Acceso usuarios
Omeyr Cheloufi
, Larbi Djedi, Tahar Chermat, Mohammed Saidi
Objective: This Article aims to investigate the impact of oil price fluctuations on economic growth in Algeria using the Mixed Data Sampling (MIDAS) model during the period 1990-2022 Theoretical Framework: The theoretical aspect addressed the different time-frequency models by defining the Midas models and addressing the weighting functions used in estimating these models.
Method: Estimating the relationship between a high-frequency variable (oil price) and a low-frequency variable (economic growth rate GDP) using the MIDAS model using Almon's PDL Weighting Function.
Results and Discussion: The results of the study concluded economic growth in Algeria is directly affected by oil prices, The study also found that MIDAS models have a great predictive ability, allowing researchers to utilize all available information for high-frequency variables, instead of using annual average values that lose a lot of information. avoid converting low-frequency variables to match high-frequency variables, reducing econometric issues in model diagnostics.
Research Implications: Research Implications: It is suggested that rentier countries such as Algeria work to diversify their economy away from oil, and follow up the process of economic diversification and accelerate it during periods of high fuel prices by working to develop non-strategic sectors as agriculture, tourism and manufacturing industries.
Originality/Value: These results are expected to benefit policymakers in government, by urging them to invest in renewable energies as a crucial strategy for achieving sustainable development and a key factor in mitigating oil price shocks, particularly during recent recurring global crises. Future research directions include exploring existing gaps and promoting standardized studies.
