The impact of COVID-19 measures on intraday electricity load curves in the European Union: A panel approach

Berezvai, Zombor; Hortay, Olivér; Szöke, Tamás

doi:10.1016/j.segan.2022.100930

Cited by 2 publications

(1 citation statement)

References 51 publications

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“…With this method, the covariance matrix of error terms is estimated with a two-step procedure. At the primary stage, the OLS approach is applied to get the predicted residuals; then, the matrix is re-estimated by using OLS to obtain the new residuals 63 , 70 , 72 – 75 .…”

Section: Methodsmentioning

confidence: 99%

Driving factors of energy related CO2 emissions at a regional level in the residential sector of Iran

Ata,

Pakrooh,

Pénzes

2023

Sci Rep

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Iran has increased its CO2 emissions significantly during the past few decades. The household sector in Iran contributes one of the largest sectors of CO2 emissions. Despite this significant contribution, the existing policies have predominantly concentrated on large-scale initiatives while overlooking the regional role in shaping and implementing these plans. Therefore, this study investigates the relationship between CO2 emissions and the efficient factors in three major groups including energy, climate, and household socio-economic factors. This study aims to address regional carbon emissions and develop CO2 reduction policies tailored to each region's specific circumstances. It focuses on planning strategies at the regional level to effectively tackle CO2 emissions. Household panel data of 28 provinces of Iran are employed by using both static and dynamic panel models for the years 2001 to 2019. Static estimation includes Fixed Effect (FE), Random Effect (RE) and pooled Partial least squares (PLS), Dynamic estimation includes difference Generalized Method of Moments (GMM) and system Generalized Method of Moments (GMM). The empirical result of the static method showed positive dependence of household CO2 emissions on Heating Degree Days (HDD), Cooling Degree Days (CDD), precipitation level, oil consumption, gas consumption, household income, size of household, and also building stocks. In more detail, educational rate, dummy variable (removal of energy subsidy), and oil price reveal the greatest negative impact on the emissions with elasticities of − 0.428, − 0.31, and − 0.15; It represents 1% increase causes − 0.428, − 0.31, − 0.15, decrease CO2 emissions, respectively. however, household size, gas consumption, and oil consumption show the most significant positive effects on CO2 emissions with 1 percent increase causes CO2 emissions increases by 0.1, 0.044, and 0.026, respectively. Regarding the impact of climate factors, a 1% increase in Heating Degree Days, Cooling Degree Days, and precipitation level causes CO2 emissions increase by 0.024%, 0.004%, and 0.011% respectively, due to an increase in fossil energy demand. Results of the dynamic method of the system Generalized Method of Moments are similar to the static estimation results, except for that household size and urbanization are not significant. Also, removing the energy subsidy for fossil fuels due to substantial subsidy in fossil fuels in Iran or implementing a re-pricing energy policy can be a beneficial way to control carbon emissions from households within the provinces of the country. However, it is important to consider that this shift could potentially transfer subsidies to investments in the private sector for renewable energies.

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Section: Methodsmentioning

confidence: 99%

Driving factors of energy related CO2 emissions at a regional level in the residential sector of Iran

Ata,

Pakrooh,

Pénzes

2023

Sci Rep

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Analysis of the Czech Intraday Electricity Market During COVID-19 Pandemic from the Multifractal Perspective

Čurpek

2023

Fluct. Noise Lett.

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This paper investigates a progress of the maturity of the Czech intraday electricity market during the COVID-19 pandemic by employing the multifractal analysis. Our results indicate that since intraday electricity returns display multifractal property originating both from long-range correlations and fat-tailed distribution, a sole use of the Hurst exponent is not sufficient, and multifractality characteristics should be used. The quantities describing a multifractal behavior indicate in some periods higher stage of market development operating on short temporal scales compared to the larger temporal scales, especially the MLM index. In some periods, they are in close agreement with the Hurst approach (e.g., July 2020). Moreover, the ADL models indicate a positive association of the Hurst exponent on short temporal scales with its lagged values and new cases of the COVID-19. On short temporal scales, the rate of new COVID-19 cases was positively related to the strength of multifractality, i.e., smaller degree of maturity, both by singularity spectrum width and MLM index. We found a nonlinear relationship between the government stringent policy and the Hurst exponent on long temporal scales, singularity spectrum width and the MLM index on short temporal scales, indicating that the loose anti-COVID policies are associated with more mature market and vice versa. On the contrary, on its long counterpart, the relationships are weaker and opposite in signs.

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The impact of COVID-19 measures on intraday electricity load curves in the European Union: A panel approach

Cited by 2 publications

References 51 publications

Driving factors of energy related CO2 emissions at a regional level in the residential sector of Iran

Driving factors of energy related CO2 emissions at a regional level in the residential sector of Iran

Analysis of the Czech Intraday Electricity Market During COVID-19 Pandemic from the Multifractal Perspective

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