OVI for September 2018: Labor demand reaches its peak?

In September, the OVI index rose by 24.4 percent compared to the same period last year, while in the first nine months of this year the index recorded a 29.4 percent growth compared to the average index value in the first three quarters of 2017. Despite an increase in the absolute number of job advertisements, seasonally adjusted index values indicate a decrease in labor demand on a monthly level by -2.8 percent. After June and July, this is the third decrease in the index on a monthly level in the last six months, which points to the possibility that labor demand has reached its peak.
The top five occupations in demand, accounting for nearly a third of all job advertisements in September, were sales assistants, waiters, teachers and cooks, while compared to the same month last year, warehouse workers replaced drivers on the list. The largest positive contribution to the index growth on an annual level, amounting to 24.4 percent, came from demand for teachers (3.2 percentage points), while the largest negative contribution came from demand for mechanical engineers (-0.5 percentage points) and programmers (-0.4 percentage points). There was also a noticeable drop in demand for occupational training without commencing employment, by 40.3 percent compared to September 2017, representing another negative contribution to the total annual index growth (-2.2 percentage points).


What is OVI?

Online Vacancy Index (OVI) is a monthly index of online job advertisements developed by the Institute of Economics, Zagreb in cooperation with the web portal MojPosao. The index aims to provide timely information regarding current labor demands. OVI index is developed by means of simple enumeration of single new job advertisements whose application deadlines end within the same month for which the index is being calculated. Given that advertisements published by only one web portal are taken into account, the number of job advertisements is expressed as an index (with the base year being 2015). 

The index is to be interpreted in such a way that the values greater than 100 represent growth when compared to 2015, and accordingly, that the values less than 100 represent a decrease with respect to the base year. Index is seasonally adjusted using the X-12-ARIMA method.

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