Labor mobility across the formal/informal divide in Turkey Evidence from individual-level data

Abstract

Purpose - This paper, the first one to use individual-level Turkish panel data, examines the labor market transitions in Turkey along the formal/informal employment divide. The purpose of this paper is to contribute to the limited body of empirical evidence available on mobility and informality in the Turkish labor market.

Design/methodology/approach - Toward this end, the authors use Turkish income and Living Conditions Survey panel data for 2006, 2007, 2008 and 2009 to compute the Markov transition probabilities of individuals moving across six different labor market states: formal-salaried (FS), informal-salaried, formal self-employed, informal self-employed, unemployed and inactive. In order to examine the nature of mobility patterns in more detail, the authors then estimate six multinomial logit models individually for each transition adopting a number of individual and employment characteristics as explanatory variables.

Findings - The authors find evidence that mobility patterns are fairly similar across different time spans, the probability of remaining in initial state is higher than the probability of transition into another state for all the labor market states, except for unemployment, there is only very limited mobility into the FS state. Gender, education and sector of economic activity are observed to display significant effects on mobility patterns. The results reveal several relationships between the covariates and likelihood of variant transitions.

Research limitations/implications - This study provides a comprehensive and detailed diagnosis of the Turkish labor market. The market is observed to display a rather static structure throughout the period considered. The results indicate that a well recognition of underlying dynamics may help policy makers to produce various effective tools for addressing informality.

Originality/value - First study to analyze labor market mobility across formal/informal sectors using newly available panel data.