CAUSALITY RELATIONSHIP BETWEEN YOUTH UNEMPLOYMENT AND NEET RATES BY GENDER: A COMPARISON OF BALTIC AND MEDITERRANEAN COUNTRIES

Abstract

This study examines the causal relationship between youth unemployment and NEET rates in Baltic and Mediterranean countries. In the Baltic countries, a transition from NEET to youth unemployment is observed, while no causal relationship is found in terms of gender. In Mediterranean countries, it has been determined that male NEETs are a cause of youth unemployment, while there is a transition from unemployment to NEET among females. The differences between genders deepen the socio-economic impacts of these two concepts. Additionally, the findings between Baltic and Mediterranean countries demonstrate the effects of gender discrimination in labor markets. As a result, while gender equality is higher in Baltic countries, female NEETs emerge as the most disadvantaged group in Mediterranean countries. This situation emphasizes the need for policies to increase youth participation in the labor market.

Keywords

• NEET
• YOUTH UNEMPLOYMENT
• YOUTH
• GENDER
• CAUSALITY ANALYSIS

CİNSİYETLER ARASI GENÇ İŞSİZLİĞİ VE NEET ORANLARI ARASINDA NEDENSELLİK İLİŞKİSİ: BALTIK VE AKDENİZ ÜLKELERİ KARŞILAŞTIRMASI - CAUSALITY RELATIONSHIP BETWEEN YOUTH UNEMPLOYMENT AND NEET RATES BY GENDER: BALTIC VERSUS MEDITERRANEAN

Abstract

Bu çalışma, Baltık ve Akdeniz ülkelerinde genç işsizlik ile NEET oranları arasındaki nedensellik ilişkisini incelemektedir. Baltık ülkelerinde NEET'ten genç işsizliğine doğru bir geçiş gözlemlenirken, cinsiyet açısından bir nedensellik ilişkisi bulunmamaktadır. Akdeniz ülkelerinde ise erkek NEET'lerin genç işsizliğin nedeni olduğu, kadınlarda ise işsizlikten NEET'e geçiş olduğu tespit edilmiştir. Cinsiyetler arasındaki farklılıklar, bu iki kavramın sosyo-ekonomik etkilerini derinleştirmektedir. Ayrıca, Baltık ülkeleri ile Akdeniz ülkeleri arasındaki bulgular, işgücü piyasalarındaki toplumsal cinsiyet ayrımcılığının etkisini göstermektedir. Sonuç olarak, Baltık ülkelerinde cinsiyet eşitliği daha yüksekken, Akdeniz ülkelerinde kadın NEET'lerin en dezavantajlı grup olduğu ortaya çıkmaktadır. Bu durum, gençlerin işgücü piyasasına katılımını artıracak politikaların gerekliliğini vurgulamaktadır. JEL CODE: C01, C33, C51, E24 Declaration of Competing Interest: There is no conflict of interest among the authors. Author Contribution Rate: Authors contributed equally to the study. Funding (Finansman): No funding was received from any organization

Keywords

• NEET
• GENÇ İŞSİZLİĞİ
• GENÇLİK
• CİNSİYET
• NEDENSELLİK ANALİZİ

References

1. Abrigo, M. R., & Love, I. (2016). Estimation of panel vector autoregression in Stata. The Stata Journal, 16(3), 778-804.
2. Akaike, H. 1974. A new look at the statistical model identification. IEEE transactions on Automatic Control 19: 716-723.
3. Arulampalam W (2001) Is unemployment really scarring? Effects of unemployment experiences on wages. Econ J 111(475), 585–606.
4. Avagianou, A., Kapitsinis, N., Papageorgiou, I., Strand, A. H., & Gialis, S. (2022). Being NEET in Youthspaces of the EU South: A Post-recession Regional Perspective. YOUNG, 30(5), 425-454. https://doi.org/10.1177/11033088221086365.
5. Bălan, M. (2013). Estimates of the rise of neet and youth unemployment in South East European countries3. European perspectives of the labour market, 29-41.
6. Bayrakdar, S., & İncekara, A. (2013). Türkiye’nin Genç İşsizlik Profili. Çalışma İlişkileri Dergisi, 4(1), 15-38.
7. Bell B, Bindler A, Machin S (2014) Crime scars: recessions and the making of career criminals. CEP Discussion Papers dp1284, Centre for Economic Performance, LSE, London.
8. Bell DN, Blanchflower DG (2010) Youth unemployment: Déjà Vu?. IZA Discussion Papers 4705, Institute for the Study of Labor (IZA), Bonn.

9. Bradley S, Migali G, Navarro Paniagua M. Spatial variations and clustering in the rates of youth unemployment and NEET: A comparative analysis of Italy, Spain, and the UK. J Regional Sci. 2020; 60: 1074–1107. https://doi.org/10.1111/jors.12501.
10. Breitung, J. 2000. The local power of some unit root tests for panel data. In Advances in Econometrics, Volume 15: Nonstationary Panels, Panel Cointegration, and Dynamic Panels,ed. B. H. Baltagi, 161-178. Amsterdam: JAI Press.
11. Breitung, J., and S. Das. 2005. Panel unit root tests under cross-sectional dependence. Statistica Neerlandica 59: 414-433.
12. Breusch, T.S., and A.R. Pagan (1980): “The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics,” Review of Economic Studies 47, 239-253.
13. Bruno, G., Marelli, E. & Signorelli, M. The Rise of NEET and Youth Unemployment in EU Regions after the Crisis. Comp Econ Stud 56, 592–615 (2014). https://doi.org/10.1057/ces.2014.27
14. Caliendo, M., & Schmidl, R. (2016). Youth unemployment and active labor market policies in Europe. IZA Journal of Labor Policy, 5, 1-30.
15. Cambridge Working Papers in Economics 0346, Faculty of Economics (DAE), University of Cambridge Choudhry MT, Marelli E, Signorelli M (2012) Youth unemployment rate and impact of financial crises. Int J Manpow 33(1):76–95.
16. Çolak, K. & Koç, S., (2023b). Türkiye ve AB Aktif İşgücü Piyasası Neet’lerin Mevcut Durum Analizi ve Çözüm Politikaları, International Marmara Social Sciences Congress (Imascon Spring), 238-250.
17. Çolak, K. & Koç, S., (2024). "Impact of Economic Growth on NEET Rate in Developed and Developing Countries," 47th EBES Conference - Berlin, Berlin, Germany, Proceeding Book, 1136-1148.
18. Çolak, K., & Koç, S. (2023a). Bibliometric Analysis and Mapping with Vosviewer in Neet-Head Researchin Social Sciences. Journal of Ekonomi, 5(2), 77-91.
19. Daly M, Delaney L (2013) The scarring effect of unemployment throughout adulthood on psychological distress at age 50: Estimates controlling for early adulthood distress and childhood psychological factors. Soc Sci Med 80(0),19–23.
20. Dietrich, H. (2012). Youth unemployment in Europe. Theoretical considerations and empirical findings, 16(7), 2012.
21. Dinku, Y. (2024). Future Labour Market Prospects of Youth Not in Employment, Education or Training (NEET). New Zealand Journal of Employment Relations, 48(2), 1-14.
22. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460.
23. Erdayı, Utku (2009) Dünyada Genç İşsizliği Sorununun Çözümüne Yönelik Ulusal Politikalar ve Türkiye, Çalışma ve Toplum, 3:22,133-162.
24. Fahmy, E. (2006). Youth, poverty and social exclusion. In C. Pantazis, et al. (Eds.), Poverty and social exclusion in Britain: The millennium survey. Bristol: The Policy Press
25. Forrest, C., Skujins, P., & Stanwick, J. (2018). Predictors and consequences of being persistently not in employment, education or training (NEET): Evidence from the longitudinal surveys of Australian youth. In M. Best, T. Corcoran, & R. Slee (Eds.) Who’s in? Who’s out? (pp. 113- 128). Leiden.
26. Fougère D, Kramarz F, Pouget J (2009) Youth unemployment and crime in France. J Eur Econ Assoc 7(5),909–938.
27. France, A. (2007). Understanding youth in late modernity. London: McGraw-Hill Education.
28. Gazizova, M. R., Khusainova, Z. S., Vechkinzova, Y. A., & Abauova, G. M. (2022). Characteristics and features of NEET youth in the context of country analysis. Bulletin of the Karaganda university Economy series, 106(2), 48-61.
29. Goldsmith A, Veum J, Darity W (1997) Unemployment, joblessness, psychological well-being and self-esteem: Theory and evidence. J Socio-Econ 26:133–158
30. Granger, C. W. J. (1969). Investigating causal relations by econometric models and crossspectral methods. Econometrica, 37(3), 424e438.
31. Gregg P (2001) The impact of youth unemployment on adult unemployment in the NCDS. Econ J 111(475),626–653
32. Gregg P, Tominey E (2005) The wage scar from male youth unemployment. Labour Econ 12(4),487–509.
33. Guido, C. (2015). Young people in transitions: conditions, indicators and policy implications. To NEET or not to NEET?. In Youth and the Crisis (pp. 272-287). Routledge.
34. Hadri, K. 2000. Testing for stationarity in heterogeneous panel data. Econometrics Journal 3: 148-161.
35. Holte, B. H. (2018). Counting and meeting NEET young people: Methodology, perspective and meaning in research on marginalized youth. Young, 26(1), 1-16.
36. Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica, 56(6), 1371e1395.
37. ILO, (2024). World Employment and Social Outlook – Trend 2024, ILO Publications https://www.ilo.org/publications/flagship-reports/world-employment-and-social-outlook-trends-2024
38. Jacobs, Marita (2008) Unemployment Benefits and Parental Resources: What Helps The Young Unemployed with Labour Market Integration?, Journal of Youth Studies, Vol: 11, 147-163.
39. Kahn LB (2010) The long-term labor market consequences of graduating from college in a bad economy. Labour Econ 17(2),303–316.
40. Lau, L. S., Ng, C. F., Cheah, S. P., & Choong, C. K. (2019). Panel data analysis (stationarity, cointegration, and causality). In Environmental Kuznets Curve (EKC) (pp. 101-113). Academic Press.
41. Maguire, S., Cockx, B., Dolado, J.J. et al. Youth unemployment. Intereconomics 48, 196–235 (2013). https://doi.org/10.1007/s10272-013-0464-9
42. O'higgins, N. (1997). The challenge of youth unemployment. International Social Security Review, 50(4), 63-93.
43. Özdemir, M. O., Metin Ozcan, K., & Üçdoğruk, Ş. (2023). Youth not in Employment, Education, or Training (NEET) in Turkey: A Regional Analysis. Ege Academic Review, 23(3), 409-426. https://doi.org/10.21121/eab.1178984
44. Pennoni, F., Bal-Domańska, B. NEETs and Youth Unemployment: A Longitudinal Comparison Across European Countries. Soc Indic Res 162, 739–761 (2022). https://doi.org/10.1007/s11205-021-02813-5.
45. Pesaran, H., (2003), A Simple Panel Unit Root Test in the Presence of Cross Section Dependence,
46. Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias‐adjusted LM test of error cross‐section independence. The econometrics journal, 11(1), 105-127.
47. Quintini G, Martin JP, Martin S (2007) The changing nature of the school-to-work transition process in OECD countries. IZA Discussion Papers 2582, Institute for the Study of Labor (IZA), Bonn.
48. Ralston, K., Everington, D., Feng, Z., & Dibben, C. (2022). Economic inactivity, not in employment, education or training (NEET) and scarring: The importance of NEET as a marker of longterm disadvantage. Work, Employment and Society, 36(1), 59-79.
49. Ralston, K., Feng, Z., Everington, D., & Dibben, C. (2016). Do young people not in education, employment or training experience long-term occupational scarring? A longitudinal analysis over 20 years of follow-up. Contemporary Social Science, 11(2-3), 203-221.
50. Ranzani, M., & Rosati, F. C. (2013). The NEET trap: a dynamic analysis for Mexico. (Understanding Children’s Work Project). UNICEF Rome.
51. Sakamoto, Y., M. Ishiguro, and G. Kitagawa. 1986. Akaike Information Criterion Statistics. Dordrecht, The Netherlands: Reidel.
52. Samoilenko, A., & Carter, K. (2015). Economic outcomes of youth not in education, employment or training (NEET) (Working Paper 15/01). New Zealand Treasury.
53. Swamy, P. A. V. B. 1970. Efficient inference in a random coefficient regression model. Econometrica 38: 311-323. Verick S (2011) Who is hit hardest during a financial crisis? The vulnerability of young men and women to unemployment in an econonomic downturn. In: Islam I, Verick S (eds). From the Great Recession to Labour Market Recovery: Issues, Evidence and Policy Options. ILO/Palgrave Macmillan, Basingstoke
54. Yates, S., & Payne, M. (2006). Not so NEET? A Critique of the Use of ‘NEET’ in Setting Targets for Interventions with Young People. Journal of Youth Studies, 9(3), 329–344. https://doi.org/10.1080/13676260600805671
55. Yerdelen Tatoğlu, F., (2017), Panel zaman serileri analizi stata uygulamalı, (3. Baskı 2020). .