Report No. 52 67432 South Asia Human Development Sector Baseline Survey: Labor Market Outcomes of Punjab TEVTA Graduates March 2012 Discussion Paper Series Report No. 52 South Asia Human Development Sector Baseline Survey: Labor Market Outcomes of Punjab TEVTA Graduates March 2012 __________________________________________________________ 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 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. Abstract Increasing employment among youth and increasing the earnings and job-stability of youth is important for Pakistan. This study examines the labor market outcomes of graduates from training institutes run by Punjab TEVTA, the largest technical and vocational education and training provider in the province of Punjab, Pakistan. The study uses an SMS-based survey of 7,840 graduates from 2010. This is a promising and inexpensive method to assess the impact of education and training in developing countries. Using SMS is feasible, fast, and very low-cost, but it comes with a set of challenges, notably a low response rate. We summarize lessons for future SMS-administered surveys. For the labor market outcomes, we find that only 39 percent of graduates are employed post training with considerable variation in employment outcomes across trades, districts, gender, and schools. We conclude that there is overall strong need for the improvement of quality and relevance of technical education and vocational training, and that some schools, trades, and districts are substantially better at linking to labor market demand than others. Acknowledgements This discussion paper is authored by Ayesha Khan and Andreas Blom. We are grateful to the former Chairman of Punjab TEVTA, Mr. Saeed Alvi, and the MIS team at Punjab TEVTA, for their support. We would like to thank Abdul Rehman Naeem and Asim Fayyaz for developing the survey platform, and Sangeeta Goyal, Huma Ali Waheed and Zubair Khursheed Bhatti for their valuable technical input into the survey instrument and design. CONTENTS I. Introduction .................................................................................................................................... 1 II. Methodology ................................................................................................................................... 2 Rationale for using SMS to conduct baseline survey ...................................................................... 2 The Sample ...................................................................................................................................... 4 Questionnaire ................................................................................................................................... 5 Platform used ................................................................................................................................... 6 Process ............................................................................................................................................. 6 III. Results ............................................................................................................................................. 7 Current employment status .............................................................................................................. 7 Number of hours worked per week ................................................................................................ 11 Income earned last month .............................................................................................................. 12 Relationship between Training and Current Job ............................................................................ 12 Effect on Survey Completion and Response Rates of an Incentive to Reply ................................ 13 Lessons Learned for Future Mobile-phone Tracer Studies ............................................................ 14 IV. Conclusion .................................................................................................................................... 15 Annex 1 ......................................................................................................................................... 17 Annex 2 ......................................................................................................................................... 22 Annex 3A: Questionnaire (Phase 1) .............................................................................................. 38 Annex 3B: SMS Flowchart (Phase 1) ........................................................................................... 40 Annex 3C: Questionnaire (Phase 2) .............................................................................................. 41 Annex 3D: Questionnaire (Phase 3) .............................................................................................. 42 Tables Table 1: Proportion of Household Members with a Mobile Phone, Punjab MICS 2007-08 ........................ 3 Table 2: Descriptive Statistics - Survey Sample ........................................................................................... 5 Table 3: Baseline Survey – All Phases ......................................................................................................... 7 Table 4: Survey Question – Current Employment Status ............................................................................. 7 Table 5: Top 10 Trades by Employment Rate .............................................................................................. 9 Table 6: Top 5 Districts by Employment Rate ............................................................................................. 9 Table 7: Survey Question: How Many Hours Do Respondents Work Each Week? .................................. 12 Table 8: Survey Question – Income Earned Last Month ............................................................................ 12 Table 9: Survey Question – Relationship between Job and Training ......................................................... 13 Table 10: Effect of an Incentive on Survey Completion Rates ................................................................... 13 Table 11: Effect of an Incentive on Survey Response Rates ...................................................................... 14 Table 12: Comparison of Population-Sample Characteristics, by Trade .................................................... 17 Table 13: Comparison of Population-Sample Characteristics, by District ................................................. 20 Table 14 Comparison of population-sample characteristics: By gender..................................................... 21 Table 15: Pair-wise T-test of Difference in Employment Rate across Top 10 Trades ............................... 22 Table 16: T-test of Employment Rate, by Gender ...................................................................................... 23 Table 17: Employment Rate and Mean Income by Trade .......................................................................... 24 Table 18: Employment Rate by Duration of Course ................................................................................... 26 Table 19: Pair-wise T-test of Difference in Employment Rate across Duration of Training ..................... 27 Table 20: Employment Rate by Level of Previous Education .................................................................... 28 Table 21: Employment Rate and Mean Income by District ........................................................................ 29 Table 22: Employment Rate and Mean Income by Gender ........................................................................ 30 Table 23: Employment Rate and Mean Income by Institution ................................................................... 32 Figures Figure 1: Employment Rate by District ...................................................................................................... 10 Figure 2: Employment Rate by type of TVET institution (%).................................................................... 10 Figure 3: Employment rate by sub-group of Technical Training Centre .................................................... 10 Figure 4: Employment Rate by Duration of Course ................................................................................... 11 Figure 5: Employment Rate by Duration of Course ................................................................................... 27 Figure 6: Employment Rate by Prior Education Level ............................................................................... 28 Figure 7: Employment Rate by Prior Education Level (More than 15 Observations) ................................ 29 Figure 8: Employment Rate by Institution .................................................................................................. 31 I. INTRODUCTION 1. One of the key indicators for measuring performance of the Technical and Vocational Education and Training (TVET) sector is the labor market outcomes of its graduates. As part of the Pakistan Education Sector Review that focuses on technical education and vocational training, this survey establishes background and labor market information for a sample of trainees who graduated from public training institutions run by the Punjab Technical Education and Vocational Training Authority (P- TEVTA) in 2010. 2. The Government of Punjab awards high priority to the development of its TVET sector. It boasts 456 technical education and vocational training public institutions in the province. However, these institutions face a number of important challenges, notably relevance of training is reportedly low, training opportunities for youth are few, investments are far in-between, infrastructure is increasingly becoming outdated and accountability for results could be increased. The Province has taken several steps to address some of these, the most significant being re-organization of the sector by providing autonomy to the Punjab Technical Education and Vocational Training Authority (P-TEVTA) and giving it administrative authority over all TVET related public activity in the province. 3. This study sets a baseline for labor market outcomes of the graduates, and is informed by an SMS-based survey of graduates. The introduction of an incentive in the form of mobile phone credit was also tested to investigate whether it increased survey response and completion rates. 4. The survey was administered to 7,840 graduates in 3 phases: Phase 1 marks the pilot phase; in Phase 2 the survey was rolled out after design adjustments informed by Phase 1 and; Phase 3 was conducted at the end to investigate the effect of an incentive in the form of mobile phone credit on the survey response rate. 5. The overall response rate of the survey was 16 percent. This introduces a possibility that the survey suffers from significant biases, and one should therefore be cautious in drawing conclusions from the study. Further, the study allowed us to draw a number of lessons for future mobile phone tracer studies. 6. The findings of the survey indicate a strong need for the improvement of quality and relevance of technical education and vocational training. Excluding the group of graduates in further studies, the employment percentage is 39 percent while 61 percent remain without job, almost all of which were looking for employment. 28 percent of the respondents were engaged in further education. As expected employment outcomes differ across trades, districts, gender, and schools. Among other things, this variation indicates that training is substantially better linked to labor market demand in some schools, trades, and districts. Details on the findings are presented in the rest of this paper. 7. This paper is organized as follows. After this introduction follows a section on methodology, including data collection method (mobile phone), the questionnaire, and the sample. The third section describes the results, while the fourth concludes and draw lessons for future tracer studies. 1 II. METHODOLOGY Rationale for using SMS to conduct baseline survey 8. Paper-based surveys are typically expensive and require a substantial duration of time to train the surveyors, conduct the survey, and enter the data obtained. The fact that the vocational training and technical education trainees are literate/educated (see Table 2) presented us with an opportunity to administer the survey via SMS without having to conduct a more traditional survey where the respondents were interviewed, necessary had they been illiterate. Developing a simple platform to conduct the survey was not expensive or did not take long, and graduates could be contacted directly. Given low SMS costs, the cost of designing a platform to administer the survey was minimal and required only the services of a consultant.1 9. As shown in a Punjab household survey from 2007-08, the Multiple Indicator Cluster Survey, the mobile phone penetration rate in Punjab is quite high: 71 percent of households own mobile phones, and almost 29 percent of households belonging to the lowest wealth quintile own a mobile phone. Since then, mobile phone penetration is expected to have further increased. 1 The combined cost of the consultant‟s services and the SMS costs is Rs. 77,000, or approximately USD$865. 2 Table 1: Proportion of Household Members with a Mobile Phone, Punjab MICS 2007-08 Proportion of households with mobiles (%) Punjab 71.0 Area Rural 65.0 Urban 84.3 Major city 87.8 Other urban 80.8 Education of Household head None 57.9 Primary 73.6 Middle 79.1 Secondary 86.4 Higher 94.0 Madrassa/NSC 66.0 Missing/DK 68.2 Wealth index quintiles Lowest 28.8 Second 60.4 Middle 79.4 Fourth 89.5 Highest 96.9 Source: Bureau of Statistics, Planning and Development Department, Government of the Punjab – Multiple Indicator Cluster Survey, Punjab 2007–08, Lahore, Pakistan. 10. Despite the advantages of using SMS to conduct the baseline survey, the use of SMS poses several limitations. First, the sample of graduates with mobile phones may not be representative of the population of TVET graduates – as a matter of fact, the sample may consist of graduates from relatively higher income quintiles. This introduces a bias in the results. Second, the response rate is expected to be much lower than that of a paper-based/interview-based survey given that the response is dependent wholly on the graduate‟s willingness to respond and cannot be elicited or encouraged by the physical presence of an interviewer. Also, the graduates were not informed of the survey and thus did not expect it, potentially further reducing the response rate. Third, the use of SMS necessarily limits the number of questions in the survey, given that there are costs, however minimal, to the graduate to reply. There is also a limit on the number of characters which can be sent in each SMS, thus placing constraints on the language used, as well as the number of forced-response choices which can be sent with each question. Fourth, a dataset with updated mobile phone numbers must be accessible. Last, the order of the questions must be structured, so as to ensure that the most important information is obtained first in the event that the respondent does not complete the survey. This may not be possible with all surveys. 3 The Sample 11. At the time of sample identification, the Management Information System cell at P-TEVTA was in the process of collating data on trainees who graduated in 2010 from its training institutions. P-TEVTA had data available for 13,171 graduates. The data was downloaded in May 2011, so the population consists of graduates whose data was already present in the database on that day. The focus of the tracer study was on graduates from technical and vocational education and training at the diploma (post- secondary level) and the certificate level (vocational and technical secondary education). Bachelor-level students, for example in commerce were excluded in order to measure outcomes for non-tertiary technical and vocational education and training. 12. The survey design uses SMS to administer the survey to the graduates, so the larger sample was further filtered to include only those graduates with valid mobile numbers. This reduced the number of graduates by about 40 percent to 7,840. Table 12, Table 13, and Table 14 in Annex 1 show the change in the sample structure with respect to trade representation, location, and gender. The proportion of graduates across the 36 districts sees little variation except for the district of Rahim Yar Khan where the proportion of graduates is halved, and Sahiwal, which sees its representation increase by almost 50 percent. 13. Representation across trades doesn't change by more than 2.5 percent (positively or negatively) from the data set to the sample with valid phone numbers. However, some trades are not represented in the sample (those are marked in italic in Annex 1, Table 12), but only a very small percentage of graduates are enrolled in these courses in the population. Overall the sample appears to be representative of the spectrum of programs in the province. The ten most popular courses by enrolment accounted for 57 percent of all enrolment, with the Diploma in Commerce accounting for over 20 percent of enrolment, followed by the Certificate in Computer Applications (9 percent), and the Mechanical DAE course (almost 6 percent). The sample may be under-representative of females. Information on gender was available for approximately 72 percent of graduates in the dataset of graduates, of which 32 percent were female graduates. Missing information on gender was filled in based on the name of the graduate. The share of female graduates in the sample with valid phone numbers is about 23 percent. It would therefore seem that female graduates are underrepresented in the sample. However, given the missing gender data in the sample, it is difficult to make any definitive statements with regards to female overrepresentation or underrepresentation in the sample. The following table illustrates basic descriptive statistics for the sample. 4 Table 2: Descriptive Statistics - Survey Sample Total number of graduates 7,840 Male 76.8% Female 23.2% Number of trades 104 Number of districts 36 Previous education (only available for 2,350 graduates) Level % of graduates Illiterate 0.08 Primary 1.53 Middle (8 years of schooling) 25.23 Under Matric (below 10 years of schooling) 1.15 Matric (10 years of schooling) 56.63 FA FSc Icom 10.75 Undergraduate (BA BSc BCom BEd) 2.93 Master (MA MSc MCom MEd) 0.76 CCA 0.08 DCom (Diploma – post-secondary) 0.51 DAE (Diploma – post-secondary) 0.04 Religious education 0.17 Other 0.13 14. Information on previous education was limited – only available for 2,350 graduates. As seen in the sample with information on previous education, most students would have completed either middle school (8 years of schooling) or Matric (10 years of schooling) in order to qualify for technical and vocational education and training. Questionnaire 15. The survey questions sent to the graduates can be seen in Annexes 3A, 3B and 3C. The questions are sent in roman Urdu. As can be seen, though there are minor variations in the surveys, the following information is collected:  Current employment status  Numbers of hours worked per week  Income earned last month  Whether training was useful to current employment 16. The information received was appended to the database of graduate information downloaded from the P-TEVTA MIS database. The database already contained information such as the graduate 5 name, gender, mobile phone number, address, name of institution and course attended, duration of the course, district, marks obtained, and education level attained before training. Platform used 17. Four SIM (Subscriber Identity Module) cards were used to send messages to trainees using a modem connected to a computer, which sends and receives messages through an SMS Gateway. This was developed using SMSLib which is a JAVA library for sending/receiving SMS. The Core Application sends out the surveys, parses the incoming messages and generates the responses. This was developed as a simple state machine in PHP using a PHP framework called Yii. Both parts of the application communicate to each other using a MySQL database, which is where the data received is stored. Process 18. The sample of graduates with valid mobile numbers was split into 3 groups: Phase 1, Phase 2 and Phase 3. 19. Phase 1 marks the pilot of the survey, in which the survey was administered to 600 randomly selected graduates from the sample over the course of 4 days. The survey questions sent can be seen in Annex 3A. The 600 graduates were split into 3 further groups: Group 1 to receive no incentive, Group 2 to receive Rs. 10 (US$ 0.11) upon completion of the survey, and Group 3 to receive Rs. 30 (US$ 0.34) upon the completion of the survey. The incentive was not offered until the respondent had confirmed his/her identity and the name of the training institute; hence the effect of the incentive can only be seen on the survey completion rate and not the response rate. 20. The pilot revealed certain areas of the survey which required improvement or change. Details are provided in the “Lessons Learned� section of this working paper. Design adjustments were made to shorten the number of questions in the survey by combining questions where possible; the order of the questions was rearranged so that the critical questions were asked earlier during the survey; and the incentive was revoked because of the difficulty in transferring the credit to those who completed the survey. Also, given the lack of “credibility� of the survey illustrated by the numerous messages asking for further identification, it was decided that instead of sending the survey on behalf of the trainee‟s institution, it would be sent out on behalf of Punjab TEVTA. 21. In Phase 2, the survey (see Annex 3B) was sent to 6,840 graduates over a 12-day period2, incorporating the changes described above. No incentive was offered to any of the graduates from Phase 2. 22. Phase 3 was used as to test the effect of offering an incentive (credit) at the beginning of the survey. Two subgroups of 200 randomly chosen graduates each were sent Rs. 10 and Rs. 30 separately. The survey from Phase 2 was used, adjusted only to provide the incentive and collect information necessary to send the credit (see Annex 3C). 2 The rate at which the survey was sent was slowed down because some respondents tried calling the number back, slowing the program down. 6 III. RESULTS 23. The table below shows survey response and completion rates. The response rate is the proportion of graduates from the sample who answer at least one question. The completion rate is the number of surveys completed by respondents as a proportion of the number of surveys which receive at least one response. As evident from the table, the adjustments to the phase 1 questionnaire seemingly succeeded in raising the share of respondents who completed the survey. Table 3: Baseline Survey – All Phases Phase 1 Phase 2 Phase 3 All phases (pooled) Total surveys sent 600 6,840 400 7,840 No. of surveys with at least one response (1) 118 1,148 46 1,312 Response rate 19.7 16.8 11.5 16.7 Number of completed surveys (2) 57 691 35 783 Completion rate [(2)/(1)*100] 48.3 60.2 76.1 59.7 No response 482 5,692 354 6,528 24. The rest of the section lists the key findings of the survey. Detailed results are presented in Annex 2. Minor discrepancies may be present in the figures given that the structure of the questions from the Phase 1 survey differed slightly from Phases 2 and 3. Current employment status Table 4: Survey Question – Current Employment Status Type of No. of Percentage Percentage Percentage employment respondents Private 197 21.1 28 Employed employment 39 Government 25 2.7 employment Own/family 42 4.5 business employment Further 262 28.1 28 Excluded training/study Not employed 406 43.6 44 Not employed 61 Total (no. of 932 100 100 100 responses / %) 7 25. The current employment status of the respondents to the related question is presented in the table above for all three phases. If the respondents in further education and training are excluded, which is standard for calculation of employment rates, the employment percent is estimated to 39%.3 More than 93 percent of the unemployed respondents were looking for a job.4 It is likely that with time, the share of graduates with a job increases as graduates gain practical experience and become more successful in contacting employers. Although there is no information on how long the graduates have been in the labor market except for the year of graduation, the unemployment percentage clearly indicates that youths face problems transitioning from TVET school to a job. This could be for several reasons: (i) low relevance and/or quality of education, including a lack of practical skills; (ii) little job-search assistance on how to find a job; (iii) reduced connections to employers and no assistance was provided in this regard, and (iv) stagnant economy with few employers hire. These are reasons that are likely to vary substantial across the trades, gender, schools, districts, and prior education. We explore this further in the next paragraphs. 26. The following table shows the corresponding employment rates for the top 10 trades which account for over 57 percent of graduate responses.5 The table excludes trades for which the number of responses was 15 or less. Table 15 in Annex 2 shows that there is no statistically significant difference in the average employment rate amongst the top 5 trades; however, when the top 10 trades are considered, the employment rate for those with training in the Draftsman Civil (G-III) trade is statistically significantly lower than the employment rates of those in Electrical (DAE) and Civil (DAE) at the 5 percent level, and those in Diploma in Commerce and Certificate in Computer Applications at the 10 percent level. The employment rate for those graduates with a Diploma in Vocational Girls is lower than that of those graduates with training in Electrical (DAE), significant at the 10 percent level.6 The bottom line is that employment varies substantially between trades. Our main interpretation is that some trades are more relevant to the labor market needs of the province and/or of higher quality, while others are unfortunately unrelated to demand and/or of low quality, and graduates consequently face unemployment upon graduation.7 3 95 percent confidence interval: 35.7%-43.1%. 4 Please note that although 406 respondents are listed as unemployed, only 376 reply to the following question asking whether or not they are seeking employment. 5 Does not include further training/studying responses. 6 Pair-wise t-tests were conducted for the top 10 trades, under the assumption that variances are unequal within each pair, given that the size of each group differs. 7 Two supplementary interpretations are that the employment percentage increases with (a) the required level of education, for example DAE courses (diploma) require at least matric, which is not required by certificate level courses; and (b) the length of the courses. We explore this below. 8 Table 5: Top 10 Trades by Employment Rate Trade Employment rate No. of responses Electrical (DAE) 51 51 Civil (DAE) 50 36 Welder 44 18 Diploma in Commerce (Diploma 2 Years) 44 70 Certificate in Computer Applications 44 75 Electrician 38 24 Mechanical (DAE) 37 60 Electrical (G-III) 29 17 Diploma in Vocational Girls ( Diploma 2 28 18 Draftsman Civil (G-III) 20 15 Note: Excludes trades with less than 15 responses 27. The male employment rate is over 12 percentage points higher than the female employment rate (41% versus 29% – see Table 16: T-test of Employment Rate, by Gender , Annex 2). The difference is statistically significant at the 5 percent level. A number of factors could explain this substantial gender difference. First, gender specific factors are likely to be associated with job-search efforts and mobility. Second, there are likely to be systematic gender differences in educational factors affecting employment, notably trades. Most females graduate from courses in dress-making, beautician courses, glass-painting, home-economics, office automation/secretarial services, etc. These courses may have lower labor market relevance than traditionally male-oriented trades. 28. Employment rates for the top 5 districts are shown in Table 6. These districts account for almost one-fifth of graduate responses. The table excludes districts for which the number of responses is less than 15. Pair-wise t-tests amongst the top 5 districts reveal no statistically significant differences in the employment rate at the 1, 5 or 10 percent levels, except between Lodhran and Sahiwal, which is statistically significant at the 10 percent level. Figure 1 shows the employment rate by district for those districts with a minimum of 10 observations. Table 6: Top 5 Districts by Employment Rate District Employment rate No. of responses Lodhran 67 15 Bhakkar 54 26 Bahawalpur 51 35 Sargodha 51 37 Sahiwal 43.3 180 9 Figure 1: Employment Rate by District Employment rate by district (%) (Min. 10 observations) 80 67 57 54 54 51 51 60 45 43 42 40 40 38 33 33 33 31 29 40 19 18 14 20 0 0 Employment rate 29. The employment rates differ substantially across the types of TVET institutions. There are graduates from 6 types of institutions in the survey (there were no responses from graduates from the seventh type, Agricultural Machinery Training School). Graduates from the Institutes of Commerce have the highest employment percentage (51%), followed by graduates from colleges of commerce (46%) and technology (43%), graduates from technical training centres (37%), technical training institutes (33%), and graduates from vocational training centres, who have the lowest employment rate (28%). The differences seem to signal a higher success in commerce streams than in technical streams, however, gender differences are likely to be part of the explanation. 30. There are several sub-groups of Technical Training Centers, see below. The employment outcomes are relatively similar across the different sub-groups, with the exception of the women Centers where graduates have a lower employment rate (although it is above the average employment rate for female in the total sample. Figure 2: Employment Rate by type of TVET Figure 3: Employment rate by sub-group of institution (%) Technical Training Centre 60 45 42 51 39 Employment rate in % 50 46 43 40 37 Employment rate in % 37 35 32 33 40 33 28 30 30 25 20 20 10 15 0 10 5 0 G Tech GTTC GTTC GTTC GTTC Trg Ctr (ABAD) (DMTC) (M) (W) Note: Only employment percentage based upon a minimum of 10 observations are shown. 10 31. The employment rate seems to be unrelated to the duration of the program. Interestingly, the employment rates for those who attended courses lasting 12 months are statistically significantly lower than for those who attended courses 3, 6, 24 or 36 months long. While the employment rate for those who attended 3 month courses is the highest, it is not statistically significantly higher than those who attended longer courses (the exception being 12 month courses).8 9 This is a puzzling finding, which could be related to differences in the background of the graduates between those in short versus long duration courses. We therefore caution against policymaking solely based upon this finding. Figure 4: Employment Rate by Duration of Course 60 Employment rate in % 50 51 40 41 43 39 30 20 24 10 0 0 3 6 12 24 36 Duration of course in months Employment rate Linear (Employment rate) 32. Caution is warranted when interpreting these results. The representativeness of the sample is compromised by potential biases stemming from the fact that not all graduates have a mobile phone and only 1 in 6 graduates answered the survey. It could be that the outcomes of those who responded systematically differed from the total sample. However, it is not clear whether such biases increase or decrease the employment percentage. Further, the sub-categories rely on a low number of responses to the survey questions. Also, given the varying duration of different courses, it is difficult to estimate how long the graduates were in the labor market before they were surveyed, as no data on graduation dates was available. Finally, the names of trade courses are not standardized, and have been kept in their original form for the purpose of this study. It is possible that some courses are actually the same but have been grouped separately because of differences in spelling or notation. Number of hours worked per week 33. Out of the 221 respondents to this question, over 60 percent worked between 20-40 hours every week. Less than 5 percent of the respondents worked over 40 hours a week. 8 Only employment percentage based upon a minimum of 10 observations are shown. 9 See Table 19. 11 Table 7: Survey Question: How Many Hours Do Respondents Work Each Week? No. of hours worked per week No. of respondents Percentage Less than 10 hours 53 24.0 10 - 20 hours 23 10.4 20 - 40 hours 136 61.5 More than 40 hours 9 4.1 Total no. of responses 221 100.0 Income earned last month 34. Over 77 percent of respondents reported income levels less than Rs. 10,000 (US$120). The mean income is Rs. 7,590 (US$85), and the 95 percent confidence interval is Rs. 6,216 – Rs. 8,962 (US$70- US$101). Seventy responses reporting income less than Rs.300 (US$3.4) were not included in the table above as they appeared to be incorrectly reported. Table 8: Survey Question – Income Earned Last Month Salary range No. of respondents Percentage Rs. 300 or greater but less than Rs. 5,000 31 33.0 Rs. 5,000 or greater but less than Rs. 10,000 42 44.7 Rs. 10,000 or greater but less than Rs. 15,000 7 7.4 Rs. 15,000 or greater but less than Rs. 20,000 7 7.4 Rs. 20,000 or greater but less than Rs. 25,000 3 3.2 Rs. 25,000 or greater but less than Rs. 30,000 3 3.2 Rs. 30,000 or greater but less than Rs. 35,000 0 0.0 Rs. 35,000 or greater 1 1.1 Total no. of responses 94 100.0 Relationship between Training and Current Job 35. Out of 158 respondents, 55 percent reported that their job was in the same field as the training they received. In response to a follow-on question, 43 percent of respondents reported that they use the skills obtained during training in their jobs to a large extent. 12 Table 9: Survey Question – Relationship between Job and Training Is your job in the same field as the training you received? No. of Percentage respondents Yes 87 55.1 No 71 44.9 Total no. of responses 158 100.0 To what extent do you use skills obtained during training in your job? No. of Percentage respondents To a large extent 61 43.0 To some extent 57 40.1 Not at all 24 16.9 Total no. of responses 142 100.0 Effect on Survey Completion and Response Rates of an Incentive to Reply 36. In Phase 1, subsequent to the respondent confirming his/her identity and training institute in Messages 1 and 2, an incentive is offered in the form of credit to Group 2 (Rs.10) and Group 3 (Rs.30) 10. The amounts were determined based on an estimate of the cost of responding to the survey. Although subscriptions to SMS “buckets� (bulk purchase of SMSs) are quite popular, the lower incentive was calculated to be the cost of responding to the survey if the respondent had no such subscription. A higher incentive of Rs. 30 was offered to Group 3 to explore the effect of actual benefit to the respondent (a premium above the estimated cost of responding to the survey). 37. The table below shows that roughly the same proportion of respondents „reach‟ the incentive message, i.e. they respond to identity confirmation questions in each group. After receiving the message, the survey completion rates increase proportionately with the amount of credit offered. Table 10: Effect of an Incentive on Survey Completion Rates Phase 1 No Rs.10 Rs.30 credit Number of recipients 200 200 200 No. of respondents to the first SMS (and hence who 22 18 21 'reach' incentive message) Completed surveys 17 16 20 Completed surveys as a % of respondents who reach 77% 89% 95% incentive message Note: Pakistan Rs. 10 and 30 is equivalent to USD 12 cents and 36 cents. 10 No credit is offered to Group 1. 13 38. Phase 3 of the baseline survey tests the impact of an incentive offered on the response rate of the survey in the first SMS. This is different from Phase 1 where the incentives were only offered after the respondent had confirmed her/his identity. The comparison group (no incentive) is the group of graduates from Phase 2 as the surveys sent to Phase 2 and Phase 3 graduates are identical with the exception of the offer of an incentive in the first message sent to graduates in Phase 3. The credit appears to have no effect on raising the response rate of the graduates; in fact, the response rate is lower for the incentive groups (though rises proportionately with the amount of credit offered). We have little explanation for this finding except that this relatively small incentive seems not to be a motivating factor for responding or not in the first place. While the phase 1 incentives seem to show that a small incentive may be effective in incentivizing interested graduates to complete the survey. Table 11: Effect of an Incentive on Survey Response Rates Phase 2 Phase 3 Rs.10 Rs.30 Total no. of surveys sent 6,840 200 200 No. of responses 1,148 21 25 Response rate 16.8 10.5 12.5 Lessons Learned for Future Mobile-phone Tracer Studies 39. Overall, using SMS to administer the baseline survey is feasible and very low-cost, but it comes with a set of challenges. This section looks at the lessons learned.  Establishing credibility with regards to the source of the survey is important. Sending the messages from a regular mobile phone number (so-called long code) seemed to lack credibility, judging by the large number of messages which were sent back requesting the identity of the sender. Purchasing an “800-number/short code� would allow the sender to purchase a sending phone number that identifies the sender with a name to all recipients. In Phase 1 of the survey, the introductory message was sent on behalf of the respondent‟s institution; however, this did not seem to work and was later adjusted to Punjab TEVTA for Phases 2 and 3. Neither the respondent‟s institution name nor Punjab TEVTA (contained in the message) seemed to be effective in establishing credibility at the onset of the survey. Since the respondents are addressed by name, and information of a personal nature (employment status, income) is requested, establishing credibility is key to raising the response and completion rates. This can be done by informing the institutions (who inform their trainees) before the survey so that the respondents expect to be surveyed a certain period after graduation, and understand the objective of the survey.  The length of the survey must be kept in consideration. The questionnaire used in Phase 1 was shortened and restructured because of the large number of people who “dropped out� of the survey. 14  Not all graduates from the sample seemed familiar with responding to a forced-response/multiple- choice question format and responded with actual text. Their answers could not be used in this format. The method of responding to the survey questions via SMS may be explained to trainees when they are informed about the survey by their institution.  While the offer of credit upon completion of the survey offered later on during the survey increases the completion rate of the survey of those who do respond, it appears to be ineffective in increasing the survey response rate. It should be noted that credit had to be sent to respondents from a kiosk or shop where “Easy Load� facilities were available and could not be sent via the platform. Telecom operators can be contracted to send the credit; however, this can be explored further given the potentially high costs of such contracts, especially when offering a small credit to respondents seemingly has no obvious effects on the initial interest in responding. However, it may be that a larger amount or a lottery with larger prices would be more successful in soliciting a response.  Using SMS provides an excellent opportunity to inexpensively pilot the survey and make appropriate adjustments to the questions. IV. CONCLUSION 40. This survey serves to set a baseline for employment, income and other indicators used to assess the labor market outcomes of a sample of 2010 technical education and vocational training graduates in the province of Punjab, Pakistan. Given the high rate of cell phone penetration in the Punjab, the method of survey administration via SMS provides a low-cost, quick and feasible way to reach out to a large sample of TVET graduates. The key drawback was a low response rate of only 17 percent of contacted graduates. The introduction of an incentive in the form of extra mobile credit offered to respondents did not improve the respondent rate. 41. Only 39 percent of graduates are in employment. This employment excludes the graduates engaged in further training or studies (28 percent of respondents). More than 93 percent of those graduates who listed themselves as unemployed reported that they were seeking employment. Another 28 percent of graduates pursue further studies. The employment rate is the highest for those with an Electrical Diploma of Associate Engineering (DAE) at 51 percent, followed by Civil DAE (50 percent), and Welder (43 percent). The employment rate is highest for those graduates from Lodhran district (67 percent), followed by Bhakkar (54 percent) and Bahawalpur (51 percent). The male employment rate is over 12 percentage points higher than the female employment rate (41 percent versus 29 for females). 42. Over 60 percent of employed respondents worked between 20-40 hours every week. Seventy-seven percent of graduates earn less than Rs. 10,000. The mean income reported was approximately Rs. 7,600. More than fifty-five percent of graduates reported that their job was in the same field as their training. 43. Caution is advised in over-interpreting the results due to the potential statistical bias present in the sampling itself, as well as the low number of responses to the survey questions. To conclude, it is important to note the possible limitations of the use of SMS in administering the survey. The sample of graduates with mobile phones may not be representative of the population of TVET 15 graduates on the basis of income, introducing a bias in the results. The use of SMS necessarily limits the number of questions in the survey, given that there are costs, however minimal, to the graduate to reply. It is also important to further explore ways in which the response rate can be increased. 44. The findings seem to suggest that more needs to be done to improve the employment outcomes of trainees and meeting industry demand for skilled labor. A key step for the Government and Punjab TEVTA is to increase employability of graduates through improvement in the labor market relevance and quality of training, and as a second step continuously measure the employability of graduates to see if the improvement raises employability. 16 ANNEX 1 Table 12: Comparison of Population-Sample Characteristics, by Trade Before dropping duplicate With valid mobile numbers mobile numbers Trade Freq. Percent Cum. Freq. Percent Cum. Agriculture(DAE) 37 0.28 0.28 26 0.33 0.33 Architectural Drafting (G-II) 16 0.12 0.40 10 0.13 0.46 Auto & Diesel (DAE) 29 0.22 0.62 18 0.23 0.69 Auto & Farm Machinery 37 0.28 0.90 13 0.17 0.85 Auto & Farm Machinery(G-III) 54 0.41 1.31 25 0.32 1.17 Auto and Farm 36 0.27 3.94 21 0.27 3.84 Auto and Farm (DAE) 42 0.32 4.26 36 0.46 4.30 Auto and Farm(G-II) 30 0.23 4.49 23 0.29 4.59 Auto and Farm(G-III) 11 0.08 4.57 11 0.14 4.73 Auto Cad 39 0.30 1.61 33 0.42 1.59 Auto Electrician 24 0.18 1.79 23 0.29 1.89 Auto Electrician(G-II) 35 0.27 2.06 17 0.22 2.10 Auto Electrician(G-III) 9 0.07 2.13 9 0.11 2.22 Auto Mechanic(Diesel) 5 0.04 2.16 3 0.04 2.26 Auto Mechanic(G-II) 82 0.62 2.79 34 0.43 2.69 Auto Mechanic(G-III) 106 0.80 3.59 63 0.80 3.49 Auto Mechanic(Petrol) 9 0.07 3.66 5 0.06 3.56 Auto Mechanic(Petrol) (G-III) 1 0.01 3.67 1 0.01 3.57 Beautician 472 3.58 8.15 174 2.22 6.95 Bulldozer Operator 39 0.30 8.45 38 0.48 7.44 Carpenter 6 0.05 8.50 6 0.08 7.51 Certificate in Computer Application 59 0.45 14.47 58 0.74 12.31 Certificate in Computer Applications 1,134 8.61 23.08 717 9.15 21.45 Certificate Vocational Girls (1 Year 728 5.53 14.02 318 4.06 11.57 Certificate) Chemical (DAE) 12 0.09 23.17 4 0.05 21.51 Civil (DAE) 449 3.41 26.58 305 3.89 25.40 Commercial Arts / Graphics (G-II) 7 0.05 26.64 2 0.03 25.42 Computer and Electronics(G-III) 11 0.08 27.85 11 0.14 26.67 Computer Information Technology 40 0.30 26.94 25 0.32 25.74 (DAE) Computer Operator 47 0.36 27.30 38 0.48 26.22 Computer Operator(G-III) 62 0.47 27.77 24 0.31 26.53 Cooking & Baking 12 0.09 27.94 3 0.04 26.71 Decoration 6 0.05 27.99 1 0.01 26.72 17 Diploma in Business Administration 51 0.39 28.38 22 0.28 27.00 (Dip) Diploma in Commerce (Diploma 2 Years 56 0.43 28.80 47 0.60 27.60 Diploma in Commerce (Diploma 2 2,443 18.55 47.35 1,605 20.47 48.07 Years) Diploma in Office Management 8 0.06 47.41 3 0.04 48.11 Diploma in Vocational Girls 1 0.01 47.42 1 0.01 48.12 Diploma in Vocational Girls (Diploma 2 691 5.25 52.67 232 2.96 51.08 Years) Diploma in Vocational Girls (Additional) 31 0.24 52.90 8 0.10 51.19 Diploma in Vocational Teacher Training 10 0.08 52.98 0 0.00 51.19 Domestic Tailoring 325 2.47 55.44 184 2.35 53.53 Draftsman Civil(G-II) 89 0.68 56.12 65 0.83 54.36 Draftsman Civil(G-III) 129 0.98 57.10 87 1.11 55.47 Draftsman Mechanical(G-II) 128 0.97 58.07 43 0.55 56.02 Draftsman Mechanical(G-III) 37 0.28 58.35 12 0.15 56.17 Dress Designing & Making (DAE) 35 0.27 58.62 12 0.15 56.33 Dress Designing & Making (G-III) 195 1.48 60.10 51 0.65 56.98 Dress Making 16 0.12 60.22 0 0.00 56.98 Dress Making (G-II) 8 0.06 60.28 8 0.10 57.08 Electrical (DAE) 340 2.58 62.86 241 3.07 60.15 Electrical Wiring Technician 29 0.22 63.08 28 0.36 60.51 Electrical(G-II) 127 0.96 64.05 83 1.06 61.57 Electrical(G-III) 332 2.52 66.57 200 2.55 64.12 Electrician 291 2.21 68.78 228 2.91 67.03 Electrician(G-II) 218 1.66 70.43 112 1.43 68.46 Electrician(G-III) 91 0.69 71.12 66 0.84 69.30 Electronics (DAE) 179 1.36 72.48 83 1.06 70.36 Electronics Application (Radio & TV) 114 0.87 73.35 60 0.77 71.12 Electronics Application (Radio & TV)(G- 38 0.29 73.64 29 0.37 71.49 III) Electronics(G-III) 2 0.02 73.65 1 0.01 71.51 Elementary Food Preservation 27 0.21 73.86 25 0.32 71.82 Fabric Printing 52 0.39 74.25 20 0.26 72.08 Fashion Designing 21 0.16 74.41 5 0.06 72.14 Fashion Designing (G-III) 17 0.13 74.54 3 0.04 72.18 Fitter General (G-III) 31 0.24 74.78 13 0.17 72.35 Fitter General(G-II) 92 0.70 75.47 35 0.45 72.79 Food Technology (DAE) 51 0.39 75.86 47 0.60 73.39 General Mechanic(G-III) 11 0.08 75.95 9 0.11 73.51 Hand Embroidery 127 0.96 76.91 54 0.69 74.20 Handicraft 61 0.46 77.37 10 0.13 74.32 Heating Ventilation & Air Conditioning 89 0.68 78.05 71 0.91 75.23 18 Heating Ventilation Air Conditioning 20 0.15 78.32 2 0.03 75.26 Heating Ventilation Air Conditioning 16 0.12 78.17 0 0.00 75.26 (HVACR) (G-III) Home Appliances & Repair 15 0.11 78.44 14 0.18 75.43 Industrial Electrician 15 0.11 78.55 13 0.17 75.60 Industrial Electronics(G-III) 13 0.10 78.65 0 0.00 75.60 Instrumentation (DAE) 45 0.34 78.99 39 0.50 76.10 Leather Manufacturing(G-III) 2 0.02 79.01 1 0.01 76.11 Machine Embroidery 170 1.29 80.30 95 1.21 77.32 Machine Shop(G-III) 26 0.20 80.49 17 0.22 77.54 Machinist 2 0.02 80.51 2 0.03 77.56 Machinist(G-II) 197 1.50 82.00 82 1.05 78.61 Machinist(G-III) 100 0.76 82.76 61 0.78 79.39 Mechanical (DAE) 521 3.96 86.72 434 5.54 84.92 Mobile Repairing 14 0.11 86.83 0 0.00 84.92 Motor Cycle Mechanic 73 0.55 87.38 66 0.84 85.77 Motor Winding 69 0.52 87.90 61 0.78 86.54 Motor Winding(G-III) 45 0.34 88.25 26 0.33 86.87 Office Management Assistant (G-III) 27 0.21 88.45 18 0.23 87.10 Office Secretary (G-III) 7 0.05 88.50 4 0.05 87.16 Paint Polish 7 0.05 88.56 6 0.08 87.23 Painting 2 0.02 88.57 2 0.03 87.26 Plumber 67 0.51 89.08 57 0.73 87.98 Plumber (G-II) 7 0.05 89.13 6 0.08 88.06 Refrigeration & Air Conditioning (DAE) 7 0.05 89.19 2 0.03 88.09 Refrigeration & Air Conditioning(G-II) 164 1.25 90.43 105 1.34 89.43 Refrigeration & Air Conditioning(G-III) 52 0.39 90.83 26 0.33 89.76 Tailoring 161 1.22 92.05 91 1.16 90.92 Tailoring(G-III) 42 0.32 92.37 31 0.40 91.31 Telecom(DAE) 12 0.09 92.46 6 0.08 91.39 Tractor Mechanic 1 0.01 92.47 0 0.00 91.39 Tractor Operator 115 0.87 93.34 98 1.25 92.64 Turner 92 0.70 94.04 68 0.87 93.51 Welder 220 1.67 95.71 154 1.96 95.47 Welder(G-II) 98 0.74 96.45 54 0.69 96.16 Welder(G-III) 81 0.62 97.07 61 0.78 96.94 Wireman 366 2.78 99.85 229 2.92 99.86 Wood Work 1 0.01 99.86 1 0.01 99.87 Wood Work(G-III) 19 0.14 100.00 10 0.13 100.00 Total 13,170 100 7,840 100 Note: trades not represented in the sample are marked in italic 19 Table 13: Comparison of Population-Sample Characteristics, by District Before dropping duplicate With valid mobile numbers mobile numbers District number Freq. Percent Cum. Freq. Percent Cum. Attock 722 5.48 5.48 400 5.1 5.1 Bahawalnagar 338 2.57 8.05 255 3.25 8.35 Bahawalpur 667 5.06 13.11 448 5.71 14.07 Bhakkar 774 5.88 18.99 493 6.29 20.36 Chakwal 275 2.09 21.08 182 2.32 22.68 Chiniot 103 0.78 21.86 75 0.96 23.64 D.G.Khan 411 3.12 24.98 185 2.36 25.99 Faisalabad 140 1.06 26.04 118 1.51 27.5 Gujranwala 260 1.97 28.02 133 1.7 29.2 Gujrat 454 3.45 31.46 255 3.25 32.45 Hafizabad 71 0.54 32 43 0.55 33 Jhang 387 2.94 34.94 226 2.88 35.88 Jhelum 375 2.85 37.79 227 2.9 38.78 Kasur 666 5.06 42.84 420 5.36 44.13 Khanewal 259 1.97 44.81 161 2.05 46.19 Khushab 143 1.09 45.9 103 1.31 47.5 Lahore 234 1.78 47.67 95 1.21 48.71 Layyah 165 1.25 48.93 73 0.93 49.64 Lodhran 177 1.34 50.27 134 1.71 51.35 Mandi Baha-ud-din 171 1.3 51.57 69 0.88 52.23 Mianwali 510 3.87 55.44 273 3.48 55.71 Multan 47 0.36 55.8 27 0.34 56.06 Muzaffargarh 169 1.28 57.08 61 0.78 56.84 Nankana Sahib 12 0.09 57.17 6 0.08 56.91 Narowal 234 1.78 58.95 113 1.44 58.35 Okara 412 3.13 62.08 281 3.58 61.94 Pakpattan 313 2.38 64.45 160 2.04 63.98 R.Y.Khan 710 5.39 69.84 173 2.21 66.19 Rajanpur 124 0.94 70.78 84 1.07 67.26 Rawalpindi 201 1.53 72.31 186 2.37 69.63 Sahiwal 1,272 9.66 81.97 1,075 13.71 83.34 Sargodha 835 6.34 88.31 610 7.78 91.12 Sheikhupura 139 1.06 89.36 28 0.36 91.48 Sialkot 276 2.1 91.46 126 1.61 93.09 Toba Tek Singh 313 2.38 93.83 194 2.47 95.56 Vehari 812 6.17 100 348 4.44 100 Total 13,171 100 7,840 100 20 Table 14: Comparison of Population-Sample Characteristics, by Gender Before dropping duplicate mobile numbers With valid mobile numbers Gender Freq. Percent Cum. Freq. Percent Cum. Female 2,969 31.25 31.25 1,437 22.83 22.83 Male 6,533 68.75 100 4,857 77.17 100 Total 9,502 100 6,294 100 21 ANNEX 2 Table 15: Pair-wise T-test of Difference in Employment Rate across Top 10 Trades Trade Trade Mean (J) I-J P-value Certificate in Computer Applications Civil DAE 0.500 -0.060 0.560 Mean, I = Diploma in Commerce 0.449 -0.009 0.973 0.44 Diploma Girls Vocational 0.278 0.162 0.198 Draftsman Civil GIII 0.200 0.240 0.0603* Electrical DAE 0.510 -0.070 0.446 Electrical GIII 0.294 0.146 0.264 Electrician 0.375 0.065 0.579 Mechanical DAE 0.367 0.073 0.391 Welder 0.444 -0.004 0.974 Civil DAE Diploma in Commerce 0.449 0.051 0.583 Mean, I = Diploma Girls Vocational 0.278 0.222 0.115 0.500 Draftsman Civil GIII 0.200 0.300 0.035** Electrical DAE 0.510 -0.010 0.929 Electrical GIII 0.294 0.206 0.156 Electrician 0.375 0.125 0.347 Mechanical DAE 0.367 0.133 0.209 Welder 0.444 0.056 0.708 Diploma in Commerce Diploma Girls Vocational 0.278 0.171 0.194 Mean, I = Draftsman Civil GIII 0.200 0.249 0.0591* 0.449 Electrical DAE 0.510 -0.061 0.471 Electrical GIII 0.294 0.155 0.258 Electrician 0.375 0.074 0.566 Mechanical DAE 0.367 0.082 0.381 Welder 0.444 0.005 0.991 Diploma Girls Vocational Draftsman Civil GIII 0.200 0.078 0.614 Mean, I = 0.278 Electrical DAE 0.510 -0.232 0.0828* Electrical GIII 0.294 -0.016 0.918 Electrician 0.375 -0.097 0.516 Mechanical DAE 0.367 -0.089 0.484 Welder 0.444 -0.166 0.312 Draftsman Civil GIII Electrical DAE 0.510 -0.310 0.0225** Mean, I = 0.200 Electrical GIII 0.294 -0.094 0.551 0.200 Electrician 0.375 -0.175 0.242 22 Mechanical DAE 0.367 -0.167 0.191 Welder 0.444 -0.244 0.139 Electrical DAE Electrical GIII 0.294 0.216 0.118 Mean, I = Electrician 0.375 0.135 0.280 0.510 Mechanical DAE 0.367 0.143 0.133 Welder 0.444 0.066 0.643 Electrical GIII Electrician 0.375 -0.081 0.598 Mean, I = Mechanical DAE 0.367 -0.073 0.582 0.294 Welder 0.444 -0.150 0.371 Electrician Mechanical DAE 0.367 0.008 0.944 Mean, I = Welder 0.444 -0.069 0.661 0.375 Mechanical DAE Welder 0.444 -0.077 0.572 Mean, I = 0.367 * Significant at the 10% level ** Significant at the 5% level *** Significant at the 1% level Table 16: T-test of Employment Rate, by Gender Gender Obs. Mean Std. Err. Std. Dev. [95% Conf. Interval] Female 116 0.293 0.042 0.457 0.209 0.377 Male 554 0.415 0.021 0.493 0.374 0.456 combined 670 0.394 0.019 0.489 0.357 0.431 diff -0.122 0.047 -0.215 -0.029 diff = mean(Female) - mean(Male) t = -2.5785 Ho: diff = 0; Ha: diff not equal to 0 P-value = 0.0107 23 Table 17: Employment Rate and Mean Income by Trade Trade Employment No. of Mean No. of rate responses income responses Electrical (DAE) 51.0 51 7,922 6 Civil (DAE) 50.0 36 7,100 5 Welder 44.4 18 15,733 3 Diploma in Commerce (Diploma 2 Years) 44.3 70 12,733 6 Certificate in Computer Applications 44.0 75 7,462 17 Electrician 37.5 24 5,440 5 Mechanical (DAE) 36.7 60 7,179 8 Electrical(G-III) 29.4 17 2,000 1 Diploma in Vocational Girls ( Diploma 2 Years) 27.8 18 3,200 2 Draftsman Civil(G-III) 20.0 15 26,200 1 Refrigeration & Air Conditioning(G-II) 69.2 13 5,875 4 Certificate Vocational Girls (1 Year Certificate) 25.0 12 10,000 1 Domestic Tailoring 27.3 11 - 0 Electrical(G-II) 10.0 10 - 0 Electronics (DAE) 20.0 10 15,000 1 Machine Embroidery 30.0 10 4,133 3 Wireman 40.0 10 3,900 2 Beautician 44.4 9 - 0 Electrician(G-II) 22.2 9 3,000 1 Machinist(G-III) 33.3 9 4,000 1 Motor Winding 44.4 9 4,000 1 Plumber 33.3 9 - 0 Certificate in Computer Application 50.0 8 6,550 2 Tailoring 50.0 8 1,000 1 Auto and Farm (DAE) 42.9 7 - 0 Draftsman Mechanical(G-II) 14.3 7 - 0 Food Technology (DAE) 71.4 7 8,000 2 Heating Ventilation & Air Conditioning 42.9 7 4,750 2 Motor Cycle Mechanic 28.6 7 - 0 Welder(G-II) 42.9 7 7,350 2 Electronics Application (Radio & TV) 50.0 6 6,000 1 Machinist(G-II) 50.0 6 13,200 1 Bulldozer Operator 20.0 5 - 0 Fitter General(G-II) 20.0 5 6,500 1 Auto Electrician(G-II) 0.0 4 - 0 Auto Mechanic(G-II) 25.0 4 - 0 Auto Mechanic(G-III) 25.0 4 6,500 1 Computer Operator(G-III) 0.0 4 - 0 Dress Designing & Making (G-III) 0.0 4 - 0 Electrician(G-III) 50.0 4 500 1 24 Auto & Farm Machinery(G-III) 66.7 3 1,000 1 Auto Cad 66.7 3 15,000 1 Auto and Farm(G-III) 33.3 3 2,000 1 Computer Operator 33.3 3 1,000 1 Diploma in Commerce (Diploma 2 Years) 66.7 3 - 0 Draftsman Civil(G-II) 33.3 3 - 0 Electronics Application (Radio & TV)(G-III) 0.0 3 - 0 Machine Shop(G-III) 33.3 3 23,000 1 Turner 66.7 3 - 0 Agriculture(DAE) 0.0 2 - 0 Commercial Arts / Graphics (G-II) 100.0 2 5,000 1 Computer Information Technology (DAE) 50.0 2 5,000 1 Diploma in Business Administration 50.0 2 15,000 1 Dress Making (G-II) 100.0 2 - 0 Elementary Food Preservation 0.0 2 - 0 Fashion Designing (G-III) 0.0 2 - 0 Home Appliances & Repair 100.0 2 8,000 1 Instrumentation (DAE) 100.0 2 7,000 1 Tailoring(G-III) 0.0 2 - 0 Auto Electrician 100.0 1 4,000 1 Computer and Electronics(G-III) 0.0 1 - 0 Cooking & Baking 0.0 1 - 0 Draftsman Mechanical(G-III) 0.0 1 - 0 Electrical Wiring Technician 0.0 1 - 0 Fabric Printing 0.0 1 - 0 General Mechanic(G-III) 0.0 1 - 0 Hand Embroidery 100.0 1 - 0 Industrial Electrician 0.0 1 - 0 Motor Winding(G-III) 100.0 1 - 0 Refrigeration & Air Conditioning(G-III) 100.0 1 8,000 1 Telecom(DAE) 0.0 1 - 0 Welder(G-III) 0.0 1 - 0 Wood Work(G-III) 0.0 1 - 0 Architectural Drafting (G-II) - 0 - 0 Auto & Diesel (DAE) - 0 - 0 Auto & Farm Machinery - 0 - 0 Auto Electrician(G-III) - 0 - 0 Auto Mechanic(Diesel) - 0 - 0 Auto Mechanic(Petrol) - 0 - 0 Auto Mechanic(Petrol) (G-III) - 0 - 0 Auto and Farm - 0 - 0 Auto and Farm(G-II) - 0 - 0 Carpenter - 0 - 0 25 Chemical (DAE) - 0 - 0 Decoration - 0 - 0 Diploma in Office Management - 0 - 0 Diploma in Vocational Girls - 0 - 0 Diploma in Vocational Girls (Additional) - 0 - 0 Dress Designing & Making (DAE) - 0 - 0 Electronics(G-III) - 0 - 0 Fashion Designing - 0 - 0 Fitter General (G-III) - 0 - 0 Handicraft - 0 - 0 Heating Ventilation Air Conditioning - 0 - 0 Leather Manufacturing(G-III) - 0 - 0 Machinist - 0 - 0 Office Management Assistant (G-III) - 0 - 0 Office Secretary (G-III) - 0 - 0 Paint Polish - 0 - 0 Painting - 0 - 0 Plumber (G-II) - 0 - 0 Refrigeration & Air Conditioning (DAE) - 0 - 0 Tractor Operator - 0 - 0 Wood Work - 0 - 0 Table 18: Employment Rate by Duration of Course Duration in months Unemployed Employed No. of responses 3 48.8 51.2 43 6 61.3 38.7 186 12 76.4 23.6 89 18 57.1 42.9 7 24 58.6 41.4 162 36 56.6 43.4 182 26 Figure 5: Employment Rate by Duration of Course 60 Employment rate in % 50 51 40 41 43 39 30 20 24 10 0 0 0 3 6 12 24 36 Duration of course in months Employment rate Linear (Employment rate) Table 19: Pair-wise T-test of Difference in Employment Rate across Duration of Training Duration (in months) Duration (in months) Mean (J) I-J P-value 3 6 0.387 0.125 0.148 Mean, I = 12 0.236 0.276 0.003*** 0.512 24 0.414 0.098 0.260 36 0.434 0.078 0.368 6 12 0.236 0.151 0.010*** Mean, I = 24 0.414 -0.027 0.616 0.387 36 0.434 -0.047 0.361 12 24 0.414 -0.178 0.003*** Mean, I = 36 0.434 -0.198 0.001*** 0.236 24 36 0.434 -0.021 0.702 Mean, I = 0.414 * Significant at the 10% level ** Significant at the 5% level *** Significant at the 1% level 27 Table 20: Employment Rate by Level of Previous Education Previous education Unemployed Employment rate No. of responses Middle 66.7 33.3 45 Under Matric 75.0 25.0 4 Matric 67.1 32.9 140 FA FSc ICom 54.5 45.5 33 BA BSc Bcom Bed 75.0 25.0 4 MA MSc Mcom Med 100.0 0.0 2 DCom 100.0 0.0 1 Table 20 shows the employment rate of graduates by previous education level. If only those education levels with more than 15 observations are considered, graduates with an FA, FSc, or ICom (Grade 12) level of education have the highest employment rate at 45 percent, and those with a Matric the lowest at 33 percent. Graduates who have completed middle school but not Matric have the same employment rate as those with a Matric level of education. Pair-wise t-tests show that the employment rates of graduates with Middle, Matric, and FA, FSc, ICom levels of education are not statistically different from each other. Figure 6: Employment Rate by Prior Education Level Employment rate 50 Employment rate in % 45 40 33 33 30 25 25 20 10 0 0 0 Middle Under Matric FA FSc DCom BA BSc MA MSc Matric ICom Bcom Mcom Bed Med Employment rate Linear (Employment rate) 28 Figure 7: Employment Rate by Prior Education Level (More than 15 Observations) Employment rate (min. 15 observations) 50 45 Employment rate in % 40 30 33 33 20 10 0 Middle Matric FA FSc ICom Employment rate Table 21: Employment Rate and Mean Income by District District Employment rate No. of responses Mean Income No. of responses Attock 14.3 28 5,000 1 Bahawalnagar 41.7 24 8,083 6 Bahawalpur 51.4 35 5,971 7 Bhakkar 53.8 26 2,150 2 Chakwal 0.0 13 - 0 Chiniot 25.0 4 - 0 D.G.Khan 57.1 14 4,260 5 Faisalabad 33.3 9 8,000 1 Gujranwala 50.0 4 - 0 Gujrat 53.8 13 15,400 3 Hafizabad 25.0 4 - 0 Jhang 33.3 12 - 0 Jhelum 18.5 27 12,233 3 Kasur 37.8 45 2,938 4 Khanewal 17.6 17 - 0 Khushab 50.0 2 - 0 Lahore 40.0 10 5,000 1 Layyah 25.0 8 5,000 1 Lodhran 66.7 15 9,600 3 Mandi Baha-ud-din 25.0 4 5,500 1 Mianwali 29.2 24 19,860 5 Multan 0.0 4 - 0 Muzaffargarh 50.0 2 - 0 29 Nankana Sahib 0 - 0 Narowal 30.8 13 - 0 Okara 33.3 18 3,000 3 Pakpattan 50.0 8 - 0 R.Y.Khan 45.5 11 6,750 2 Rajanpur 0.0 1 - 0 Rawalpindi 33.3 30 4,129 7 Sahiwal 43.3 180 7,194 24 Sargodha 51.4 37 7,570 10 Sheikhupura 0.0 2 - 0 Sialkot 75.0 4 4,600 1 Toba Tek Singh 85.7 7 - 0 Vehari 40.0 15 10,475 4 Table 21 shows the employment rate and average income by district. The top 5 districts by employment rate account for 19 percent of graduate responses. Pair-wise t-tests amongst the top 5 districts reveal no significant differences in the employment rate at the 1, 5 or 10 percent levels. Graduates from Lodhran have the highest employment rate at 67 percent, while only 14 percent of respondents from Attock listed themselves as employed11. Table 22: Employment Rate and Mean Income by Gender Gender Employment rate No. of responses Mean income No. of responses Female 29.3 116 3,142 13 Male 41.5 554 8,303 81 Table 22 shows that there is a statistically significant difference between male and female employment rates; the employment rate for males is over 12 percent higher than that for females. The number of observations for female income is too limited to infer the average income, but the mean income for male graduates is Rs. 8,303. 11 Note: Highest and lowest employment rates described for those districts with 15 and above responses. 30 Figure 8: Employment Rate by Institution Employment rate by institution (Min. 10 observations) 60 50 Employment rate in % 40 30 20 10 0 Employment rate Figure 8 shows the employment rate of graduates by institution. The Government College of Technology, Sahiwal, has the highest employment rate at 48 percent, followed by the Government College of Commerce, Bhawalnagar, and the Government College of Technology, Sargodha (both at 47 percent). The lowest employment rate is for graduates of Government Technical Training Institute, Jhelum, at 21 percent. 31 Table 23: Employment Rate and Mean Income by Institution Institution Employment No. of Mean No. of rate responses income responses Agricultural Machinery Training School, Sargodha - 0 - 0 Agriculture Machinery Training School, Talagang - 0 - 0 Govt. College of Commerce , Lodhran 60 5 12,000 1 Govt. College of Commerce , Liaqatpur 0 1 - 0 Govt. College of Commerce, Bahawalnagar 47.1 17 9,250 4 Govt. College of Commerce, Bhakkar 50 6 - 0 Govt. College of Commerce, Chichawatni 66.7 3 - 0 Govt. College of Commerce, Gojra, District T.T. Singh - 0 - 0 Govt. College of Commerce, Gujrat - 0 - 0 Govt. College of Commerce, Jauharabad, District Khushab - 0 - 0 Govt. College of Commerce, Mianwali 28.6 7 28,650 2 Govt. College of Technology (W), Lytton Road, Lahore 0 2 - 0 Govt. College of Technology (W) Katchary Road Jaranwala 0 2 - 0 Govt. College of Technology (W), Bahawalpur - 0 - 0 Govt. College of Technology, Attock 28.6 7 5,000 1 Govt. College of Technology, Bahawalpur 60 5 5,250 2 Govt. College of Technology, Burewala 0 2 - 0 Govt. College of Technology, Chak Daulat, Jhelum 0 3 - 0 Govt. College of Technology, Faisalabad - 0 - 0 Govt. College of Technology, Layyah 25 8 5,000 1 Govt. College of Technology, Rasul 0 2 - 0 Govt. College of Technology, Sahiwal 48.1 131 7,586 17 Govt. College of Technology, Sargodha 46.7 15 11,000 2 Govt. College of Technology, Sharif Pura G.T. Road, - 0 - 0 Gujranwala. Govt. College of Technology,Rahim Yar Khan 40 5 12,000 1 Govt. Institute of Commerce (W), Gujrat - 0 - 0 Govt. Institute of Commerce (W), Mianwali - 0 - 0 Govt. Institute of Commerce (W), R.Y Khan 100 1 1,500 1 Govt. Institute of Commerce (W), Sohawa - 0 - 0 Govt. Institute of Commerce , Talagang - 0 - 0 Govt. Institute of Commerce Darya Khan, District Bhakkar 50 8 300 1 Govt. Institute of Commerce, Arifwala 50 2 - 0 Govt. Institute of Commerce, Burewala 33.3 3 15,000 1 Govt. Institute of Commerce, Chakwal 0 2 - 0 Govt. Institute of Commerce, Chiniot 33.3 3 - 0 Govt. Institute of Commerce, Chishtian 0 1 - 0 Govt. Institute of Commerce, Chunian 100 1 - 0 Govt. Institute of Commerce, Depalpur 33.3 6 1,000 1 32 Govt. Institute of Commerce, Gujar Khan, District 33.3 3 - 0 Rawalpindi Govt. Institute of Commerce, Haroonabad 50 2 5,000 1 Govt. Institute of Commerce, Hasilpur 100 1 - 0 Govt. Institute of Commerce, Isakhel 50 4 16,500 2 Govt. Institute of Commerce, Jand 0 3 - 0 Govt. Institute of Commerce, Kabirwala 50 4 - 0 Govt. Institute of Commerce, Kamalia, T.T. Singh 100 3 - 0 Govt. Institute of Commerce, Kharian - 0 - 0 Govt. Institute of Commerce, Mailsi 75 4 12,750 2 Govt. Institute of Commerce, Mandi Baha-ud-Din - 0 - 0 Govt. Institute of Commerce, Minchanabad - 0 - 0 Govt. Institute of Commerce, Narowal 50 4 - 0 Govt. Institute of Commerce, Naushera, Tehsil & District - 0 - 0 Khushab Govt. Institute of Commerce, Pakpattan 0 1 - 0 Govt. Institute of Commerce, Pattoki 100 1 - 0 Govt. Institute of Commerce, Phalia - 0 - 0 Govt. Institute of Commerce, Pind Dadan Khan, District 0 1 - 0 Jhelum Govt. Institute of Commerce, Pindi Gheb - 0 - 0 Govt. Institute of Commerce, Rajanpur 0 1 - 0 Govt. Institute of Commerce, Rojhan - 0 - 0 Govt. Institute of Commerce, Sadiqabad 66.7 3 - 0 Govt. Institute of Commerce, Shahpur Sadar, District 0 1 - 0 Sargodha Govt. Institute of Commerce, Shorkot 100 2 - 0 Govt. Institute of Commerce, Sialkot 100 2 4,600 1 Govt. Institute of Commerce, Taunsa Sharif - 0 - 0 Govt. Institute of Commerce, Yazman 62.5 8 11,500 2 Govt. Techncial Training Centre, Talagang 0 3 - 0 Govt. Technical Training Centre (M), (ABAD), Kallur Kot, - 0 - 0 Bhakkar Govt. Technical Training Centre, Fortabbas - 0 - 0 Govt. Technical Training Center (M), Haroonabad, District - 0 - 0 Bahawalnagar Govt. Technical Training Center (M), Jandanwala, District 50 4 4,000 1 Bhakkar Govt. Technical Training Center, Bahtar - 0 - 0 Govt. Technical Training Center, Sadiqabad - 0 - 0 Govt. Technical Training Centre (M), ( ABAD), Jand 0 1 - 0 Govt. Technical Training Centre (M), (ABAD), Fateh Jang - 0 - 0 Govt. Technical Training Centre (M), (ABAD), Kharian 0 1 - 0 Govt. Technical Training Centre (M), (ABAD), Jampur - 0 - 0 Govt. Technical Training Centre (M), Qila Didar Singh, 50 2 - 0 District Gujranwala 33 Govt. Technical Training Centre (Male) Piplan 33.3 6 9,000 1 Govt. Technical Training Centre (W) Sambrial 50 2 - 0 Govt. Technical Training Centre Lalian, (DMTC), Tehsil 0 1 - 0 Chiniot Govt. Technical Training Centre, (ABAD), Bhakkar 50 4 - 0 Govt. Technical Training Centre, (ABAD), Choa Saidan 0 5 - 0 Shah Govt. Technical Training Centre, (ABAD), Khushab 100 1 - 0 Govt. Technical Training Centre, (ABAD), Shakargarh 28.6 7 - 0 Govt. Technical Training Centre, (ABAD), Zafarwal 0 2 - 0 Govt. Technical Training Centre, (ABAD), Isakhel 0 3 - 0 Govt. Technical Training Centre, (ABAD), Jalalpur Jattan 100 1 23,000 1 Govt. Technical Training Centre, (ABAD), Kot Chutta 50 8 6,550 2 Govt. Technical Training Centre, (ABAD), Pasrur - 0 - 0 Govt. Technical Training Centre, (ABAD), Sarai Alamgir 100 1 - 0 Govt. Technical Training Centre, (AMTS), D.G.Khan 100 2 2,500 2 Govt. Technical Training Centre, (DMTC), Arifwala - 0 - 0 Govt. Technical Training Centre, (DMTC), Burewala 33.3 3 - 0 Govt. Technical Training Centre, (DMTC), Dahranwala 0 1 - 0 Govt. Technical Training Centre, (DMTC), Hafizabad 0 2 - 0 Govt. Technical Training Centre, (DMTC), Kamoki 50 2 - 0 Govt. Technical Training Centre, (DMTC), Kot Addu 50 2 - 0 Govt. Technical Training Centre, (DMTC), Pakpattan 60 5 - 0 Govt. Technical Training Centre, (DMTC), Samundri - 0 - 0 Govt. Technical Training Centre, (DMTC), Wahndo - 0 - 0 Govt. Technical Training Centre, (Male) Jehanian District 12.5 8 - 0 Khanewal Govt. Technical Training Centre, (Male) Karor Pacca District 66.7 9 15,000 1 Lodhran Govt. Technical Training Centre, (Male) Khairpur Tamewali 0 1 - 0 District Bahawalpur Govt. Technical Training Centre, (Male) Malikwal, District 50 2 5,500 1 ,Mandi Baha-ud-Din Govt. Technical Training Centre, (Male) Safdarabad District 0 2 - 0 Sheikhupura Govt. Technical Training Centre, (Male) Tribal Area (Fort 50 4 3,200 1 Minro) District, D.G.Khan Govt. Technical Training Centre, (Male), Chak Jhumra 66.7 3 8,000 1 District, Faisalabad Govt. Technical Training Centre, (Male), Kallar Kahar 0 1 - 0 District Chakwal Govt. Technical Training Centre, (Male), Kallar Sydian 44.4 9 5,167 3 Govt. Technical Training Centre, (Male), Kot Momin , 45.5 11 12,400 3 District Sargodha Govt. Technical Training Centre, (Male), Renala Khurd, 50 6 4,000 2 District Okara Govt. Technical Training Centre, (Male),Kot Radha Kishen, 29.4 17 - 0 District Kasur 34 Govt. Technical Training Centre, (PSIC), Khurrianwala - 0 - 0 Govt. Technical Training Centre, (PSIC), Tamman - 0 - 0 Govt. Technical Training Centre, (VTC) (PSIC) ,Shahpur, 100 1 - 0 District Sargodha Govt. Technical Training Centre, (W) Ahmadpur Sial, 33.3 3 - 0 District Jhang Govt. Technical Training Centre, (W) Jehanian District 0 1 - 0 Khanewal Govt. Technical Training Centre, (W) Karor Pacca District 100 1 1,800 1 Lodhran Govt. Technical Training Centre, (W) Khairpur Tamewali 66.7 3 - 0 District Bahawalpur Govt. Technical Training Centre, (W), Kallar Sydian 33.3 15 3,350 4 Govt. Technical Training Centre, (W), Kot Momin , District 33.3 3 - 0 Sargodha Govt. Technical Training Centre, (W), Phool Nagar, District 27.3 11 1,000 1 Kasur Govt. Technical Training Centre, (W), Renala Khurd, 16.7 6 - 0 District Okara Govt. Technical Training Centre, (W),Kot Radha Kishen, 30 10 2,875 2 District Kasur Govt. Technical Training Institute (W) College Road, 50 8 5,000 1 Township, Lahore Govt. Technical Training Institute (W) Kamal Gunj, Lahore - 0 - 0 Govt. Technical Training Institute Kamalia 50 2 - 0 Govt. Technical Training Institute, Ahmad Murad Road, 22.7 22 5,750 4 Sahiwal Govt. Technical Training Institute, Attock 16.7 6 - 0 Govt. Technical Training Institute, Bahawalnagar 50 2 6,500 1 Govt. Technical Training Institute, Bahawalpur 44.4 9 500 1 Govt. Technical Training Institute, Chichawatni 57.1 7 6,250 2 Govt. Technical Training Institute, Daulat Gate, Multan 0 2 - 0 Govt. Technical Training Institute, Gujranwala - 0 - 0 Govt. Technical Training Institute, Gujrat 44.4 9 13,200 1 Govt. Technical Training Institute, Harapa Road, Sahiwal 30 10 8,200 1 Govt. Technical Training Institute, Jauharabad 0 1 - 0 Govt. Technical Training Institute, Jhang 20 5 - 0 Govt. Technical Training Institute, Jhelum 21.4 14 15,100 2 Govt. Technical Training Institute, Kasur 80 5 5,000 1 Govt. Technical Training Institute, Khanewal 0 4 - 0 Govt. Technical Training Institute, Mianwali 0 1 - 0 Govt. Technical Training Institute, Muzaffargarh - 0 - 0 Govt. Technical Training Institute, Pindi Gheb 0 6 - 0 Govt. Technical Training Institute, Sohawa 22.2 9 6,500 1 Govt. Technical Training Institute, T.T.Singh 100 2 - 0 Govt. Technical Training Institute,Sillanwali Road Sargodha 100 3 3,500 3 Govt. Vocational Training Institute (W), (RMGTC), 0 1 - 0 Rawalpindi 35 Govt. Vocational Training Institute (W),(ABAD), Dhamial, 0 2 - 0 Rawalpindi Govt. Vocational Training Institute (W) Vehova, Taunsa - 0 - 0 Sharif Govt. Vocational Training Institute (W), (ABAD), Kachery - 0 - 0 Road, D.G.Khan Govt. Vocational Training Institute (W), (ABAD), Taunsa - 0 - 0 Sharif Govt. Vocational Training Institute (W), (RMGTC) 0 1 - 0 Bahawalpur Govt. Vocational Training Institute (W), Attock 0 2 - 0 Govt. Vocational Training Institute (W), Bahawalpur 50 2 - 0 Govt. Vocational Training Institute (W), Bhakkar 75 4 - 0 Govt. Vocational Training Institute (W), Burewala 0 2 - 0 Govt. Vocational Training Institute (W), Chichawatni 0 3 - 0 Govt. Vocational Training Institute (W), Chiniot - 0 - 0 Govt. Vocational Training Institute (W), Chunian - 0 - 0 Govt. Vocational Training Institute (W), D.G.Khan - 0 - 0 Govt. Vocational Training Institute (W), Daska - 0 - 0 Govt. Vocational Training Institute (W), Depalpur - 0 - 0 Govt. Vocational Training Institute (W), Dhudial Camp, 0 1 - 0 Chakwal Govt. Vocational Training Institute (W), Fateh Jang 100 1 - 0 Govt. Vocational Training Institute (W), Fort Abbas 0 1 - 0 Govt. Vocational Training Institute (W), Gujranwala - 0 - 0 Govt. Vocational Training Institute (W), Gujrat 100 1 10,000 1 Govt. Vocational Training Institute (W), Hafizabad 50 2 - 0 Govt. Vocational Training Institute (W), Hasilpur 0 1 - 0 Govt. Vocational Training Institute (W), Isakhel 33.3 3 - 0 Govt. Vocational Training Institute (W), Jhang 0 2 - 0 Govt. Vocational Training Institute (W), Kabirwala - 0 - 0 Govt. Vocational Training Institute (W), Kallurkot - 0 - 0 Govt. Vocational Training Institute (W), Kamar Mushani, - 0 - 0 District Mianwali Govt. Vocational Training Institute (W), Kharian - 0 - 0 Govt. Vocational Training Institute (W), Khushab - 0 - 0 Govt. Vocational Training Institute (W), Kot Addu - 0 - 0 Govt. Vocational Training Institute (W), Lodhran - 0 - 0 Govt. Vocational Training Institute (W), Mankera - 0 - 0 Govt. Vocational Training Institute (W), Multan (New) 0 2 - 0 Govt. Vocational Training Institute (W), Nankana Sahib - 0 - 0 Govt. Vocational Training Institute (W), Naushera, District - 0 - 0 Khushab Govt. Vocational Training Institute (W), Okara - 0 - 0 Govt. Vocational Training Institute (W), Pattoki - 0 - 0 Govt. Vocational Training Institute (W), Pindi Gheb 0 2 - 0 36 Govt. Vocational Training Institute (W), R.Y Khan 0 1 - 0 Govt. Vocational Training Institute (W), Rajanpur - 0 - 0 Govt. Vocational Training Institute (W), Sahiwal 25 4 - 0 Govt. Vocational Training Institute (W), Sammundri 25 4 - 0 Govt. Vocational Training Institute (W), Sargodha 66.7 3 3,000 2 Govt. Vocational Training Institute (W), Shorkot - 0 - 0 Govt. Vocational Training Institute (W), Talagang 0 1 - 0 Govt. Vocational Training Institute (W), Vehari 100 1 1,400 1 Govt. Vocational Training Institute (W),(ABAD), Darya - 0 - 0 Khan, Bhakkar Govt. Vocational Training Institute (W),(ABAD), Noorkot - 0 - 0 Govt.Technical Training Center, (DMTC) Ahmad Pur East - 0 - 0 Govt.Technical Training Center, (DMTC) Hasilpur. 0 2 - 0 Govt.Technical Training Center, (DMTC) Yazman 100 2 3,900 2 Govt.Technical Training Center, Tranda Muhammand - 0 - 0 Pinnah Govt.Technical Training Centre, (AMTS), Gujranwala - 0 - 0 37 ANNEX 3A: QUESTIONNAIRE (PHASE 1)12 Message 1: This message is being sent to you from [Institution Name]. Are you [Mr./Ms.] [Name]? 1. Yes [go to Message 3] 2. No [go to Message 1] Message 2: Do you know [Mr./Ms.] [Name]? Please send us their mobile number so we can contact them directly. [If number received, send Message 1] Message 3: [Mr./Ms.] [Name], according to our records, you received training from [Institution Name]. Is this correct? 1. Yes [go to Message 4] 2. No [go to Message 13] Message 4: Please answer the following questions to tell us how you have benefited from your training. Message 5: You will receive Rs.[Credit amount] upon answering all questions. Please choose your operator. 1. Mobilink [go to Message 6] 2. Telenor [go to Message 6] 3. Warid [go to Message 6] 4. Ufone [go to Message 6] 5. Zong [go to Message 6] Message 6: What are you doing these days? 1. Private employment [go to Message 9] 2. Government employment [go to Message 9] 3. Own/family business [go to Message 9] 4. Not doing anything [go to Message 7] Message 7: Are you searching for employment? 1. Yes [go to Message 13] 2. No [go to Message 8] Message 8: What are you doing these days? 1. Further studies 2. Further training 3. Housework 4. Nothing Message 9: 12 For the subgroup which did not receive credit, Message 5 is excluded. 38 Is your job in your area of training? 1. Yes [go to Message 10] 2. No [go to Message 10] Message 10: To what extent do you use skills learned during training at your job? 1. To a large extent [go to Message 11] 2. To some extent [go to Message 11] 3. Not at all [go to Message 11] Message 11: On average, how many hours do you work every week? 1. Less than 10 hours [go to Message 12] 2. 10-20 hours [go to Message 12] 3. 20-30 hours [go to Message 12] 4. 30-40 hours [go to Message 12] 5. More than 40 hours [go to Message 12] Message 12: How much did you earn last month? Please type the figure. Message 13: Thank you 39 ANNEX 3B: SMS FLOWCHART (PHASE 1) 40 ANNEX 3C: QUESTIONNAIRE (PHASE 2) Message 1: This message is being to sent to you on behalf of Punjab TEVTA. Are you [Name]? Please reply by replying either 1 or 2. 1. Yes [go to Message 3] 2. No [go to Message 2] Message 2: Do you know [Mr./Ms.] [Name]? Please send us their mobile number so we can contact them directly. [If number received, send Message 1] Message 3: The Government of Punjab would like to know how you have benefited from receiving training at [Institution Name]. What are you doing these days? 1. Private sector employment [go to Message 5] 2. Government employment [go to Message 5] 3. Own/family business [go to Message 5] 4. Further education or training [go to Message 9] 5. Not doing anything [go to Message 4] Message 4: Are you searching for employment? 1. Yes [go to Message 9] 2. No [go to Message 9] Message 5: On average, how many hours do you work every week? 1. Less than 10 hours [go to Message 6] 2. 10-20 hours [go to Message 6] 3. 20-40 hours [go to Message 6] 4. More than 40 hours [go to Message 6] Message 6: How much did you earn last month? Please type the figure. [go to Message 7] Message 7: Is your job in your area of training? 1. Yes [go to Message 8] 2. No [go to Message 8] Message 8: To what extent do you use skills learned during training at your job? 1. To a large extent [go to Message 9] 2. To some extent [go to Message 9] 3. Not at all [go to Message 9] Message 9: Thank you 41 ANNEX 3D: QUESTIONNAIRE (PHASE 3) Message 1: This message is being sent to you on behalf of Punjab TEVTA. Are you [Name]? Please reply by replying either 1 or 2. You will receive Rs.[Credit amount] upon completion of the survey. 1. Yes [go to Message 3] 2. No [go to Message 2] Message 2: Do you know [Mr./Ms.] [Name]? Please send us their mobile number so we can contact them directly. [If number received, send Message 1] Message 3: The Government of Punjab would like to know how you have benefited from receiving training at [Institution Name]. What are you doing these days? 1. Private sector employment [go to Message 5] 2. Government employment [go to Message 5] 3. Own/family business [go to Message 5] 4. Further education or training [go to Message 9] 5. Not doing anything [go to Message 4] Message 4: Are you searching for employment? 1. Yes [go to Message 9] 2. No [go to Message 9] Message 5: On average, how many hours do you work every week? 1. Less than 10 hours [go to Message 6] 2. 10-20 hours [go to Message 6] 3. 20-40 hours [go to Message 6] 4. More than 40 hours [go to Message 6] Message 6: How much did you earn last month? Please type the figure. [go to Message 7] Message 7: Is your job in your area of training? 1. Yes [go to Message 8] 2. No [go to Message 8] Message 8: To what extent do you use skills learned during training at your job? 1. To a large extent [go to Message 9] 2. To some extent [go to Message 9] 3. Not at all [go to Message 9] Message 9: 42 Thank you for your cooperation. Choose your operator. 1. Mobilink 2. Telenor 3. Warid 4. Ufone 5. Zong Message 10: Thank you. You will receive your credit shortly. 43