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What is ARDL Model

Smart Strategies and Societal Solutions for Sustainable International Business
Autoregressive Distributed Lag Stationarity model, it is an econometric model used for analyzing long and short run relationships between different time series variables. The AR component in the ARDL model represents the lagged values of the dependent variable. It captures the short-term dynamics of the relationship between variables. Distributed Lag Component represents the lagged values of the explanatory variables. It captures the lagged effects of these variables on the dependent variable.
Published in Chapter:
The Impact of Health Crisis on the Volatility of Commodity Price Return: Does Economic Uncertainty Matter?
Amal Jmaii (Faculty of Economic Sciences and Management of Tunis, Tunisia) and Ramla Gargouri (Faculty of Economic Sciences and Management of Tunis, Tunisia)
DOI: 10.4018/979-8-3693-0532-4.ch008
Abstract
This chapter examines the impact of the Covid-19 pandemic on commodity price returns, taking into consideration the role of economic policy uncertainty. Using global monthly data from September 2019 to September 2022, and applying the ARDL model, the study shows that Covid-19 has opposite effects on oil and gold price returns. While oil price returns dropped dramatically, gold continued to rise, serving as a safe asset during this health crisis. Moreover, the results indicate that economic uncertainty has a significant impact on these two commodities, as their importance to the global economy extends beyond their roles as raw materials. Therefore, an uncertain event can affect their stability. These findings can be beneficial to investors and decision-makers, as they should consider turning to gold in times of economic turbulence and uncertainty due to its resistance despite the Covid-19 pandemic.
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Green Convergence in Emerging Nations: The Determinants and the Possibilities
Autoregressive distributed lag model, where the dependent variable is a function of its own past lagged values as well as current and past values of other explanatory variables.
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