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Inflation Rate Prediction in Kuwait Using Data Mining Techniques

Kuwait has been under constant inflation over the last couple of years. Kuwait’s annual rate of inflation has been growing steadily over a number of years. Effective assessment of the rate of inflation helps articulate community issues and enhance economic development. Kuwait’s rate of inflation may be predicted through machine learning as it is more efficient in terms of accuracy and time spent while conducting the research.

Factors Affecting Inflation

            Kuwait has a flexible policy for labor that heightens its reliance on foreign force of labor. This adds to the sensitivity of the levels of prices to outward factors (Martin, 2019). Monetary policy attached to the exchange rate regime curtails active use of a financial policy that would help achieve actual sector objectives. The presence of an open capital account facilitates the dissipation of extra money supply via capital outflows.

Kuwait has a model of demand to facilitate and study inflation.  As much as demand comes at the cost of losing close to five years of observations, it is essential in that it facilitates accuracy (Martin, 2019). The model helps assess any forms of splits between years.

Predicting Model

            In Kuwait, there are vital constituents of the consumer price index (CPI) that would help assess the extent of inflation. Among them is housing that stands at 33.2%, food, and beverages at 16.7%, furnishing at 11.4%, clothing and transport at 8% and 7.5% respectively (Cohen & Keinan,2015). Other components include miscellaneous services and goods accounting for 5.8%, communication at 4%, education 4.2%, hotels, and restaurants at 3.4% and culture that lies at 3.9%.

As of 2019, the CPI for Kuwait rose by 0.3% in July in comparison to the previous month. Kuwait’s Mom rate of inflation averages 0.25% since 2001 to 2019 (Cohen & Keinan,2015). The all-time high was 2.2% in 2007 and the lowest ever recorded was -0.8 in July 2005.

References

Cohen, R.A. & Keinan, Y. ( 2015). The Issue of Citizenship for the Bidun Minority in Kuwait after the Arab Spring.

Martin, C.L. (2019). Machine Learning vs. Traditional Forecasting Methods: An Application to South African GDP.

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