Appraising the lifetime private economic returns of postgraduate degrees: Evidence from Pakistan

The study examines higher education as an investment in human capital and quantifies private lifetime economic returns to postgraduate degrees in Pakistan. Motivated by substantial growth in the higher education sector—universities and faculty numbers have expanded markedly since the establishment of the Higher Education Commission (HEC)—the paper asks: what are the lifetime private economic returns for faculty with Ph.D. degrees compared to non-Ph.D. counterparts, and how do returns differ by domestic versus foreign Ph.D. credentials? The research is grounded in human capital theory (Schultz; Becker; Mincer), which posits a trade-off between years of schooling and working life, and evaluates whether the present value of expected lifetime earnings exceeds the direct and forgone costs of education. The objectives are to estimate returns to educational investment at the higher education level in Pakistan, compare lifetime economic returns of Ph.D. versus non-Ph.D. faculty, and contrast domestic versus foreign Ph.D. outcomes, including sensitivity to retirement age, degree completion time, and discount rates.

The review situates the analysis within human capital theory, highlighting foundational work by Becker (1964, 1975, 1993) and Mincer (1974) on education as investment and earnings functions. Cross-country and sectoral studies (Psacharopoulos, Blundell et al., Patrinos et al.) consistently find positive private returns to higher education. Pakistan-specific research (Nasir, Afzal, Bashir and Iqbal, Khan, Nazar and Chaudhry) reports higher returns for higher education, with nuances by degree level and sector. Evidence underscores that returns rise with skills and schooling but are tempered by direct and opportunity costs. Prior Pakistani studies note that public sector wages can be higher, returns differ by gender, and that retirement age and time-to-degree can influence private returns. The literature also identifies disciplinary differences and the importance of job switching, with mixed findings on the impact of foreign versus domestic credentials due to cost differentials.

Design: Cross-sectional, questionnaire-based survey of 784 faculty members (Ph.D. and non-Ph.D.) from universities across Pakistan (Islamabad, Rawalpindi, Lahore, Multan, Rahim Yar Khan, Bahawalpur, Faisalabad, Karachi, Jamshoro, Larkana, Quetta, Mardan, Peshawar). Stratified random sampling by degree (Ph.D./non-Ph.D.), gender, and sector (public/private). Respondents completed terminal degrees between 2001 and 2020, spanning social sciences, management sciences, engineering and computer sciences, and natural sciences. Sample size was computed using standard formula with 95% confidence, 5% margin of error, population N≈47,346 (HEC 2017–18). Data reflect labor force participation rates for gender. Measures: Dependent variable is average monthly after-tax earnings (PKR). Key independent variables include level of education (Ph.D.=1), experience (years) and its square, job switching (none/once/more than once), employment sector (public=1), nature of work (faculty=1), area of study (with engineering & computer sciences as base; dummies for social & management sciences and natural sciences), marital status (married=1), funded degree (1), gender (male=1), and country of degree. Empirical model: A modified Mincer earnings function (without log transformation to retain absolute PKR coefficients) estimated via Ordinary Least Squares (OLS): monthly earnings as a function of the listed covariates. Experience is computed as E = A − S − B, where A is current age, S is education level (years; non-Ph.D. 18, Ph.D. 21 for simulation), and B=6 (starting age at grade 1). Diagnostics include Breusch–Pagan test (heteroskedasticity remedied with robust standard errors), VIF (2.79, indicating no multicollinearity), and Wu–Hausman test (no endogeneity detected). Simulation of lifetime earnings: Using regression coefficients to infer starting wages and constant annual increments by education level, the study simulates undiscounted annual earnings across working life to retirement (T=60). Assumptions: starting work at 25 (non-Ph.D.) and 29 (Ph.D.); working years: 36 (non-Ph.D.) and 32 (Ph.D.). Present values are computed with a 7% discount rate (Pakistan Investment Bonds), generating PV of lifetime earnings (PVLE). Costing and NPV: Education costs include explicit (direct) and implicit (forgone) costs, adjusted for average inflation (6.07%). Domestic Ph.D.: explicit ≈ PKR 0.673 million; implicit ≈ PKR 2.72 million; total ≈ PKR 3.4 million; interim earnings during degree ≈ PKR 0.509 million; net cost ≈ PKR 2.89 million. Foreign Ph.D.: explicit ≈ PKR 4.8 million; implicit ≈ PKR 2.72 million; total ≈ PKR 7.51 million; interim earnings ≈ PKR 1.12 million; net cost ≈ PKR 6.38 million. Net Present Value (NPV) of the Ph.D. equals PVLE(Ph.D.) minus PVLE(non-Ph.D.) adjusted for the Ph.D. cost, presented as both absolute PKR and as a percentage change over non-Ph.D. PVLE. Sensitivity analyses vary retirement age (55, 65), time-to-degree (+1, +2 years), and discount rates (3%, 11%).

• Earning function (OLS): Holding controls constant, Ph.D. holders earn PKR 70,326 more per month than non-Ph.D. faculty (p<0.001). Each additional year of experience increases monthly earnings by PKR 2,876 (diminishing returns; squared term not significant). Public sector coefficient is positive but insignificant. Relative to engineering & computer sciences, social & management sciences (−PKR 10,324; p=0.02) and natural sciences (−PKR 10,060; p=0.03) have lower earnings. Married faculty earn PKR 16,364 more (p<0.001). Male faculty earn PKR 9,042 more (p=0.01). One-time job switching is associated with −PKR 10,617 (p=0.03); more than once: +PKR 9,738 (p=0.02). Country of degree effect is negative and not significant. Model R²=0.54; robust SE applied; no serious multicollinearity or endogeneity detected.
• Undiscounted simulated lifetime earnings: Non-Ph.D. ≈ PKR 45.7 million; Domestic Ph.D. ≈ PKR 67.8 million; Foreign Ph.D. ≈ PKR 70.4 million.
• PV of lifetime earnings @7%: Non-Ph.D. ≈ PKR 14.7 million; Domestic Ph.D. ≈ PKR 24.46 million (difference 9.74M); Foreign Ph.D. ≈ PKR 25.5 million (difference 10.77M).
• NPV (after net Ph.D. costs): Domestic Ph.D. ≈ PKR 6.85 million; Foreign Ph.D. ≈ PKR 4.37 million. Relative to non-Ph.D.: Domestic Ph.D. +46.5%; Foreign Ph.D. +29.8%. Net return over cost: ≈237% (domestic), ≈68.5% (foreign).
• Gender-specific NPVs @7%: Males—Domestic ≈ PKR 7.3M (+49.7%), Foreign ≈ PKR 4.8M (+32.9%). Females—Domestic ≈ PKR 5.9M (+40.4%), Foreign: +23.6%.
• Descriptive highlights: Domestic Ph.D. monthly earnings are nearly double those of non-Ph.D. faculty; foreign Ph.D. monthly earnings similar to domestic Ph.D., but foreign non-Ph.D. earn more than domestic non-Ph.D. Public sector averages exceed private sector. Job switching associates with higher earnings for non-Ph.D. (+25% once; +17% more than once) and modest gains for Ph.D. (domestic +15.74%; foreign +1.14%). Assistant professors (typical post-Ph.D. entry rank) earn 108% more than non-Ph.D. faculty.
• Sensitivity analyses: Retirement age 55 reduces Ph.D. NPVs (Domestic ≈ PKR 6.1M; +44.3%; Foreign ≈ PKR 3.58M; +26%) and narrows the Ph.D.–non-Ph.D. gap; age 65 increases NPVs (Domestic ≈ PKR 7.4M; +47.9%; Foreign ≈ PKR 5.1M; +33%). Extending Ph.D. completion by 1 year lowers net earnings by ≈5.7% (domestic) and ≈5.8% (foreign); by 2 years, ≈11.5% (domestic) and ≈11.7% (foreign). At 3% discount rate: Domestic NPV ≈ PKR 10.9M (+40.1%), Foreign ≈ PKR 8.7M (+32%); at 11%: Domestic ≈ PKR 4.42M (+47.9%), Foreign ≈ PKR 1.92M (+20.88%).

The findings directly address the research question by demonstrating that Ph.D. education yields higher private lifetime earnings than non-Ph.D. education among Pakistani university faculty, even after accounting for direct and opportunity costs via NPV. The magnitude of the premium depends on the cost structure: domestic Ph.D. holders realize higher net returns than foreign Ph.D. holders due to much lower education costs despite similar earnings profiles. The earning function results corroborate human capital theory: education level and experience increase earnings, with diminishing returns to experience. Discipline-specific differentials favor engineering and computer sciences over social/management and natural sciences. Gender and marital status gaps indicate persistent disparities, with men and married faculty earning more. Job mobility shows heterogeneous effects: switching once appears penalized while multiple switches are associated with gains, suggesting complex dynamics of career progression. Sensitivity analyses underscore robustness: altering retirement age does not overturn the core result that Ph.D. yields higher NPVs, though the Ph.D.–non-Ph.D. gap contracts at lower retirement ages and expands at higher ones. Longer time-to-degree and higher discount rates reduce NPVs, reinforcing the importance of timely completion and financing conditions. Collectively, the results emphasize that policy levers affecting costs (funding, stipends), career length (retirement age), and time-to-degree materially influence private returns and, thus, incentives to invest in doctoral education.

The study quantifies lifetime private economic returns to doctoral education for Pakistani university faculty using an earnings function and NPV simulation. Ph.D. holders earn significantly more than non-Ph.D. peers, and after accounting for education costs, domestic Ph.D. degrees deliver higher net lifetime returns than foreign Ph.D. degrees due to lower costs. Sensitivity analyses show that increasing retirement age modestly boosts returns, while delays in completion and higher discount rates reduce them. Policy implications include: improving pay scales for Ph.D. holders—especially those with higher-cost foreign degrees; increasing interim earnings/stipends during Ph.D. studies; and raising the retirement age for Ph.D. faculty from 60 to 65. Future research could extend beyond academia to compare returns in research and development (R&D) sectors and use longitudinal designs to strengthen causal inference.

• Cross-sectional survey data of faculty who completed degrees between 2001–2020 limits causal inference and may reflect cohort effects.
• Focus restricted to the academic sector (due in part to COVID-19), limiting generalizability to other sectors such as R&D or industry.
• Self-reported earnings and costs may introduce measurement error; data contain confidentiality constraints limiting public sharing.
• Results are specific to Pakistan’s higher education context and policy environment, including assumed retirement ages and discount rates.