Peter, Eckley (2015): Measuring economic uncertainty using newsmedia textual data.
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Abstract
We develop a newsmedia textual measure of aggregate economic uncertainty – the fraction of Financial Times articles containing uncertaintyrelated keyphrases – for 1982–2014 at daily to annual frequencies. We contribute to the literature in three areas. First, we provide a measurement framework that links observed expressions of uncertainty in newspaper articles to a latent propensity to express uncertainty, which we argue is an ordinal proxy for the uncertainty that matters for economic decisionmaking, namely the intensity of the cognitive state of uncertainty. We use this framework to estimate how the noisetosignal ratios varies with sample size (or frequency) and show that noise variance is modest at monthly and lower frequencies, and approaching signal variance at daily frequency. Second, we study key choices in the empirical implementation of such measures more deeply than has been done previously, focusing on uncertainty keyphrase selection, isolating economic uncertainty, deduplication of articles, and appropriate scaling of the uncertainty measure, with a critique of scaling methods commonly used in the literature. Our findings provide empirical foundations for the extant literature, and evidencebased recommendations for methodological improvements. Third, we conduct the first detailed comparative analysis of a newsmedia uncertainty measure with another uncertainty proxy, stock returns volatility. Our narrative analysis establishes the plausibility of our newsmedia measure. Our quantitative analysis reveals a strong relationship to stock volatility on average. But this relationship breaks down periodically, with timing that suggests that the semantics of the word “uncertainty” may be biased towards downside uncertainty or risk. Finally, we establish the absence of Granger causation between the measures down to daily frequency, except for a oneday lead of stock volatility over newsmedia uncertainty, which is to be expected given that the FT is published before the market opens.
Item Type:  MPRA Paper 

Original Title:  Measuring economic uncertainty using newsmedia textual data 
Language:  English 
Keywords:  economic uncertainty; newsmedia; textmining; stock returns volatility 
Subjects:  C  Mathematical and Quantitative Methods > C8  Data Collection and Data Estimation Methodology ; Computer Programs > C80  General D  Microeconomics > D8  Information, Knowledge, and Uncertainty D  Microeconomics > D8  Information, Knowledge, and Uncertainty > D80  General E  Macroeconomics and Monetary Economics > E6  Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook > E66  General Outlook and Conditions G  Financial Economics > G1  General Financial Markets > G10  General 
Item ID:  69784 
Depositing User:  Mr Peter Eckley 
Date Deposited:  03 Mar 2016 07:33 
Last Modified:  03 Mar 2016 08:46 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/69784 
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Measuring economic uncertainty using newsmedia textual data. (deposited 08 Jun 2015 14:04)
 Measuring economic uncertainty using newsmedia textual data. (deposited 03 Mar 2016 07:33) [Currently Displayed]