2022
DOI: 10.1016/j.resourpol.2021.102543
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Revisiting the relationship between oil prices, exchange rate, and stock prices: An application of quantile ARDL model

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Cited by 55 publications
(36 citation statements)
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“…Like the previous literature (Hashmi et al, 2021a(Hashmi et al, , 2021b(Hashmi et al, , 2022 our estimates indicate that negative income changes reduce consumer spending; nevertheless, this fall in spending is significant in China and Indonesia. According to our estimates, a 1% decrease in income causes a 0.35% to 0.42% decrease in household spending.…”
Section: Resultssupporting
confidence: 84%
“…Like the previous literature (Hashmi et al, 2021a(Hashmi et al, , 2021b(Hashmi et al, , 2022 our estimates indicate that negative income changes reduce consumer spending; nevertheless, this fall in spending is significant in China and Indonesia. According to our estimates, a 1% decrease in income causes a 0.35% to 0.42% decrease in household spending.…”
Section: Resultssupporting
confidence: 84%
“…One stream of the literature investigates the relationship between EPU and macroeconomic variables such as inflation, consumption, investments, economic development, money demand, unemployment, and financial distress (Hashmi and Chang, 2021 ; Hashmi et al, 2021 ; Jones and Olson, 2013 ; Brogaard and Detzel, 2015 ; Aastveit et al, 2017 ; Caggiano et al, 2017 ). In contrast, another stream of literature examines the impact of EPU on different asset classes such as commodities, derivatives and insurance, gold futures, bonds, and stocks (Syed et al, 2019 ; Hashmi et al, 2021 ; Hashmi et al, 2022 ; Arouri et al, 2016 ; Li et al, 2018 ; Fang et al, 2018 ; Uche et al, 2022b ).…”
Section: Introductionmentioning
confidence: 99%
“…Following the resolution of the current studies in terms of providing updates to existing knowledge, we applied several modern econometric procedures, including pre-estimation diagnostic tests such as descriptive statistics, the correlation matrix, unit-root (stationarity) tests beginning with the traditional augmented Dickey-Fuller, and the Perron and Lee-Strazicich tests that account for breaks in the series. The study also adopted various cointegration tests, including the Bayer-Hanck joint cointegration technique (Bayer & Hanck, 2013 ), 1 the ARDL bounds tests Pesaran et al ( 2001 ) based on insight from Ohlan ( 2017 ), and the quantile cointegration process following Hashmi et al ( 2022 ) and Uche and Effiom ( 2021b ). Meanwhile, the quantile cointegration process follows the Pesaran et al ( 2001 ) bounds test to predict the long-run relationship among the enlisted series across the quantile distributions on the basis of the following null hypothesis: [ 05] lnGDPR = [ 10] lnGDPR [ 95] lnGDPR = [ 05] lnTOUR = [ ] lnTOUR lnTOUR = [ lnFIDV = [ 10] lnFIDV [ 95] lnFIDV = [ 05] lnTROP = [ 10] lnTROP [ 95] lnTROP = [ 05] lnNATR = [ 10] lnNATR [ 95] lnNATR = 0.…”
Section: Data Description and Methodologymentioning
confidence: 99%
“…The QARDL procedure allows us to discover the dynamic effects of tourism on productivities over various states of the economy in the long and short run. Another unique feature of the QARDL model is that it accounts for distributional asymmetries, unlike other time-varying frameworks that account for asymmetry only within the conditional mean (Hashmi et al, 2022 ; Omoke & Uche, 2021 ; Sharif et al, 2020 ; Uche & Effiom, 2021b ).…”
Section: Data Description and Methodologymentioning
confidence: 99%