There has been a recent surge in the application of machine learning and natural language processing in the field of economics and finance. In particular, in being able to quantify sentiment and what that measure means for asset pricing. In terms of a macroeconomic indicator; one would think that policy uncertainty is pretty explanatory for real investment expenditure. This has been a particularly important question given the short term effect from the UK Brexit referendum; see for example a speech by the BoE member Ben Broadbent (click link).
As such, I thought I would drop a post on a few sources that seem to be at the front of this area of research.
A link to the paper explains how they measure it:
And in particular, their application of it regarding Brexit:
A further study that also takes into account the VIX:
Here is a link to some further research:
The one that caught my eye was this one:
And some further sources that were recommended to me:
Thank you Lukas for the suggestions.
Furthermore, regarding the macroeconomics of uncertainty shocks, earlier this year UCL had a masterclass in this; here is a list of references from the course.
- Bloom, N. (2009): “The Impact of Uncertainty Shocks”, Econometrica, 77, 623-685.
- Caldara, D., J. Fernandez-Villaverde, J. F. Rubio-Ramirez, and W. Yao (2012) “Computing DSGE Models with Recursive Preferences and Stochastic Volatility” Review of Economic Dynamics, 15, 188-206.
- Fernandez-Villaverde, J., P. Guerron-Quintana, K. Kuester, and J. Rubio-Ramirez (2015): “Fiscal Volatility Shocks and Economic Activity,” American Economic Review, 105(11), 3352-84.
- Fernandez-Villaverde, J., P. A. Guerron-Quintana, and J. F. Rubio-Ramirez (2015): “Estimating Dynamic Equilibrium Models with Stochastic Volatility”, Journal of Econometrics, 185, 216-229.
- Fernandez-Villaverde, J., P. A. Guerron-Quintana, J. F. Rubio-Ramirez, and M. Uribe (2011): “Risk Matters: The Real Effects of Volatility Shocks”, American Economic Review, 101, 2530-2561.