Avoiding a Microeconomics of AI
I’m worried things are hurtling into a microeconomics of AI. I think micro is the wrong bet.
I’m worried things are hurtling into a microeconomics of AI. I think micro is the wrong bet.
From 1980 to 2015, China reduced its official poverty rate by 95 percent. The following are notes from some prominent literature that discuss how this happened and the significance (or lack thereof) of decentralization in that journey.
This volatile bounce back triggered me to write on the growing, increasingly erratic gap between our stock markets and real economy. I do not think we understand this gap or its wideness perfectly yet, both at home and globally. But a few perspectives seem sensible.
For the first time, the RBI is buying state government debt. With COVID-19 and the GST shortfall, should we reward stronger fiscal performance with better borrowing rates, or subsidize debt for poorer states?
School inspections can help address the principal-agent problem in education delivery. But inspectors are agents too. Reform needs three things: incentives tied to performance, safeguards against corruption and collusion, and better measurement that informs action. Ultimately, as we improve our data on schools and understand which schools work, we can then figure out why.
Notes from a guest lecture I delivered in March 2019 at the Department of Computer Science at Stella Maris College, Chennai, offering a simple introduction to GitHub with R and R Markdown.