This project aims to analyze the more than 10,000 annual applications for the issuance or renewal of a permit for a cross-border worker in Ticino, Switzerland, in light of the new tax agreement between Italy and Switzerland.

The project is in the initial stage of evaluating data and methods.

Attached is a presentation (in Italian) on the topic.

Unlocking the Power of Web Data: Analyzing Occupations and Skills in demand through Big Data

New technologies provide opportunities for fast data collection. Using the web-scraping tools in Python, this post shows how the occupation and skills demand of more than 6,000 online job vacancies (OJVs) published in the most popular job portal in North Macedonia were collected, structured, visualized and analyzed.

This resource is a comprehensive collection of labour market intelligence sources, collected under the LMI-EUniv project. The projects primary objective is to analyse and comprehend the utilisation of labour market intelligence in European universities, identifying key LMI sources at the national level and fostering collaboration to develop a set of tools that enhance its implementation. All data are centralised on the LMI-EUniv Hub, an exclusive platform designed for Higher Education Institutions, containing valuable LMI sources and information gathered throughout the project's various stages. The LMI-Hub offers unrestricted access, serving as a vital information source for HEIs to align curricula with the demands of the labour market. Data set is available at www.lmi-euniv.eu/lmi-sources.

The document contains the presentation delivered at the first seminar of the Big Data Knowledge Hub of the European Network on Regional Labour Market Monitoring. The presentation focused on using sentiment analysis as a valuable source for labour market intelligence. It explored how sentiment analysis, particularly job seekers' sentiment, was effectively employed to comprehend specific characteristics and peculiarities of the labour market.

The research presents a novel approach using data from PIAAC (Program for the International Assessment of Adult Competences by OECD) and from online job ads (WIH-OJA by Eurostat and Cedefop) to measure the skill mismatch. The contribution suggest an innovative way to map existing surveys to international classification standards and then exposes an application to evaluate the skill mismatch in 17 European countries using objective measures.
The documentation include the presentation held on the Big Data Knowledge Hub seminar that took place on November 24, 2022 and some additional methodological notes.

In refugee and immigrant integration, data-driven tools have the potential to deepen our understanding about drivers of migrant integration outcomes
and serve as input for personalized policies. In the paper a data-driven tool is presented that improves the outcomes of the labour market integration of refugees based on improved distribution across the Swiss cantons.

Against the background that the topic of AI is also gaining importance within the cantonal labour market authorities, SECO has made initial considerations for guidelines on the use of AI in public employment services.

Lanbide has developed its own profiling methodology that focuses on the three most important aspects of  profiling: expert profiling, quantitative profiling and statistical profiling. The methodology applied allows to create a profiling system that overlaps the three existing profiling. 

The methodology consists of an iterative process, in which each iteration is divided into three parts:
1 Classification/Grouping (Clustering) in groups
2 Classification/Grouping (Clustering) in subgroups
3 Calculation of the employability index

In the first part, we use a set of variables from the administrative register of jobseekeres (age, gender...) over which change/improvement actions  cannot be performed, to generate the groups. The second part of the iterative process performs an unvised cataloging process using a "kmeans" algorithm applied to administrative registry variables over which LANBIDE can perform improvement actions. The idea is therefore to apply this unsupervised algorithm to the 24 groups that have been obtained in expert cataloguing and thus obtain a series of subsets. 
The third phase of iteration calculates the employability rate for each group/subgroup member.

By using specific actions on the subgroups, you allow a person belonging at any given time to a subgroup to move to another subgroup.

UWV Employee Insurance Agency has been publishing the result of the Labour Market Tension Indicator since 1 October 2012. This indicator shows the existing tension between labour market supply and demand.

Jobfeed serves as the basis of the estimation of the total number of vacancies. This database of online vacancies is provided to UWV Employee Insurance Agency by the company Textkernel. The vacancies are presented via werk.nl, allowing registered jobseekers to consult them. The database is also used as a new labour market information source.

The Labour Market Tension Indicator presents detailed labour market information, categorised by occupational group and region. The data are calculated on a quarterly basis. The indicator encompasses all professions and all educational levels. The proportion of existing demand and directly available supply provides an indication of the tension on the labour market. It does not provide an indication of future labour market tension. The categorisation by BRC profession categories does allow for making a comparison with the per-occupational group forecast for the medium term published by the Research Centre for Education and the Labour Market.

Purpose of graduate tracking

In 2018, the graduate tracking project was initiated in the Labour market information and advice department of UWV which is in line with a recommendation of the European Commission. Its purpose is to create reliable labour market information for prospective students of initial education. Prospective students are no natural target group of UWV. UWV does indeed have a legal duty to make the labour market more transparent, and this project contributes to a preventive and more comprehensive role of UWV. Since the labour market lacks transparency for prospective students, UWV has decided to initiate this project. A more transparent picture of the (economic) consequences of study choices by means of better information may facilitate the transition from school to work, may prevent unemployment and decrease the pushing out of low-skilled workers in favour of the highly-skilled. Besides, acquired knowledge and skills will be better used, leading to higher educational output. Certain skill shortages may also be prevented. In brief, it may contribute to a more adequate adjustment of the education system to the needs of the labour market. 

Design of graduate tracking project

In this project, UWV collaborates with research institute SEO which is affiliated to the University of Amsterdam. In order to analyse the labour market position of graduates, SEO analyses anonymised administrative data from the microdata of CBS (Central Bureau of Statistics). The microdata consists of various data (educational data, personal characteristics, income, type of contract) which are linked on a personal level. This microdata will be annually processed and analysed by SEO for the annual publication Study and Work. UWV performs additional analyses for:

-       70 clusters of master programmes in university education;

-       87 clusters of bachelor programmes in higher professional education;

-       102 clusters of 2nd level vocational education (3 different sublevels, both school-based and traineeships)  

It’s no sample but a comprehensive measurement among 218,000 graduates annually. The labour market positions of the various clusters are compared to each other. The labour market position is determined on the basis of time required to find a job, gross hourly wage, annual income and the percentage of permanent employees. The starting position of graduates is examined as well as the labour market position ten years after graduation. Furthermore, an analysis has been made of the development and robustness of the labour market position.