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Frequently asked questions


1. Why is it important to forecast changes at the labour market?
2. What are the methods of forecasting labour market changes?
3. Why are occupations in the Job Futures section arranged to form groups?
4. What sources of data does the Czech Futur skills! portal use?
5. How are the employment prospects for the occupational groups identified and measured?
6. What does the number of graduates with suitable qualifications for this occupation express?
7. How is the median age of employees calculated? 

  • Question 1:  Why is it important to forecast changes at the labour market?

At present we may see two seemingly contradicting trends at the labour market. Due to the economic downturn many people have been laid off, while at the same time companies face difficulties filling a number of jobs. These discrepancies are caused by a mismatch between the qualification requirements for jobs and the actual qualifications of jobseekers. These two problems have one thing in common – there is no way of solving them immediately. They often require fundamental changes in legislation, in the education system, curricula or investment incentives, and, most importantly, no one can learn to perform a new occupation overnight.  Normally it takes several years to implement such measures and to ensure that workers have the relevant professional competencies. The forecasting of skills needs is concerned with identification of links between economic trends and future occupational requirements. This provides information, well in advance, as to what skills will be needed in the upcoming years and for what qualifications there are likely to be good job opportunities. This information makes the choice of an occupation or a career change easier, and it may also be used by labour market and education experts, policy-makers and others. In recent years countries such as Ireland, Great Britain, the Netherlands, Germany, Austria, Finland and Canada invested considerable efforts and resources in the development of forecasting schemes that regularly provide information of this kind.  The National Observatory of Employment and Training pursues a similar objective as part of its projects. More detailed information about skills needs forecasting can be found at

  • Question 2:  What are the methods of forecasting labour market changes?

The best way in which to ascertain skills needs is to combine information obtained by means of employing various approaches. One of them is a quantitative approach that uses mathematical modelling. This method is employed by the Observatory in cooperation with the Research Institute for Labour and Social Affairs. For this purpose the ROA-CERGE prognostic model is used that draws on the experience gained while developing similar projections abroad and that is adjusted to Czech conditions. The model seeks to identify employment prospects for holders of various qualifications in the next five years, as well as the employers’ chances of finding such workers. One disadvantage associated with a forecast developed using the model is a considerable degree of aggregation of the results and a lack of information about the qualitative aspects of the qualifications required.

It is therefore advisable to complement mathematical modelling with more thorough analyses of selected sectors of the economy that build on expert opinions concerning future development trends and examine their impact on occupations and qualifications.  The term “sector studies” is used to describe this type of analytical and prognostic work, and it represents a qualitative methodological approach. Sector studies seek to answer questions such as: What are the likely scenarios for the development of the economy and its sectors in relation to economic, technological, demand and other trends? What implications may these scenarios have for employment and the required qualification structure? What opportunities and threats are involved? Will there be major changes in some occupations in terms of qualification requirements and job description? What demands will this place on the education system and what changes in the curricula will have to be made?

  • Question 3:  Why are occupations in the Job Futures section arranged to form groups?

The forecast of the future development of demand for an occupation and the relevant supply of suitable candidates is based on statistical data obtained through sample surveys. In order to achieve sufficient statistical reliability of the calculations it was necessary to form sufficiently large groups of occupations. This is why all occupations are organised, using a cluster analysis, into 30 groups for which the future development projection is made. 

  • Question 4:  What sources of data does the Czech Future skills! portal use?

Occupational forecasting is immensely demanding in terms of data sources. Sufficiently long time series are required along with the possibility of an appropriate desegregation while maintaining statistical reliability.  This website uses the Labour Force Survey that is regularly conducted by the Czech Statistical Office as the main source of data. Similar surveys are carried out in all EU countries where Eurostat is responsible for the methodology. All published data on employment and its industry, occupational, qualification and age structure that are available on the Future of Occupations portal come from the Labour Force Survey. The data about the future of occupations are a product of the ROA-CERGE model for forecasting skills needs. In addition to the Labour Force Survey the model uses data about the number of graduates, the monitoring of which is the responsibility of the Institute for Information on Education, and a projection of employment structure by industry as developed by the National Observatory of Employment and Training. Some information in the Sector Studies section comes from original surveys implemented under the guidance of the National Observatory of Employment and Training. Do not hesitate to contact us for more detailed information about the ROA-CERGE model, sector studies and other sources of data. 

  • Question 5: How are the employment prospects for the occupational groups identified and measured?

The future chances of finding employment for the occupational groups are ranked using a ten-degree scale. Figure10 means that there are very good very good employment prospects for the occupational group, figure 0 means that the prospects are poor. 

The employment prospects for a given occupational group are ranked based on a number of factors. These include, above all, the current rate of employment within the occupational group, the future economic development in industries that employ the relevant people, the age structure of those who perform these occupations and the expected rate of natural departures (e.g. retirement, maternity leave), the number of unemployed people with qualifications suitable for these occupations and the number of graduates with such qualifications who will enter the labour market in the future. The employment prospects are identified using the results of the ROA-CERGE modelling that takes account of all these factors.  

  • Question 6: What does the number of graduates with suitable qualifications for this occupation express?

It is necessary to have a particular qualification to perform an occupation. However, the link between a qualification and an occupation is not entirely straightforward. An individual with a particular qualification can perform various occupations. This must be taken into account when data about graduates in a specific field of education are interpreted. A certain part of these graduates will take up jobs within the given subgroup of occupations, while others may find employment in other occupations.

  • Question 7: How is the median age of employees calculated?

The age of employees in a given occupational subgroup is identified using a median – i.e. a value that divides an array of values arranged by quantity into two equal parts. In this case it is the age of an employee that is in the middle of an array of employees arranged by age. Median age is similar to average age, but as opposed to average age it is not so sensitive to extreme values. 

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