Analyzing the impact of oil price volatility on electricity demand: the case of Turkey

Akarsu, Gülsüm

doi:10.1007/s40822-017-0079-8

Cited by 4 publications

(2 citation statements)

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“…The generalized autoregressive conditional heteroscedasticity (GARCH (1, 1)) method was used to forecast crude oil price volatility. This approach is justified because of its adequacy in measuring volatility as used in most empirical literature [21,[22][23][24][25][26]. The main reason is that oil prices are subject to random movements, and failure to measure volatility may result in spurious regression; hence the use of the GARCH model.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Crude Oil Market Volatility and Macroeconomic Conditions: Empirical Evidence from Nigeria

Musa

2024

RoBES

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This study aims to investigate the relationship between the volatility of the crude oil market and the macroeconomic conditions in Nigeria. The author used the methods of the auto-regressive distributed lag (ARDL) model in conjunction with the generalized autoregressive conditional heteroscedasticity (GARCH) to determine the extent of volatility using a monthly dataset from January 2012 to December 2022. The author regressed the crude oil price volatility index on Organization of the Petroleum Exporting Countries (OPEC) production quotas, conflicts, GDP growth rate, exchange rate and inflation. The results indicate that oil price volatility relates negatively to GDP, implying that the volatility of crude oil prices dampens growth in Nigeria. The paper concludes that rising oil prices heighten inflation, depreciate the exchange rate and depress growth in Nigeria. To hedge against oil price volatility, the paper recommends that the Nigerian government adopt policy measures that would increase energy efficiency and reduce the country’s dependency on oil exports through diversification in other related productive sectors such as agriculture and manufacturing.

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Section: Methodsmentioning

confidence: 99%

Analysis of Crude Oil Market Volatility and Macroeconomic Conditions: Empirical Evidence from Nigeria

Musa

2024

RoBES

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“…The literature discusses oil prices as a central factor affecting world economies. Many have investigated the relationship between oil price shocks and several macroeconomic indicators, including industrial production and inflation (Hamilton, 1983;James & Kaul, 1996;Aykırı, 2020) and even other energy sources demand, such as electricity (Akarsu, 2017). Yet, studies examining the effects of oil price changes on financial markets are relatively new.…”

Section: Literaturementioning

confidence: 99%

Petrol Fiyatları ile Seçilmiş Makroekonomik Değişkenlerin Hisse Senedi Piyasasına Asimetrik Etkileri: Türkiye Örneği

Akçağlayan¹,

Tuzcu²

2023

Sosyoekonomi

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This paper investigates the asymmetric impacts of crude oil prices and other selected macroeconomic variables on the Turkish stock market for the period between 2005:01-2021:06 through the combination of the NARDL model and the quantile regression approach. The findings support the existence of cointegration between the stock market and oil prices. The variations in oil prices have asymmetric impacts in the long run. A positive shock by 1% decreases stock returns by 0.67%, while oil price declines have no significant impact. Quantile regressions show that the effects of oil price shocks are more visible at the low levels of the stock market.

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The Impact of Barrel Oil Price Variation in MIBEL Prices: A Longitudinal Approach

Borges

Silva

2018

Innovation, Engineering and Entrepreneurship

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Analyzing the impact of oil price volatility on electricity demand: the case of Turkey

Cited by 4 publications

References 43 publications

Analysis of Crude Oil Market Volatility and Macroeconomic Conditions: Empirical Evidence from Nigeria

Analysis of Crude Oil Market Volatility and Macroeconomic Conditions: Empirical Evidence from Nigeria

Petrol Fiyatları ile Seçilmiş Makroekonomik Değişkenlerin Hisse Senedi Piyasasına Asimetrik Etkileri: Türkiye Örneği

The Impact of Barrel Oil Price Variation in MIBEL Prices: A Longitudinal Approach

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