7.1 47.7 0.7 Plant and machine operators 9.9 5.6 1.0 Elementary occupations 14.4 14.0 6.9 0 20 40 0 20 40 0 20 40 Proportion (%) Proportion (%) Proportion (%) Occupation Finance Education All Managers 3.7 0.0 3.7 Professionals 21.1 42.8 13.4 Technicians and associate prof.. 6.1 1.3 7.1 Clerical support 34.2 24.7 15.5 Sales workers 3.1 0.0 1.4 Service workers 18.1 16.4 9.3 Skilled agricultural workers 0.1 0.0 0.2 Construction, craft 0.1 0.2 32.2 Plant and machine operators 0.5 0.4 4.1 Elementary occupations 13.0 14.2 13.0 0 10 20 30 40 50 0 10 20 30 40 50 0 10 20 30 40 50 Proportion (%) Proportion (%) Proportion (%) Professional level Non-Professional Professional Source: Authors’ analysis using ESS 2012 Formal education is one of the key determinant of occupational differences in the formal economic sector. Figure 6 reports that the proportion of workers by occupation category differs greatly across graduates of different educational levels. Differences in occupational categories imply different skills practiced by different educational groups. For workers with less than secondary education, the share of construction and craft workers is the largest followed by elementary occupations, and the share of professional level workers is less than 10 percent. The share of clerical or service workers increases as the level of education goes up. On the other hand, the share of construction and craft workers as well as elementary occupations gradually declines as the education level goes up. For HSC graduates, the most commonly employed occupation is clerical job, which consists of about 35 percent. This share is the highest among all educational levels. Graduates from three technical and vocational education and training degrees—SSC (voc), HSC(voc), and Diploma—engage in both non-professional and professional level occupations. 5 Yet, the share of professional workers is relatively higher than that of general SSC and HSC graduates when they find jobs. 6 Higher education graduates, including bachelor and post- graduate degree holders, generally work as professionals or managers although some good 5 Compared to other levels of education, the shares of TVET graduates in the ESS sample was 0.3% (21 cases), 0.5% (50 cases), and 1.0% (71 cases) for ssc(voc), hsc(voc) and diploma respectively (total sample size of 6,981). Due to very small sample size, sampling error is relatively large for these groups. 6 As discussed later in the section, their rate of finding jobs is reported very low. 13 proportions of bachelor and post-graduate workers also take clerical support jobs (31.7 percent and 17.2 percent respectively). Figure 6: Proportion of workers by occupation for each education level No education Incomplete Primary Primary JSC Managers 0.2 0.5 0.7 1.8 Professionals 0.8 1.0 1.6 2.3 Technicians and assoc. profs. 2.5 5.2 5.0 3.5 Clerical support workers 0.7 3.4 4.1 5.9 Service workers 4.5 3.0 10.2 12.3 Sales workers 0.6 1.2 1.8 1.7 Skilled agri. forestry, fish 0.8 0.9 0.1 0.2 Construction and craft 59.3 52.5 50.8 46.0 Plant and machine operators 5.7 3.8 6.0 7.5 Elementary occupations 25.1 28.5 19.7 18.7 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 SSC HSC SSC(v) HSC(v) Managers 2.6 4.9 1.3 4.3 Professionals 2.2 10.0 2.5 26.5 Technicians and assoc. profs. 5.5 11.6 23.8 28.6 Clerical support workers 14.0 34.9 20.9 4.5 Service workers 14.9 6.4 14.3 16.4 Sales workers 2.6 1.3 0.0 1.9 Skilled agri. forestry, fish 0.1 0.0 0.0 1.2 Construction and craft 35.4 24.0 30.4 14.7 Plant and machine operators 6.6 1.8 6.8 1.7 Elementary occupations 16.1 5.1 0.0 0.3 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 Diploma Bachelor Post graduate All Managers 4.4 8.4 10.0 3.7 Professionals 19.9 38.4 64.9 13.4 Technicians and assoc. profs. 55.2 9.4 6.7 7.1 Clerical support workers 9.5 31.7 17.2 15.5 Service workers 8.8 10.4 0.8 9.3 Sales workers 0.3 0.7 0.2 1.4 Skilled agri. forestry, fish 0.0 0.2 0.0 0.2 Construction and craft 1.4 0.2 0.1 32.2 Plant and machine operators 0.5 0.0 0.0 4.1 Elementary occupations 0.0 0.5 0.1 13.0 0 20 40 60 0 20 40 60 0 20 40 60 0 20 40 60 Professional Non-Professional Professional Source: Authors’ analysis using ESS 2012 There is a gender difference in the share of professional workers – the shares of professional workers are 26 percent among men and 15 percent among women. About a half of female workers are found in the craft (and construction) occupational category. This can be explained by the fact that the increasing number of garment and manufacturing workers are women (World Bank 2012b). Elementary occupations (14 percent) and clerical support workers (12 percent) are the next two common occupational categories. Among male workers, while the largest share of workers are in the construction and craft sector (28 percent), the share if much smaller than that of women. Clerical workers (16 percent) and professional workers (14 percent) are next two common occupations. The gender difference is clearly seen for managers and technical level workers. 14 Figure 7: Proportion of workers by occupation for male and female Source: Authors’ analysis using ESS 2012 3.1.2. Participation in Pre-Employment Training Short-term formal TVET programs attract relatively better educated workers, especially those who have vocational and technical degrees. Short-term training courses are supposed to provide basic skills training to workers who are already in the labor market but don’t have an education so that they can have breadwinning skills in hands. However, the courses do not usually benefit the intended audience, because the courses require a minimum grade 8-level education.7 Employees with a lower level of education are far less likely than highly educated groups to access these programs (figure 8). For instance, only 2–5 percent of workers with less than a junior secondary-level education take short-term courses, but more than 10 percent of post-secondary graduates take them, and 60 percent of HSC (vocational) graduates take them. Figure 8: Percent of workers who took short-term training courses Participation in short-term training (%) primary Primary Bachelor edu SSC Incomplete JSC HSC SSC(v) HSC(v) Diploma Post Graduate Total No formal Source: Authors’ analysis using ESS 2012. 7 The new NTVQF will open a door to the uneducated through pre-vocational levels of training. 15 Participation in apprenticeship/internship in formal sector is also more common among educated workers. The ESS finds that the rate of participation in apprenticeship/internship was the highest among diploma graduates, 21.4 percent for both formal and informal apprenticeship/ internship combined (figure 9). Bachelor degree holders (11.9 percent), SSC graduates (9.6 percent), and HSC graduates (8.4 percent) are the next most participated groups in apprenticeship/internship. Given that formal sector internship opportunities are likely to be offered as a test for applicants, it is probably most suitable for testing educated workers. However, this raises an issue of inequitable training opportunities for less educated workers. Figure 9: Participation in apprenticeships by education level apprenticeship/internship (%) 4.0 Participation in 3.5 17.4 2.5 8.4 7.9 5.9 4.4 Post 3.0 Primary 2.1 Diploma edu Incomplete Primary HSC Graduate Total No formal JSC SSC Bachelor SSC(v) HSC(v) Source: Authors’ analysis using ESS 2012. 3.1.3. Work experience and wages Overall, 90 percent of workers stay with their first jobs while the proportions of workers who changed the jobs are marginally higher among the professional occupations. Staff turnover in the formal sector may not be as high as it is perceived – as 90 percent of workers have never changed jobs. It is commonly perceived that the turnover is relatively high for low skilled manual jobs, the proportions of workers who have ever changed jobs in construction and craft, machine and plant operators, and elementary workers are respectively 9.3 percent, 13.3 percent, and 7.2 percent. On the other hand, professional workers are more likely to experience a job change. 17.2 percent of mangers, 12 percent of professionals and 14.7 percent of technicians have experienced a job change. 16 Figure 10: Proportion of workers who have changed jobs, by occupation Source: Authors’ analysis using ESS 2012 An average entry salary differs by occupation, educational level, and industry. Table 7 indicates the average entry salary of workers who entered the labor market during the last three years. On average, workers who come to managerial positions and professional positions receive much higher salary than the rest of workers. Managers receive on average Tk. 14,607 per month at entry while workers of elementary occupations receive Tk. 3,784 on average. The difference corresponds to the educational levels. Bachelor and post-graduate degree holders on average receive respectively Tk. 10,560 and Tk. 11,311 at entry while workers with no education receive Tk. 4,753 (lowest entry salary is observed among those who have incomplete primary education, Tk. 4,072). By industry, finance and public administration sectors provide relatively high entry salary, Tk. 8,052 and Tk. 8,070 respectively as opposed to the average Tk. 6,030. 17 Table 7: Average entry salary of workers who entered the labor market during the last three years Public Commerce Education Finance Manufacture Admin Total By Occupation Managers 9,225 - 14,702 14,959 8,412 14,607 Professionals 11,282 8,170 12,026 8,977 14,660 9,917 Technicians and associate professionals 6,190 9,473 14,298 7,392 8,605 7,804 Clerical support 6,843 5,731 7,394 4,814 7,188 6,393 Service workers 4,482 4,648 5,687 5,286 5,939 5,281 Sales workers 5,969 - 6,737 4,791 4,909 5,218 Skilled agricultural workers 8,000 4,487 - 3,856 5,462 4,973 Construction, craft 4,777 6,375 - 4,697 7,335 4,709 Plant and machine operators 4,970 7,435 7,849 4,974 6,922 5,098 Elementary occupations 4,205 3,744 4,954 3,590 4,970 3,784 By Education No education 5,086 2,535 5,149 4,865 4,197 4,753 Incomplete Primary 4,105 3,485 5,440 4,083 3,666 4,072 Primary 4,187 3,179 4,737 4,354 3,570 4,282 JSC 4,782 4,206 4,716 4,405 5,043 4,432 SSC 5,375 5,187 5,561 5,209 5,606 5,255 HSC 6,799 5,115 6,075 6,371 6,024 6,073 TVET 8,009 7,469 12,933 6,529 7,364 6,889 Bachelor 8,831 7,299 11,199 11,733 11,888 10,560 Post-graduate 14,760 10,423 14,071 14,139 8,624 11,311 Total 6,263 6,286 8,052 5,469 8,070 6,030 Source: Authors’ analysis using ESS 2012 Note: Italic indicates the sample size is less than 30 3.1.4. Assessment of Cognitive and Non-Cognitive Skills of the Workers A major portion of the Bangladeshi workforce lacks basic literacy and numeracy skills. ESS measured literacy and numeracy skills of formal sector workers, testing them with eight basic (primary education-level) questions.8 As figure 11 shows, the average score among groups of different educational levels increases from 0.5 among non-educated to 2.1 among primary school completers, 3.5 among junior secondary school completers, and 5.5 among secondary school completers. However, considering that this assessment measures primary education-level competencies, a score of 5.5 points out of 8 for secondary-school graduates (grade 10) is quite dismal. The numeracy score average is slightly better for groups with less than a secondary education. Even those with no education scored 3.3 out of 8 questions on an average, a skill quite possibly stemming from their functional experience. Yet, given that the assessment measures only primary-level competency, an average of 6.2 points is still too low for secondary graduates. 8 The literacy test consists of eight questions, including reading of words and sentences, and understanding short passages, grammar, and English translation. The numeracy test consists of simple mathematical operations (addition, subtraction, multiplication, division, measurement, and functional mathematics, such as cost calculation). Scores are calculated by assigning one point for each item that an interviewee answers correctly (minimum = 0, maximum = 8). Test items are in Annex 2. 18 Figure 11: Literacy and numeracy test score by educational level 8.0 7.4 7.2 6.7 7.1 6.9 7.3 7.0 6.5 7.2 7.0 7.2 6.5 6.2 6.4 6.0 5.5 5.2 5.0 4.3 4.0 3.5 Literacy 3.3 3.0 Numeracy 2.0 2.1 1.0 0.6 0.0 Source: Authors’ analysis using ESS 2012 Cognitive skills, as measured by academic performance, are correlated with getting good jobs in the formal labor market. According to workers’ self-reported school performance, those who performed better at school are more likely to take professional occupations— especially with TVET 9 and higher education. Ninety-four percent of TVET graduates who achieved first division in the school’s final examination are in professional occupations, while 85 and 64 percent of TVET graduates with second- and third-division scores are in professional occupations (figure 12). Among university graduates, the proportions are respectively 82, 63, and 59 percent. This correlation implies that either employers screen academic performance of the candidates or that graduates with high academic performance are found more qualified for high skills jobs through recruitment processes and hence they are offered better job opportunities. 9 ESS 2012 considers SSC (vocational), HSC (vocational), and Diploma graduates as TVET graduates. It does not include trainees of short courses or non-formal TVET courses. 19 Figure 12: Proportion of workers in professional occupations, by academic performance at each school level Proportion Source: Authors’ analysis using ESS 2012. Note: Categories for first to third divisions correspond to marks of final examinations as (i) 60–100, (ii) 45–60, and (iii) 33–45 percent. TVET graduates include SSC (vocational), HSC (vocational), and Diploma graduates, but not trainees of short courses or non-formal TVET courses. About 40 percent of managers, professionals, and clerical workers use computers regularly while other workers do not very often. Email and internet are the most commonly used software. About one third of managers, professionals, and clerical workers use these programs almost every day. Use of word processing, spreadsheet, and databases is less frequent – about 15 percent to 20 percent among these professionals. While workers of these three occupational types use computers regularly, other occupational workers are much less likely to use computer – 27 percent among technicians, less than 8 percent for the other occupations. Table 8: Proportion of workers who use computer at work Type of software and activities Use Specific computer Data Word Spreads Data- software Program Email Internet entry processing heets base for the ming company Managers 42% 34% 31% 23% 17% 20% 20% 18% 16% Professionals 40% 31% 29% 24% 20% 16% 13% 7% 10% Technicians and 27% 10% 9% 8% 9% 8% 9% 4% 2% Clerical support 38% 30% 31% 20% 14% 16% 15% 20% 24% Service workers 8% 3% 4% 1% 4% 4% 1% 1% 1% Sales workers 6% 5% 5% 3% 3% 2% 2% 3% 2% Skilled agriculture 0% 0% 0% 0% 0% 0% 0% 0% 0% Construction, craft 3% 0% 0% 0% 0% 0% 1% 0% 0% Plan and machine 2% 1% 1% 1% 1% 1% 0% 0% 0% Elementary 3% 1% 0% 1% 3% 0% 0% 0% 0% Total 17% 11% 11% 8% 7% 7% 6% 5% 6% Source: Authors’ analysis using ESS 2012. Note: Workers who reported that they used each software almost everyday is included in this analysis. 20 It appears that the current labor force lacks some non-cognitive skills for effectiveness at work. Employers were asked to evaluate employees’ skills among 12 categories, weighing the importance of those skills, and listing their satisfaction with employees’ skills. 10 Employers weighted non-cognitive skills (namely responsibility, communication, problem solving, and team work; see figure 13) as more important than cognitive (numeracy and literacy) and technical skills (vocational or ICT).11 For professional workers, three non-cognitive skills were ranked as most important: responsibility, communication, and problem solving, followed by two cognitive skills: numeracy and literacy. On the other hand, for non-professionals, seven behavioral skills occupied the top ranks: responsibility, problem solving, team work, customer care, communication, motivation, and creativity, followed by cognitive and hard skills. However, employers do not feel that employees are sufficiently equipped with those skills. Only 43 percent of professional employers reported that employees are sufficiently responsible, and only 17 percent of non-professional employers reported that employees are sufficiently responsible. Employers’ satisfaction with employees’ skills are generally higher for professionals, but there is a considerable gap for all skills between what employers deem as important versus what they feel employees sufficiently possess or embody. Figure 13: Employers’ perceptions of skills’ importance and employees’ skill sufficiency 80 69 67 70 64 58 58 58 56 60 53 47 46 50 43 40 40 39 38 38 40 36 37 38 37 35 38 36 35 31 30 27 25 26 26 24 19 19 21 18 20 16 15 17 17 16 13 11 15 How important 11 10 7 10 7 How sufficient 4 4 0 Responsibility Responsibility Motivation ICT ICT Communication Problem solving Problem solving Communication Motivation Customer care English Vocational skills Vocational skills English Literacy Team work Creativity Team work Customer care Creativity Numeracy Literacy Numeracy Professional Non-Professional Source: Authors’ analysis using ESS 2012 Note: All information is presented in percentages. ICT = information and communication technologies. 10 These categories are adopted from similar skills surveys from other countries, including England, Poland, and Macedonia (see World Bank 2012c, Martin et al. 2008, Rutkowski 2010, and Rutkowski 2011). Some categories were modified after the pilot tests, to adjust to Bangladesh’s context, but it maintains comparability in terms of categories. 11 Similar findings are also found in other countries. In Poland, the top three valued skills are: (i) responsibility and reliability, (ii) motivation and commitment, and (iii) teamwork (World Bank 2012b; Rutkowski 2011). In Macedonia, the top three are: (i) responsibility and reliability, (ii) literacy, and (iii) communication (Rutkowski 2010). 21 Employees also value non-cognitive skills over cognitive skills. Employees were also asked to evaluate for each of the pre-identified skills how important they are and how sufficient the employees are equipped with. Non-cognitive skills, such as responsibility, communication, and team work are rated relatively high while cognitive skills such as literacy and numeracy are rated somewhat lower, and hard skills like vocational and English are rated even lower. Figure 14: Workers’ perceptions on importance of skills and their self-evaluation 70 59 60 54 50 48 50 42 42 41 42 41 39 38 38 40 34 34 33 30 29 33 32 31 30 33 29 30 27 27 25 26 24 24 22 18 17 18 21 20 20 20 15 14 14 13 12 17 15 15 12 9 7 Important 10 6 Sufficient 0 ICT Motivation Motivation ICT Communication Problem solving Communication Problem solving Responsibility Team work Customer care English Vocational skills Vocational skills English Literacy Creativity Responsibility Numeracy Team work Customer care Creativity Numeracy Literacy professional non-professional Source: Authors’ analysis using ESS 2012 Employees’ evaluations of their skills do not correlate with employers’ evaluations. Professional employees give relatively humble evaluations of themselves. Except for ICT skills, employers evaluate the skills of professional workers more highly than professional workers evaluate themselves (figure 15). Conversely, non-professional workers’ self-assessment is generally higher than their employers’ evaluation, creating a mismatch between employers’ expectations and employees’ perceptions. For example, only 17 percent of employers think non- professional workers possess a sufficient sense of responsibility, while more than 30 percent of non-professional workers think their responsibility skill is sufficient. 22 Figure 15: Comparison of skills evaluation (% sufficient) by managers and workers Professional Workers Non-Professional Workers Responsibi Customer lity care Vocational 50 Communic 50 Team skills ation English 40 40 work English 30 Problem 30 Problem solving ICT 20 solving 20 10 10 Vocational Responsi ICT 0 Numeracy skills 0 bility Communi Creativity Literacy Creativity cation Customer Numeracy Literacy Motivation care Team work Motivation Employers Employers Employees Employees Source: Authors’ analysis using ESS 2012 Note: Skills are presented clockwise, in order of highly evaluated categories by employers. 3.1.5. Household and personal backgrounds of workers Domestic migration is common for the educated: higher education graduates tend to migrate for school or work while secondary graduates migrate for work. More than 10 percent of bachelor holders have moved to the current location for the purpose of schooling and stays on. On the other hand, 40 percent of JSC, SSC, and HSC, and Diploma holders have moved to the current location for the purpose of working. They are generally more mobile than less educated workers (no education or primary level) and their move is largely influenced by economic reason (i.e. work). Moving due to family decision is more frequently observed among bachelor and post-graduate workers. This may be a result of family decision to give better education to their children (this can be investigated further by reviewing parental education). 23 Figure 16: Pattern of domestic migration by education level and reasons 80% 70% 60% 50% 40% 30% 20% 10% 0% no education psc jsc ssc hsc diploma bachelor post graduate not moving moving for work moving for school moving due to family decision Source: Authors’ analysis using ESS 2012. Household income tends to be higher among workers from a relatively higher education. Figure 17 displays the household income of interviewed workers. While the displayed household income not only includes the interviewed workers income but also income generated by other household members, the distribution tends to correlate with the educational level of interviewed worker. Among workers with no education, highest frequency of household income is between Tk. 5,001 – Tk. 7,500 per month. On the other hand, highest frequency among post-graduate worker is Tk. 20,001-30,000. Overall, Tk. 10,001 – Tk. 15,000 per month is a most frequent household income. Figure 17: Distribution of workers by their household income and by educational level Source: Authors’ analysis using ESS 2012. 24 3.2. Demand for Skills and Skills Mismatches In formal sector, which constitutes about 11 percent of employment in Bangladesh, half of the employment demands are for secondary or less levels of education. ESS has found that skills demand varies by economic sector and occupation. In manufacturing and commerce sectors, 93 percent and 78 percent of labor demand is for workers with less than secondary education. While finance and education sectors mostly need workers with university and above degrees, the share of finance sector is relatively small in terms of employment. Public administration has a mixed demand of secondary graduates and university graduates (figure 18). As a result, about half of labor demand is for less than secondary school graduates and another half is for higher education and TVET graduates in the formal sector. Considering the entire scope of labor market, half of 11 percent of formal sector employment means roughly 5.5 percent of demand is for university and TVET graduates in the entire labor market. Figure 18: Share of graduates expected to be recruited the most in the next 3 years (%) Manufactu 35 57 3 4 Commerce 10 68 5 17 Less than primary Pub Admin 1 42 8 49 Secondary (JSC-HSC) Finance 0 22 2 77 TVET University and above Education 2 4 1 93 Total (weighted) 16 34 3 47 0% 20% 40% 60% 80% 100% Source: Authors’ analysis using ESS 2012 The demand for TVET graduates is small in the formal sector. Several factors can be considered for this. First, employers do not have experience of hiring TVET graduates – especially the ones whose final degree is formal vocational training – because there are so few TVET graduates in the labor market (i.e. less than 1 percent of labor force). Some employers even do not know there is such a degree as SSC (voc) (Hossain 2012). Secondly, the employers are used to train the workers after workers are employed, so they just need unskilled workers and trained them after employed (Hossain 2012; World Bank 2007). As shown in figure 18, public administration seems to demand the largest proportion of TVET graduates – 8 percent of new recruitment. However, all in all, demand for TVET graduates is mostly diploma level graduates and not SSC or HSC (voc). Demand for higher education graduates is relatively weak in the private profit seeking sectors, but more evident in education sector and public administration. According to the ESS, 63 percent of university graduates are working in education and public administration while only 29 percent of workers belong to these two sectors in the surveyed five economic sectors of 25 formal labor market. This shows that more than half of university graduates are found in non- profit seeking sectors. In terms of the future recruitment prospect, while the finance sector expects large proportion of university graduates for their new recruitment, manufacturing and commerce sectors do not expect much university graduates. Due to relatively small size of finance sector (4 percent of formal sector employment), the needs for university graduates is relatively small in these three profit seeking sectors (as opposed to non-profit seeking industries of education and public administration in the ESS), and relative demand size for university graduate from education and public administration becomes large – constituting as much as 80 percent of university graduates demand in the five largest formal economic sector. 12 This relatively weak demand for higher education from sectors other than education and public administration implies private profit seeking industries do not signal strong demand for university education. There are some mismatches between the labor market demand for academic specialties and academic disciplines that university students study. At universities in Bangladesh, 31 percent of students are enrolled in arts and humanities courses, 27 percent are enrolled in business administration, 17 percent are enrolled in engineering. However, the market demands are somewhat mismatching. Supply of graduates from arts and humanities as well as engineering seem to exceed the market demand while business administration, science, and education seems short of the demand. Relatively small demand for engineering and technical knowledge may be related to the fact that employers expect more general skills from fresh graduates and plan to train job-specific skills after recruitment. Demand for education mostly comes from education sector enterprises – i.e. private schools. Figure 19: University enrollment by academic fields and employers’ skills demand Source: Authors’ analysis using ESS 2012 for demand and UGC 2011 for enrollment. Academic disciplines of higher education graduates do not always match their occupations in the formal sector. Figure 20 presents the number of workers in five sampled formal economic sectors by academic disciplines and proportion of workers who take professional level occupations. By absolute number, graduates with business major are the largest in the sampled formal sector labor market. But their presence in professional occupation befitting their academic 12 The selected five sectors constitute 91% of employment and 87% of enterprises in the formal sector. 26 discipline is considerably low as many of them take secretarial jobs. Science and mathematics graduates from universities are in high proportion in professional jobs, but this is not necessarily the case with college graduates. On the whole, there are no strong correlation between academic disciplines and occupational level.13 Figure 20: Number of graduates by academic disciplines and proportion of professional workers Proportion of Workers in Professional Number of Graduates Occupation (%) Source: Authors’ analysis using ESS 2012 3.3. Skills Matching Mechanism – Recruitment Academic degree is considered the most important criterion for selecting a candidate in professional occupations. 61 percent of establishments consider academic degree is important. By economic sector, 85 percent of education sector establishments, 79 percent of finance sector establishments and 73 percent of public administration consider academic qualifications are important. On the other hand, commerce and manufacturing sectors consider work experience is the most important criterion for selecting the candidate. This trend is consistent for both professional and non-professional occupations. A tendency by sector is that education, finance, and public administration weighs more on academic degree while commerce and manufacturing sector weighs relatively more on work experience. This likely corresponds to the formality of recruitment process as commerce and manufacturing sector tend to rely more on personal network for recruitment of staff (table 9). 13 This does not deny the differences in specific occupations within the same occupation level. Some professionals from business discipline may work as accountants and professionals from science major may work as researchers. 27 Table 9: Criteria for selecting new hires in each sector (%) Public Job type Experience Commerce Education Finance Manufacturing administration Total Professional Academic degree 53 85 79 34 73 61 Work experience 61 57 69 48 48 54 Skill set 56 49 51 34 40 43 Interview 31 40 41 17 43 31 Personal network 23 7 13 14 9 11 Political affiliation 2 5 8 3 10 5 Non- Academic degree 26 42 54 14 43 31 professional Work experience 39 32 39 38 25 35 Skill set 26 18 22 19 20 20 Interview 19 21 26 8 21 16 Personal network 10 1 6 10 4 6 Political affiliation 2 0 6 2 5 2 Source: Authors’ analysis using ESS 2012 Two most common modes of advertising vacancies are media (e.g. newspapers) and personal network. Overall, 42 percent of establishments uses media for advertising vacancies and 29 percent uses personal network (multiple answers allowed). Only in manufacturing sector, personal network is the primary means of advertising vacancies. Education, finance, and public administrations, which tend to consider academic degree as most important criteria for selecting candidates, rely relatively less on personal network. Table 10: Two most common modes of advertising vacancies by sector Primary Secondary Mode % Mode % Commerce Media 40 Personal network 34 Education Media 46 public employment services 16 Finance Media 47 internet 19 Manufacturing Personal network 47 Media 31 Pub Admin Media 50 public employment services 23 Total (weighted) Media 42 Personal network 29 Source: Authors’ analysis using ESS 2012 Yet, more than half of formal sector workers find jobs through informal networks. 54 percent has found the current job through the informal networks: of which 21 percent is family or relatives, 21 percent is friends, and 11 percent is from people of the same village or town. Even though academic degrees are used as important minimum criteria for selecting workers in the formal sector, only 42 percent of enterprises use media to advertise vacancies. There appears to be limited efforts between industry and education providers to match student skills with jobs— less than 1 percent students find jobs through employment support provided by educational institutions, and less than 1 percent find jobs through job fairs (figure 21). The time required for finding jobs is usually shorter for informal means. While it commonly takes more than four weeks for jobs seekers to find a job by using formal channels such as media advertisement, public and private recruitment agencies, they spend about a week to find jobs using informal means. 28 Figure 21: How workers find jobs and median weeks to find jobs Median week of finding jobs Share (%) Source: Authors’ analysis using ESS 2012 For workers with relatively low education, having family or relatives in the same establishment is a key factor for joining the formal sector work. While 10 percent of bachelor holder and 2 percent of post graduate degree holders have family or relatives in the same establishment, about 20 percent of primary, junior secondary, and senior secondary graduates have relatives or family members in the same establishment (figure 22). Highest share is observed among SSC(voc) and HSC(voc) graduates. By industry, manufacturing has the largest share of workers who have relatives or family members in the workplace. Public administration sector also sees relatively high share of workers having family or relatives in the same establishment. Figure 22: Percentage of workers who has family or relatives working in the same establishment 45% 40% 40% 35% 33% 30% 25% 20% 20% 19% 19% 19% 20% 15% 15% 15% 12% 13% 13% 10% 10% 5% 5% 6% 5% 2% 0% Commerce no education Education incomplete psc psc jsc ssc hsc sscvoc hscvoc diploma bachelor Manufactur post graduate Finance Total Pub Admin By industry By education Source: Authors’ analysis using ESS 2012 29 Professional occupations are generally more competitive than non-professional categories of workers. For one managerial post opened, 10.5 applicants apply for the post on average. Among the non-professional occupations, clerical support work is more competitive than other types. Figure 23: Average number of applicants per post by occupation 12.0 10.5 10.0 8.2 8.0 7.0 6.0 4.0 4.3 3.8 4.0 3.3 2.0 1.8 2.0 0.0 Managers Professionals Technicians Clerical Service Sales Skilled Construction, Plant and Elementary support workers workers agriculture craft machinery occupation Source: Authors’ analysis using ESS 2012 3.4. Post-Employment Skills Building Opportunities Post-employment training represents a major part of the total education and training received by workers during their life. Enterprises, especially those in the formal sector, play a major role in providing skills training to workers in the Bangladesh labor market. ESS has found that 14.5 percent of firms provide formal off-the-job training, 18.8 percent of firms provide on- the-job training, and 68 percent of firms expect that informal training is happening.14 In contrast, about 7 percent of workers have participated in off-the-job training and 30 percent of workers have received on-the-job training. 34 percent of formal sector workers reported that they received any kind of formal training after employment. 14 Off-the-job training takes place away from normal work situations – implying that the employee does not count as a directly productive worker while such training takes place. On-the-job training, on the other hand, takes place in a normal working situation, using the actual tools, equipment, documents or materials that trainees will use when fully trained. 30 Table 11: Proportion of firms that provide formal off-the-job/on-the-job training or informal training Firm of which: Firm arranged/ Staff may learn of which: arranged/funded was funded on-the-job job informally (if was in- structured training outside training (past 12 no formal on-the- house (%) (past 12 months) (%) (%) months) (%) job provided) (%) By industry Commerce 7.7 4.3 3.4 26.1 73.7 Education 22.0 1.2 20.8 6.4 62.1 Finance 32.3 12.8 19.5 44.0 77.2 Manufacturing 1.5 1.5 0.0 17.9 71.2 Pub Admin 30.7 5.4 25.3 41.2 71.5 By size Small (≤ 20) 13.0 1.7 11.2 11.9 67.8 Medium (21-70) 20.2 4.6 15.5 27.0 68.5 Large (≥ 71) 9.2 5.6 3.6 39.9 68.6 Total 14.5 2.9 11.6 18.8 68.0 Source: Authors’ analysis using ESS Inequities in skill-development opportunities increase in post-formal education. Figure 24 shows five different types of training opportunities available in post-formal education: short training, apprenticeship, formal off-the-job training within enterprises, formal on-the-job training within enterprises, and self-motivated training or learning. In all training opportunities, workers with more formal education are more likely to receive training. Formal on-the-job training seems the most equitably available opportunity to workers with less education. This is resulted from a combination of the facts that employees with more education will be offered more post- employment training opportunities and that they will seek and take more post-employment training opportunities. Figure 24: Use of post-formal education training opportunities by education level (%) Source: Authors’ analysis using ESS 2012 Note: TVET graduates include SSC (vocational), HSC (vocational), and Diploma graduates, but not trainees of short courses or non-formal TVET courses. 31 Enterprises seem to provide job-specific skills training while they expect more general skills from newly recruited workers. 86 percent of post-employment off-the job training is focused on job-specific skills, followed by computer skills (6 percent) and general thinking skills (4 percent). Earlier sections have discussed that enterprises are more prone to expect general or behavioral skills rather than job-specific skills from newly recruited workers. These two findings present enterprises’ attitude where they expect general (transferrable) skills from fresh workers and provide job-specific (non-transferrable) skills after employment. Government institutions and formal education institutions are major providers of post- employment training. While the survey is focused on five largest formal economic sectors, which includes public administration and education, the role of government institutions in providing post-employment training is noteworthy. 54 percent of off-the-job training is conducted through government institutions. 23 percent and 9 percent of training is provided respectively by private training institutions and public vocational and technical institutions. These statistics reminds that the role of government institutions and formal education institutions in providing post-employment training is quite significant. Figure 25: Types of off-the-job training Figure 26: Share of training providers Manage- University Computer ment skills 2% General 1% Language Public behavioral 6% skills vocational Industry skills 1% and 2% associa- technical tions institutions 12% General 9% thinking skills Govern- 4% Private ment Job- training institutes specific schools/ 54% skills institutes 86% 23% Source: Authors’ analysis using ESS 2012. Source: Authors’ analysis using ESS 2012. 32 4. Conclusions The ESS was conducted in 2012 as part of background studies for the Bangladesh ESR. One of the unique features of the survey was the collection of skills related information from both employers and employees in the same enterprises. The survey covered five economic sectors of the formal sector, including manufacturing, commerce, education, finance, and public administration. This background report was prepared for the purpose of documenting the survey properties, including the scope of the survey, sampling, and instruments, as well as providing basis descriptive statistics generated from both the employer and employee modules of the ESS. From the initial statistical analysis of the ESS data, several key findings and policy implications emerged. 4.1. Summary of Key Findings The formal sector labor market in Bangladesh is characterized by a large share of low educated workers, which leads to a considerable advantage of higher levels of education. In the formal sector labor market, 28 percent of workers have primary education or less, and 48 percent has secondary education or less. Formal education is the key determinant of occupations and earnings. About one-quarter of workers have professional level occupations in the sampled five economic sectors, but the share of professional level workers is more than 80 percent among post-graduate workers. Education, in close link to occupations, also determines the average entry salary. While bachelor or post-graduate degree holders on average receive more than Tk. 10,000 per month, workers with less than or equal to JSC holders receive less than Tk. 5,000 per month. It appears that a major part of the current labor force lacks both cognitive skills, such as literacy and numeracy, and non-cognitive skills for effectiveness at work. An assessment of primary education level competency in literacy and numeracy revealed that even workers with SSC certificate scored on average 5.5 points out of 8 questions in Bangla and 6.2 points out of 8 questions in mathematics. This implies that graduates of each educational level do not have acquired right competencies for the respective levels of education they completed. The survey has shown that non-cognitive skills are generally more highly valued than cognitive skills by the employers – given the educational qualifications are met. However, an assessment of non- cognitive skills by employers has also indicated insufficient non-cognitive skills among employees – especially among non-professional workers. There seems to exist some forms of inconsistencies between skills demand and supply. In formal sector, which constitutes about 11 percent of employment in Bangladesh, half of the employment demands are for less than secondary education graduates. It is likely because a large part of recent economic and employment growth is driven by the manufacturing sector. In manufacturing and commerce sectors, 93 percent and 78 percent of labor demand is for workers with secondary education or less. A large part of demand for university graduates comes from education, finance, and public administration sectors. While university graduates are more likely to take professional levels of occupations, there seems to exist a mismatch between the labor market demand for academic specialties and academic disciplines that university students study. The process of skills matching, as observed in recruitment process, is rather informal. More than half of formal sector workers find jobs through informal networks, including family or 33 relatives, friends, and people from the same village or town. Although academic degree is considered the most important criterion recruitment, only 42 percent of enterprises use public media to advertise vacancies. There appears to be limited efforts between industry and education providers to match student skills with jobs. Inequalities in skills development opportunities increase in the post-formal education – as participation in pre-employment training and post-employment training is more commonly provided to and received by educated workers. Participation in pre-employment training opportunities, including short-courses, apprenticeships, and internships, is more common among TVET graduates and post-secondary degree holders, such as diploma holders or bachelor degree holders, than uneducated or less educated workers. This finding indicates that the workers with low levels of formal education are not benefiting from such skills development opportunities. Inequalities in access to training opportunities grow larger even after workers join the labor market. Formal off-the-job training is commonly offered by the enterprises to those who have TVET or post-secondary degree holders but not to workers with low educational levels. Only on- the-job training is relatively equitably provided to all workers. 4.2. Policy Implications From the findings of the ESS, a few key policy implications have emerged. These policy implications concern only the formal sector employment, and policy discussions for the skills development for the wider labor market, including informal sector, will be further discussed in the ESR. There should be a stronger tie between the education system and the labor market. The ESS has discovered that the tie between the education system and the labor market is weak in every aspect. First, the skills that education systems are providing to students are not necessarily fitting the labor market needs in terms of the kinds and the quality. The labor market demands higher non-cognitive skills, but the education system pays less attention to this type of skills. Second, communications between the educational and training institutions and employers seem limited. There is no systematic support to the graduates of educational and training institutions for job placement. It is also rare that the employers discuss with training institutions about their skills needs. Because skills demand is evolving in the labor market as the economic structure changes, it is important that educational and training institutions keep being informed about the skills demand and respond to the demands. The labor market and skills development policy should be aligned to the economic growth trend. The government of Bangladesh has set education and training as one of the pillars for economic development. In its Vision 2021, the government aims to develop skilled workforce especially for migration work and for the ICT sector (CPD 2007). While these sectors are important sources of growth, it is also important to objectively assess the main source of economic growth in the next decades. While it is important to diversify the economic structure and attract ICT sector to the domestic market, the largest volume of economy is still manufacturing and agriculture. Notably, manufacturing sector led by garment industry has seen the fastest growth during the past decade. It is therefore important to assess the employment generating economic sectors and sectors that are growing over the next decades. Unless the 34 economic structure changes drastically over the next decade, better quality of basic skills, including cognitive and non-cognitive, likely continues to be most demanded by the labor market. The existing workforce also needs skills development opportunities. While the main beneficiaries of educational and training programs are usually new generations of students, a large part of today’s existing workforce will continue to contribute to the economy for decades. Therefore, it is important to bring up the skill levels of the existing workforce for higher productivity. The ESS discovered that even in the formal sector, which consists of only 11 percent of the labor force in Bangladesh, 28 percent of workers have up to primary education and 48 percent of workers have up to secondary education. 30 percent of workers in their twenties have less than primary education in the formal sector, and they will remain in the labor force for the next 30 years. To achieve a more robust economic growth, upgrading skills of this already working uneducated labor force is important. Such a policy is also important from a perspective of reducing inequalities. The ESS has found that the workers with higher levels of formal education will have more education and training opportunities after joining the work force. Providing educational and training opportunities to those who have less formal education also helps reducing inequalities in such educational and training opportunities. 35 References Centre for Policy Dialogue (CPD). 2007.; Bangladesh Vision 2021. Dhaka. Enterprise Survey Website. http://www.enterprisesurveys.org/ Accessed on May 24, 2013. Hossain, S.S. 2012. Situation Analysis of SSC (voc) Institutions. Skills and Training Enhancement Project. Directorate of Technical Education. Martin, R.F. Villeneuve-Smith, L. Marshall, and E. McKenzie. 2008. Employability Skills Explored. London: Learning and Skills Network. McKinsey & Company. 2011. Bangladesh’s Ready-Made Garments Landscape: The Challenges of Growth. Apparel, Fashion & Luxury Practice. Rutkowski, J. 2010. “Demand for Skills in FYR Macedonia—Technical Note.” World Bank. Rutkowski, J. 2011. “Skills for Productivity and Competitiveness: The Employers’ Perspective.” Europe 2020 Poland: Fueling Growth and Competitiveness in Poland through Employment, Skills, and Innovation. Washington, DC: World Bank. University Grants Commission (UGC). 2011. Annual Report 2011. World Bank. 2007. Learning for Job Opportunities: An Assessment of the Vocational Education and Training in Bangladesh. Bangladesh Development Series Paper No. 19. World Bank. 2010. Stepping Up Skills For More Jobs and Higher Productivity. Human Development Network. Washington, DC. World Bank. 2012a. More and Better Jobs in South Asia. South Asia Development Matters. Washington, DC. World Bank. 2012b. Bangladesh: Economic Growth in Bangladesh: Achievements, Prospects and Challenges. Volume I: Main Report. Poverty Reduction and Economic Management Sector Unit. South Asia Region. World Bank. 2012c. The Right Skills for the Jobs? Rethinking Training Policies for Workers. R. Almeida, J. Behrman, and D. Robalino, Eds. Washington DC. 36 Annex 1: Occupational List Managers Chief executives, senior officials, and legislators Traditional chiefs and heads of villages Managing directors, administrative, and commerce Sales managers, production managers in agriculture, managers mining, and construction Business services and administration managers such as Specialized services managers, such as managers in Finance managers, Human resource managers, advertising health services, hotels, retail or wholesale, and sports and public relations managers center managers Professionals Science professionals such as physicists, astronomers, Administration professionals, sales and marketing, and chemists, geologists, biologists, farming or fisheries public relations professionals advisers, environmental protection professionals Social and religious professionals such as economists, Information and communications technology sociologists, authors, social workers, religious professionals, such as software developers, programmers, professionals, translators and Web developers Teaching professionals—all teachers Legal professionals, such as lawyers and judges Architects, planners, surveyors, and designers Librarians, archivists, and curators Health professionals such as doctors, nurses, midwives, Business and administration professionals, accountants, veterinarians, dentists, physiotherapists, and dietitians and financial advisors Engineering professionals, in industrial, mining, Creative and performing artists, such as dancers, actors, construction, and so on radio announcers, and musicians Mathematicians, actuaries, and statisticians Technicians and associate professionals Science and engineering associate professionals, such as Health associate professionals such as medical and dental engineering technicians, electrical engineering technicians, technicians, laboratory technicians, nursing associate mining and metallurgical technicians, power plant professionals, veterinary technicians and assistants, operators, incinerator operator, mining supervisors, community health workers, and ambulance workers construction supervisors, and draughts persons Administrative and specialized secretaries such as office Agricultural and forestry technicians supervisors, legal secretaries, and medical secretaries Business and administration associate professionals, such as Legal, social, cultural, and related associate professionals, finance dealers and brokers, credit and loans officers, religious associate professionals, athletes, sports coaches, insurance representatives, sales and purchasing agents, real photographers, decorators, library and museum estate agents, and property managers technicians, and chefs Ship and aircraft controllers and technicians, such as ships' Information and communications technicians, such as engineers, deck officers, ship pilots, air traffic controllers, user-support technicians, Web technicians, and and aircraft pilots broadcasting technicians Clerical support workers Office clerks, general secretaries, customer service clerks, Data entry clerks and data entry operators bank tellers and clerks, and debt collectors Client information workers, such as travel consultants and Accounting and bookkeeping clerks, payroll clerks, stock clerks, telephone operators, and receptionists clerks, mail carriers, and filing clerks Travel consultants and clerks Service workers Domestic housekeepers, cleaning and housekeeping Fortune tellers, undertakers, pet groomers, animal care supervisors in offices, hotels, and other establishments workers, and driving instructors Call center operators Travel attendants, conductors, and guides Personal care health workers, health care assistants, child Firefighters, police officers, prison guards, and security care workers, and teachers' aides guards 37 Hairdressers, beauticians, and related workers Cooks, waiters, and bartenders Building and housekeeping supervisors, building caretakers Sales workers Street and market salespersons, shopkeepers, shop Door to door salespersons, and contact center supervisors, sales assistants, and sales demonstrators salespersons Cashiers and ticket clerks Service station attendants Fashion and other models Food service counter attendants Skilled agricultural, forestry, and fishery workers Market-oriented skilled forestry, and fishery and hunting Market gardeners and crop growers workers Animal and poultry producers, dairy producers Subsistence farmers, fishers, hunters, and gatherers Construction, craft, and related trades workers Building and related trades workers, such as carpenters, Food processing, wood working, garment and other craft bricklayers, masons, plumbers, roofers, plasterers, and and related trades workers. Bakers, butchers, and pastry painters cooks Metal, machinery and related trades workers Printing trades workers Sheet and structural metal workers, molders, and welders Tobacco preparers and tobacco products makers Blacksmiths, toolmakers, and related trades workers Electrical and electronics trades Handicraft workers such instrument makers, potters, Garment workers, tailors, dressmakers, shoemakers, and jewelry workers, workers in wood, basketry, textiles and upholstery workers leather, sign writers, and decorative painters Underwater divers, blasters, fumigators, and other pest Wood treaters, cabinet makers, and related trades workers controllers Machinery mechanics and repairers Plant and machine operators, and assemblers/drivers Mining, mineral, and stone processing plant operators, and Chemical and photographic products plant and machine miners operators Well drillers and borers and related workers Other stationary plant and machine operators Cement, stone, and other mineral products machine Mobile plant operators such as earthmoving operators, operators crane operators Metal processing and finishing plant operators Locomotive engine drivers and related workers Car, van and motorcycle drivers, and bus and lorry Wood processing and papermaking plant operators drivers Rubber, plastic, and paper products machine operators Assemblers Textile, fur, and leather products machine operators Ships' deck crews and related workers Food and related products machine operators Elementary occupations Domestic, hotel, and office cleaners and helpers Street vendors (excluding food) Vehicle, window, laundry, and other hand cleaning workers Refuse workers and other elementary workers Agricultural, forestry, and fishery laborers Messengers, package deliverers, and luggage porters Laborers in mining, construction, manufacturing, and Odd-job persons transport Transport and storage laborers Meter readers and vending-machine collectors Food preparation assistants Water and firewood collectors Street and related sales and service workers 38 Annex 2: Literacy and Numeracy Tests Literacy 1 Please read aloud– “School” (in Bangla - Show 2 Please read aloud - " I have one pen and two Card) books"(in Bangla- Show Card) Interviewer marks: Interviewer marks: 1 Reading fluently 1 Reading fluently 2 Reading with some difficulty 2 Reading with some difficulty 99 Can’t read 99 Can’t read 3 Conversation-(Show Card) (Read List) 4 Poem-(Show Card) (Read List) 1 1 2 2 3 3 4 4 98 No Answer 98 No Answer 99 Can’t Read 99 Can’t Read 5 Punctuation- (Show Card) 6 Comprehension – (Show Card) 1 2 3 4 98 No Answer 99 Can’t Read 1 2 3 4 98 No Answer 99 Can’t Read 7 Please translate the following sentence to 8 Please translate the following sentence into Bangla. “Amena is my younger sister.” (in English - English. “He lives in a village” (in Bangla - Show Show Card) Card) Interviewer marks: Interviewer marks: 1 Translating correctly and fluently 1 Translating correctly and fluently 2 Translating with some difficulty 2 Translating with some difficulty 3 Can’t translate 3 Can’t translate 39 Numeracy 1 2637 2 124 × 25 = what is the correct answer? - 1528 (a) 868 What is the remainder of above mentioned subtraction? (b) 2900 (c) 3000 (a) 1009 (d) 3100 (b) 1109 (c) 1111 (d) 1119 3 At the time of Nabila’s fever Nabila took indicating 4 The price of duck is 200 taka and the price of hen is volume of medicine from the following liter cup? How 180.75 taka. Mita bought a duck and a hen. She gave the much medicine she took?(Show Card) shopkeeper a 500 taka note. How much taka the shopkeeper will return? Answer: Tk. ________________ (a) 3 milliliter (b) 4 milliliter (c) 5 milliliter (d) 6 milliliter 5 3 + 16 + 18= 6 264/2= (a) 27 (a) 102 (b) 37 (b) 123 (c ) 47 (c ) 132 (d ) 57 (d) 134 7 Convert 29 cm into meter. What is the 8 30/5+(8-3)*2= correct answer? (a) 2 (a) 0.029 meter (b) 6 (b) 0.29 meter (c ) 16 (c) 2.09 meter (d) 22 (d) 2.90 meter 40