EN
TR
FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS
Öz
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.
Anahtar Kelimeler
Kaynakça
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Ekonometri (Diğer), Makro İktisat (Diğer)
Bölüm
Araştırma Makalesi
Erken Görünüm Tarihi
25 Şubat 2025
Yayımlanma Tarihi
15 Mart 2025
Gönderilme Tarihi
6 Ağustos 2024
Kabul Tarihi
10 Aralık 2024
Yayımlandığı Sayı
Yıl 2025 Cilt: 27 Sayı: 1
APA
Yıldız, A., & Adam, G. (2025). FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 27(1), 195-217. https://doi.org/10.16953/deusosbil.1528927
AMA
1.Yıldız A, Adam G. FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2025;27(1):195-217. doi:10.16953/deusosbil.1528927
Chicago
Yıldız, Ayşegül, ve Gülşah Adam. 2025. “FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS”. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 27 (1): 195-217. https://doi.org/10.16953/deusosbil.1528927.
EndNote
Yıldız A, Adam G (01 Mart 2025) FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 27 1 195–217.
IEEE
[1]A. Yıldız ve G. Adam, “FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS”, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, c. 27, sy 1, ss. 195–217, Mar. 2025, doi: 10.16953/deusosbil.1528927.
ISNAD
Yıldız, Ayşegül - Adam, Gülşah. “FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS”. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 27/1 (01 Mart 2025): 195-217. https://doi.org/10.16953/deusosbil.1528927.
JAMA
1.Yıldız A, Adam G. FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2025;27:195–217.
MLA
Yıldız, Ayşegül, ve Gülşah Adam. “FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS”. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, c. 27, sy 1, Mart 2025, ss. 195-17, doi:10.16953/deusosbil.1528927.
Vancouver
1.Ayşegül Yıldız, Gülşah Adam. FUTURE OF UNEMPLOYMENT IN JAPAN: AN ARTIFICIAL NEURAL NETWORK FORECAST UTILISING ARTIFICIAL INTELLIGENCE AND MACROECONOMIC DYNAMICS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 01 Mart 2025;27(1):195-217. doi:10.16953/deusosbil.1528927