Public, free-of-charge data of the Commercial Register [name of entrepreneur (company), registry code, VAT number, status, address, link to entrepreneur’s data]

Updated version of this and other open data from Estonia can be found here: http://www.rik.ee/en/open-data

Released under Creative Commons 3.0 BY-SA license

Numbers of enterprises and local units produced from a snapshot of the Inter-Departmental Business Register (IDBR) taken on 14 March 2025.

Context

This data originates from the Commercial Register of Estonia. The latest version as well as other open data from Estonia can be found from the official site of the Estonian Centre of Registers and Information Systems.

This is an updated version of this dataset by Kaggle user Christian Safka. This is the latest version of the data currently, as of July 30 2019. While the last uploaded one contained a total of 240706 public & private entitites, whereas this one contains 289051 entities. I also thought it would be good too give a fuller explanation of the data to make it more accessible to an international audience.

Content

The names, addresses, etc public, free-of-charge data for all public and private entities (companies, NPOs, local governments etc) in Estonia. I kept the column names and did not do any changes to the data itself, so people can work with the data above directly as the data itself is updated. The latest version can always be found there.

• nimi : Entity name
• ariregistri_kood : Registration number
• kmkr_nr : VAT registration number
• ettevotja_staatus : Entity status. L, N or R, respectively.
• ettevotja_staatus_tekstina : Entity status in text. Under liquidation, bankrupt or registered, respectively.
• asukoht_ettevotja_aadressis : Entity registered address
• asukoha_ehak_kood : Local autonomy classificator (EHAK) code
• asukoha_ehak_tekstina : Local autonomy classificator (EHAK) in text
• indeks_ettevotja_aadressis : Post index number
• ads_adr_id : This column appears to be a unique ID for the address
• ads_ads_oid : This column appears to be blank
• ads_normaliseeritud_taisaadress : Full entity registered address
• teabesysteemi_link : Link to the entity entry within the commercial register of Estonia

The link ‘List of Merit’ provides information on companies registered on the List of Merit for economic operators in the construction sector established by the Emilia-Romagna Region by Regional Executive Decision No 953 of 9 July 2012. The establishment of the merit list has two main objectives: the first is aimed at the establishment of a database from which contracting authorities, municipalities, customers, professionals and citizens will be able to draw to entrust tasks to companies; the second implements the principle of simplification by offering the possibility, where the regulatory and organisational conditions are met, of not having to resubmit the same documents provided for other obligations. Registration is voluntary, not subject to expiry and allowed to all construction operators in possession of one or more ATECO 2007 codes of the construction sector (letter F – Construction). The basic information (company name, registered office, VAT number, contact details) SOA certificates (with the relevant class) and ATECO codes are provided for each company on the list.

Credit report of Henkal South Africa Vat Registration No 4690105327 contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

This study examines the influence of the reduction in value-added tax (VAT) rates in China during 2018 and 2019 on corporate financialization. By employing a difference-in-differences model and utilizing data from Chinese A-share listed companies between 2017 and 2020, we assess the effects of tax reduction policies. Moreover, it achieves this outcome through three main pathways: alleviating financing constraints, boosting fixed asset investment, and weakening corporate financial arbitrage motives. Further analysis demonstrates that the inhibitory effect of VAT rate reduction on corporate financialization is more pronounced for non-manufacturing companies, businesses reliant on the basic tax rate as their primary revenue source, companies with low intermediate input rates, and those with a strong ability to shift the tax burden. Additionally, debt financing costs play a crucial role in moderating the relationship between tax reduction policies and corporate financialization. The conclusions drawn from this study provide valuable empirical evidence that can contribute to the refinement of VAT reduction policies and the prevention and resolution of financialization at the micro-level.

The main information relating to companies with a majority regional holding is given below: the dataset shows the company names of the aforementioned companies, the regional shareholding within the individual entity, the classification for the purposes of ANAC Decision No 8 of 2015, the tax code and/or VAT number of the investee, the registered office of the companies, the operating result as at 31 December 2021, the average number of employees as at 31 December 2021, the institutional website of each of them, the link to the individual sheet in the ‘Transparent administration’ section of the regional portal, and any notes on the data submitted.

Abstract

The survey was conducted in Ghana between December 2012 and July 2014 as part of the Africa Enterprise Survey 2013 roll-out, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Data from 720 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using face-to-face interviews.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Ghana was selected using stratified random sampling. Three levels of stratification were used in this country: firm sector, firm size, and geographic region.

Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).

Size stratification was defined following the standardized definition for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

Regional stratification for the Ghana ES was defined in four regions: Accra, North (Kumasi and Tamale), Takoradi, and Tema.

For the Ghana ES, several sample frames were used. The first was supplied by the World Bank and consists of enterprises interviewed in Ghana 2007. The World Bank required that attempts should be made to re-interview establishments responding to the Ghana 2007 survey where they were within the selected geographical regions and met eligibility criteria. Due to the fact that the previous round of surveys seemed to have utilized different stratification criteria (or no stratification at all) and due to the prevalence of small firms and firms located in the capital city in the 2007 sample the following convention was used. The presence of panel firms was limited to a maximum of 50% of the achieved interviews in each cell. That sample is referred to as the Panel.

The second frame was constructed using different lists acquired from relevant institutions in Ghana. The main lists used were obtained from the Ghana Statistical Service (GSS). These include: 1) The 2012 Firm Registry. The registry lacked information on firm employee size. 2) The list of firms paying VAT. The VAT dataset included a variable on firms; turnover. The VAT dataset and Firm Registry were merged by using the firms' identification number (TIN). VAT information was not available for all firms in the Firm Registry. 3) The list of Large Tax Payers. The Large Tax Payers file also lacked information on firm employee size.

Since firm size was missing from all lists mentioned above, after having discussed with GSS and with the local contractor the following methods were used to predict firm size. - All firms who were in the Firm Registry but not in the VAT dataset were considered to be micro firms and therefore not use in the current survey. - Firms who were in the Firm Registry and in the VAT dataset were considered to be small firms. - Firms in the Large Tax Payers dataset were considered medium or large firms. The original design was divided into two size groups: small firms and medium and large firms.

During fieldwork the GSS lists proved to be very inaccurate and not sufficient to reach the target sample design, As such they were complemented with additional lists of firms from the Ghana Chamber of Commerce and Industry and Business Associations. The list from the Ghana Chamber of Commerce lacked information on firm employee size or firm turnover. Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 1.3% (26 out of 1,990 establishments).

Finally, a block enumeration was also undertaken in order to build an additional list. The block enumeration allowed to physically creating a list of establishments from which to sample from. A total of 41 blocks were enumerated in the four locations included in the project out of the total 804 blocks identified. The enumeration was conducted without major problems in the time planned. The list of enumerated firms contained 958 records eligible for main Enterprise Survey.

Note: Unlike the standard ES, the universe for the Ghana ES is characterized by the presence of 5 size categories. The category medium&large was added as stratum in order to sample from the GSS large payers list, while the category "unknow size" was included in order to sample the firms in the Chamber of Commerce and Industry list.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve

The Business Register and Employment Survey (BRES) is the official source of employee and employment estimates by detailed geography and industry. It is also used to update the Inter-Departmental Business Register (IDBR), the main sampling frame for business surveys conducted by the Office for National Statistics (ONS), with information on the structure of businesses in the UK.

The survey collects employment information from businesses across the whole of the UK economy for each site that they operate. This allows the ONS to produce employee and employment estimates by detailed geography and industry split by full-time/part-time workers and whether the business is public/private.

The ONS produces a number of different measures of employment including Workforce Jobs and the Annual Population Survey/Labour Force Survey. However, BRES is the recommended source of information on employment by detailed geography and industry.

The BRES has two purposes: collecting data to update local unit information and business structures on the IDBR, and producing published annual employment statistics.

The BRES sample does not include Northern Ireland. Northern Ireland data are received direct from the Northern Ireland Department of Enterprise, Trade and Investment (DETINI) which are used to create UK estimates. The UK Data Archive holds data only for Great Britain.

The BRES replaced the Annual Business Inquiry, Part 1 (ABI/1) in 2009. ABI/1 data for 2009 and earlier are held as part of the Annual Respondents Database under UK Data Archive SN 6644.

Change in sampling from 2015-2016
In 2015, ONS made a strategic decision to include business units with a single PAYE code for which VAT data are available. Prior to 2015, such units were excluded from the sampling frame and therefore not estimated for in ONS outputs. So from January 2016, the coverage of BRES was extended to include a population of solely PAYE based businesses. This improvement in coverage is estimated to have increased the business survey population by around 100,000 businesses, with a total of around 300,000 employment and 200,000 employees between December 2015 and January 2016. The increase in business population has led to an increase in the estimate of employment and employees for the 2015 dataset. Further information is available in documentation file '7463_bres_2015_change_in_firm_sampling.pdf'.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

Latest edition information
For the fourteenth edition (September 2025), the 'revised 2022' and 'provisional 2023' data files have been added, along with a variable list for the same years.