Measuring Economic Uncertainty in Syria: An Approach to the Stochastic Volatility Model
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Author: Khder Alakkari, Shikha Yadav and Pradeep Mishra
Author Address: Department of Statistics and Programming, Faculty of Economics, University of Tishreen, Lattakia (Syria), Research Scholar, Department of Geography, Delhi School of Economics, University of Delhi, New Delhi-110007(India), and 3J.N.K.V.V., College of Agric
Keywords: Common volatility, economic uncertainty, Markov Chain Monte Carlo, Prior distribution, Stochastic volatility model
JEL Codes: C15 ,C32, C51
Abstract
This research aimed to propose an index that measures the degree of economic uncertainty in Syria. As it is a difficult situation to predict, the economic future's uncertainty may be a latent variable that drives random fluctuations in the variables of the economy. The index was estimated within Bayesian inference based on the Stochastic Volatility Model. The fact that volatility in economic uncertainty foreshadows output declines suggested that the economic uncertainty index could be used as an alternative measure of economic activity when these were not available at a high frequency (such as monthly GDP).
Description
Indian Journal of Economics and Development
Volume 18 No. 2, 2022, 281-291
DOI: https://doi.org/10.35716/IJED/21242
NAAS Score: 5.15 (2022)
Indexed in Clarivate Analytics (ESCI) of WoS
Indexed in Scopus (SJR: 0.18)
UGC Approved (UGC-Care List Group II)