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Social Indicators Research

Erschienen in:

08.05.2018

Wage Inequality and Wage Mobility in Turkey

verfasst von: Aysit Tansel, Başak Dalgıç, Aytekin Güven

Erschienen in: Social Indicators Research | Ausgabe 1/2019

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Abstract

This paper investigates wage inequality and wage mobility in Turkey using the surveys on income and living conditions. Providing the first evidence on wage mobility for Turkey, our paper also differs from the existing literature by investigating wage inequality and wage mobility over various socio-economic groups. We first present an overview of wage inequality over the period 2005–2011. Next, we compute several measures of wage mobility and explore the link between wage inequality and wage mobility. Further, emphasizing positional mobility, we compute transition matrices and investigate the determinants of transition probabilities. The results show that, overall, wage inequality exhibits a slight increase over the analysis period. Wage mobility in Turkey is lower than what is observed in European Union countries although it increases as the time horizon expands. Wage mobility has an equalizing impact on wage distribution; however, this impact is not substantial enough to overcome the high and persistent wage inequality in Turkey.

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In this study industry and service sectors are defined as follows. Industry includes mining, quarrying, manufacturing, electricity, gas, steam, water supply, sewerage, and construction. Service sector covers wholesale and retail trade, repair of motor vehicles and motorcycles, accommodation and food service activities, transportation, storage, information and communication, financial and insurance activities, real estate activities, professional, scientific and technical activities, administrative and support service activities, public administration and defense, compulsory social security, education, human health and social work activities, arts, entertainment and recreation and other service activities. The agriculture sector is excluded from the analyses due to the small number of wage-earners in the sample. Consistent with the fact that there are very few wage-earners in the agricultural sector in Turkey, the agricultural observations only range between 4 and 6% of the total during the study period.

In addition to the country level studies, there are also some sectoral level studies on wage mobility. Using income tax administrative data for the period 1993–1996, Romanov and Zussman (2003) explore wage inequality and mobility in Israel. They find that wage mobility is higher in the public sector than in the private sector, contradicting the common view that public sector wages are more stable than those of the private sector. Cardoso et al. (2010) find that private sector wage mobility exceeds the public-sector, contrary to Romanov and Zussman (2003). Raferzeder and Winter-Ebmer (2007) analyse wage mobility using tax authority data for Austria for the period 1994–2001, and find that workers in large firms have more opportunities of moving up compared to those in small firms. Workers in the public sector, in education and health sectors have the least opportunities of moving up.

Duman (2014) finds a significant negative correlation between the trade union density and unemployment rate, but no significant relationship between real wage index and the trade union density for Turkey.

Güven et al. (2011) find that minimum wages do not change the employment significantly over the period 1968–2009 in Turkey.

For further information on SILC, see TURKSTAT (2013a).

In this data we have information on 5,807, 5,950, 6,495, 6,459, 6,761, 8,656 and 10,447 individual wage earners aged between 15 and 64 from 2006, 2007, 2008, 2009, 2010, 2011 and 2012 surveys, respectively.

Following Engel and Schaffner (2012) and Bachmann et al. (2016), we merge different longitudinal files together.

The analysis in this paper was also repeated using monthly wages. Both the inequality and the mobility results are qualitatively the same. These results are available from the authors on request.

The Gini coefficient measures the average difference between all possible pairs of wages in the population, expressed as a proportion of total earnings: \(I_{Gini} = \frac{1}{{2N^{2} \bar{y}}}\mathop \sum \nolimits_{i = 1}^{N} \mathop \sum \nolimits_{j = 1}^{N} \left| {y_{i} - y_{j} } \right|\) where \(y_{i} \left( {y_{j} } \right)\) is the income of the individual i (j), \(\bar{y}\) is the average income of the population, and N is the number of individuals in the sample.

\(I_{Theil} = \frac{1}{N}\mathop \sum \nolimits_{i = 1}^{N} \frac{{y_{i} }}{{ \bar{y}}}{ \log }\left( {\frac{{y_{i} }}{{ \bar{y}}}} \right)\) and \(I_{MLD} = \frac{1}{N}\mathop \sum \nolimits_{i = 1}^{N} \frac{{y_{i} }}{{ \bar{y}}}\), where \(y_{i}\) is the income of individual i, \(\bar{y}\) is the average income of the population, and N is the number of individuals in the sample.

These figures are based on the results of Tansel et al. (2014), which also includes findings on the Gini, Theil and MLD indices by gender, age, education and sector of work.

Using the Household Labor Force Surveys, Bakis and Polat (2015) find that the 90/10 wage ratio decreased over the 2002–2010 period.

Higher wage inequality for women than for men is reported by Aretz (2013) and by Franz and Steiner (2000) for Germany.

Three- and 4-year transition probabilities are also estimated using the same specification as for 2-year transition dynamics. For the sake of brevity, we do not report those estimation results here, but they are available on request.

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Titel: Wage Inequality and Wage Mobility in Turkey
verfasst von: Aysit Tansel
Başak Dalgıç
Aytekin Güven
Publikationsdatum: 08.05.2018
Verlag: Springer Netherlands
Erschienen in: Social Indicators Research / Ausgabe 1/2019
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-018-1908-1

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