Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/281130 
Year of Publication: 
2023
Series/Report no.: 
Working Paper No. 023.2023
Publisher: 
Fondazione Eni Enrico Mattei (FEEM), Milano
Abstract: 
Since Russia's invasion of Ukraine, many countries have pledged to end or restrict their oil and gas imports to curtail Moscow's revenues and hinder its war effort. Thus, the European ministers agreed to trigger a cap on the gas price. To detect the importance of the price cap for gas, we provide a mixture representation for the gas price to detect the presence of outliers made by a truncated normal distribution and a uniform one. We focus our analysis on Germany and Italy, which are major Russian gas importers by exploiting the response of the different commodities to a gas shock through a Bayesian vector autoregressive (VAR) model. As a result, including a lower gas price cap smooths the impact of a gas shock on electricity prices, while not considering a price cap will increase exponentially this impact.
Subjects: 
Bayesian time series
Forecasted error variance decomposition
Gas price cap
Impulse response function
Mixture representation
JEL: 
C11
C32
Q41
Q43
Document Type: 
Working Paper

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