Using Multinomial Logistic Regression to Examine the Relationship Between Children’s Work Status and Demographic Characteristics

Öz

Using Multinomial Logistic Regression to Examine the Relationship Between Children’s Work Status and Demographic Characteristics

Öz

This study aims to examine the relationship between children’s work status and their demographic characteristics using multinomial logistic regression. To this end, data collected by TUIK’s Turkish Statistical Institute “Child Labor Force Survey, 2012,” conducted with the participation of 27,118 children, were used. At the first stage of the analysis, eight independent variables on the demographic characteristics of the participants were examined using the chi-square test of independence, the variable that was not significant was removed, and the subsequent analyses were conducted using the remaining seven variables. The validity of the model in the study was examined using maximum likelihood estimation, and the model was significant. Odds ratios of the variables in the model were calculated, and twocategory comparisons were made on the basis of the reference category using odds ratio coefficients. In comparisons 1 and 2, odds ratio coefficients for the variables rural/urban, gender, age group, household size, literacy, school attendance, and level of education of the head of household were significant

Anahtar Kelimeler

• Children,Working Children,Multinomial logistic regression

Kaynakça

1. Ağacabay, M. (2012). “Çocuk ve Çocuk İşçiliği Kavramları”. Eğitişim Dergisi, Issue: 33. Access link: www.egitisim.gen.tr Access date: 10.12.2015
2. Boukhari, Construir Futuro, inventir en la infancia: “Estudio economico de los costos ybeneficious de erradicar al trabojo en Iberoamerica”. ILO, San Jose, Costa Rica, September 2005.
3. Fidan, F. (2004). “Çalışan Çocuk Olgusuna Sosyo-Psikolojik Bakış Sanayide Çalışan Çocuklar Örneği”. Trakya University Journal of Social Science, 4(1): 30-49.
4. Günöz, M. (2007). “Türkiye’de Çocuk İşçi Sorunu Ve Çözüm Önerileri (Dissertation)”. Republic of Turkey General Directorate of Labour and Social Security, Ankara.
5. Hosmer, D. W. and Lemeshow, S. (2000). Introduction to the logistic regression model, in applied logistic regression, second ed. John Wiley & Sons, Inc., Hoboken, NJ, USA.
6. Hosmer, D. W., Lemeshow, S., Sturdıvant, R. (2013). Applied logistic regression. Canada: Wiley & Sons Publication.
7. Kahramanaoğlu, E. (1996) Türkiye’de Çalışan Çocuklar Sorunu ve Çözüm Yolları. Kahramanoğlu, E. (ed) Hacettepe University Academy of Social Services and Friedrich–Nauman-Foundation Publication, Ankara.
8. Karaman, B. and Özçalık, M. (2007). “Türkiye’de Gelir Dağılım Eşitsizliğinin Bir Sonucu: Çocuk İşgücü”. Yönetim ve Ekonomi, 14(1): 30-41.

9. Kayhan, N. (2012). “Çocuk İşçiliği, IPEC Deneyimi Işığında Sanayide Çalışan Çocukların Sorunları”. Hukuk ve İktisat Araştırmaları Dergisi, 4(1): 187-200.
10. Kolk, A. and Tulder, R.V. (2002). “Child Labor and Multinational Conduct: A Comparison of Intarnational Business and Stakeholder Codes”. Journal of Business Ethics, 36(3): 291-301.
11. Köksal, S. and Lordoğlu, K. (1993) Geleneksel Çıraklıktan Çocuk Emeğine: Bir Alan Araştırması. İstanbul: Friedrich Nauman Vakfı Yayınları.
12. Kleinbaum, D.G. and Klein M. (2010). Logistic regression, a self-learning text, third edition. Springer.
13. Liao, T.F.(1994). Interpreting probability models. Logit, probit and other generalized linear models. Quantitative Applications in the Social Sciences. Sage Publications.
14. Long, S. and Freese J. (2006). Regression models for categorical dependent variables using STATA, second edition. College Station, TX: Stata Press.
15. Tor, H. (2010). “Türkiye’de Çocuk İşçiliğinin Boyutları”. Zeitschrift für die Welt der Türken (ZfWT), 2(2): 35-39.
16. “Republic of Turkey General Directorate of Labour and Social Security- Statistics”. Access link: http://www.csgb.gov.tr/csgbPortal/cgm.portal?page=cc&id=3. Access date: 15.12.2015.
17. Washıngton, S., Karlaftıs, M., Mannering, F. (2003). Statistical and econometric models for transportation data analysis. Boca Raton FL.:CRC Press.