Exclusión laboral y educativa de los jóvenes en Colombia antes y después del COVID-19
Labour and educational exclusion of young people in Colombia before and after of the COVID-19
DOI:
https://doi.org/10.15446/cuad.econ.v45n97.107273Palabras clave:
Educación, trabajo, exclusión, NINI, jóvenes (es)Education, labor, exclusion, NEET, youth (en)
Descargas
Este artículo estudia los factores socioeconómicos asociados con la exclusión laboral y educativa de los jóvenes colombianos entre 14 y 28 años (nini), y el efecto potencial de la pandemia del COVID-19. Usando datos de la Gran Encuesta Integrada de Hogares, se estiman modelos de elección discreta para conocer los factores que afectan la probabilidad de ser nini. Los resultados muestran que la probabilidad de ser nini es mayor conforme aumenta la edad y el tamaño del hogar, y disminuye a medida que aumenta el nivel socioeconómico y el nivel educativo. Las personas que enfrentaron problemas laborales y de salud mental durante la pandemia tienen mayor probabilidad de ser nini.
This paper studies the socioeconomic factors associated with labour and educational exclusion of young Colombians between 14 and 28 years of age (NEET) and the potential effect of the COVID-19 pandemic. Using data from the Gran Encuesta Integrada de Hogares, discrete choice models are estimated to determine the factors affecting NEET probability. Results show that the likelihood of being NEET increases as age and household size increase and decreases as socioeconomic status and educational level increase. Persons who faced labour and mental health problems during the pandemic are more likely to be NEET.
Referencias
1. Aina, C., Brunetti, I., Mussida, C., & Scicchitano, S. (2024). Even more discouraged? The NEET generation at the age of COVID-19. Applied Economics, 56, 1-18. https://doi.org/10.1080/00036846.2024.2337790
2. Amarante, V., Filardo, V., Lasida, J., & Opertti, R. (2011). Jóvenes en tránsito: Oportunidades y obstáculos en las trayectorias hacia la vida adulta. Rumbos .
3. Angrist, J., Bettinger, E., Bloom, E., King, E., & Kremer, M. (2002). Vouchers for private schooling in Colombia: evidence from a random ized natural experiment. American Economic Review, 92(5), 1535-1558. https://doi.org/10.1257/000282802762024629
4. Apunyo, R., White, H., Otike, C., Katairo, T., Puerto, S., Gardiner, D., Kinengyere, A., Eyers, J., Saran, A., & Obuku, E. A. (2022). Interven tions to increase youth employment: An evidence and gap map. Campbell Sistematic Review, 18(1), 1-28. https://doi.org/10.1002/cl2.1216
5. Assmann, M.-L., & Broschinski, S. (2021). Mapping young NEETs across Europe: Exploring the institutional configurations promoting youth dis engagement from education and employment. Journal of Applied Youth Studies(4), 95-117. https://doi.org/10.1007/s43151-021-00040-w
6. Avanesian, G., Borovskaya, M., Masych, M., Dikaya, L., Ryzhova, V., & Egorova, V. (2024). How far are NEET youth falling behind in their non-cognitive skills? An econometric analysis of disparities. Economies, 12(1), 1-15. https://doi.org/10.3390/economies12010025
7. Baird, M. D., Engberg, J., & Gutierrez, I. A. (2022). RCT evidence on dif ferential impact of US job training programmes by pre-training employ ment status. Labour Economics, 75, 1-14. https://doi.org/10.1016/j.labeco. 2022.102140
8. Bălan, M. (2014). Youth labor market vulnerabilities: Characteristics, dimensions and costs. Procedia Economics and Finance, 8, 66-72. https:// doi.org/10.1016/S2212-5671(14)00064-1
9. Bălan, M. (2015). Methods to estimate the structure and size of the “Neet” youth. Procedia Economics and Finance, 32, 119-124. https://doi. org/10.1016/S2212-5671(15)01372-6
10. Becker, G. (1964). Human capital. Columbia University Press.
11. Belfield, C. R., & Levin, H. M. (2007). The price we pay: Economic and social consequences of inadequate education. Brookings Institution Press. https://www.jstor.org/stable/10.7864/j.ctt126269
12. Berigel, M., Boztaş, G. D., Rocca, A., & Neagu, G. (2024). Using machine learning for NEETs and sustainability studies: Determining best machine learning algorithms. Socio-Economic Planning Sciences, 94, 1-14. https:// doi.org/10.1016/j.seps.2024.101921
13. Bernal, G. L., & Penney, J. (2019). Scholarships and student effort: Evi dence from Colombia’s Ser Pilo Paga program. Economics of Education Review, 72, 121-130. https://doi.org/10.1016/j.econedurev.2019.04.008
14. Blázquez, M., Herrarte, A., & Sáez, F. (2019). Training and job search assistance programmes in Spain: The case of long-term unemployed. Jour nal of Policy Modeling, 41(2), 316-335. https://doi.org/10.1016/j.jpolmod. 2019.03.004
15. Brant, R. (1990). Assessing proportionality in the proportional odds model for ordinal logistic regression. Biometrics, 46(4), 1171-1178. https://doi. org/10.2307/2532457
16. Brown, C., Douthwaite, A., Savvides, N., & Costas Batlle, I. (2022). Five mechanisms for tackling the risks to NEEThood: Introducing a pathway to change to guide educators’ support strategies. International Journal of Adolescence and Youth, 27(1), 457-474. https://doi.org/10.1080/0267384 3.2022.2130082
17. Buitrón, K., Jami, V., & Salazar Méndez, Y. (2018). Los jóvenes ninis en el Ecuador. Revista de Economía del Rosario, 21(1), 39-80. https://doi.org/10.12804/revistas.urosario.edu.co/economia/a.6800
18. Bynner, J., & Parsons, S. (2002). Social exclusion and the transition from school to work: The case of young people not in education, employment, or training (NEET). Journal of Vocational Behavior, 60(2), 289-309. https://doi.org/10.1006/jvbe.2001.1868
19. Cabral, F. J. (2018). Key drivers of NEET phenomenon among youth peo ple in Senegal. Economic Bulletin, 38(1), 248-261. https://econpapers. repec.org/article/eblecbull/eb-17-00621.htm
20. Casarico, A., & Lattanzio, S. (2022). The heterogeneous effects of COVID-19 on labor market flows: Evidence from administrative data. The Journal of Economic Inequality, 20, 537-558. https://doi.org/10.1007/ s10888-021-09522-6
21. CEPAL. (2006). Los jóvenes y el empleo en América Latina. Desafíos y perspectivas ante el nuevo escenario laboral. Colombia: Comisión Económica para América Latina y el Caribe. https://www.cepal.org/es/ publicaciones/1902-jovenes-empleo-america-latina-desafios-perspecti vas-nuevo-escenario-laboral
22. Cieslik, K., Barford, A., & Vira, B. (2022). Young people not in Employ ment, Education or Training (NEET) in Sub-Saharan Africa: Sustainable development target 8.6 missed and reset. Journal of Youth Studies, 25(8), 1126-1147. https://doi.org/10.1080/13676261.2021.1939287
23. Collins, M. E., Kuykendall, S., Ramirez, M., & Spindle-Jackson, A. (2022). COVID impacts on U.S. youth workforce system: Challenges and opportunities. Journal of Education and Work, 35(5), 470-484. https://doi. org/10.1080/13639080.2022.2091119
24. Contini, D., Filandri, M., & Pacelli, L. (2019). Persistency in the NEET state: A longitudinal analysis. Journal of Youth Studies, 22(7), 959-980. https://doi.org/10.1080/13676261.2018.1562161
25. De Hoyos, R., Rogers, H., & Székely, M. (2016). Ninis en América Latina: 20 millones de jóvenes en busca de oportunidades. Banco Mun dial. https://igualdad.cepal.org/es/digital-library/ninis-en-america-latina 20-millones-de-jovenes-en-busqueda-de-oportunidades
26. Erten, B., & Keskin, P. (2019). Compulsory schooling for whom? The role of gender, poverty, and religiosity. Economics of Education Review, 72, 187-203. https://doi.org/10.1016/j.econedurev.2019.06.001
27. Escoto, A., & Navarrete, E. L. (2018). Qué hacer para ser NiNi. Recupe rando las particularidades de los jóvenes que no estudian y no trabajan en México y El Salvador. Papeles de Población, 96, 217-254. https://doi.org /10.22185/24487147.2018.96.20
28. Eurofound. (2012). NEETs – Young people not in employment, educa tion or training: Characteristics, costs and policy responses in Europe. Publications Office of the European Union. https://www.eurofound. europa.eu/en/publications/2012/neets-young-people-not-employment education-or-training-characteristics-costs-and
29. Fabrizi, E., & Rocca, A. (2024). NEET status duration and socio-eco nomic background. Socio-Economic Planning Sciences, 95, 1-10. https:// doi.org/10.1016/j.seps.2024.101986
30. Genda, Y. (2007). Jobless youths and the NEET problem in Japan. Social Science Japan Journal, 10(1), 23-40. https://doi.org/10.1093/ssjj/jym029
31. Ghoshray, A., Ordóñez, J., & Sala, H. (2016). Euro, crisis and unemploy ment: Youth patterns, youth policies? Economic Modelling, 58, 442-453. http://dx.doi.org/10.1016/j.econmod.2016.05.017
32. Gladwell, D., Popli, G., & 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), 485-514. https://doi.org/10.1111/rssa.12961
33. Graversen, B.-K., & Ours, J. C. (2008). How to help unemployed find jobs quickly: Experimental evidence from a mandatory activation pro gram. Journal of Public Economics, 92(10-11), 2020-2035. http://dx.doi. org/10.1016/j.jpubeco.2008.04.013
34. Gustavsson, I. N., & Jonsson, F. (2024). Exploring the experiences of NEET-situated young people within the context of the COVID-19 pan demic using resonance theory. Journal of Applied Youth Studies, 1-20. https://doi.org/10.1007/s43151-024-00119-0
35. Hanushek, E. A., & Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46(3), 607-668. https://doi.org/10.1257/jel.46.3.607
36. Hara, H. (2022). The effect of public-sponsored job training in Japan. Journal of the Japanese and International Economies, 64, 1-14. https://doi.org/10.1016/j.jjie.2021.101187
37. Hausman, J., & McFadden, D. (1984). Specification tests for the multi nomial logit model. Econometrica, 52(5), 1219-1240. https://doi.org/10. 2307/1910997
38. Henao Orozco, N. (2024). Brechas de género y corrupción: el fenómeno de las mujeres ninis en Colombia. Apuntes del CENES, 43(7), 131-149. https://doi.org/10.19053/uptc.01203053.v43.n77.2024.16103
39. Hernández Cardozo, J. C., Silva Arias, A. C., & Sarmiento Espinel, J. A. (2016). Factores asociados a la exclusión laboral y educativa de los adolescentes colombianos. Revista de Economía del Caribe, 17, 64-89. https://doi.org/10.14482/ecoca.17.7576
40. Holford, A. (2020). Youth employment, academic performance and labour market outcomes: Production functions and policy effects. Labour Eco nomics, 63, 1-27. https://doi.org/10.1016/j.labeco.2020.101806
41. Holmes, C., Murphy, E., & Mayhew, K. (2021). What accounts for changes in the chances of being NEET in the UK? Journal of Education and Work, 34(4), 389-413. https://doi.org/10.1080/13639080.2021.1943330
42. Kelly, E., & McGuinness, S. (2015). Impact of the Great Recession on unemployed and NEET individuals’ labour market transitions in Ire land. Economic Systems, 39(1), 59-71. http://dx.doi.org/10.1016/j.ecosys. 2014.06.004
43. Kim, H., & Lee, J. (2019). Can employment subsidies save jobs? Evi dence from a shipbuilding city in South Korea. Labour Economics, 61, 1-14. https://doi.org/10.1016/j.labeco.2019.101763
44. Laajaj, R., Moya, A., & Sánchez, F. (2022). Equality of opportunity and human capital accumulation: Motivational effect of a nationwide scholar ship in Colombia. Journal of Development Economics, 154, 1-20. https:// doi.org/10.1016/j.jdeveco.2021.102754
45. Lucas, R. E. (1988). On the mechanics of economic development. Jour nal of Monetary Economics, 22(1), 3-42. https://doi.org/10.1016/0304- 3932(88)90168-7
46. Málaga, R., Oré, T., & José, T. (2014). Jóvenes que no estudian ni traba jan: el caso peruano. Economía, 37(74), 95-132. http://revistas.pucp.edu.pe/index.php/economia/article/view/11414/11931
47. Mawn, L., Oliver, E. J., Akhter, N., Bambra, C. L., Bridle, C., & Stain, H. J. (2017). Are we failing young people not in employment, education or training (NEETs)? A systematic review and meta-analysis of re-engage ment interventions. Systematic Reviews, 6(16), 1-17. https://doi.org/10.11 86%2Fs13643-016-0394-2
48. Maynou, L., Ordóñez, J., & Silva, J.-I. (2022). Convergence and deter minants of young people not in employment, education or training: An European regional analysis. Economic Modelling, 110, 1-11. https://doi. org/10.1016/j.econmod.2022.105808
49. Mincer, J. (1958). Invesment in human capital and personal income distri bution. Journal of Political Economy, 66(4), 281-302. https://www.jstor. org/stable/1827422
50. Mora Rodríguez, J. J., Caicedo Marulanda, C., & González Espitia, C. G. (2017). La duración del desempleo de los jóvenes y los “ninis” en Cali, Colombia. Revista de Economía Institucional, 19(37), 167-184. http:// dx.doi.org/10.18601/01245996.v19n37.09
51. Mussida, C., & Sciulli, D. (2023). Being poor and being NEET in Europe: Are these two sidesof the same coin? The Journal of Economic Inequality, 21, 463-482. https://doi.org/10.1007/s10888-022-09561-7
52. Ochoa Diaz, D., Silva Arias, A. C., & Sarmiento Espinel, J. A. (2015). Actividades y uso del tiempo de las y los jóvenes que ni estudian ni traba jan en Colombia. Civilizar, 15(29), 149-162.
53. Odoardi, I., D’Ingiullo, D., & Quaglione, D. (2023). Gender dispari ties between young and adult NEETs: Do we need a more refined policy approach? Applied Economics, 55, 6685-6699. https://doi.org/10.1080/00 036846.2022.2161991
54. OIT. (2012). No trabajan ni estudian: el futuro de millones de jóvenes en el mundo. OIT. https://www.ilo.org/global/research/global-reports/youth/ 2012/WCMS_181079/lang--es/index.htm
55. OIT. (2021). An update on the youth labour market impact of the COVID 19 crisis. International Labour Organization. https://www.ilo.org/resource/ brief/update-youth-labour-market-impact-covid-19-crisis
56. ONU. (2015). Transformar nuestro mundo: la Agenda 2030 para el Desa rrollo Sostenible. http://www.un.org/ga/search/view_doc.asp?symbol=A/ RES/70/1&referer=http://www.un.org/sustainabledevelopment/
57. Owen, E. C., Knight, C. J., & Hill, D. M. (2024). A realist evaluation of a multi-component program with disengaged students. Evaluation and Program Planning, 103, 1-11. https://doi.org/10.1016/j.evalprogplan. 2024.102417
58. Paabort, H., Flynn, P., M. B., & Petrescu, C. (2023). Policy responses to real world challenges associated with NEET youth: A scoping review. Frontiers in Sustainable Cities, 5, 1-16. https://doi.org/10.3389/ frsc.2023.1154464
59. Parida, J. K., Pattayat, S. S., & Verick, S. (2023). Why is the size of dis couraged labour force increasing in India? Economic Change and Restruc turing, 56, 3601-3630. https://doi.org/10.1007/s10644-023-09538-0
60. Pastore, F., & Choudhry, M. T. (2022). Determinants of school to work transition and COVID-19. International Journal of Manpower, 43(7), 1487-1501. https://doi.org/10.1108/IJM-10-2022-711
61. Rahmani, H., & Groot, W. (2023). Risk factors of being a youth not in edu cation, employment or training (NEET): A scoping review. International Journal of Educational Research, 120, 1-16. https://doi.org/10.1016/j. ijer.2023.102198
62. Rahmani, H., Groot, W., & Rahmani, A. M. (2024). Unravelling the NEET phenomenon: A systematic literature review and meta-analysis of risk factors for youth not in education, employment, or training. Interna tional Journal of Adolescence and Youth, 29(1), 1-37. https://doi.org/10.1 080/02673843.2024.2331576
63. Russell, L., Simmons, O., & Thompson, R. (2012). Conceptualising the lives of NEET young people: Structuration theory and ‘disengagement’. Education, Knowledge and Economy, 5(3), 89-106. https://doi.org/10.108 0/17496896.2012.662010
64. Schultz, T. W. (1961). Investment in human capital. American Economic Review, 51(1), 1-17. https://www.jstor.org/stable/1818907
65. Spatarelu, E.-M. (2015). Youth insertion on labor market. Procedia Eco nomics and Finance, 32, 1020-1026. https://doi.org/10.1016/S2212-5671 (15)01563-4
66. Tamesberger, D., & Bacher, J. (2020). COVID-19 Crisis: How to avoid a ‘lost generation’. Intereconomics. Review of European Economic Policy, 55(4), 232-238. https://doi.org/10.1007/s10272-020-0908-y
67. Vasile, V., & Anghel, I. (2015). The educational level as a risk factor for youth exclusion from the labour market. Procedia Economics and Finance, 22, 64-71. https://doi.org/10.1016/S2212-5671(15)00227-0
68. Williams, R. (2006). Generalized ordered logit/partial proportional odds models for ordinal dependent variables. The Stata Journal, 6(1), 58-82. https://doi.org/10.1177%2F1536867X0600600104
69. Wolfe, R., & Gould, W. (1998). An approximate likelihood-ratio test for ordinal response models. Stata Technical Bulletin, 7(42), 1-52. http://sta-press.com/journals/stbcontents/stb42.pdf
70. Wooldridge, J. (2010). Econometric analysis of cross section and panel data. MIT Press.
71. Zuccotti, C., & O'Reilly, J. (2019). Ethnicity, gender and household effects on becoming NEET: An intersectional analysis. Work, Employ ment and Society, 33(3), 351-373. https://doi.org/10.1177/0950017017738945
Cómo citar
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Descargar cita
Licencia
Derechos de autor 2026 Cuadernos de Economía

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Cuadernos de Economía a través de la División de Bibliotecas de la Universidad Nacional de Colombia promueve y garantiza el acceso abierto de todos sus contenidos. Los artículos publicados por la revista se encuentran disponibles globalmente con acceso abierto y licenciados bajo los términos de Creative Commons Atribución-No_Comercial-Sin_Derivadas 4.0 Internacional (CC BY-NC-ND 4.0), lo que implica lo siguiente:




