SPATIAL PANEL DATA ANALYSIS OF REGIONAL NEET DATA IN TURKEY

Year 2022, Volume: 10 Issue: 2, 113 - 129, 29.12.2022

Melike Köken , Selçuk Koç

Abstract

The young population has a prominent place in the social and economic development of the countries. While the young population, seen as an advantage in social and economic policies, has a positive effect on the level of development and economy of the countries in terms of education, employment, and training; young people who are out of education and training, cause a cost to the countries in terms of social and economic terms. According to 2020 data, Turkey has the highest NEET rate country for both genders and in total rates among OECD countries. NEET has become an issue that requires special attention for Turkey. Therefore, in this study, spatial analysis was conducted to examine the regional-level interactions of the rates of youth in education, employment, and training (NEET) aged 15-24 in Turkey. The variables thought to affect the NEET rate were included in the model, and results showed that the spatial effect stems from the spatial error term that there is no direct relationship between the NEET rates in a region and the NEET rates in the neighboring region. However, there is dependence arising from spatial relationships.

Keywords

NEET, Spatial Panel Data Analysis, Fixed Effect Spatial Error Model

TÜRKİYE’DE BÖLGESEL NEET VERİLERİNİN MEKANSAL PANEL VERİ ANALİZİ

Abstract

Ülkelerin toplumsal ve ekonomik gelişmelerinde genç nüfus önemli bir yere sahiptir. Sosyal ve ekonomik politikalarda avantaj olarak görülen genç nüfusun eğitim, istihdam ve yetiştirmede olması ülkelerin gelişmişlik düzeylerine ve ekonomilerine olumlu etki sağlarken eğitim, öğretim ve yetiştirme dışında kalan gençler sosyal ve ekonomik açıdan ülkelere maliyet oluşturmaktadır. Türkiye 2020 yılı verilerine göre OECD ülkeleri arasında her iki cinsiyette ve toplam oranda en yüksek NEET (“Not in Education, Employment or Training”, “Ne Eğitimde Ne İstihdamda Ne De Yetiştirmede”) oranına sahip ülke konumundadır. NEET konusu Türkiye için özel önem gerektiren bir konu hâline gelmiştir. Bu nedenle bu çalışmada Türkiye’de 15-24 yaş aralığındaki istihdam, eğitim ve yetiştirmede olmayan genç oranlarının bölgesel düzeydeki etkileşimlerini incelemek amacıyla mekansal analiz yapılmıştır. NEET oranını etkilediği düşünülen değişkenler modele dahil edilmiş ve çıkan sonuçlara göre mekansal etkinin mekansal hata teriminden kaynaklandığı yani bir bölgedeki NEET oranları ile komşu bölgedeki NEET oranları arasında doğrudan bir ilişki olmadığını ancak mekansal ilişkilerden kaynaklanan bağımlılığın mevcut olduğunu göstermiştir.

Keywords

NEET, Mekansal Panel Veri Analizi., sabit etkili mekansal hata modeli

References

• Allen, M. (2014). Local Action on Health Inequalities: Reducing The Number Of Young People Not In Employment, Education Or Raining (NEET). London: Institute of Health Equity.
• Anselin, L. (1988). Spatial Econometrics: Methods and Models, Germany: Springer Science & Business Media.
• Anselin, L. (2001). Spatial Econometrics. In B. H. Baltagi(Ed.), A Companion to Theoretical Econometrics (pp.310-330). Blackwell Publishing Ltd.
• Anselin, L. and Getis, A. (1992). Spatial Statistical Analysis and Geographic Information Systems. The Annals of Regional Science, 26(1), 19-33.
• Anselin, L. and Hudak S. (1992). Spatial Econometrics in Practice: A Review of Software Options. Regional Science and Urban Economics, 22(3), 509-536.
• Anselin, L., Bera A. K., Florax R and. Yoon M. J. (1996). Simple Diagnostic Test for Spatial Dependence. Regional Science and Urban Economics, 26(1), 77-104.
• Anselin, L., Gallo J. L. and Jayet H. (2008). Spatial Panel Econometrics. In L. Mátyás, P. Sevestre(Ed.), In The Econometrics of Panel Data (pp.625-660). Berlin, Springer.
• Carcillo, S. Fernández R. And Königs S. (2015), NEET Youth in the Aftermath of the Crisis: Challenges and Policies, OECD Social, Employment and Migration Working Papers, No. 164, Retrieved 16 November 2021 from https://ssrn.com/abstract=2573655 .
• Elhorst, J. P. (2003). Specification and Estimation of Spatial Panel Data Models. International Regional Science Review, 26(3), 244-268.
• Elhorst, J. P. (2010). Applied Spatial Econometrics: Raising the Bar. Spatial Economic Analysis, 5(1), 9-28.
• Elhorst, J. P. (2014). "Spatial Panel Models." In M. M. Fischer and P. Nijkamp(Ed.), Handbook Of Regional Science (pp.1637-1652), Berlin: Springer.
• Elhorst, J. P. (2017). Spatial Panel Data Analysis. In S. Shekhar, H. Xiong and X. Zhou (Ed.), Encyclopedia of GIS (pp. 2050-2058). Switzerland: Springer International Publishing.
• European Commission. (2011). Youth Neither in Employment Nor Education And Training (NEET) Presentation of Data For The 27 Member States. EMCO Contribution.
• Fischer, M. M. and Wang J. (2011). Spatial Data Analysis: Models, Methods and Techniques, Vienna: Springer Science & Business Media.
• Gibbons, S. and Overman H. G. (2012). Mostly Pointless Spatial Econometrics?, Journal of Regional Science, 52(2), 172–191.
• Güriş, S. ve Çağlayan T. (2018). Mekansal Yapı İktisadi Büyümeyi Etkiler Mi : OECD Ülkeleri Örneği. Finansal Araştırmalar ve Çalışmalar Dergisi, 10(19), 277-290.
• Hill, J. (2003). Young People Not in Education, Training, or Employment: Key Indicators. New Zealand: Ministry of Social Development.
• Katy, S., Akister J. and Burch S. (2015). Who Are The Young People Who Are Not In Education, Employment Or Training? An Application Of The Risk Factors To A Rural Area In The UK. International Social Work, 58(4), 508-520.
• Kelejian, H. H. and Prucha I. R (2001). On The Asymptotic Distribution Of The Moran I Test Statistic With Applications. Journal of Econometrics, 104, 219–257.
• Kılıç, Y. (2014). Türkiye'de Ne Eğitimde Ne İstihdamda Ne de Yetiştirmede (NEİY) Yer Alan Gençler. Eğitim ve Bilim Dergisi,39 (175), 121-135.
• LeSage, J. P. (1999). The Theory and Practice of Spatial Econometrics. Ohio: University of Toledo.
• LeSage, J. P. and Pace R. K. (2014). Interpreting Spatial Econometric Model. In M.M. Fischer and P. Nijkamp (Ed), Handbook of Regional Science (pp. 1535-1552). Berlin: Springer.
• Mascherini, M. (2019) Origins And Future Of The Concept Of NEETS In The European Policy Agenda. In O'Reilly, J., Leschke, J., Ortlieb, R., Seeleib-Kaiser, M., and Villa, P. (Eds.), Youth Labor in Transition: Inequalities, Mobility, and Policies in Europe (pp. 503- 529). USA: Oxford University Press
• Mascherini, M., Salvatore L., Meierkord A. and Jungblut J. M. (2012). NEETs:Young People Not in Employment, Education Or Training: Characteristics, Costs And Policy Responses in Europe. Luxembourg: Publications Office of the European Union.
• Nam, J. (2011). Not in Education, Employment, or Training (NEET) in Korea: Status and Trends. e-Labor News No. 111:1-10. Retrieved 17 November 2021 from https://www.kli.re.kr/downloadBbsFile.do?atchmnflNo=9921 .
• Oden, N. (1995). Adjusting Moran's I for Population Density. Statistics in Medicine, 14(1), 17-26.
• Pitkänen, J., Remes H., Moustgaard H. and Martikainen, P. (2021). Parental Socioeconomic Resources And Adverse Childhood Experiences As Predictors Of Not In Education,Employment, Or Training: A Finnish Register-Based Longitudinal Study. Journal Of Youth Studies, 24 (1), 1-18.
• Social Exclusion Unit (1999), Bridging The Gap: New Opportunities For 16–18 Year-Olds Not In Education, Employment Or Training, London.
• Vega, S. H. and Elhorst. J. P. (2013). On Spatial Econometric Models, Spillover Effects, And W. In 53rd ERSA Congress (pp.1-28). Palermo, Italy:
• Yerdelen Tatoğlu, F. (2022). Mekansal Ekonometri Stata Uygulamalı. İstanbul: BetaYayıncılık.
• Yüji, G. (2007). Jobless Youths and the NEET Problem in Japan. Social Science Japan Journal,10 (1), 23-40.
• Zeren, F. (2010). Mekansal Etkileşim Analizi. İstanbul Üniversitesi İktisat Fakültesi Ekonometri ve İstatistik Dergisi,12, 18-39.