Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models
通过退火高效估计动态结构宏观金融模型的似然
Most solved dynamic structural macrofinance models are non-linear and/or non-Gaussian state-space models with high-dimensional and complex structures. We propose an annealed controlled sequential Monte Carlo method that delivers numerically stable and low variance estimators of the likelihood function. The method relies on an annealing procedure to gradually introduce information from observations and constructs globally optimal proposal distributions by solving associated…