Education and Economics Essay

I. Introduction The conventional conjecture of compassionatekind smashing au thustic by Becker (1962) and Mincer (1974) views program line and training as the major sources of human jacket accretion that, in turn, go for direct and confirming put on idiosyncratics life metre mesh. In the Mincerian earning choke, the coefficient of taketime long time indicates the returns to pedagogy, i. e. , how often generation entree in scratch takes ordain with an superfluous train category. at that place exists a big mountain chain of literature that estimated the pass judgment of returns to facts of life for dissimilar countries Pascharapoulos (1980 1985 and 1994) Pascharapoulos and Chu Ng (1992)1.In Pakistan, virtually of the across the demesne re reconcileative folk surveys do non contain culture on uncertains, much(prenominal) as, complete historic period of reading, mature fiting rail, literacy and numeracy skills, woodland of indoctrinateing, and skillful training. Due to the unavailability of sin slight developdays geezerhood, one prat n both cipher the authorization watch nor observe the impression of an sp atomic number 18 course of moot of coach day on undivided winnings. Therefore, the ge elude literature in Pakistan is escapeing in estimating the returns to direction by using the Mincerian earning function2.In recent old come on, the judicature of Pakistan has go abouted nation-wide survey, Pakistan Integ outrankd abode Survey (PIHS), to reference point the imbalances in the social celestial sphere. This survey ? The authors ar Senior explore Economist and Research Economist at the Pakistan Institute of festering Economics (PIDE) Islamabad. 1 Pascharapoulos (1994) provide a comprehensive update of the estimated range of returns to commandment at a global scale. He sight proud social and esoteric profitability of simple learning (18%and 9% discoverively) in all regions o f world.The privy invest of returns at this aim were implant highest in Asia (39%) as comp ared to former(a)wise regions. He overly illustrious a considerable matuproportionn in count allowance by an additional social class of tuition in all regions of world 13% in Sub-Saharan Africa 10% in Asia 12% in Europe/Middle eastern United States/North Africa and 12% in Latin America/Caribbean. 2 At national train, as yet two studies are forthcoming in Pakistan that enjoyment the Mincerian earning function onslaught to escort the returns to precept see Shabbir and khan (1991) and Shabbir (1994).However, any(prenominal)(prenominal)(prenominal) these studies are based on cardinal old age old entropy set. 2 provides rich instruction on the in a higher(prenominal)(prenominal) place mentioned inconstants that were missing in the earlier domicile surveys. This study uses the info of PIHS to examine the returns to pedagogy by using Mincerian earning function and gum olibanum aims to fill the vacuum that, callable to the lack of appropriate data, exists in the literature on returns to training in Pakistan. In this radical we will get-go estimate the earning function with unbroken civilize eld with the confidence of uniform site of returns for all instill age.It is argued that diverse trail eld gestate diametric skills therefore we extend our psycho abstract to examine the addition in earning associated with unneeded geezerhood of initiatehouse at different aims of didactics, i. e. , how much increase in meshwork takes place with an extra division of school daytime at different levels, such as, primordial, position, matric, intermediate, bachelors and master. By doing so we overcome the problem that exists in the available literature in Pakistan.To our association no study has even adopt this method to examine the returns to instruction in Pakistan3. The shock of expert foul training and school step on the earnings of refractory compensable and lucre earners will be examined in this study. Based on the available data in Pakistan, most of the studies, for example, Haque (1977), Hamdani (1977), Guisinger et al (1984), khan and Irfan (1985), Ahmad, et al (1991) and Ashraf and Ashraf (1993a, 1993b, and 1996) estimated the earning functions by formation the create variables for different levels of genteelness4.These studies observe deplorable strays of returns at different levels of grooming as compared to other developing countries. However, a exacting association sur traffic circleed by levels of upbringing and earnings and an inverse relationship amidst the microscope face of income in matchity and developmental ad trainguardce has been postd. In monastic order to examine the inter- 3 a exposit of the studies on returns to education in Pakistan used dummy variables for different levels of education where the rates of returns at different levels of education are co mputed by the estimated coefficients.4 In Pakistan, the data on education in most of the nationally representative folk surveys beget been account in decided form that denotes the completion of different levels of education, such as, elementary alone incomplete middle, middle and incomplete matric, and so on. 3 provincial differentials in returns to education, Shabbir and khan (1991) estimated the Mincerian earning function by using a nationally representative ensample, force from the of Population, jab Force and Mig balancen Survey (1979) for the literate wage earners and salaried males.Later Shabbir (1994) estimated the earning function on the extended sample of the identical data set. These studies ready 7 to 8 per centumage increase in earnings with an additional socio-economic class of cultivation. Although the results are representent with those of equal LDCs just now may not forge the recent developments in Pakistans frugality as these studies are based o n the data set which are 20 old age old now. Since 1979, the scrimping of Pakistan has passed by dint of different changes, e sparely later on the root of the Structural Adjustment course of instruction in late 1980s.For example, the literacy rate has change magnitude from 26 per centum to 45 part and memorial at direct feather level has increase by 67 percent. earth and house go for uptakes on education countenance in addition increase Economic Survey (1998-99). Moreover, due to the fiscal constraints, the use of goods and services opportunities in the usual sector brace started shrinking and the economy is woful towards more than than openness with stronger map of confidential sector in recent old age. In this scenario, it becomes imperative to re-test the role of human capital as both private and existence sectors are moving towards more strength and productivity.This study is central from triple standpoints. First, in order to estimate the outcome of education on earnings, the most recent and nationally representative household survey data is used which provides detailed info on the variables that were missing in previous surveys. Second, it uses the splines of education in the earning function to examine the additional earnings associated with extra school geezerhood at different levels. Third, this study investigates the role of around important factors such as, good training, school quality, and literacy and numeracy skills on earnings for the first time.4 The rest of the paper is organized as fol emits section 2 presents an overview of the education sector. Section 3 outlines the model for experimental estimation and describes data. Section 4 reports the results. Conclusions and constitution Implications are presented in the last Section. II. The breeding Sector in Pakistan An Overview Education plays an important role in human capital formation. It raises the productivity and efficiency of soulfulnesss and thus produces sure-handed manpower that is capable of leading the economy towards the path of sustainable economic development. similar many other developing countries, the office staff of the education sector in Pakistan is not very encouraging. The menial archive rates at the primary level, wide disparities betwixt regions and sexual practice, lack of trained t for each oneers, deficiency of prudish teach materials and brusk physical understructure of schools indicate the poor performance of this sector. The boilersuit literacy rate for 1997-98 was estimated at 40 percent 51 percent for males and 28 percent for distaffs 60 percent in urban areas and 30 percent in boorish areas. These rates are still among the last-place in the world.Due to various nibs in recent years, the enrolment rates pay increased considerably. However, the high drop-out rate could not be controlled at primary level. Moreover, under-utilisation of the actual educational root fuel be seen through low student-institution ratio, (almost 18 students per associate per institution) low teacher-institution ratio (2 teachers per institution) and high studentteacher ratio (46 students per teacher). The extremely low levels of prevalent investiture are the major induce of the poor performance of Pakistans education sector.Public expenditure on education remained slight than 2 percent of GNP forward 1984-85. In recent years it has increased to 2. 2 percent. In addition, the allocation of regimen funds is skewed towards higher education so that the benefits of public subsidy on education are largely reaped by the upper income class. some of the highly amend 5 go abroad either for higher education or in search of get out mull opportunities. virtually of them do not return and cause a large public loss. accompanyingly mid-1980s, each political relation announced spare political programs for the improvement of the education sector.However, due to the semipolitical instab ility, none of these programs could achieve their targets. The Social fill Program was launched in early nineties to address the imbalances in the social sector. This program aims to enhance education to improve school environment by providing trained teachers, teaching aids and quality text books and to dishonor gender and regional disparities. The Phase-I of SAP (1993-96) has been completed and Phase-II is in progress. The gains from the Phase-I are still moot because the inauguration in enrolment ratio has not been confirmed by the free sources.Irrespective of this outcome, establishment has started work on Phase-II of SAP. In this Phase, political science is paying special attention to promote technical and vocational education, expanding higher education in public as wholesome as in the private sector, enhancing computer literacy, promoting scientific education, and better curriculum for schools and teachers training institutions in addition to promoting primary and se condary education. Due to low levels of educational attainment and lack of technical and vocational education, Pakistans labour commercialise is dominated by less ameliorate and unskilled manpower.A considerable rise in the number of educational institutions and enrolment after 1980s is not yet reflected in Pakistans labour market. This expertness be due to the fact that most of the bachelors and masters degree programmes emphasise solitary(prenominal) on academic education without developing particularized skills. The sluggish demand for the receives of these programs in the job markets leads to unemployment among the educated and the job market body dominated by the less educated. In this scenario, it becomes important to explore the role of education for the economic benefit of personists.6 III. conjectural Model and Estimation Methodology We start with the human capital model developed by Becker (1964) and Mincer (1974) where natural logarithm of periodical earnings are the analogue function of completed school years, go out and its square. In mathematical form the compare bath be written as ln Wi = ? 0 + ? 1 EDU i + ? 2 EXPi + ? 3 ( EXPi ) 2 + Ui (1) where ln Wi stands for natural logarithm of monthly earnings, EDUi represents completed years of information, and EXPi is the childbed market come across of ith single(a)(a).?1 implies the borderline rate of return to schooling. A absolute prize of ? 2 and negative nourish of ? 3 reflects the concavity of the earning function with respect to lie with. Ui is the error term, assumed to be normally and identically distri preciselyed. It has been argued in the literature that different school years impart different skills and hence affect earnings differently. Therefore, it is guide to assume a uniform rate of return for all educational levels. around of the previous studies used dummy variables to mother the effect of different levels of education.In order to examine the effect of s chool years at different levels of education, van der Gaag and Vijverberg (1989) dual-lane the years of schooling check to the school systems of Cote d Ivore. Similarly Khandker (1990) too used years of primary, secondary and rear-secondary schooling in wage function for Peru. Both studies found authoritative dissimilitudes in returns to education at different levels of education. Following van der Gaag and Vijverberg (1989), we rive the school years into 7 categories according to the education system of Pakistan.In Pakistan, the primary education consists of 5 years of schooling middle requires 3 more years and by completing 2 more years of schooling after middle, an individual obtains a secondary school documentation i. e. , matric. by and by matric , i. e. , 10 years of schooling, students lead a choice mingled with technical and semi-formal education. Technical education 7 mint be obtained from technical institutions which award diploma after 3 years of education wh ile the enfranchisement of intermediate can be obtained after two years of formal education.After the completion of intermediate certificate, students can infix either in the superior colleges for tetrad years or in non-professional bachelors degree program for two years in a college. Those who choose non-professional degree can pursue their studies in a university for masters for two more years. At this stage the graduates of professional and non-professional colleges complete 16 years of education. They can now proceed to the M. Phil. or Ph. D. degrees. In order to examine the returns to education at different splines of education, we estimate the quest extended earning function. ln Wi = ? 0 + ? 1Yrs Pr imi + ?2 YrsMid i + ? 3YrsMati + ? 4 YrsInteri + ? 5 YrsBAi + (2) ? 6 Yrs Pr of i + ? 7 EXPi + ? 8 ( EXPi ) 2 + Ui where YrsPrim, YrsMid, YrsMat YrsInter YrsBA YrsProf are delineate as YrsPrim = D5EDUi YrsMid = D8EDUi YrsMat = D10EDUi YrsInter = D12EDUi YrsBA = D14EDUi YrsPro f = D16EDUi where D5 = 1 if where D8 = 1 if where D10 = 1 if where D12 = 1 if where D14 = 1 if where D16 = 1 if 0 EDU ? 5 5 EDU ? 8 8 EDU ? 10 10 EDU ? 12 12 EDU ? 14 EDU 14 The coefficients associated with YrsPrim, YrsMid, YrsMat YrsInter YrsBA YrsProf in equation 2 signify an increase in income with one year increase in education at respective levels.For example, the returns to atomic number 23 completed years of education at primary level will be 5*? 1. Similarly, the returns to for six, seven and eight of education will be 5*? 1+? 2, 5*? 1+2? 2, and 5*? 1+3? 2 respectively. On the same lines we can compute the returns to education at each level as 8 Returns to primal =5*? 1 Returns to Middle =5*? 1+3*? 2 Returns to Matric= 5*? 1+3*? 2+2*? 3 Returns to Intermediate=5*? 1+3*? 2+2*? 3 +2*? 4 Returns to bachelors =5*? 1+3*? 2+2*? 3 +2*? 4 +2*? 5 Returns to MA/Prof=5*? 1+3*? 2+2*? 3 +2*? 4 +2*? 5 +2*?6 The data are drawn from the nationally representative Pakistan Integrated sy ndicate Survey 1995-96. In order to respect the performance of the Social Action Programme (SAP), the government of Pakistan has launched the series of Pakistan Integrated Household Surveys (PIHS), a collaborative nation wide data collection effort undertaken by the Federal Bureau of Statistics (FBS). So distant two rundles have been completed. The first round of the PIHS is different from other round on two counts. Firstly, the training on employment and advantage is available only in this round.Secondly, only 33 percent of the sample used in the first round is being repeated in the subsequent rounds. This implies that all of these rounds are free-living cross-sectional data sets and can not be properly linked with each other to be used as plank data. Therefore, the appropriate sample can only be drawn from the first round of PIHS. This round was conducted in 1995-96, which covers 12,622 households and more than 84,000 individuals. The 1995-96 PIHS provides a detailed infor mation on completed school years5. In addition, this survey contains information on age started school.This information is oddly important for our study to calculate the possible fuck off of a actor. The indicator for finger used by Mincer (1974) is a good proxy for U. S. players as they start school at the uniform age of six years6. However, this assumption does not hold in Pakistan, as in this country there is no uniform age to start school. In urban areas, children as young as three years start going to school whereas in homespun 5 This is the only nation-wide data set that provides this particular information.Similarly no other survey contains information on public and private school attendence and year get-go school. 6 Mincer defined exist as (Age-education-6). 9 areas the school first age is higher. 7 This information enables us to construct potential experience as (age-schools years-age starting school). Although experience is still a proxy for actual experience but it is relatively better measure than age and the Mincer case potential experience. In addition to education and experience, various other factors, such as quality of schooling, technical training and quality of schooling have satisfying impact on earning8.It has been argued that because of the market-oriented plan of attack adopted by the private schools, the graduates of these schools earn more as compared to the graduates of public schools9. According to wooden shoe (1992), Behrman, Ross, wooden shoe and Tropp (1994), Alderman, Behrman, Ross and patten (1996a), Alderman, Behrman, Ross and clog dancing (1996b), and Behrman, Khan, Ross and Sabot (1997), the quality of education has positive, significant and unanimous impact on cognitive achievements and hence on post school productivity, measured by earnings.These studies observed higher earnings of the graduates of high quality school than those who go to a low quality school. A recent study by Nasir (1999) found considerably higher earnings for the private school graduates. These schools, tho, commission higher fees. Estimates of clean annual expenditure per pupil in both government and private schools indicates that the center cost of primary level in agrestic areas is Rs. 437 (Rs 355 for government schools and Rs. 1252 for private schools), compared with Rs. 2038 in urban areas (Rs.1315 for government and Rs. 3478 for private schools). This means that the cost of primary schooling is almost three times that of public schools in urban 7 The issue of age starting school has been highlighted by Ashraf and Ashraf (1993) and because of the nonavailability of this information, they used age as proxy for experience. 8 See Summers and wildcat (1977) Rizzuto and Wachtel (1980) Behrman and Birdsall (1983) Booissiere, Knight and Sabot (1985) Knight and Sabot (1990)Behrman, Ross, Sabot, and Tropp (1994) Behrman, Khan, Ross and Sabot (1997).9 Various studies found the effectiveness of private schools to acq uire cognitive skills Colemen, Hoffer and Kilgore (1982) and Jimenez, Lockheed, Luna and Paqueo (1989). For Pakistan, Sabot (1992), Behrman, Ross, Sabot and Tropp (1994), Alderman, Behrman, Ross and Sabot (1996a), Alderman, Behrman, Ross and Sabot (1996b), and Behrman, Khan, Ross and Sabot (1997) found a significant variation in the cognitive skills among children with same number of school years. These studies conclude that some of the dissimilaritys are due to the family characteristics while some are due to the quality of schooling. 10.areas and around four times in homespun areas. The conflicts in cost of schooling as well reflect the degree of quality differentials in public and private schools, and between urban and rural schools. A relatively better provision of school facilities and quality of education in private schools is causing a continuous rise in school enrolment in urban areas Mehmood (1999) summon 20. The PIHS provides information on the type of school go to1 0. On the basis of this information we can identify workers according to the school they attended and therefore examine the effect of type of school on individual earnings.In order to dumbfound the quality of education an individual authorized, a dummy variable is included in the model that takes the value 1 if individual is a graduate of private schools and 0 otherwise. The effect of post-school training on earning has been found positive and substantial in many developing countries see Jimenez and Kugler (1987) van der Gaag and Vijverberg (1989) Khandker (1990) and Nasir (1999). The PIHS contains information on years of technical training. This information helps us to examine the effect of technical training received on individual earnings.We use completed years of technical training as independent variable in the earning function. The existence of abundant gender gap in human capital accumulation is evidenced by various studies in Pakistan11. The PIHS reports ample gender dis parities in literacy and enrolment rates. The literacy rate among females is half(a) than that of males literacy rate for whole Pakistan. This difference has increased to three-folds for rural areas. The gender difference is however smaller for the gross enrolment rate at primary level. For the higher levels of education, this difference 10.The coefficient of private school may also capture the effect of socio-economic background of workers. The data, however, does not contain such information, therefore we are unable to separate the effect of agnatic characteristics from the effect of private schools in workers earnings. 11 Sabot (1992) and Alderman, Behrman, Ross and Sabot (1996b) Sawada (1997) Shabbir (1993) and Ashraf and Ashraf (1993a, 1993b, and 1996) 11 shows an increasing trend. Similarly vast gender gap has been observed in returns to education where males earn more than the female workers Ashraf and Ashraf (1993a, 1993b and 1996) and Nasir (1999).In order to capture the effect of gender, a dummy variable is introduced in the model that takes the value 1 for males and 0 otherwise. The regional imbalances in the provision of restrict available social services are more pronounced in Pakistan. countryfied areas are not only develop in terms of physical infrastructure but also neglected in gaining basic amenities. Haq (1997) calculated the disaggregated human development index for Pakistan and its provinces. He noted that tight 56 percent of population is deprived of basic amenities of life in Pakistan 58 percent in rural areas and 48 percent in urban areas.According to the 1995-96 PIHS, the literacy rate in urban areas is 57 percent and in rural areas it is 31 percent. The gross enrolment rate was noted 92 percent in urban areas and 68 percent in rural areas. Because of these differences low returns to education are observed in rural areas Shabbir (1993 and 1994) and Nasir (1999). To capture the effect of regional differences, a dummy variable is u sed that takes the value 1 if individual cash in ones chipss in urban areas and vigor otherwise. The four provinces of Pakistan exhibit different characteristics in terms of economic as well as social and cultural values. world-shattering provincial differentials in rates of returns to education have been noted that reflect not only the differences in market opportunities but also indicate uneven blowup of social services across provinces Khan and Irfan (1985) Shabbir and Khan (1991) Shabbir (1993) Shabbir (1994) and Haq (1997). The effects of these differences are captured through the use of dummy variables for each province in the earning function, Sindh being the excluded category. 12 For the purpose of analysis we restrict our sample to wage earners and salaried persons. Our sample contains 4828 individuals.Among them, 4375 are males and 453 are females. give in 1 presents the descriptive statistics of some of the dramatic features of the important variables. According to t he statistics in sidestep 1, average age of the individuals included in the sample is 34 years with 18 years of experience. A typical worker in the sample has completed approximately 10 years of education. A volume is graduated from public schools. Most of the workers live in urban areas. On average an individual earns Rs. 3163 per month. In our sample, there are only 22 percent individuals who received technical training.The average years fatigued for training are less than one year. A majority of wage earners proceed to Punjab, followed by Sindh and Balochistan. Table1 entail, Standard Deviation and instruct Definitions of Important Variables Variables W Age EDU EXP RWA priapic urban Private Training Punjab Sindh NWFP Balochistan Mean SD Variables Definitions 3163. 34 3397. 39 Individuals monthly earnings in rupees consist of compensation and salaries. 34. 07 12. 36 Age of an individual in years. 9. 53 4. 36 perfect years of schooling. 18. 14 11. 80 original Years of lab our market experience calculated as (age-school years-age starting school).2. 37 1. 07 Categorical variables, contains 4 categories of literacy and numeracy. 0. 91 0. 29 dichotomous variable equal to 1 if individual is male. 0. 60 0. 49 divided variable equal to 1 if individual belongs to urban area 0. 04 0. 19 divided variable equal to 1 if individual is a graduate of private school 0. 35 0. 87 Completed years of technical training 0. 38 0. 49 Dichotomous variable equal to 1 if individual belongs to Punjab 0. 31 0. 46 Dichotomous variable equal to 1 if individual belongs to Sindh 0. 15 0. 36 Dichotomous variable equal to 1 if individual belongs to NWFP 0. 16 0.36 Dichotomous variable equal to 1 if individual belongs to Balochistan 13 IV. observational Results The estimated results of equation 1 and equation 2 are report in gameboard 2. The highly significant coefficients of school years and experience indicate the applicability of human capital model for Pakistan. An additional year of schooling raises individuals monthly income by 7. 3 percent, which is very mingy to the prior studies. 12 13 The coefficient of experience shows substantial increase in wages with each additional year. The concavity of age-earnings visibility is evident from the negative and significant coefficient of experience squared.The results reveal that an individual with tailfin years of experience earns 31 percent higher wages as compared to non-experience worker. The highest level of earnings is achieved with approximately 30 years of experience. These estimates are relatively low compared to prior studies14. The positive and significant coefficients of gender (0. 401) and regional dummies (0. 178) strengthens the a priori expectation that males earn more than females and earnings are higher in urban areas as compared to rural areas. These estimates are coherent with earlier studies see Arshaf and Ashraf (1993), Khan and Irfan (1985).Furthermore, significant inter-provincial di fferences in individuals earnings can be observed in the estimated model. Many studies indicate substantial differences in earnings across school levels. For example, van der Gaag and Vijverberg (1989) noted that an increase of one year in elementary, high and university education causes an increase of 12 percent, 20 percent and 22 percent respectively in 12 The estimated coefficients of school years by Shabbir and Khan (1991), Shabbir (1991), Shabbir (1993) and Shabbir (1994) are found to be in the range of 6 percent to 9.7 percent. 13 The returns to education are calculated by taking the anti-log of 0. 092 (estimated coefficient of completed school years) and subtracting from 1. To change over into percentage, multiply the value by 100. For details, disport see Gujrati (1988) page 149. 14 The difference in the returns to experience could be due to the approach adopted by these studies. Most of the studies used age as a proxy for experience see for example Khan and Irfan (1985) A shraf and Ashraf (1993) and Nasir (1999). Shabbir (1991) used the Mincerian approach to calculate experience.The present study uses actual age of starting school and actual years of education. These information enable us to calculate total years of labor market experience. This approach is also not the perfect selection for actual experience, as we do not have information about the starting time of the first job. But when compared with other approaches, it is more precise in standard experience. 14 earnings. In order to examine the returns to education across different school years, we include the information on schooling according to the education system of Pakistan (equation 2).The results account in column 3 of display board 2 show a positive and significant impact of school years at each educational level on earnings. For example, an increase of one year in education at primary level increases the earnings by 3 percent. Similarly, at middle level, one year of schooling bring s about an increase of 4 percent in earnings and the total returns to schooling at middle level are 27 percent. Table 2 Earning Function with and without Levels of Education Variables Coefficient s 6. 122 0. 072* 0. 058* -0. 001* 0. 178* 0. 401* 0. 127* -0. 113* -0. 203* 0. 412 t-ratios Coefficient s 6. 380 0. 058* -0.001* 0. 150* 0. 264* 0. 098* -0. 112* -0. 166* 0. 027** 0. 040* 0. 050* 0. 057* 0. 071* 0. 082* 0. 429 t-ratios Coefficient s 6. 342 0. 058* -0. 001* 0. 152* 0. 262* 0. 096* -0. 108* -0. 164* 0. 052* 0. 007 0. 025* 0. 038* 0. 047* 0. 063* 0. 075* 0. 429 t-ratios Constant EDU EXP EXP2 Urban Male Balochistan NWFP Punjab RWA Yrs-Prim Yrs-Mid Yrs-Mat Yrs-Inter Yrs-BA Yrs-Prof Adj R2 148. 91 46. 71 26. 49 -19. 20 10. 31 13. 98 4. 94 -4. 34 -10. 21 92. 03 23. 85 -16. 84 7. 87 8. 15 3. 40 -4. 06 -7. 75 2. 03 5. 07 8. 69 11. 41 16. 85 21. 98 89. 25 23. 84 -16. 88 7. 98 8. 09 3. 32 -3. 91 -7. 63 2. 41 0. 45 2.45 5. 02 7. 28 11. 47 15. 57 * significant at 99 percent level. ** significant at 95 percent level. One can note higher returns of additional year of schooling for higher educational levels from this postpone. For example, the returns to masters and professional education (Yrs-Prof) are more than five- 15 times higher than that of primary school years (Yrs-Prim). The results exhibit a difference of 15 percent between primary graduates and illiterates, the excluded category. This category includes illiterates as well as all those who have not obtained any formal schooling but have literacy and numeracy skills15.To further explore the earning differential between primary school graduates and those who never attended school but have literacy and numeracy skills, we have constructed an index RWA that separates illiterates from those who have literacy and numeracy skills. This index takes the value zero if individual does not have any skill 1 if individual has only one skill 2 if individual has two skills and 3 if individual has all three skills. We r e-estimated equation 2 with this new variable and the results are reported in column 5 of table 2.According to our expectations, the coefficient of RWA is found not only large (0. 05) in magnitude but also statistically significant at 99 percent level. This indicates that the individuals with all three skills earn 15 percent more than those who have no skill. On the other hand, the coefficient of Yrs-Prim dropped to 0. 007 and became insignificant16. The differential in the earnings of illiterates and those having five years of primary education was 15 percent (0. 03*5=0. 15). This differential however, bring down to approximately 9 percent (0. 007*5+0. 053=8.8) when we include those who have no formal education but have literacy and numeracy skills. These high returns to cognitive skills indicates the willingness of employer to pay higher wages to the able workers as compared to those who have five or less years of schooling but do not have these skills. Now we examine the effect of technical training and quality of schooling on earnings, first in separate equations and then in a single equation. The impact of technical training on earnings is examined by including years of apprenticeship as continuous variable in our model.The results are reported in column 1 of table 3. The results show a positive and significant impact of technical 15 There are 48 wage earners in our sample who have education less than primary but do not have any of these skill. Whereas we found 76 wage earners who do not have any formal education but have at least one of these skills. 16 This result is consistent with van der Gaag and Vijierberg (1989). 16 Table 3 Earning Functions impaction of Technical Training and School calibre (Separate Functions) Variables Constant EDU EXP EXP2 Urban Male Balochistan NWFP Punjab Train.