Abstract:

Unemployment, which is one of the chronic problems of the undeveloped and developing countries, can become agenda, especially in the times of global crisis, even in the developed countries. Unemployment can be seen as a common problem for all countries. Therefore, it becomes very important to predict the values that such a significant economic change can take in future periods by moving from the values it has received in past periods. Today, many quantum techniques are used to predict time series. But the important thing here is that the error rates resulting from the predictions they make can be kept at a minimum level. In this sense, sometimes the modification of the error terms, sometimes the combination of different techniques, is attempted to reduce the error rates and get more accurate predictions. For the plans for the future and the policies that can be determined only get meaning by these forecasts. Our study also focuses on making more accurate predictions, the unemployment rate in Turkey has been predicted with the GM (1,1) model after the GM (1,1) model has been integrated with the Markov chains and the Gri Markov model has been established and the unemployment rate has been re-predicted in this way. Finally, the GM (1,1) model’s forecast results were compared with the Grey Markov model’s forecast results and the Grey Markov model was shown to produce forecast values with high accuracy values.

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