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We develop a production-network model to capture how decentralized finance (DeFi) has evolved across different sectors of financial services. The model allows us to measure the value added by different DeFi sectors and to study how the connections across the sectors influence token prices.

I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best.