FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS

Abstract

Since the unemployment rate is a critical factor that directly affects a country's economic performance and social health, reducing unemployment with effective policies is of great importance for sustainable development and prosperity. Therefore, precise forecasting of the unemployment rate is pivotal to effective policymaking and planning, especially in Japan, where unique demographic structures and economic challenges prevail. This study aims to estimate the unemployment rate in Japan using an Artificial Neural Network (ANN) model with the annual data for the period 1985-2017. Key factors shaping Japan's labour market dynamics, such as artificial intelligence-related technology patent applications, inflation rate, population growth rate, and labour productivity, are used to estimate the unemployment rate. The findings indicate that the Japanese unemployment rate is expected to increase gradually until 2030. This research provides significant insights to the Japanese government and policymakers through a non-linear forecasting model that includes the variable of artificial intelligence, which has not previously been used in the literature.

Keywords

• Artificial Neural Networks
• Unemployment Forecasting
• Artificial Intelligence
• Japan

JAPONYA’DA İŞŞİZLİĞİN GELECEĞİ: YAPAY ZEKA VE MAKROEKONOMİK DİNAMİKLER İLE BİR YAPAY SİNİR AĞI TAHMİNİ

Abstract

Öz İşsizlik oranlarını azaltmak bir ülkenin hem ekonomik performansını hem de sosyal sağlığını doğrudan etkileyen kritik bir faktör olduğundan, etkili politikalarla işsizlikle mücadele etmek sürdürülebilir kalkınma ve refah için büyük önem taşımaktadır. Bu nedenle işsizlik oranını doğru bir şekilde tahmin etmek, özellikle benzersiz demografik yapıların ve ekonomik zorlukların hakim olduğu Japonya'da, etkili ekonomik planlama ve strateji geliştirmenin merkezinde yer almaktadır. Bu çalışma, 1985-2017 dönemine ait yıllık verilerle Yapay Sinir Ağı (YSA) modeli kullanarak Japonya'daki işsizlik oranını tahmin etmeyi amaçlamaktadır. Yapay zeka ile ilgili teknoloji patent başvuruları, , enflasyon oranı, nüfus artış hızı ve işgücü verimliliği gibi Japonya'nın işgücü piyasası dinamiklerini şekillendiren temel faktörler işsizlik oranını tahmin etmek için kullanılmıştır. Sonuçlar, işsizlik oranının 2030 yılına kadar kademeli olarak artacağının beklendiğini göstermektedir. Bu araştırma, literatürde daha önce kullanılmamış olan yapay zekayı değişkenini de içeren doğrusal olmayan bir tahmin modeli aracılığıyla hesaplandığından Japon hükümetine ve politika yapıcılara önemli bilgiler sağlamaktadır.

Keywords

• Yapay Sinir Ağları
• İşsizlik Tahmini
• Yapay Zeka
• Japonya

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