The role of energy prices in the Great Recession - A two-sector model with unfiltered data
MetadataShow full item record
We investigate the role of energy shocks during the Great Recession. We study the behaviour of the UK energy and non-energy intensive sectors firms in a real business cycle (RBC) model using unfiltered data. The model is econometrically estimated and tested by indirect inference. Output contraction during the Great Recession was largely caused by energy price and sector-specific productivity shocks, all of which are non-stationary and hence tend to dominate the sample variance decomposition. We also found that the channel by which the energy price shock reduces output in the model is via the terms of trade: these fall permanently when world energy prices increase and as substitutes for energy inputs are strictly limited there are few reactions via production channels. Therefore, there is no other way to balance the deteriorating current account than through lower domestic absorption.
Aminu, N., Meenagh, D. and Minford, P. (2018) 'The role of energy prices in the Great Recession—A two-sector model with unfiltered data', Energy Economics, 71, pp.14-34
Article published in Energy Economics available at https://doi.org/10.1016/j.eneco.2018.01.030
Showing items related by title, author, subject and abstract.
Energy Prices Volatility and the United Kingdom: Evidence from a Dynamic Stochastic General Equilibrium Model Aminu, Nasir (Elsevier, 2019-01-19)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 ...
Aminu, Nasir (Springer, 2017-02-09)I examine the impact of energy price shock (oil prices shock and gas prices shock) on the economic activities in the United Kingdom using a dynamic stochastic general equilibrium model with a New Keynesian Philips Curve. ...
Nancy, Youssef; Rowe, Surraya (FRDN Incorporated, 2021-03)The purpose of this paper is to evaluate the forecasting performance of linear and non-linear (GARCH) models in terms of their in-sample and out-of-sample forecasting accuracy for EGX30 and Nikkei225 indices as an example ...