A running list of the questions that I think about frequently:
In Indonesian data, what actually drives business cycles: productivity shocks, commodity terms of trade, monetary policy, or financial frictions, and can one DSGE model match output, inflation, and the exchange rate at the same time.
How should we model Indonesia’s financial system in macro: what balance sheet channels matter most for amplifying shocks, and which macroprudential tools meaningfully change the cycle.
If AI is a general purpose technology, what are the first places it shows up in Indonesia: task reallocation inside firms, new firm entry, changes in markups, or measurable TFP growth.
How much does Indonesia’s AI adoption depend on compute costs and access to hardware, and does that create a new kind of bottleneck that standard growth models miss.
What is the best policy mix for Indonesia to get broad productivity gains from AI: competition policy, training and education, data and digital infrastructure, or targeted support for adoption by SMEs.