ALTERNATIVE WAYS FOR EXPRESSING THE LEVEL OF UNEMPLOYMENT IN OSTRAVA Milan Šimek 1.

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1 ALTERNATIVE WAYS FOR EXPRESSING THE LEVEL OF UNEMPLOYMENT IN OSTRAVA Milan Šimek 1 1 VSB-Technical University of Ostrava, Faculty of Economics, Sokolská třída 33, Ostrava milan.simek@vsb.cz Abstract: The aim of the article Alternative ways for expressing the level of unemployment in Ostrava is to express the level of unemployment in Ostrava using different indicators, compare the results and classify city districts in Ostrava in terms of the level of unemployment. Basic statistical methods and cluster analysis were used as part of the solution. The solution showed significant differences in expressing the level of unemployment in the region using different indicators. When the Registered Unemployment Rate was used, the differences between individual territorial units were bigger than in the case of using the new indicator Rate of Unemployed Persons. Keywords: unemployment, registered unemployment rate, cluster analysis, Ostrava city, labor supply JEL classification: J 21, J64, R11 1. Introduction Based on an agreement with the Czech Statistical Office, the Ministry of Labor and Social Affairs (MPSV) began in January 2013 to use the new indicator of registered unemployment called Rate of Unemployed Persons which indicates the ratio of attainable job applicants aged 15 to 64 out of all the inhabitants of the same age expressed in %. This indicator replaced the registered unemployment rate which could relate all the attainable job applicants to economically active persons. The reason for the change of registered unemployment indicator was the fact that the indicator for registered unemployment rate was comparing attainable job applicants with the labor force created by a combination of data from different sources. Attainable job applicants used for the calculation were taken from the register of the Ministry of Labour and Social Affairs and employed persons from the register of Labor Force Survey (Výběrové šetření pracovních sil) of the Czech Statistical Office (CZSO). CZSO processes the outputs of Labour Force Survey only up to the regional level. Due to its smaller extent the set of the data from Labour Force Survey are not suitable for providing information on a higher than regional level. CZSO provided MPSV with employment data to calculate the labor force up to the district level. For smaller territorial and administrative units the number of economically active persons from the Population and Housing Census (carried out once in every ten years) by CZSO was used. The problem was that the unemployment data from Labour Force Survey were not representative enough. Detailed results contained quite a high number of mistakes and there were no detailed results for smaller territorial units. Another reason for the change was the comparison of both rates of unemployment or the confusion of MPSV and the general rate from Labour Force Survey of the CZSO and their wrong interpretation. During the first half of 2015 as part of the solution of the ESF project for service development in job openings, an evaluation of the current situation and development in unemployment in the Czech Republic was carried out based on the values of the indicator Rate of Unemployed Persons on a group of inhabitants in productive age. The aim of this study is to compare the values of the indicator, its behavior and influence when compared to the previously used unemployment rate

2 Based on these results possible problems were noted that can occur when using this indicator, when interpreting its values and monitoring the development in a particular region. The evaluation of the influence of demographic situation, labor migration and the use of age standardization were also part of the analysis of the indicator's behavior. The identification of differences between individual aggregation levels, the study of geographical differences and time development were also included. Based on the study of these influences, the impacts on interpretation were evaluated and recommendations formed accordingly. The aim of the article Alternative ways for expressing the level of unemployment in Ostrava is to express the level of unemployment in Ostrava using different indicators, compare the results and classify Ostrava city districts in all the cases in terms of the level of unemployment. 2. Theory and methodology Different approaches can be used to define unemployment. An unemployed person can be a person who is able to work or who wants to work but for some reasons is unable to gain a valid employment agreement and receive regular wages and therefore have enough funds for all their living expenses. It can be a person who can and wants to work but cannot find a job matching his/her skills and abilities, i.e. his/her qualification. Unemployment is usually defined as a phenomenon where people who meet all the requirements and want to work cannot find a job. However, statistically and administratively they are in the same group with those who can work but who do not want to and who exploit the weaknesses and gaps of the existing employment regulation system. (Nový, Syrůnek, 2002) Commission Regulation (EC) No 1897/2000 of 7 September 2000 implementing Council Regulation (EC) No 577/98 on the organization of a labor force sample survey in the Community concerning the operational definition of unemployment defines unemployment as follows. In accordance with the ILO standards adopted by the 13th and 14th International Conference of Labour Statisticians (ICLS), for the purposes of the Community labor force sample survey, unemployed persons comprise persons aged 15 to 74 who were without work during the reference week, i.e. neither had a job nor were at work (for one hour or more) in paid employment or selfemployment. At the same time, they are currently available for work, i.e. are available for paid employment or self-employment before the end of the two weeks following the reference week. They must also actively seek work. This means that they had taken specific steps in the four week period ending with the reference week to seek paid employment or self-employment. In case they found a job, but would start to work later, it is necessary to start within a period of three months. Specific steps mean having been in contact with a public employment office to find work, whoever took the initiative (renewing registration for administrative reasons only is not an active step); having been in contact with a private agency (temporary work agency, firm specializing in recruitment, etc.) to find work; applying to employers directly; asking among friends, relatives, unions, etc., to find work; placing or answering job advertisements; studying job advertisements; taking a recruitment test or examination or being interviewed; looking for land, premises or equipment; applying for permits, licenses or financial resources. Education and training are considered as ways of improving employability but not as methods of seeking work. Persons without work and in education or training will only be classified as unemployed if they are currently available for work and seeking work. Lay-offs are classified as unemployed if they do not receive any significant wage or salary ("significant" is set at 50 %) from their employer and if they are "currently available for work" and are seeking work. Lay-offs are treated as a case of unpaid leave initiated by the employer

3 including a leave paid out of government budget or by funds. In this case, lay-offs are classified as employed if they have an agreed date of return to work and if this date falls within a period of three months. During the off-season, seasonal workers cannot be considered as having a formal attachment to their high-season job because they do not continue to receive a wage or salary from their employer although they may have an assurance of return to work. If they are not at work during the offseason, they are classified as unemployed only if they are currently available for work and seeking work. CZSO (2015) reports that unemployed persons in the Czech Republic according to the internationally comparable methodology are persons aged 15 and older who usually live in the monitored region and who during the reference week fulfilled the three following ILO conditions. They were not employed, they were available for work, i.e. during the reference period they were currently available or available within 14 days for paid work or self-employment and had been actively seeking work for the past four weeks (via labor office or private employment agencies, directly in companies, via advertising, taking steps to found own company, filing an application for a work permission and a license or through any other way). Unemployed persons are also persons who are not seeking work because they have already found one and are able to start working within 14 days. The indicator is designed based on the Eurostat methodology created according to ILO (International Labor Organization) recommendations. MPSV (2015). The Ministry of Labour and Social Affairs in its statistics operates with the so called Registered Unemployed Person - a person that is in the MPSV's database since a particular date. To calculate the level of unemployment the number of attainable unemployed persons is used. These are job applicants who do not have any objective obstacles to be employed and can start working immediately. An attainable job applicant is not a person who is temporarily registered as unable to work, is on maternity leave or has a short-term work as stated in the paragraph 25, article 6 of the Employment Act, is in a re-training course and also a job applicant for a period of six months since being taken into custody. Until December 31, 2012, the Ministry of Labour and Social Affairs had expressed the level of unemployment using the indicator Registered Unemployment Rate, which was a rate of attainable job applicants and the labor force expressed in %. Since 2013 the Ministry has been using the indicator Rate of Unemployed Persons which expresses the rate of attainable job applicants aged 15 to 64 out of all inhabitants of the same age. MPSV (2012). Inspector (2011) use the alternative ways for expressing the level of unemployment in the Ostrava region. Their task is to prove the correlation between the indicator Unemployment Rate and the Rate of Unemployed Persons at the level of Ostrava city districts. The Rate of Unemployed Persons indicator is also used to determine the level of unemployment at a level smaller than city districts (streets, houses). The Rate of Unemployed Persons per the number of inhabitants in productive age (Šimek et al., 2015) is a study that provides a comprehensive view of the behavior of the indicator Rate of Unemployed Persons at different levels in the Czech Republic. 3. Data and methods Three indicators were used for the assessment of the unemployment level: Unemployment Rate by March 31, 2011 (GIS official statistics, the denominator used is a modification of a number of economically active persons from the Population and Housing Census -605-

4 in 2001 due to the absence of preliminary or definitive data from 2011 Census for the processing date in 2011) - Unemployment Rate (UR) official from GIS. Unemployment Rate by March 31, 2011 using current data on economically active inhabitants (EAO) in the city from the results of the Population and Housing Census 2011 (the indicator calculated in 2015) - Unemployment Rate (UR) on EAO_2011. The Rate of Unemployed Persons aged 15 to 64 per inhabitants of the productive age from 15 to 64 by March 31, Rate dos_2011. Data were taken from the following sources. Number of attainable job applicants in Ostrava city districts aged 15 to 64 by March 31, Ministry of Labour and Social Affairs of the Czech Republic (MPSV), taken from the job applicants database for Ostrava city districts. Age structure of the population in Ostrava city districts - Czech Statistical Office, final results from the Population and Housing Census Economically active inhabitants in Ostrava city districts - Czech Statistical Office, final results from the Population and Housing Census. Unemployment Rate by March 31, Ministry of Labour and Social Affairs of the Czech Republic, Official GIS statistics. Quartile characteristics of a statistic division were evaluated within the solution, and a correlation and a cluster analyses were taken from the statistical methods. Correlation analysis is used to describe the mutual relation between two cardinal (continuous numeric) or ordinal variables. The direction and intensity (strength) of dependence is measured using correlation coefficients. The value of the correlation coefficient is from -1 to +1. The sign determines the direction of dependence, i.e., positive figures of the correlation coefficient mean a positive correlation (if one variable goes up the other one goes up too, i.e. if one variable goes down, the other one goes down too), in the case of negative figures, we talk about a negative correlation (if one variable goes up the other one goes down, and vice versa). The intensity of correlation is related to the value of the correlation coefficient itself (it is not dependant on the plus/minus sign which only shows the direction). If the correlation coefficient equals zero, there is no linear relationship between the variables. The cluster analysis is a multivariate statistic method used for the classification of objects. It is used to classify units into groups (clusters) so as the units belonging to the same cluster would be more similar than objects from other groups. The cluster analysis can be carried out on a set of objects from which each object has to be described through the same set of signs that are worth studying in a particular set, as well as on a set of signs that are characterized through a particular set of objects which have these signs. The cluster analysis belongs to the methods that investigate similarities of multivariate objects, i.e. objects where a higher number of signs was measured and followed by classifying objects into clusters. Within the cluster analysis, a method of quadratic Euclidic distance (which forms the basis of the Ward s cluster method) was used in this article to measure the distance among objects. It is based on minimizing the information loss when connecting two classes. At each step a possible pair of subjects (clusters) is considered so as the sum of squared deviations from the mean value would reach its minimum upon the creation of its cluster. 4. Results The three indicators mentioned above which show the level of unemployment in Ostrava city districts were selected for comparison. Figure 1 shows the characteristics of the values division of -606-

the examined indicators throughout the years in Ostrava city districts and all the values are expressed in table 1. Using the indicator Job Applicants Ratio caused a slight shift towards lower values.

5 the examined indicators throughout the years in Ostrava city districts and all the values are expressed in table 1. Using the indicator Job Applicants Ratio caused a slight shift towards lower values. In this case there are also districts with high level of unemployment. There is an outlier in the city district Ostrava-Vítkovice in each method for expressing values. This is related to an extremely high level of unemployment in that particular district. For example: Unemployment Rate (UR) on EAO reached 28.4 %, UR official from GIS0 reached 24 % and Rate dos_2011 reached 17.6 %. Fig. 1. The boxplot of the quartile values division of the indicators UR official from GIS0, UR on EAO 2011, Rate dos_ Ostrava city districts Source: own calculation Tab. 1. The statistic division of values of the quartile indicators examined - Ostrava city districts UR official from GIS0 Rate dos_2011 UR on EAO2011 Percent ,4 6, Source: own calculation From the view of differences between values, the highest differences were reached in the regions with a high level of unemployment, that is in the districts Ostrava-Vítkovice (10.9 p.b.), Ostrava Slezská Ostrava (7.4 p.b.), Ostrava Moravská Ostrava a Přívoz (6.1 p.b.), Ostrava-Mariánské Hory a Hulváky (5.7 p.b.). On the other hand, very small differences were detected in the city -607-

6 districts Ostrava-Krásné Pole (1.9 p.b.), Ostrava-Nová-Bělá (1.9 p.b.), Ostrava-Martinov (1.9 p.b.), Ostrava-Polanka nad Odrou (1.9 p.b.) a Ostrava-Stará Bělá (1.9 p.b.). The correlation between individual indicators was also studied. A high level of correlation (0.996) was reached in the indicator UR EA0_2011 and Rate dos_2011. A lower level of the correlation coefficient was detected between the indicators UR official from GIS0 and Rate dos_2011 (0.964). Next step was a cluster analysis for the Ostrava city districts for each analyzed indicator separately. Fig. 2. Dendrogram Ostrava city districts - UR official from GIS0 for March 31, Source: own calculation Cluster analysis based on the indicator UR official from GIS0_2011 divided Ostrava city districts into four groups: 1. Ostrava-Hošťálkovice (554332), Ostrava-Pustkovec (554243), Ostrava-Hrabová (554669), Ostrava-Proskovice (554375), Ostrava-Lhotka (554324), Ostrava-Plesná (554723), Ostrava- Petřkovice (554308), Ostrava-Jih (546135), Ostrava-Poruba (556224) 2. Ostrava-Nová Bělá (554219), Ostrava-Polanka nad Odrou (554588), Ostrava-Stará Bělá (554235), Ostrava-Martinov (554570), Ostrava-Třebovice (554715), Ostrava-Svinov (554685), Ostrava-Krásné Pole (554561) -608-

7 3. Ostrava Mariánské Hory a Hulváky (554286), Ostrava Nová-Ves (554367), Ostrava- Michálkovice (554430), Ostrava-Moravská Ostrava a Přívoz (554911), Ostrava-Radvanice a Bartovice (554537) 4. Ostrava-Slezská Ostrava (546046), Ostrava-Vítkovice (554227) The cluster analysis and the values of the unemployment level showed that in terms of unemployment, districts from the cluster 3 belong to the problematic ones and the districts from the cluster 4 are highly problematic. Fig. 3. Dendrogram Ostrava city districts - Ratio dos_2011 Source: own calculation The cluster analysis of the region according to the indicator Rate of Unemployed Persons divided the Ostrava city districts into five clusters: -609-

1. Ostrava-Hošťálkovice (554332), Ostrava-Plesná (554723), Ostrava-Lhotka (5543247), Ostrava- Hrabová (554669), Ostrava-Proskovice (554375), Ostrava-Pustkovec (554243), Ostrava-Svinov (554685),

8 1. Ostrava-Hošťálkovice (554332), Ostrava-Plesná (554723), Ostrava-Lhotka ( ), Ostrava- Hrabová (554669), Ostrava-Proskovice (554375), Ostrava-Pustkovec (554243), Ostrava-Svinov (554685), Ostrava-Petřkovice (554308) 2. Ostrava-Jih (546135), Ostrava-Nová Ves (554367), Ostrava-Poruba (546224), Ostrava-Polanka nad Odrou (554588) 3. Ostrava-Krásné Pole (554561), Ostrava-Martinov (554570), Ostrava-Stará Bělá (554235), Ostrava-Nová Bělá (554219), Ostrava-Třebovice (554715) 4. Ostrava-Moravská Ostrava a Přívoz (545911), Ostrava-Slezská Ostrava (546046), Ostrava- Michálkovice (554430), Ostrava-Radvanice a Bartovice (554537), Ostrava-Mariánské Hory a Hulváky (554286) 5. Ostrava-Vítkovice (554227) The cluster analysis and the values of the unemployment level showed that in terms of unemployment, the districts from the cluster 4 belong to the problematic ones and the districts from the cluster 5 are highly problematic. The shifts in classification are obvious. For example in the first group with the indicator Rate of Unemployed Persons, the districts Pustkovec and Svinov are added while Ostrava-jih and Poruba are missing. Fig. 4. Dendrogram Ostrava city districts - UR on EAO_2011 Source: own calculation -610-

9 The cluster analysis of the region according to the indicator UR on EAO_2011 divided Ostrava city districts into six clusters: 1. Ostrava-Nová Bělá (554219), Ostrava-Stará Bělá (554235), Ostrava-Polanka nad Odrou (554588), Ostrava-Martinov (554570), Ostrava Krásné Pole (554561) 2. Ostrava-Lhotka (554324), Ostrava-Třebovice (554715), Ostrava-Petřkovice (554308), Ostrava- Svinov (554685), Ostrava-Hrabová (554669), Ostrava-Plesná (554723), Ostrava-Proskovice (554375), Ostrava-Hošťálkovice (554332), Ostrava-Pustkovec (554243) 3. Ostrava-Moravská Ostrava a Přívoz (545911), Ostrava-Slezská Ostrava (546046) 4. Ostrava-Jih (546135), Ostrava-Poruba (546224), Ostrava-Nová Ves (554367) 5. Ostrava-Michálkovice (554430), Ostrava-Radvanice a Bartovice (554537), Ostrava-Mariánské Hory a Hulváky (554286) 6. Ostrava-Vítkovice (554227) The cluster analysis and the values of the unemployment level showed that in terms of unemployment, the districts from the cluster 3 belong to the less problematic ones and the districts from the cluster 4 and 5 are problematic and the district Vítkovice in the cluster 6 is highly problematic. The cluster analyses performed for the city districts showed different districts classifications into similar clusters. It shows the importance of denominator, its correct determination. The properties of the indicator Rate of Unemployed Persons, which can be used for the purposes of territorial units classification from the labor market point of view, can be deduced. 5. Conclusion The solution showed significant differences in expressing the level of unemployment in the region using different indicators. In the case of a standard level of unemployment the differences between individual territorial units are more prominent than in the case when the new indicator Rate of Unemployed Persons was used. The level of values is different also because of a different calculation methodology. Comparison of both levels of unemployment is also interesting. Results from the Population and Housing Census 2011 were not reflected in the value of denominator for the UR official from GIS0. It is obvious that during the period of ten years there were changes in calculation and in the territorial distribution of economically active inhabitants in the district. The conclusion is in favor of using the indicator Rate of Unemployed Persons for regional and local labor market analyses, because the number of inhabitants aged 15 to 64 is available more frequently than every ten years. 6. Acknowledgement This research was financially supported by the European Social Fund (Grant NO. CZ.1.04/2.2.00/ ). References [1] CZSO Zaměstnanost a nezaměstnanost podle výsledků VŠPS Metodika. Metodické popisy ukazatelů VŠPS. Available from Internet: [2] EC Commission Directive (EC) No 1897/2000 of 7 September 2000 implementing Council Regulation (EC) No 577/98 on the organization of a labour force sample survey in the Community concerning the operational definition of unemployment

10 [3] Inspektor, T Metody agregace a adjustace geodat pro sledování prostorové segregace na příkladu Ostravy. Ostrava: HGF VŠB-TUO. [4] MPSV Změna metodiky ukazatele registrované nezaměstnanosti. Available from Internet: [5] MPSV Statistics of unemployment. Available from Internet: [6] Nový, I. and Syrůnek, A Sociologie pro ekonomy a manažery. Praha: Grada Publishing. [7] Šimek, M. et. al Podíl nezaměstnaných osob na počtu obyvatel v produktivním věku. Ostrava: VSB-TUO

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