The Impact of Macroeconomic Factors on the Rate of Young People in Neither Education nor Employment in OECD Countries

Yıl 2023, Cilt: 11 Sayı: 31, 56 - 68, 04.12.2023

Erhan Açar , Canan Güneş

https://doi.org/10.52528/genclikarastirmalari.1314685

Cited By: 1

Öz

Young individuals who are unemployed, not in the labor force, and have not received any training in the last four weeks are defined as NEET. In the study, with the 2005-2019 annual data of 38 OECD countries, the macroeconomic determinants of the NEET ratio are examined with the linear panel data model. Since it was determined that there were deviations from the assumptions that distorted the efficiency in the model, it was determined that the per capita GDP, GDP growth rate, gross national expenditure and population growth had a reducing effect on the NEET rate by estimating the fixed unit effect model with the Driscoll-Kraay resistive estimator. In addition, it was concluded that the increase in foreign direct investments, trade volume, labor productivity and education expenditures will increase the NEET rate.

Anahtar Kelimeler

Neet, young employment, linear panel date model

OECD Ülkelerinde Makroekonomik Faktörlerin Ne Eğitimde Ne İstihdamda Olan Gençlerin Oranına Etkisi

Öz

İşsiz, işgücüne dahil olmayan ve son dört hafta içinde herhangi bir eğitim almamış genç bireyler NEET olarak tanımlanmaktadır. Bu çalışmada OECD’ye üye 38 ülkenin 2005-2019 yıllık verileri ile NEET oranının makroekonomik belirleyicileri doğrusal panel veri modeli ile incelenmiştir. Modelde etkinliği bozan varsayımlardan sapmalar olduğu tespit edildiğinden Driscoll-Kraay dirençli tahmin edicisi ile sabit birim etkili model tahmin edilerek kişi başına düşen GSYİH, GSYİH büyüme oranı, gayri safi milli harcama ve nüfus artışının NEET oranı üzerinde azaltıcı etkisi olduğu tespit edilmiştir. Ayrıca doğrudan yabancı yatırımlar, ticaret hacmi, işgücü verimliliği ve eğitim harcamalarında meydana gelecek artışın NEET oranını arttıracağı sonucuna ulaşılmıştır.

Anahtar Kelimeler

NEET, genç işsizliği, doğrusal panel veri modelleri

Kaynakça

• Abayasekara, A. ve Gunasekara, N. (2019). Determinants of youth not in education, employment or training: Evidence from Sri Lanka. Review of Development Economics, 23(4), 1840–1862. https://doi.org/10.1111/rode.12615
• Baah-Boateng W. (2016). The youth unemployment challenge in Africa: What are the drivers? The Economic and Labour Relations Reviews, 27 (4), 413–31. https://doi.org/10.1177/1035304616645030
• Bal-Domańska, B. (2021). The impact of macroeconomic and structural factors on the unemployment of young women and men. Economic Change and Restructuring Advance Online Publication, 55(2), 1141–1172. https://doi.org/10.1007/s10644-021-09341-9
• Baltagi B. H. ve Wu P. (1999) Unequally spaced panel data regression with AR(1) disturbances. Econometric Theory, 15(6), 814–823.
• Bayrak, R. ve Tatlı, H. (2018). The determinants of youth unemployment: A panel data analysis of OECD Countries. The European Journal of Comparative Economics, 15(2), 231-248.
• Bhargava, A., Franzini, L. ve Narendranathan, W. (1982). Serial correlation and the fixed effects model. The Rewiev of Economic Studies, 49(4), 533-549.
• Bingöl, U. (2020). The macroeconomic determinants of neet: A panel data analysis for fragile five countries and Russia. Journal of Management and Economics Research, 18(4) , 173-189. https://doi.org/10.11611/yead.822305
• Bruno, G. S., Marelli, E. ve Signorelli, M. (2014). The rise of Neet and youth unemployment in EU Regions after the crisis. Comparative Economic Studies, 56(4), 592–615. https://doi.org/10.1057/ces.2014.27
• Caporale, G. M. ve Gil-Alana, L. (2014). Youth unemployment in Europe: Persistence and macroeconomic determinants. Comparative Economic Studies, 56(4), 581–591. https://doi.org/10.1057/ces.2014.29
• Caroleo, F.E., Rocca, A. ve Mazzocchi, P. (2020). Being neet ın Europe before and after the economic crisis: An analysis of the micro and macro determinants. Social Indicators Research, 149, 991–1024. https://doi.org/10.1007/s11205-020-02270-6
• Chen, L. X., Chew, Y. B., Lim, R. L. H., Tan, W. Y. ve Twe, K. Y. (2017). Macroeconomic factors affecting unemployment rate in China. Final Year Project, UTAR.
• De Lannoy, A. ve Mudiriza, G. (2019). A profile of young neets: Unpacking the heterogeneous nature of young people not in employment, education or training in South Africa cape town. SALDRU Working Paper No. 249.
• Driscoll, J. ve Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent data. Review of Economics and Statistics, 80 (4), 549–560.
• Ekiz, F. M. ve Örk Özel, S. (2020). Genç işsizliğini belirleyen unsurlar: Türkiye örneği. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 19(39), 1022-1045.
• European Training Foundation (ETF). (2015). Young People not in Employment, Education or Training (NEET). Torino.
• Folawewo, A. O. ve Adeboje, O. M. (2017). Macroeconomic determinants of unemployment: Empirical evidence from economic community of West African States. African Development Review, 29(2), 197-210. https://doi.org/10.1111/1467-8268.12250
• Frees, E. W. (2004). Longitudinal and Panel Data: Analysis and Applications in the Social Sciences. Cambridge University Press.
• Greene, W. H. (2000) Econometric analysis. Prentice-Hall.
• Gujarati, D. ve Porter, C. (2008). Basic Econometrics. McGraw-Hill Education.
• Halsall, A., Hollingworth, S. ve Mendick, H. (2005) Dropping out and drifting away: An investigation of factors affecting inner-city pupils' identities, aspirations and post-16 routes. Institute for Policy Studies in Education.
• Hausman, J. A. (1978) Specification tests in econometrics. Econometrica, 46(6), 1251–1271. https://doi.org/10.2307/1913827
• International Labour Organization (ILO). (2013). Decent work indicators: Guidelines for producers and users of statistical and legal framework indicators. ILO Publications.
• Karyda, M. ve Jenkins, A. (2018). Disadvantaged Neighbourhoods and young people not in education, employment or training at the ages of 18 to 19 in England. Journal of Education and Work, 31(3), 307–319. https://doi.org/10.1080/13639080.2018.1475725
• Köleoğlu, Y. (2019). Yüksek eğitimli gençlerin işe alımında yetenek temelli karar destek sistemi önerisi [Yayımlanmamış doktora tezi]. Sakarya Üniversitesi.
• Organisation for Economic Co-operation and Development (OECD). (2022). Youth not in employment, education or training (NEET). https://data.oecd.org adresinden 20 Mart 2022 tarihinde erişildi.
• Pemberton, S. (2008). Tackling the NEET generation and the ability of policy to generate a solution evidence from the UK. Environment and Planning C: Government and Policy, 26(1), 243–259. https://doi.org/10.1068/c0654
• Quintano, C., Mazzocchi, P. ve Rocca, A. (2018). The determinants of Italian Neets and the effects of the economic crisis. Genus, 74(1). https://doi.org/10.1186/s41118-018-0031-0
• Ranzani, M. ve Rosati, F. (2013). The NEET trap: A dynamic analysis for Mexico. Understanding Children’s Work Project.
• Strelitz, J. (2003). Tackling disadvantage: Education. David Darton ve Jason Strelitz (Ed), Tackling UK poverty and disadvantage in the twenty-first century: An exploration of the issues (s. 57–75) içinde. Joseph Rowntree Foundation.
• Susanli, Z. B. (2016). Understanding the NEET in Turkey. Eurasian Journal of Economics and Finance, 4(2), 42-57.
• Tsaurai, K. (2020). Macroeconomic determinants of unemployment in Africa: A panel data analysis approach. Acta Universitatis Danubius, 16(2), 89-112.
• Türkiye İstatistik Kurumu (TÜİK). (2021). Hanehalkı İşgücü Araştırması Hakkında Genel Açıklama. İşgücü istatistikleri, 2020. Haber Bülteni: 37484 içinde. https://data.tuik.gov.tr/Bulten/Index?p=Isgucu-Istatistikleri-2020-37484 adresinden 21 Ocak 2022 tarihinde erişildi.
• Wickremeratne, N. ve Dunusinghe, P. (2018). Youth not in education, employment and training (NEET) in Sri Lanka. Advances in Economics and Business, 6(5), 339-352.
• Wong, M. (2016). The Characteristics of youth not in education, employment or training (Neet) in Australia and Japan. Japan Institute for Labour Policy and Training.
• World Bank. (2022). Dünya Bankası Veri Tabanı. https://data.worldbank.org adresinden 20 Mart 2022 tarihinde erişildi.
• Yerdelen Tatoğlu, F. (2022). Panel veri ekonometrisi. Beta Basım Yayın Dağıtım A.Ş.