Explained: How innovation drives economic growth

Who won and why it matters

• Joel Mokyr received half the prize for identifying the conditions that make technological progress continuous.

• Philippe Aghion and Peter Howitt share the other half for modeling how innovation replaces older technologies and sustains growth through creative destruction.
  

  Mokyr’s core idea: useful knowledge has two parts

  • Propositional knowledge: the why. Scientific explanations of how the world works. Example: laws of thermodynamics or semiconductor physics.

  • Prescriptive knowledge: the how. Detailed, reproducible instructions, drawings, measurements and protocols that let artisans and firms build things that work at scale. Example: process recipes for wafer fabrication or turbine blade casting.

  Why this distinction matters
  For centuries many societies had good theory but weak practical codification, so ideas did not scale. Growth accelerated when experiments, standard measures, reproducibility and skilled artisans turned theory into reliable practice. Policy lesson: invest in skilling, engineering, standards and diffusion, not just in abstract science.

  Aghion–Howitt: creative destruction in a model

  Creative destruction is the continual process where new technologies make old ones obsolete. Their model shows:

  • Firms invest in R and D to move the frontier and capture temporary profits.

  • Competition can raise innovation because firms try to escape rivals by improving faster. Too little rivalry breeds complacency. Too much can kill the rents that fund R and D. The sweet spot depends on sector and stage of development.

  • Reallocation is essential. Productivity rises when capital and labor shift from laggards to leaders. That requires bankruptcy resolution, contestable markets and active antitrust.

  So, how much should a country invest in R and D

  There is no one-size-fits-all number. Aghion–Howitt show two opposing forces:

  1. Positive externalities: Society benefits from old knowledge even after the innovator’s profits fade. Markets underinvest relative to what is socially optimal. This argues for supporting R and D.

  2. Market power distortion: Winners can earn large markups for small incremental gains, leading to overinvestment in races that mostly reshuffle profits.

  Implication
  The optimal R and D share varies by income level, sector mix and institutions. Practical guideposts:

  • Frontier economies: 2 to 3 percent of GDP in R and D or more, with strong competition policy and university–industry links.

  • Catch-up economies: 1 to 2 percent of GDP paired with big spending on diffusion: technical education, standards, quality infrastructure, and management upgrading for SMEs.

  • Use targeted instruments: competitive grants, R and D tax credits, mission-oriented programs for public goods like green tech, and procurement for early markets. Pair with antitrust and open standards to prevent lock-in.

  A balanced innovation policy toolkit

  • People: Scale engineering, technician and apprenticeship pathways. Reward translational skills.

  • Ideas to impact: Tech transfer offices, patent quality, open data, test beds and standards labs.

  • Markets that reward merit: Faster insolvency, easier firm entry, vigilant competition enforcement.

  • Safety nets for disruption: Reskilling, portability of benefits and region-sensitive transition aid so creative destruction is socially acceptable.

  • Green and digital priorities: Direct public funding toward climate solutions and general purpose technologies while ensuring diffusion beyond superstar firms.

  Bottom line

  Innovation drives growth when theory meets craftsmanship and when markets let new entrants challenge incumbents. Mokyr tells us to make knowledge usable. Aghion and Howitt show how competition and reallocation keep the engine running. Smart policy turns that engine into broad-based prosperity by funding research, sharpening rivalry and cushioning the social costs of change.

  Source: The Hindu