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ARE EMPIRICAL MEASURES OF MACROECONOMIC UNCERTAINTY ALIKE?
Author(s) -
Chua Chew Lian,
Kim David,
Suardi Sandy
Publication year - 2011
Publication title -
journal of economic surveys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.657
H-Index - 92
eISSN - 1467-6419
pISSN - 0950-0804
DOI - 10.1111/j.1467-6419.2010.00662.x
Subject(s) - econometrics , survey of professional forecasters , bivariate analysis , economics , heteroscedasticity , measure (data warehouse) , inflation (cosmology) , autoregressive model , series (stratigraphy) , estimation , statistics , mathematics , computer science , monetary policy , macroeconomics , paleontology , physics , management , database , biology , theoretical physics
There is a plethora of time series measures of uncertainty for inflation and real output growth in empirical studies but little is known whether they are comparable to the uncertainty measure reported by individual forecasters in the survey of professional forecasters. Are these two measures of uncertainty inherently distinct? This paper shows that, compared with many uncertainty proxies produced by time series models, the use of real‐time data with fixed‐sample recursive estimation of an asymmetric bivariate generalized autoregressive conditional heteroskedasticity model yields inflation uncertainty estimates which resemble the survey measure. There is, however, overwhelming evidence that many of the time series measures of growth uncertainty exceed the level of uncertainty obtained from survey measure. Our results highlight the relative merits of using different methods in modelling macroeconomic uncertainty which are useful for empirical researchers.