Revealing priors from posteriors with an application to inflation forecasting in the UK
提出一种从数据和后验信息反推先验的方法，并应用于英国央行和国民经济与社会研究所的通胀预测，以揭示政策制定者在脱欧、疫情和俄乌冲突等不确定性下的先验信念。
Summary A Bayesian typically uses data and a prior to produce a posterior. We shall follow the opposite route, using data and the posterior information to reveal the prior. We then apply this theory to inflation forecasts by the Bank of England and the National Institute of Economic and Social Research in an attempt to get some insight into the prior beliefs of the policy makers in these two institutions, especially under the uncertainties about the Brexit referendum, the Covid-19 lockdown, and the Russian invasion of Ukraine.