Labour Market for Teachers: Demographic Characteristics and Allocative Mechanisms
This paper examines teachers’ labour market in Italy. Quality and motivation of teachers are receiving large attention as crucial determinants of pupils’ achievement. These characteristics are difficult to measure as testified by the lack of data. To overcome these difficulties we look at the composition of teachers’ pool and to their behaviour in the market in a first attempt to infer some information about their quality and motivation. We show that Italian teachers have traits and behaviour that are consistent with an implicit contract in which relatively low wages are compensated by low involvement in the job and low effort exerted. Next we look at the institutional features that might have motivated this implicit contract. In particular we examine the mechanism that allocates teachers to schools. For each school we construct three indicators; one indicating the level of turnover that we interpret as source of turmoil with potentially negative implications for pupils’ achievement; one that refers to the mismatch between tenured teachers and their school; the third indicator measures the quality of the school as evaluated by the whole population of tenured teachers and thus we name it “revealed preferences indicator”. We show that the geographical and across school distribution of these three indicators resemble that of perceived quality of the schools. While we do not attempt to identify, in any econometric sense, the causal link of these indicators with students performance, we do measure the association at the school level of our indicators with pupils achievement as provided by PISA 2003. It appears that our indicators are strongly correlated to the school’s performance, negatively to the turnover and to the mismatch indicator, positively to the revealed preferences expressed by the whole population of teachers. It seems that teachers know which are the best schools and gradually attempt to move there.
Volume (Year): 66 (2007)
Issue (Month): 3 (November)
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