Using the Box-Jenkins methodology to forecast unemployment rates in Iraq

Abstract

AbstractThe phenomenon of unemployment is one of the main problems facing the various global economic systems, developed and underdeveloped alike. Today, in light of globalization, it represents one of the serious challenges of new global systems. And if the term economic development implies a specific concept, then that concept corresponds to broader social goals, including providing each individual with the ability to meet their own needs, and not remain the same, but in the event that economic development cannot be returned simply because of a purely cumulative physical process, then it must Looking at it from the point of view of the real jobs it provides, especially as the Iraqi economic and social system in particular has suffered and is still suffering from the complications of unemployment and its negative consequences. The research aims to use the Box-Jenkins methodology (ARIMA) to predict unemployment rates in Iraq for the period 2020-2025 based on a time series of unemployment rates in Iraq that covered the period 1991-2019. Statistical methods were used to study the properties of the time series, where a clear fluctuation was observed in the time series. Through statistical analysis, the two researchers reached a set of results, the most important of which was that the appropriate model for predicting unemployment rates is the ARIMA model (1,1,1) out of a set of proposed models for having the lowest values for AIC and BIC standards and the remainder of this model to achieve white noise characteristics. This model was used to predict unemployment rates for the period 2020-2025.Key words: Unemployment, Box-Jenkins, Time Series, Prediction.