Petersen Luba, Rholes Ryan
Department of Economics, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada.
National Bureau of Economic Research.
J Econ Dyn Control. 2022 Oct;143:104460. doi: 10.1016/j.jedc.2022.104460. Epub 2022 Jun 26.
This paper explores the robustness of laboratory expectation formation and public signal credibility to external uncertainty shocks and online experimentation. We exploit the recent pandemic as a source of exogenous background uncertainty in a New Keynesian learning-to-forecast experiment (LtFE) where participants receive projections of varying precision about future inflation. We compare results from identical LtFE completed immediately before the onset of the pandemic, soon after (online), and well after (online and in-person). Baseline LtFEs with no communication are robust to both factors. However, both background uncertainty and online experimentation impact how subjects use public signals. The pandemic led to a decreased appetite for and tolerance of overly precise communication while increasing the efficacy of projections that also convey uncertainty. Subjects became more averse to central bank forecast errors after the onset of the pandemic if the central bank conveyed a precise outlook but not if it conveyed forecast uncertainty.
本文探讨了实验室预期形成和公共信号可信度对外生不确定性冲击及在线实验的稳健性。我们利用近期的大流行作为新凯恩斯主义预测学习实验(LtFE)中外生背景不确定性的来源,在该实验中,参与者会收到关于未来通胀的不同精度的预测。我们比较了在大流行开始前、开始后不久(在线)以及很久之后(在线和线下)完成的相同LtFE的结果。没有交流的基线LtFE对这两个因素都具有稳健性。然而,背景不确定性和在线实验都会影响受试者对公共信号的使用方式。大流行导致人们对过于精确的交流的兴趣和容忍度降低,同时提高了那些也传达不确定性的预测的效力。如果央行传达的是精确的前景,那么在大流行开始后,受试者会更厌恶央行的预测误差,但如果央行传达的是预测不确定性,则不会如此。