Makroekonomik Faktörlerin NEET’e Etkisi: Seçilmiş Gelişmekte Olan Ülkeler için Panel Veri Analizi

Öz

Ekonomik ve sosyal politikalara, toplumsal ve bireysel nedenlere dayalı karmaşık bir yapının etkileşimi sonucunda gençler, eğitimden ve işgücü piyasasından uzaklaşıp ne eğitimde ne istihdamda (NEET) statüsünde yer almaya başlayarak önemli bir sorun haline gelmektedir. Bu çalışmada, makroekonomik göstergelerin NEET oranına etkisinin 10 gelişmekte olan ülke için 2001-2024 yılları kapsamında panel ARDL (Autoregressive Distirbuted Lag-otoregresif dağıtılmış gecikmeli model) ile analiz edilmesi amaçlanmıştır. Bulgulara göre, uzun dönemde gayri safi yurtiçi hasıla ve sabit sermaye oluşumundaki artış NEET oranını azaltıcı etki yaratırken, eğitim harcamalarındaki artışın NEET oranını artırıcı etkisi olduğu tespit edilmiştir. Enflasyon ve işgücü verimliliği değişkenlerinin uzun dönemde istatistiksel olarak anlamlı olmadığı görülmüştür. İktisadi büyüme ve yatırımlardaki artışın gelişmekte olan ülkelerde istihdam olanaklarını artırmaları ve işgücü piyasası koşullarını iyileştirmeleri ile NEET oranını azalttığını söylemek mümkündür. Eğitim harcamalarının NEET oranını azaltması için gençleri ekonomik alanda karşılığı olan yetkinliklerle donatacak nitelikli eğitim sistemi yaratacak şekilde değerlendirilmesi gerekmektedir. Gelişmekte olan ülkelerde, gençlerin NEET olma eğiliminin azaltılmasının ülkelerin öncelikle olumlu ekonomik yapısı ile ilişkili olduğu ve buna dayalı olarak etkin sosyal politikaların ve kurumsal yapılanmaların geliştirebileceği dikkate alınmalıdır.

Anahtar Kelimeler

• NEET
• Genç işsizliği
• İstihdam
• Panel veri analizi

The Impact of Macroeconomic Factors on NEET: Panel Data Analysis for Selected Developing Countries

Öz

The interaction of a complex structure based on economic and social policies, as well as societal and individual factors, is causing young people to become disengaged from education and the labor market, leading them to fall into the NEET (Not in Education, Employment, or Training) category, which has become a significant problem. The aim of this study is to analyze the effect of macroeconomic indicators on the NEET rate for 10 developing countries using annual data covering the period 2001-2024 with a panel ARDL (Autoregressive Distributed Lag) model. According to the findings, while increases in gross domestic product and fixed capital formation in the long run have a reducing effect on the NEET rate, increases in education spending have been found to have an increasing effect on the NEET rate. Inflation and labor productivity variables were found to be statistically insignificant in the long run. It is possible to say that economic growth and increased investment in developing countries have reduced the NEET rate by increasing employment opportunities and improving labor market conditions. In order for education spending to reduce the NEET rate, it is necessary to evaluate the creation of a quality education system that will equip young people with skills that are economically relevant. In developing countries, it should be considered that reducing the tendency of young people to become NEETs is primarily related to the positive economic structure of countries, and, based on this, effective social policies and institutional structures can be developed.

Anahtar Kelimeler

• NEET
• Youth unemployment
• Employment
• Panel data analysis

Kaynakça

1. Açar, E. ve Güneş, C. (2023). OECD ülkelerinde makroekonomik faktörlerin ne eğitimde ne istihdamda olan gençlerin oranına etkisi. Gençlik Araştırmaları Dergisi, 11(31), 56-65.
2. Amendola, S. (2022). Macro-determinants of NEET: An ecological study at the country level of analysis for the period 1997–2020. Youth, 2, 384–390.
3. Bal-Domanska, B. (2022). The impact of macroeconomic and structural factors on the unemployment of young women and men. Economic Change and Restructuring, 55, 1141-1172.
4. Bayrak, R. ve Tatli, H. (2018). The determinants of youth unemployment: A panel data analysis of OECD Countries. The European Journal of Comparative Economics, 15(2), 231-248.
5. Bell, D. N. F. ve Blanchflower, D. G. (2011). Young people and the Great Recession. Oxford Review of Economic Policy, 27(2), 241-267.
6. Benito, S. M. R., Laxe, F. G. ve Picatoste, X. (2018). Sustainable development, poverty, and risk of exclusion for young people in the European Union: The case of NEETs. Sustainability, 10(12), 1-15.
7. Bingöl, U. (2020). The macroeconomic determinants of NEET: A panel data analysis for Fragile Five Countries and Russia. Yönetim ve Ekonomi Araştırmaları Dergisi, 18(4), 173-189.
8. Breusch, T. S., & Pagan, A. R. (1980). The lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.

9. Brunetti, I. ve Corsini, L. (2019). School-to-work transition and vocational education: A comparison across Europe. International Journal of Manpower, 40(8), 1411-1437.
10. 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, 592-615.
11. Caporale, G. M. ve Gil-Alana, L. (2014). Youth unemployment in Europe: Persistence and macroeconomic determinants. Comparative Economic Studies, 56, 581-591.
12. Caroleo, F. E. ve Pastore, F. (2007). The youth experience gap: Explaining differences across EU countries. Quaderni del Dipartimento di Economia, Finanza e Statistica No: 41. Perugia: Università degli Studi di Perugia.
13. Caroleo, F. E., Rocca, A., Mazzocchi, P. ve Quintano, C. (2020). Being NEET in Europe before and after the economic crisis: An analysis of the micro and macro determinants. Social Indicators Research, 149, 991-1024.
14. Choudhry, M. T., Marelli, E. ve Signorelli, M. (2012). Youth unemployment rate and impact of financial crises. International Journal of Manpower, 33(1), 76-95.
15. De Luca, G., Mazzocchi, P., Quintano, C. ve Rocca, A. (2020). Going behind the high rates of NEETs in Italy and Spain: The role of early school leavers. Social Indicators Research, 151, 345-363.
16. Drakaki, M., Papadakis, N., Kyridis, A. ve Papargyris, A. (2014). Who’s the greek neet? Neets’ profile in Greece: Parameters, trends and common characteristics of a heterogeneous group. International Journal of Humanities and Social Science, 4(6), 240–254.
17. Ekiz, F. M. ve Örk Özel, S. (2020). Genç işsizliğini belirleyen unsurlar: Türkiye örneği. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, (39), 1022-1045.
18. Elder, S. (2015). What does NEETs mean and why is the concept so easily misinterpreted?. ILO Youth Employment Programme Work4Youth Technical Brief No: 1. Geneva: International Labor Office.
19. Eurofound. (2012). NEETs – Young people not in employment, education or training: characteristics, costs and policy responses in Europe. Luxembourg: Publications Office of the European Union. https://assets.eurofound.europa.eu/f/279033/9e48d8f2be/ef1254en.pdf
20. Ghoshray, A., Ordonez, J. ve Sala, H. (2016). Euro, crisis and unemployment: Youth patterns, youth policies?. Economic Modelling, 58, 442-453.
21. Gladwell, D., Popli, G. ve Tsuchiya, A. (2022). Predictors of becoming not in education, employment or training: A dynamic comparison of the direct and indirect determinants. Journal of the Royal Statistical Society: Series A (Statistics in Society), 185(Supple. 2), s. 485-514.
22. Gunnes, M., Thaulow, K., Kaspersen, S. L., Jensen, C. ve Ose, S. O. (2025). Young adults not in education, employment, or training (NEET): a global scoping review. BMC Public Health, 25, 1-20.
23. Güney, K. ve Cin, M. F. (2020). Avrupa Birliği ve Türkiye’de genç işsizliğin belirleyicileri: Panel veri analizi. ÇAKÜ Sosyal Bilimler Enstitüsü Dergisi, 11(1), 232-252.
24. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251-1271.
25. International Labour Organization (ILO). (2019). Young People not in Employment, Education, or Training. ILO Employment Policy Department Technical Brief No: 3. https://www.ilo.org/sites/default/files/wcmsp5/groups/public/%40ed_emp/documents/publication/wcms_735164.pdf
26. International Labour Organization (ILO). (2020). Global Employment Trends for Youth 2020: Technology and The Future Jobs. Geneva: International Labour Office.
27. International Labour Organization (ILO). (2025). SDG labour market indicators (ILOSDG) - ILOSTAT data explorer. https://ilostat.ilo. org/data/
28. International Labour Organization (ILO). (2025). World Employment and Social Outlook: Trends 2025. Geneva: International Labour Office.
29. International Labour Organization (ILO). (2026). World of Work Series: Employment and Social Trends. Geneva: International Labour Office.
30. International Monetary Fund (IMF). (2025). World economic outlook: Global economy in flux, prospects remain dim. Washington, DC: IMF Publications. https://www.imf.org/-/media/files/publications/weo/2025/october/english/text.pdf
31. Kabakçı Günay, E. (2025). Macroeconomic indicators affect the NEET: A panel data analysis for BRICST countries. bmij, 13(1), 229-242.
32. Karma, E. (2024). NEET youth in central and eastern European countries: a panel model approach. Journal of Youth Studies, 28(9), 1458-1475.
33. Kelly, E. ve McGuinness, S. (2015). Impact of the Great Recession on unemployed and NEET individuals’ labour market transitions in Ireland. Economic Systems, 39(1), 59-71.
34. Kraak, A. (2013). State failure in dealing with the NEET problem in South Africa: which way forward?. Research in Post-Compulsory Education, 18(1-2), 77-97.
35. Levels, M., Brzinsky-Fay, C., Holmes, C., Jongbloed, J. ve Taki, H. (2022). Not in Employment, Education, or Training around the World. M. Levels, C. Brzinsky-Fay, C. Holmes, J. Jongbloed ve H. Taki (Ed.), The Dynamics of Marginalized Youth (ss. 1-24) içinde. London: Routledge.
36. Lordoğlu, K. ve Özkaplan, N. (2005). Çalışma İktisadı (2. bs.). İstanbul: Der Yayınları.
37. Malo, M. A., Mussida, C., Cueto, B. ve Baussola, M. (2023). Being a NEET before and after the Great Recession: persistence by gender in Southern Europe. Socio-Economic Review, 21(1), 319-339.
38. Mascherini, M. (2018). Origins and future of the concept of NEETs in the European policy agenda. J. O’Reilly, J. Leschke, R. Ortlieb, M. Seeleib-Kaiser ve P. Villa (Ed.), Youth labor in transition: Inequalities, mobility, and policies in Europe (ss. 503-529) içinde. Oxford: Oxford University Press.
39. Maynou, L., Ordonez, J. ve Silva, J. I. (2022). Convergence and determinants of young people not in employment, education or training: An European regional analysis. Economic Modelling, 110, 1-11.
40. Mehmetaj, N. ve Xhindi, N. (2022). Public expenses in education and youth unemployment rates— a vector error correction model approach. Economies, 10(12), 1-14.
41. Mussida, C. ve Sciulli, D. (2023). Being poor and being NEET in Europe: Are these two sides of the same coin?. The Journal of Economic Inequality, 21, 463-482.
42. O’Higgins, N. (1997). The challenge of youth unemployment. International Social Security Review, 50(4), 63-93.
43. Pennoni, F. ve Bal-Domanska, B. (2022). NEETs and youth unemployment: A longitudinal comparison across European Countries. Social Indicators Research, 162, 739-761.
44. Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics No: 0435. https://files.econ.cam.ac.uk/repec/cam/pdf/cwpe0435.pdf
45. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22, 265-312.
46. Pesaran, M. H., Shin, Y. ve Smith, R. P. (1997). Pooled estimation of long-run relationships in dynamic heterogenous panels. DAE Working Papers Amalgamated Series 9721.
47. Pesaran, M. H., Shin, Y. ve Smith, R. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621-634.
48. Pesaran, M. H. ve Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79-113.
49. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias-adjusted LM test of error cross-section independence. Econometrics Journal, 11, 105-127.
50. Quintini, G. ve Martin, S. (2014). Same Same But Different: School-to-Work Transitions in Emerging and Advanced Economies. OECD Social, Employment and Migration Working Papers No: 154. https://www.oecd.org/content/dam/oecd/en/publications/reports/2014/ 01/same-same-but-different-school-to-work-transitions-in-emerging-and-advanced economies _g17a2450/5jzbb2t1rcwc-en.pdf
51. World Bank. (2025). World development indicators. https://databank.worldbank.org/source/world-development-indicators