Energy prices volatility and the United Kingdom: Evidence from a dynamic stochastic general equilibrium model. (1st April 2019)

• Record Type: Journal Article
• Authors: Aminu, Nasir
• Is Part Of: Energy. Volume 172(2019)
• Page Start: 487
• Page End: 497
• Publication Date: 2019-04-01
• Subjects: Business cycle -- Energy prices -- Great recession -- Output -- Volatility; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.01.092
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper analyses the consequences and effects of volatile energy prices in the UK. The evidence provided are from an estimated DSGE model of energy. The model is applied on filtered data from 1981:Q1 to 2013:Q1 and evaluated by the indirect inference testing. In analysing the structural shocks, the study found higher volatility in energy prices shock during the Great Recession compared to the sample period. The high volatility of energy prices shock caused inflationary pressures in the economy. The study found energy prices shock amplified the Great Recession by significantly contributing to the fall in output. Thus, energy prices shock is an important driver of economic activity. However, given the shocks are stationary, energy prices shock is temporary. Therefore, all consequences of energy prices in the economy are short-term. By implication, when volatile energy prices create an output shortfall, monetary policy is the tool used to off-set short-term falls in output. We find results persists with robustness check. The findings justified why the DSGE model is a policymakers' workhorse. Highlights: Analysed the effects of volatile energy prices in the UK in an estimated DSGE model. The model implies energy prices shock significantly drives economic activity. Found volatile energy prices shock contributed to the Great Recession in the UK. Monetary authorities were able to reduce the consequences of world energy prices. Results persists with robustness check of VAR-IRF and variance decomposition.