Find UNdata on Facebook Follow UNdata on Twitter Please send us your feedback

Table 2.6 Output, gross value added and fixed assets by industries at current prices (ISIC Rev. 4)Go toSearch glossaries

Source: National Accounts Official Country Data | United Nations Statistics Division

Select filters:

Country or Area (102)






































































































Up
Down
Fiscal Year (69)





































































Up
Down
Sub Item (29)





























Up
Down
Item (23)























Up
Down
Spinner
364 records | Page 1 of 8 | 
Next Last
Country or AreaSNA93 Table CodeSub ItemSub GroupItemSNA93 Item CodeYearSeriesCurrencySNA systemFiscal year typeValue 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20171000dram2008Western calendar year9,200 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20161000dram2008Western calendar year8,800 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20151000dram2008Western calendar year8,000 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20141000dram2008Western calendar year7,900 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20131000dram2008Western calendar year10,000 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2012300dram1993Western calendar year10,000 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2011300dram1993Western calendar year15,500 
Armenia2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2010300dram1993Western calendar year11,000 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2018400Azerbaijan new manat1993Western calendar year40,300 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2017400Azerbaijan new manat1993Western calendar year37,900 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2016400Azerbaijan new manat1993Western calendar year38,100 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2015400Azerbaijan new manat1993Western calendar year39,100 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2014400Azerbaijan new manat1993Western calendar year41,500 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2013400Azerbaijan new manat1993Western calendar year42,300 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2012400Azerbaijan new manat1993Western calendar year41,800 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2011400Azerbaijan new manat1993Western calendar year41,200 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2010400Azerbaijan new manat1993Western calendar year41,500 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2009400Azerbaijan new manat1993Western calendar year42,700 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2008400Azerbaijan new manat1993Western calendar year44,200 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2007400Azerbaijan new manat1993Western calendar year44,300 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2006400Azerbaijan new manat1993Western calendar year44,100 
Azerbaijan2.6Mining and quarrying (B) Employment (average, in 1000 persons) 2005400Azerbaijan new manat1993Western calendar year42,300 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20171100Belarussian rouble (re-denom. 1:10000)2008Western calendar year10,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20161100Belarussian rouble (re-denom. 1:10000)2008Western calendar year11,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20151100Belarussian rouble (re-denom. 1:10000)2008Western calendar year11,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20151000Belarussian rouble (re-denom. 1:1000)2008Western calendar year11,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20141100Belarussian rouble (re-denom. 1:10000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20141000Belarussian rouble (re-denom. 1:1000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20131100Belarussian rouble (re-denom. 1:10000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20131000Belarussian rouble (re-denom. 1:1000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20121100Belarussian rouble (re-denom. 1:10000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20121000Belarussian rouble (re-denom. 1:1000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20111100Belarussian rouble (re-denom. 1:10000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20111000Belarussian rouble (re-denom. 1:1000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20101100Belarussian rouble (re-denom. 1:10000)2008Western calendar year12,000 
Belarus2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20101000Belarussian rouble (re-denom. 1:1000)2008Western calendar year12,000 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20161000real2008Western calendar year243,531 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20151000real2008Western calendar year287,556 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20141000real2008Western calendar year301,964 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20131000real2008Western calendar year308,412 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20121000real2008Western calendar year299,804 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20111000real2008Western calendar year292,736 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20101000real2008Western calendar year266,941 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20091000real2008Western calendar year243,127 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20081000real2008Western calendar year241,309 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20071000real2008Western calendar year240,147 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20061000real2008Western calendar year220,867 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20051000real2008Western calendar year223,565 
Brazil2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20041000real2008Western calendar year221,634 
Bulgaria2.6Mining and quarrying (B) Employment (average, in 1000 persons) 20171000lev2008Western calendar year23,340 
Source

National Accounts Official Country Data

Source:  United Nations Statistics Division

The Economic Statistics Branch of the United Nations Statistics Division (UNSD) maintains and annually updates the National Accounts Official Country Data database. This work is carried out in accordance with the recommendation of the Statistical Commission at its first session1 that the Statistics Division of the United Nations should publish regularly the most recent available data on national accounts for as many countries and areas as possible. The database contains detailed official national accounts statistics in national currencies as provided by the National Statistical Offices2.

Data are available for most of the countries or areas of the world and form a valuable source of information on their economies. The database contains data as far back as 1946, up to the year t-1, with data for most countries available from the 1970s. The database covers not only national accounts main aggregates such as gross domestic product, national income, saving, value added by industry and household and government consumption expenditure and its relationships; but also detailed statistics for institutional sectors (including the rest of the world), comprising the production account, the generation of income account, the allocation of primary income account, the secondary distribution of income account, the use of disposable income account, the capital account and the financial account, if they are compiled by countries.

The statistics for each country or area are presented according to the uniform table headings and classifications as recommended in the United Nations System of National Accounts 1993 (1993 SNA). A summary of the 1993 SNA conceptual framework, classifications and definitions are included in the yearly publication “National Accounts Statistics, Main Aggregates and Detailed Tables”. A pdf version of the 2018 yearbook with detailed national accounts statistics of 210 countries or areas for the years 2007 to 2018 can be accessed free-of-charge from http://unstats.un.org/unsd/nationalaccount/pubsDB.asp?pType=3. Former editions of the yearbook (in pdf and print versions) are also available. Details on the publication can be found at http://unstats.un.org/unsd/nationalaccount/madt.asp. Requests for customized data downloads can be addressed to sna@un.org.


1/ United Nations, 1947, Official Records of the Economic and Social Council Supplement No. 6 (E/264), chap. VIII, para. 42. New York: United Nations Publications.
2/ Different series numbers (column “Series”) are used to store different time-series versions of national accounts statistics. Series numbers with two digits (10,20) refer to data compiled following the 1968 SNA national accounts methodology, while series numbers with three digits (100, 200, etc) refer to data compiled using the 1993 SNA national accounts methodology, and series numbers with four digits (1000, 1100, etc) refer to data compiled using the 2008 SNA national accounts methodology. In addition to different methodologies, different series numbers are used when data are reported in different currencies, fiscal years, or by different sources. Furthermore, data are stored under a new series number whenever there are significant changes in compilation practices which make the time series no longer comparable.

Last update in UNdata: 2019/10/01
Next update in UNdata: 2020/10/01