Microeconometric Analysis of Earnings Oriented Educational System of Lahore (pakistan)


Abstract. This study explores the factors that affect earnings and estimates returns to education (RTEdu) for the workforce of educational institutions in Lahore (Pakistan). Primary data were collected by the researcher himself from a sample of 8327 respondents in 2011. Education experience training computer use gender marital status institution sector from where the respondent has completed Secondary School Certificate nature of job family background and family status are found to be contributing to the earnings of the workforce of various categories of the educational institutions. RTEdu for the workforce of schools colleges and universities increases on average by 12.4 15.8 and 12.5 percent respectively for every one year increase in schooling. RTEdu has been found higher for the workforce of various categories of private sector as compared to the workforce of various categories of public sector educational institutions.

Human capital theory is found to be valid. The concavity in experience-earning profile is observed. This study recommends some solid measures that address reduce and minimize the ever widening relative earning differentials.

Keywords: Returns to education Microeconometric analysis Earnings oriented educational system Earning differentials Human capital theory


    The importance of education as a basis of income differentials is well recognized in both theoretical and empirical literature. Education experience trainings and skills are the main levers for acquiring and accumulating human capital. Some nations are richer and prosperous than others. Education proved itself to be the main cause of these variations across nations. Besides education there are other factors for example working experience training acquired computer skills publications gender marital status sector from where the respondent has acquired his/her Secondary School Certificate (SSCsector) nature of job family background and family status that determine individual's earnings. Identification of factors that determine workforce earnings can help in designing and formulating policies not only to boost up the social and economic status of the workforce but also to minimize the overall inequalities between regions and gender regarding income distribution.

    The positive linkage between formal education and earnings is well established in empirical literature in case of Pakistan (Abbas and Foreman- Peck 2007; Afzal 2011; Ahmad and Sirageldin 1994; Asadullah 2005 2009; Ashraf and Ashraf 1993a; 1993b; Ashraf 2011; Aslam 2007; Arif and Iqbal 2008; Aslam Bari and Kingdon 2008; Awan et al. 2008; Guisinger Henderson and Scully 1984; Hamdani 1977; Haq 1977; Hyder 2007; Khan and Irfan 1985; Kurosaki and Khan 2006; Nasir 1998; Nasir and Nazli 2000; Nasir 2002; Nasir 1999; Nazli 2004; Pasha and Wasti 1989; Qureshi and Arif 2001; Riboud Savchenko and Tan 2006; Siddiqui and Siddiqui 1998; Shabbir 1991; 1994; Shabbir and Khan 1991; Shah 2007) and in abroad (Ashenfelter Harmon and Oosterbeck 1990; Carnoy 1997; Cohn and Addison 1998; Griffin and Edwards 1993; Griffin and Ganderton 1996; Kurosaki and Khan 2006; Light 1998; Mincer 1974; Mace 1992; Psacharopoulos and Layard 1979; Psacharopoulos 1985; Preston 1997).

    The above-mentioned studies related to Pakistan have investigated the rate of RTEdu and earning differentials and found enhancing role of education in determining the earnings of the individuals. Education and earnings of the workforce are directly correlated in case of Pakistan.

    There are a variety of factors that play a decisive role in determining the earnings of both teaching and non-teaching workforce of educational institutions of Pakistan. Differential labour market RTEdu for teaching (both male and female) and non-teaching (both male and female) workforce in private as well as public sector educational institutions is one of the potential explanations for large gender and occupation earning differentials in Pakistan. The present study empirically tested this argument by first examining the role of different major determinants on the workforce earnings profiles and then estimates the rate of RTEdu for the workforce of institutions of general education located in Lahore district of Punjab province of Pakistan.

    The present study has the following objectives:

    1. To explore the connection between individual's earnings and major determinants of earnings and to evaluate the rate of RTEdu when education of the workforce is measured by years of schooling completed'.

    2. To explore the nature of education-earnings relationship for both teaching and non-teaching workforce of both private and public sector educational institutions.

    3. To test the validity of the Psacharopoulos (1994) finding for the workforce of educational institutions such that the private sector workforce has a higher rate of RTEdu than that of the public sector.

      The present study was planned to test the following hypotheses:

    4. Is there any linkage between individual's earnings and major determinants of earnings for the workforce of educational institutions

    5. Is the nature of education-earning relationship for both teaching and non-teaching workforce same for each category of educational institutions

    6. Is the marginal rate of RTEdu for the workforce of private sector educational institutions higher than that of their counterparts in public sector educational institutions

      This research is of great value for individuals as to decide whether to pursue further education or to join the labour market. Individuals will prefer to continue further formal education if they expect that the present value of the marginal benefit of schooling is greater than the present value of the marginal cost of schooling. Public decision makers want to know how to allocate scarce resources between education sector and other sectors of the economy and among various categories of educational institutions (school college university). The results of this study serve as a guideline to education policy makers in Pakistan particularly relating to efficient allocation of scarce resources among various levels of educational institutions and how funding and access to various levels of educational institutions affects equity.

      This study has its own significance in empirical literature because it is based on purposive primary data collected by the researcher himself on the workforce of institutions of general education.


    The linkage between education and its wage benefit is well known in market economies. Human capital theory that is mainly based on education has supplied the basis for the investigation of effect of education on earnings since the late1950s.

    Ashenfelter Harmon and Oosterbeck (1990); Carnoy (1997); Cohn and Addison (1998); Griffin and Edwards (1993); Griffin and Ganderton (1996); Griliches (1977); Light (1998); Mace (1992); Mincer (1974); Psacharopoulos (1985); Psacharopoulos and Layard (1979); Preston (1997) and Afzal (2011) used Earning Function" to set up a linkage between earnings and education and evaluated the rates of RTEdu. The results of all these studies supported the positive association between education and earnings. Harmon Oosterbeek and Walker (2000) found that the European countries like UK had 7-9 percent returns to a year of schooling which was higher than the Nordic countries. They have also explained that if the simple OLS method is applied then the RTEdu at school level becomes more stable. More educated workers received higher earnings as compared to less educated (Mincer 1974; Takii 2003).

    The returns to an additional year of schooling are relatively higher than an additional year of job-specific experience. Higher level of education leads to more earnings as the employment experience lengthens (Kirby and Riley 2004).

    A few attempts by Hamdani (1977) Haq (1977) and Guisinger Henderson and Scully (1984) using data from 1975 Socio-Economic Survey of Rawalpindi (Pakistan); Khan and Irfan (1985) using the Population Labour Force and Migration Survey (PLMS); Pasha and Wasti (1989); Shabbir (1991; 1994) and Shabbir and Khan (1991) by using data from PLMS 1979; Ashraf and Ashraf (1993; 1996) using data from 1975 Socio- Economic Survey of Rawalpindi (Pakistan) and data for industrial groups from Household Income and Expenditure Surveys (HIES) 1979 and 1985- 86; Ahmad and Sirageldin (1994); Nasir (1998); Siddiqui and Siddiqui (1998); Nasir (1999); Nasir and Nazli (2000) using data from the PIHS 1995-96 which covered 12622 households and more than 84000 individuals; Nasir (2002) ) using data from the PIHS 1995-96; Nazli (2004) using data from the Pakistan Socio-Economic Survey (PSES) 1998-99; Asadullah (2005 2009); Riboud Savchenko and Tan (2006); Aslam (2007) using the PIHS 2002; Aslam Bari and Kingdon (2010); Hyder (2007) using data from the Pakistan Labour Force Survey (PLFS) 2001-02; Abbas and Foreman-Peck (2007) using data from the Pakistan Social and Living Standards Measurement Survey (PSLSMS) 2004-05; Shah (2007); Ashraf (2011) using 2001-02 PIHS (PIHS) data have been made to investigate RTEdu and earning differentials by using secondary source data such as PSLSMS PLFS and PIHS in Pakistan labour market.

    All of the above-mentioned studies on Pakistan about PRTEdu were mostly out dated and often constrained by data number of variables included and methods of estimation. Comparison between the results of the above studies on Pakistan was little bit difficult. However two consistent findings from these studied emerged: (i) rate of RTEdu in Pakistan was lower than that of other developing countries and (ii) rate of PFR increases with the level of education. There is hardly any study except Afzal (2011) based on primary data collected by the researcher himself that estimates the RTEdu the determinants of individual's personal earnings and earning differentials of the general educational institutions workforce of Pakistan...

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