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Structural Changes and Energy Consumption in the Japanese Economy 1975-95: An Input-Output Analysis

Xiaoli Han and TK. Lakshmanan

Year: 1994
Volume: Volume15
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol15-No3-9
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Abstract:
This paper analyzes the effects of the pervasive structural changes in the Japanese economy on its energy intensity in the decade 1975-85. It advances the energy input-output (I-O) structural decomposition analysis (SDA) in two ways. First, it introduces a double denominator method to relax the assumption that all electricity is derived from fossil fuels in energy I-O analysis. Second, it develops a model which identifies explicitly the effect of energy imports. The application of our model to the Japanese experience suggested that changes in final demand structure contributed more to reducing the energy intensity of the economy than the much discussed effects of changes in technology. The overall decline in the energy intensity of the economy was accompanied by drastic shifts in the fuel mix of its energy supply, in particular, a substitution of oil by natural gas.



Volatility Forecasting of Crude Oil Market: Which Structural Change Based GARCH Models have Better Performance?

Yue-Jun Zhang and Han Zhang

Year: 2023
Volume: Volume 44
Number: Number 1
DOI: 10.5547/01956574.44.1.yzha
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Abstract:
GARCH-type models have been widely used for forecasting crude oil price volatility, but often ignore the structural changes of time series, which may lead to spurious volatility persistence. Therefore, this paper focuses on the smooth and sharp structural changes in crude oil price volatility, i.e., smooth shift and regime switching, respectively, and investigates which structural change based GARCH models have better performance for forecasting crude oil price volatility. The empirical results indicate that, first, the flexible Fourier form (FFF) GARCH-type models considering smooth shift can accurately model structural changes and yield superior fitting and forecasting performance to traditional GARCH-type models. Second, the Markov regime switching (MRS) GARCH model incorporating regime switching exhibits superior fitting performance compared to the single-regime GARCH-type models, but it does not necessarily beat the counterparts for forecasting. Finally, the FFF-GARCH-type models outperform MRS-GARCH for forecasting crude oil price volatility and portfolio performance.





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