USA Economic Policy Uncertainty Indices
Buiding uncertainty indices using unsupervised machine learning in the fasion of Azqueta-Gavaldon (2017) has opened a new venue for extensive research. The purpose of this entry is to track the research which uses the uncertainty indices or the methodology to build new ones.
Research which uses the uncetainty indices (here):
Research which uses the methodology to build new uncertainty indicators:
Euro Area Economic Policy Uncertainty Indices
This section contains the uncertainty indicators produced by Azqueta-Gavaldon A., Hirschbühl D., Onorante L., and Saiz L. (2020): Sources of economic policy uncertainty in the euro area: an unsupervised machine learning approach, Working Paper Series 2359, European Central Bank .
To see in detail how the indices were constructed, please see Section 2 (page 6) of the working paper. Nonetheless, a brief summary of the steps followed is offered here:
Notes: All indices (aggregates and sub-indices) are standardize to mean 100 and 1 standard deviation.
Notation: EPU_EA stands for the aggregate economic policy uncertainty index for the euro area while Monetary_IT would stand for the Monetary Policy uncertainty for Italy. Moreovoer, Monetary_EA stands for Monetary Policy Uncertainty accross the euro area countries here examined.