Economic indicators of territories in regions, municipalities, cities, parishes (according to borders at the beginning of 2023), neighbourhoods and densely populated areas (experimental statistics)

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Dataset information

Country of origin
Updated
2023.03.17 14:00
Created
2020.09.23
Available languages
Latvian
Keywords
reģions, nodarbinātība, novads, nace, uzņēmums, pagasts, režģis, apkaime, migrācija, profesija, pilsēta, bat, uzņēmējdarbība, vdvv, pievienotā vērtība, produkcijas vērtība, administratīvā teritorija, blīvi apdzīvota teritorija, saimnieciskās darbības veidi, eksperimentālā statistika
Quality scoring
215

Dataset description

Economic indicators of territories: number of people and jobs employed, added value created and output value by actual place of residence and place of work (local units of activity of enterprises and institutions in the economically active market sector ([VVV](https://stat.gov.lv/lv/termini?Terms=%22vdvv+teritori%C4%81l%C4%81%22)) as well as commuting, including by type of activity (NACE 2), occupation and sector. Place of employment according to the situation in December of the year indicated. The added value and production value of the employed population is calculated by redistributing the economic indicators of the enterprise in proportion to the employment income of the employee or if the SRS data did not contain data on employees or the amount of their wages was 0 in proportion to the number of persons employed (if the number of employees was more than 0) or in proportion to the number of employees (if the number of employees was 0). Enterprises and institutions classified under NACE 2 classification as K (financial and insurance activities) and O (public administration and defence; compulsory social insurance), and the Red Cross of Latvia. The professions of the National Armed Forces are not included. Areas with less than 10 employees and areas with less than 10 employees and 3 enterprises are excluded. If a person is employed in more than one enterprise, he or she may be included in several flows. The total also includes the values of VDVs with unknown NACE 2 and occupational codes and those values that could not be published at NACE 2 and occupational code level due to the confidentiality criteria laid down. Actual place of residence according to the situation on 1 January of the year following the year indicated. More about determination of actual residence in Latvia in experimental statistics: https://stat.gov.lv/lv/metadati/8113-iedzivotaju-skaits-un-galvenie-demografiskie-raditaji-eksperimentala-statistika For persons not included in the population assessment, the address indicated in the Population Register, if it is in Latvia, for persons not in the register — the territorial unit code of the place of residence indicated in the SRS data. Since, directly from the administrative data, only the employee’s attachment to the undertaking is known, in the case of several VDVs, the place of work closest to the place of residence, but in such a way as to minimise the aggregate distance between the place of residence and the place of work of all employees within the company. The distance is calculated on the roads using the topographic map of the Latvian Geospatial Information Agency in scale 1:10 000 data (combined 3 rd and 4th cycle data with manual corrections and additions). In the calculations, the distance is reduced according to the correspondence between the occupation of the employed person and the type of activity of the VDVV (NACE 2). More on the calculation of indicators characterising economic activity in [metadata](https://stat.gov.lv/lv/metadati/8110-teritoriju-ekonomiskie-raditaji-eksperimentala-statistika). ##NPV table fields explanation * EMP: number of persons employed. * EMP_X: special values (column not used). * WP: number of jobs. * WP_X: special values (column not used). * PROD: value of production, euro. * PROD_X: specific values (90 — phenomenon not detected (NPV03* tables only)). * ADDED: added value, euro. * ADDED_X: specific values (90 — phenomenon not detected (NPV03* tables only)). * TIME: period (2017). * Area (NPV01\* and NPV02\* tables): code of the territorial unit. * AllAreaLV_H (NPV03* tables): code of the territorial unit of residence. * AllAreaLV_W (NPV03* tables): the code of the territorial unit of the workplace. * NACE (NPV0*1 tables): type of activity code (NACE 2). * ENTSECTORS (NPV0*2 tables): sector 2 (TOTAL — Total; MS — Market Sector; NMS — Non-Market Sector). * Occupation (NPV0*3 tables): professional code (UNK — unknown). Version 2 of the Statistical Classification of Economic Activities in the European Community (NACE 2) is published at https://data.gov.lv/dati/lv/dataset/nace2. Professional codes are published at https://data.gov.lv/dati/dataset/profesijas_csb. Territory codes are published at https://data.gov.lv/dati/dataset/teritorijas_csb. The Classification of Administrative Territories, Territorial Units and Statistical Regions is published at https://data.gov.lv/dati/dataset/atvk. Generalised boundaries of territorial units are published at https://data.gov.lv/dati/dataset/robezas. The neighborhoods are published at https://data.gov.lv/dati/dataset/apkaimes. Densely populated areas are published at https://data.gov.lv/dati/dataset/bat. Grid coverage published at https://data.gov.lv/dati/dataset/rezgis. The calculation of experimental statistics shall be based on new data sources and methods, seeking to widen the range or level of detail of statistics according to user needs. It should be noted that experimental statistical methods are not constant, approbated and internationally agreed and may be changed to improve data quality. The CSB publishes experimental statistics in order to receive user feedback, evaluate the analytical potential of the data, relevance to reality and user needs. The CSB considers that time series of experimental data can also be useful for users and the opinion of the users of the statistics is the basis for deciding on the inclusion of these statistics in the Official Statistics Programme. When publishing experimental statistics, the CSB provides data users with new sources of information for decision making.
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