Rising GDP, Lagging Productivity: Why Labour Productivity Holds the Key to India’s Development Goals?
Improving labour productivity is crucial to India’s goal of becoming a developed country by 2047, which is embodied in the “Viksit Bharat” vision. This was emphasized by NITI Aayog Vice Chairman Suman Bery during the Confederation of Indian Industry’s (CII) annual business summit in New Delhi.
Bery also underlined that raising living standards and quickening economic growth require a steady rise in labour productivity. He noted that although India’s economy is half as big as the U.S. in terms of purchasing power parity, its labour force is three times as big, suggesting a big chance to increase productivity.
What Is Labour Productivity?
Labour productivity is the amount of economic output produced per unit of labour—typically per worker or per hour worked.
Labour Productivity= GDP (PPP) / Total Employment
A higher value means each worker is producing more, often due to:
- Better education and skills
- Improved technology (TFP)
- Greater capital per worker
- Efficient institutions and infrastructure
Comparative Labour Productivity: India vs. The World
To see how India stacks up, we compare PPP-adjusted GDP per worker across four major economies:
| Country | GDP per Worker (PPP, USD) |
|---|---|
| USA | $130,000 |
| Germany | $115,000 |
| China | $45,000 |
| India | $28,000 |
These figures show that while India is now the third-largest economy in PPP terms, its per-worker output is still relatively low. This is due in part to:
- A large, young labour force still entering the formal economy
- Informal sector dominance
- Lower average levels of capital and skill per worker
Despite the gap, this doesn’t mean India is underperforming—it signals room for growth. With continued investment in education, digital infrastructure (like UPI and ONDC), and skill development, India’s productivity can rise substantially.
Economic Model Behind the Scenes: Solow Growth Model & TFP
In growth models like Solow’s, labour productivity improvements come from two main inputs:
- Capital per worker (K/L)
- Total Factor Productivity (A)
Y=A⋅Kα⋅L1−α
So, rising productivity indicates that either:
- Capital investment is increasing (like factories, machines, digital infrastructure)
- TFP (technology, policy, efficiency) is improving
India’s $15 trillion PPP figure shows that A is growing—India is better at converting inputs into outputs than before.
Path Forward
To realize the ‘Viksit Bharat’ vision, India must:
- Invest in Skill Development: Equip the workforce with relevant skills to meet the demands of evolving industries.
- Promote Technological Adoption: Encourage the integration of advanced technologies to enhance efficiency and output.
- Implement Market Reforms: Create a conducive environment for businesses to thrive and innovate.
- Foster Gender Inclusivity: Ensure greater participation of women in the workforce to fully utilize the available talent pool.
- Engage Globally: Forge strategic partnerships and trade agreements to integrate with global value chains.
My Thoughts:
Enhancing labour productivity is not merely an economic imperative but a societal one, pivotal for ensuring the dignity and prosperity of India’s citizens. As Bery aptly noted, achieving the status of a developed nation requires a concerted focus on productivity, innovation, and inclusive growth.
Related Articles:
Solow Growth Model Explained with India’s Economic Growth Trajectory
Related Links:
Resources:
N. Gregory Mankiw’s Macroeconomics Textbook
- Widely used for undergraduate economics courses; contains intuitive explanations of the Solow model.
International Monetary Fund (IMF) – World Economic Outlook: Offers comprehensive data on GDP per capita and PPP adjustments.
Python Codes for the Graph
import matplotlib.pyplot as plt
import numpy as np
# Countries
countries = ["USA", "Germany", "China", "India"]
# Labor productivity in PPP terms (approximate GDP per worker in USD)
# These are illustrative estimates based on available World Bank and IMF data
productivity = [130000, 115000, 45000, 28000]
# Plotting
plt.figure(figsize=(10, 6))
bars = plt.bar(countries, productivity, color=['blue', 'green', 'red', 'orange'])
plt.title("Labor Productivity (PPP GDP per Worker, USD) - Comparative Analysis")
plt.ylabel("GDP per Worker (PPP, USD)")
plt.xlabel("Country")
plt.grid(axis='y', linestyle='--', alpha=0.7)
# Annotate each bar with the value
for bar in bars:
yval = bar.get_height()
plt.text(bar.get_x() + bar.get_width()/2, yval + 3000, f"${yval:,}", ha='center', fontsize=10)
plt.tight_layout()
plt.show()