CANVAS: A Canadian behavioral agent-based model for monetary policy
开发了一个加拿大行为主体模型（CANVAS），引入家庭和企业异质性、非理性预期及生产网络中的定价和数量设定启发式，用于预测和货币政策分析，其预测性能与VAR和DSGE模型相当。
We develop the Canadian behavioral Agent-Based Model (CANVAS) that complements traditional macroeconomic models for forecasting and monetary policy analysis. CANVAS represents a next-generation modelling effort featuring enhancements in three dimensions: introducing household and firm heterogeneity, departing from rational expectations, and modelling price and quantity setting heuristics within a production network. The expanded modelling capacity is achieved by harnessing large-scale Canadian micro- and macroeconomic datasets and incorporating adaptive learning and simple heuristics. The out-of-sample forecasting performance of CANVAS is found to be competitive with a benchmark vector auto-regressive (VAR) model and a DSGE model. When applied to analyze the COVID-19 pandemic episode, our model helps explain both the macroeconomic movement and the interplay between expectation formation and cost-push shocks. CANVAS is one of the first macroeconomic agent-based models applied by a central bank to support projection and alternative scenarios, marking an advancement in the toolkit of central banks and enriching monetary policy analysis. 1