Impact of oil price changes on domestic price inflation at disaggregated levels: Evidence from linear and nonlinear ARDL modeling

Sek, Siok Kun

doi:10.1016/j.energy.2017.03.152

Cited by 102 publications

(62 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Secondly, Shin et al () argue that financial shocks, structural reforms, regional and global imbalances, and policy shifts may affect macroeconomic variables, which in turn, could trigger asymmetries in their dynamic relationships. Thirdly, as explained by Herrera, Lagalo, and Wada (:113) and Sek (:205–206), asymmetric effects of oil price changes can occur through sectoral allocation, unemployment, uncertainty, and precautionary savings. (i) Innovations in oil prices can result in the reallocation of labour and capital to expanding sectors.…”

Section: Introductionmentioning

confidence: 99%

The asymmetric impact of oil prices on remittances: evidence from India

Akçay

Karasoy

2019

OPEC Energy Review

View full text Add to dashboard Cite

Remittances make up a sizeable part of the Indian economy. Using recently advanced non‐linear autoregressive distributed lag (NARDL) model (Shin et al, 2014), this study aims to address the asymmetric impact of oil prices on international remittances over the period 1975–2017, in the context of India. The results reveal that: (i) changes in oil prices and remittances are asymmetrically associated in both short and long run; (ii) remittances react differently to changes in oil prices: while positive movements in oil prices lead to an increase in remittances, negative movements lower remittances; (iii) compared to positive oil price shocks, negative shocks have more profound impact on remittances in the long run; (iv) exchange rate has an asymmetric effect on remittances only in the short run; (v) financial development has negative influence on remittance inflows in the long run; and (vi) GDP per capita does not have any significant impact on remittance inflows in the long run, whereas it negatively affects remittances to India in the short run.

show abstract

Section: Introductionmentioning

confidence: 99%

The asymmetric impact of oil prices on remittances: evidence from India

Akçay

Karasoy

2019

OPEC Energy Review

View full text Add to dashboard Cite

show abstract

“…Autoregression is a regression of a variable Q t with its own lag term, referred to as the Autoregressive Model. When a variable is estimated by the AR model and is also affected by the current and lag values of other variables P t , the model is the autoregressive distribution lag (ARDL) model for the event analysis of hysteresis effects [45][46][47]. This paper uses a traditional linear ARDL model constructed by Pesaran et al, which is suitable for the small sample data in this paper [48].…”

Section: Ardl Lag Modelmentioning

confidence: 99%

“…For the above reasons, in this paper, the Spearman rank correlation analysis method is suitable to be used to calculate the correlation between ship frequency and the oil price. model for the event analysis of hysteresis effects [45][46][47]. This paper uses a traditional linear ARDL model constructed by Pesaran et al, which is suitable for the small sample data in this paper [48].…”

Section: Nonlinear Correlationmentioning

confidence: 99%

The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road

et al. 2019

View full text Add to dashboard Cite

Nearly 70% of the world’s maritime crude oil transportation relies on the Maritime Silk Road (MSR). In order to deeply explore the impact of slumping oil price on the shipping situation of tanker along the MSR, this paper establishes the relationship between monthly ship and oil price through Autoregressive Distributed Lag model. Distributions of cargo flow before and after the oil price slumped are compared to explore the changing law of tanker shipping situation. The study finds: (1) The correlation between the cargo flow situation of the tanker seaborne export and oil price, where the export cargo flow correlation is stronger than that of the import cargo flow. (2) The MSR tanker shipping situation is lagging (3 months) behind the impact of oil price. The lag effect in Europe, North Asia and East Asia is strong while that in Southeast Asia and South Asia is weak. (3) After the oil price slumped, the tanker shipping cargo flow increased less during the crude oil export stage, and the increase in the crude oil shipping trade after the transfer period was larger. The research results can provide a scientific basis for improving the decision-making ability of the crude oil shipping market and formulating maritime operations management measures.

show abstract

“…The second strand of studies focuses on single‐commodity price–inflation relationships, such as the strong link between gold and inflation found by Van Hoang et al () and similar results for the oil price and inflation (Salisu, Ademuyiwa, & Isah, ; Salisu & Isah, ; Salisu, Isah, & Ademuyiwa, ; Sek, ). For indexes of multiple commodities, Fernandez () shows that commodities such as beverages (coffee), food (maize, rice and wheat) and minerals display bidirectional linear and nonlinear feedback effects with the general price level.…”

Section: Motivation For the Augmented Phillips Curve‐based Inflation mentioning

confidence: 99%

Can urban coffee consumption help predict US inflation?

Salisu

Swaray

Adediran

2019

Journal of Forecasting

View full text Add to dashboard Cite

Motivated by the importance of coffee to Americans and the significance of the coffee subsector to the US economy, we pursue three notable innovations. First, we augment the traditional Phillips curve model with the coffee price as a predictor, and show that the resulting model outperforms the traditional variant in both in‐sample and out‐of‐sample predictability of US inflation. Second, we demonstrate the need to account for the inherent statistical features of predictors such as persistence, endogeneity, and conditional heteroskedasticity effects when dealing with US inflation. Consequently, we offer robust illustrations to show that the choice of estimator matters for improved US inflation forecasts. Third, the proposed augmented Phillips curve also outperforms time series models such as autoregressive integrated moving average and the fractionally integrated version for both in‐sample and out‐of‐sample forecasts. Our results show that augmenting the traditional Phillips curve with the urban coffee price will produce better forecast results for US inflation only when the statistical effects are captured in the estimation process. Our results are robust to alternative measures of inflation, different data frequencies, higher order moments, multiple data samples and multiple forecast horizons.

show abstract

Impact of oil price changes on domestic price inflation at disaggregated levels: Evidence from linear and nonlinear ARDL modeling

Cited by 102 publications

References 32 publications

The asymmetric impact of oil prices on remittances: evidence from India

The asymmetric impact of oil prices on remittances: evidence from India

The Impact of Slumping Oil Price on the Situation of Tanker Shipping along the Maritime Silk Road

Can urban coffee consumption help predict US inflation?

Contact Info

Product

Resources

About