The missing learning curve:

The missing learning curve:

Context:

• There’s an urgent need to improve decision making along with institutional knowledge.

Introduction:

• In accordance with accelerating learning curve of the human species, can the collective brain also refuse to learn some lessons or even unlearn?
• Writers have penned down that either due to rapid population growth, a breakdown of social mores, changing economic incentives or all of these results in negligence of maintaining the old skills.
• Moreover, though all the three arms of government, legislature may be progressive in nature, but there’s an absence of a learning curve on several fronts.
• This absence is the reason for which we know most of our problems reasonably well but have struggled to solve them.
• One can observe policies swinging between extremes even in the developed economies.
• But those swings are minimal and can easily be diagnosed and a learning curve is visible.

Policy makers and institutional memory

• Policy-making should not suffer while the policy-maker is on a learning curve.

Economic:

• As economic analysis often has political implications, making biases unavoidable, data can be the starting point that all sides to an argument can agree on.
• Economic history in India lacks depth, and explanations of even basic questions lack rigor.
• The lack of technology research in Indian universities is much lamented, but the lack of quality research on economic history could be as damaging if not more.
• As a matter of fact, decision-makers are individuals or groups of individuals, and no one person or group of persons can learn it all before they start drafting policy.

Solution:

• An institutional framework is much needed; an empowered institutions supported by a body of researchers in academia and industry to make sure past lessons are not forgotten, and mistakes not repeated.
• For example, several Indian states have annual output of hundreds of billions of dollars, but lack chief economic advisors when even small business groups have chief economists.

Conclusion:

• Data analysis needs manifold improvement in quality, depth and accessibility. It may also be the easiest to rectify.