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HIGH-PERFORMANCE WORK SYSTEMS AND THE LABOUR SHARE OF INCOME

📘 Volume 14 📄 Issue 8 📅 September 2026

👤 Authors

Dr. N Subbukrishna Sastry 1 , Dr. Manjula Mallya M 2
1. Professor, School of Management, CMR University, Bangalore, Karnataka, India, .
2. Associate Professor & Head, Dept. of Economics, Government First Grade College for Women Balmatta Mangalore, Karnataka, India

📄 Abstract

The labour share of income has fallen across most economies for four decades, and the explanations offered have been macroeconomic: the falling relative price of capital, the rise of superstar firms, weakening bargaining institutions. This study asks whether a firm-level human resource choice belongs on that list. Using an unbalanced panel of 214 Indian technology-sector firms observed over 2019 to 2026 — 1,512 firm-year observations — it estimates whether adopters of high-performance work systems sustain a higher labour share than comparable firms, and how that relationship changes as artificial intelligence drives capital deepening. HPWS adoption is measured by an eighteen-item index built on the ability–motivation–opportunity architecture and verified against documentary evidence; the labour share is employee benefit expense over gross value added, computed from published accounts. Three results follow. First, HPWS adoption is associated with a significantly higher labour share under two-way fixed effects (γ = 0.0187 per ten index points, p < 0.001), and the association is not a productivity sacrifice: high-adoption firms record both faster wage growth and faster productivity growth than low-adoption firms. Second, AI capital deepening reduces the labour share on average (γ = −0.0412, p < 0.001), but HPWS adoption conditions that effect (interaction γ = 0.0055, p < 0.001), with the marginal effect crossing zero at an index value near 75 — a level only the top adoption quartile has reached. Third, and most consequentially, estimation of the constant-elasticity-of-substitution first-order condition separately by adoption group returns σ = 1.34 for low-HPWS firms and σ = 0.87 for high-HPWS firms, with non-overlapping confidence intervals: work-system design moves AI capital and labour across the unit elasticity, from substitutes to complements. A Melitz–Polanec decomposition attributes 63.8 per cent of the aggregate 5.8-point decline to reallocation between firms rather than to within-firm change, so the distributional question is partly one of which firms grow. Counterfactual simulation to 2032 finds that 11.6 percentage points of labour share separate the best and worst human resource trajectories. The study argues that the labour share is not only a macroeconomic residual but in part a managed outcome.

🏷️ Keywords

High-Performance Work Systems Labour Share of Income Functional Income Distribution Elasticity of Substitution AI Capital Deepening Ability–Motivation–Opportunity Framework Rent Sharing Melitz–Polanec Decomposition Panel Fixed Effects Superstar Firms Counterfactual Simulation Indian IT Services Strategic HRM.

📚 How to Cite:

Dr. N Subbukrishna Sastry, Dr. Manjula Mallya M , HIGH-PERFORMANCE WORK SYSTEMS AND THE LABOUR SHARE OF INCOME , Volume 14 , Issue 8, September 2026, EPRA International Journal of Climate and Resource Economic Review (CRER) , Pages: 1 - 24 ,

🔗 PDF URL

https://cdn.eprapublishing.org/article/1790078948418-1.EPRA31608.pdf

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