Analysis of the Potential of International Migration Issues in the Context of Economic Indicators is Provided in Time Series Analysis: The Case of Turkey

Abstract

The phenomenon of migration, starting with the existence of humanity and continuing until today, can be evaluated in the context of two main functions, especially in recent years. The first is the phenomenon of illegal migration and the other is the phenomenon of international migration.
The phenomenon of illegal immigration is a phenomenon that gains importance with the change of international security perceptions and is considered as a security threat.
Turkey, both geographical location as being sourced from the environmental status of developed country by country, international migration and illegal immigration, as well as being the country of transit countries also come to the fore. However, it is clear that it does not have as strict measures as other countries that have a say in the context of migration effects. This situation is directly related to the phenomenon of irregular migration as well as lack of data on migration and other migration related issues.
In this study, since the realization of the basic concepts explaining the phenomenon of migration for international migration in Turkey will be discussed likely to cause socio-economic problems. Turkey should both source and transit in migration issues in the target countries qualify as international issues will be discussed. In this case the cost of Turkey or sing with a clearer impact on market conditions functioning in Turkey will be investigated.
In this study, time series analysis will be studied. As the dependent variable is the number of immigrants who are present in Turkey determined arguments producer price index, consumer price index and gross domestic revenue. Gretel Lab Cloud program will use Breusch-Godfrey autocorrelation analysis. The study will be analyzed to cover the years 2005-2023. On the other hand, the data set to be used in the analysis will be discussed on an annual basis.
Machine learning models have the ability to detect hidden patterns in data and identify complex relationships between variables. The machine learning algorithms that will be used in this research can help us to analyse the factors affecting the migration phenomenon in Turkey and the effects of these factors on economic indicators.
Machine learning methods can reveal important information about the migration phenomenon in Turkey. Moreover, machine learning models can also be used to predict future migration trends. This may be effective in making more informed decisions while shaping Turkey’s policies on migration phenomenon.
However, should also consider the limitations of the machine learning methods. To use in our project. The quality and representativeness of the data set may affect the reliability of the machine learning results. Also, the complexity of the model and the interpretability of the results are important.