Key Details
The Report of the Committee on Knowledge Systems: Actionable Policy Paper on Framework for Measuring the Contribution of Knowledge and Knowledge Products to the Economy identifies a gap in how economic activity is measured. While existing statistics capture production, investment, research and development (R&D), employment and innovation, they do not fully account for the contribution of knowledge embedded in workers’ skills, technologies, enterprises, products and production processes.
To address this gap, the Committee recommends developing a coordinated set of thematic statistics and accounts covering different parts of the knowledge economy, rather than relying on a single indicator to measure its overall contribution.
Proposed priority areas for measurement
Component | What the proposed accounts would measure |
Human capital | Skills, STEM and research workforce, training and returns to skills |
R&D | Research inputs and outputs, their use, technological capabilities and intellectual property |
Creative economy | Creative employment, occupations and industry-wise Gross Value Added (GVA) |
AI systems | Development, deployment and trade of AI models and systems |
Data and databases | Economic value and employment associated with data production and use |
High-tech products and frontier technologies | Output, value addition, domestic contribution and trade by technology intensity |
Digital economy | Scale and spread of digitally enabled activities and capabilities |
The Committee recommends aligning these accounts with the System of National Accounts (SNA 2025) to maintain consistency in statistical concepts, classifications and valuation. It also proposes a coordinated institutional framework involving MoSPI, relevant ministries, State Governments, research institutions, universities and industry.
The initial measurement priorities would be assessed against four criteria: growth, inclusion, future significance and measurability. The report recommends using existing data, preliminary estimates and pilot studies to identify gaps and gradually expand the framework.
Distinguishing Knowledge Products from Knowledge-Embedded Products
The report identifies two categories that need to be measured separately:
Knowledge Products (KPs): Outputs in which knowledge itself is captured in an identifiable form, such as software, databases, research outputs, designs and qualifying intellectual property.
Knowledge-Embedded Products (KEPs): Goods and services that rely substantially on knowledge in their production, such as advanced machinery, pharmaceuticals, aircraft and smartphones.
The distinction helps identify where knowledge is itself the economic output and where it contributes to the value of another product or service.
The Committee proposes five conditions for identifying knowledge products: knowledge as an input, knowledge content, identifiability, codification and economic value. Reusability, transferability and durability are additional considerations for assessing their eligibility for economic accounting.
This separation is also necessary to prevent double counting—for example, counting the value of software separately and then counting the same contribution again as part of a product that uses it.
Developing Separate Accounts for Different Parts of the Knowledge Economy
The Committee recommends separate but coordinated accounts for areas such as human capital, R&D, AI, data, creative industries and the digital economy. These accounts would help capture activities that span several conventional industry categories while maintaining consistency across measurements.
The report also discusses three approaches to valuing knowledge products and intangible assets:
Market approach: Uses comparable market prices, licences and royalties.
Income approach: Estimates value based on expected future net cash flows.
Cost approach: Uses replacement cost, adjusted for the loss of value of an asset over time.
The choice of method would depend on the type of asset, the purpose of measurement and the availability of data. The Committee recommends developing these accounts progressively, with common definitions and clear methods to account for overlaps.
Prioritising What Should Be Measured
The Committee proposes assessing potential measurement areas against four criteria:
Growth: Their contribution to productivity, competitiveness, technological advancement and participation in global value chains.
Inclusion: Their contribution to employment, livelihoods and wider economic opportunities.
Future significance: Their relevance to emerging technological and structural changes, including the effects of AI on occupations, productivity and business models.
Measurability: The availability of reliable data and the feasibility of collecting additional information.
It recommends beginning with preliminary estimates and case studies of selected knowledge ecosystems. These exercises would help identify data gaps, assess the feasibility of measurement and determine which thematic accounts should be developed.
Thematic Accounts: Supplementary statistical accounts that examine a particular area of the economy—such as R&D, tourism or the digital economy—in greater detail. They use additional classifications and data while remaining consistent with the core National Accounts framework.
SNA 2025: The international framework used by countries to compile comparable economic statistics. Its provisions for thematic and extended accounts allow specific areas of economic activity to be examined in greater detail without replacing the core National Accounts.
Policy Relevance
Strengthening technology and industrial policy: Separate accounts for AI, R&D and high-tech products could provide a clearer picture of domestic technological capabilities and India's contribution to higher-value segments of production.
Connecting skills with economic outcomes: Better human-capital statistics could help assess how education, technical training and research contribute to workforce capabilities and economic activity.
Improving the visibility of traditional and creative sectors: More systematic measurement could help capture the contribution of traditional knowledge, creative industries and related activities to output, employment and livelihoods.
Strengthening Centre–State statistical coordination: Greater State participation could improve the measurement of regional knowledge capabilities and geographically concentrated production activities.
Improving the quality of economic data: Common definitions, classifications and institutional responsibilities could make knowledge-related statistics more consistent and reduce duplication across data collection systems.
Follow the Full Report Here: Report of the Committee on Knowledge Systems Actionable Policy Paper on Framework for Measuring the Contribution of Knowledge and Knowledge Products to the Economy