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ՎիզուալԵլատեքստ
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Տող 1.
This is a list of [[Administrative division|first-level country subdivisions]] which have a nominal [[gross state product]] in excess of [[USD|$]]200 billion. There are almost 100 subdivisions that have more than $200 billion GDP. Those subdivisions which are the largest in their respective countries are shown in '''bold'''.
==Մատենագիտություն==
===Ոչ գեղարվեստական===
*{{cite book|url=https://books.google.com/books?id=GQ1nO61pKf4C|title=Իմ անեկդոտային կյանքը|year=2003|publisher=Thorndike Press|isbn=978-0-786-25590-0}}
* {{cite book|url=https://books.google.com/books?id=qj-TStWgwIgC|title=Ես հիշում եմ ինձ|year=2012|publisher=AuthorHouse|isbn=978-1-477-26458-4}}
* {{cite book|url=https://books.google.com/books?id=BbgBoQEACAAJ|title=Ես պարզապես հիշեցի|publisher=Clear Productions, Incorporated|year=2014|isbn=978-0-991-53670-2}}
* {{cite book|url=https://books.google.com/books?id=ZBESrgEACAAJ|title=Այն ինչ մոռացել եմ հիշել|publisher=Clear Productions, Incorporated|year=2015|isbn=978-0-991-53681-8}}
* {{cite book|url=https://books.google.com/books?id=h3MfswEACAAJ|title=Ինչու և երբ ծնվեց Դիկ Վան Դայքի շոուն|year=2015|publisher=Clear Productions, Incorporated|isbn=978-0-991-53686-3}}
* {{cite book|url=https://books.google.com/books?id=B15gvgAACAAJ|title=Կարլ Ռայներ, Հիմա դու իննսունչորս տարեկան ես.|publisher=Clear Productions, Incorporated|year=2016|isbn=978-0-991-53687-0}}
* {{cite book|url=https://books.google.com/books?id=i8hStAEACAAJ|title=Ապրում եմ իննսունհինգ տարեկանում։ Հիշում եմ այն ֆիլմերը, որոնք սիրում եմ|year=2017|publisher=Clear Productions, Incorporated|isbn=978-0-999-51820-5}}
* {{cite book|url=https://books.google.com/books?id=7LwqswEACAAJ|title=Մոտենում է իննսունվեցը. Ֆիլմերը, որոնք ես սիրում եմ դիտել և սիրում էի անել|year=2017|publisher=Clear Productions, Incorporated|isbn=978-0-999-51821-2}}
* {{cite book|url=https://books.google.com/books?id=UwgwMQAACAAJ|title=Շատ զբաղված է մեռնելու համար|year=2017|publisher=Clear Productions, Incorporated|isbn=978-0-991-53689-4}}
*Ինչպե՞ս ապրել հավերժ․[[2017 թվական]]<ref>{{ cite web | url=https://www.randomcontent.com/media//carl-reiner-reads-first-twenty-words-of-how-to-live-forever|title=CARL REINER READS FIRST TWENTY WORDS OF "HOW TO LIVE FOREVER }}</ref>
* {{cite book|url=https://books.google.com/books?id=98p1swEACAAJ|title=Թրամփի տապալումը|year=2018|publisher=Clear Productions, Incorporated|isbn=978-0-999-51822-9}}
* {{cite book|url=https://books.google.com/books?id=G_LBtQEACAAJ|title=Ես հիշում եմ ռադիոն|year=2018|publisher=Clear Productions, Incorporated|isbn=978-0-999-51823-6}}
* {{cite book|url=https://books.google.com/books?id=898DzAEACAAJ|title=Աշխարհի գեղարվեստի մեծագույն գործերի փորագրված լուսանկարներ|year=2019|publisher=Clear Productions, Incorporated|isbn=978-0-999-51825-0}}
* {{cite book|url=https://books.google.com/books?id=mzh-vwEACAAJ|title=Համարձակ լուսանկարներ|year=2019|publisher=Clear Productions,
Incorporated|isbn=978-0-999-51824-3}}
 
[[File:Country subdivisions by GDP over 200 billion USD.png|thumb|Country subdivisions by GDP over 200 billion USD {{Update inline|date=March 2020|reason=Some regions (e.g. Western Australia) aren't yet included}}|400px]]
===Գեղարվեստական===
 
* {{cite book|title=Մտեք ծիծաղելով․|year=1958|publisher=Crest Books|oclc=1803102}}
''Note: the use of nominal GDP and currency conversion in this list makes inter-area comparison difficult''
* {{cite book|url=https://books.google.com/books?id=gjBZCxn_9ygC&q=All+Kinds+of+Love+carl+reiner|title=Սիրո բոլոր տեսակները|year=1993|publisher=Carol Publishing Group|isbn=978-1-559-72163-9}}ḁ
 
* {{cite book|url=https://books.google.com/books?id=GYJ72vswwE4C|title=Շարունակեք ծիծաղել|publisher=Carol Publishing Group|year=1995|isbn=978-1-559-72273-5}}
==List==
* {{cite book|url=https://books.google.com/books?id=4FVpPwAACAAJ|title=2000 տարեկան ծերունին 2000 թվականին|year=1997|publisher=HarperCollins|isbn=978-0-060-17480-4}} (Մել Բրուքսի հետ)
{|class="wikitable plainrowheaders sortable" style="font-size:100%; text-align:left;"
* {{cite book|url=https://books.google.com/books?id=QbmENAAACAAJ&dq=How+Paul+Robeson+Saved+My+Life|title=Ինչպե՞ս Փոլ Ռոբեսոնը փրկեց իմ կյանքը (և այլ՝ հիմնականում ուրախ պատմություններ)|year=1999|publisher=Cliff Street Books|isbn=978-0-060-19451-2}}
|-
* {{cite book|url=https://books.google.com/books?id=0nfTmAEACAAJ|title=Պատմեք ինձ մի սարսափելի պատմություն, բայց ոչ շատ վախենալու|year=2003|publisher=Little, Brown and Company|isbn=978-0-316-83329-5}}
! Rank
* {{cite book|url=https://books.google.com/books?id=hqoW5oSyeMwC|title=2000 տարեկան ծերունին դպրոց է գնում|publisher=HarperCollins|year=2005|isbn=978-0-060-76676-4}} (Մել Բրուքսի հետ)
! Subdivision
* {{cite book|url=https://books.google.com/books?id=T0cgAQAAIAAJ|title=Վեպ՝ Սայմոնն ու Շուստերը|year=2006|publisher=Simon and Schuster|isbn=978-0-743-28669-5}}
! Country
* {{cite book|url=https://books.google.com/books?id=bmuJPgAACAAJ|title=Պատմեք ինձ մեկ այլ վախենալու պատմություն|year=2009|publisher=Dove Books|isbn=978-1-597-77630-1}}
! [[Continent]]
* {{cite book|url=https://books.google.com/books?id=fWiJPgAACAAJ|title=Պատմիր ինձ ինչ-որ հիմար պատմություն։ Picvik Մամուլի|year=2009|publisher=Phoenix Books|isbn=978-1-59 7-77627-1}}
! <small>[[Nominal GDP|Nominal<br>GDP]]<br>(billions<br>[[USD]])</small>
* {{cite book|title=Պատմիր ինձ կարճ պատմություն|year=2010|publisher=Pickwick Press|isbn=978-1-607-47713-6}}
! Year
* {{cite book|url=https://books.google.com/books?id=QhAdrgEACAAJ|title=Թահկա պակայի գաղտնի գանձը|year=2015|publisher=Clear Productions, Incorporated|isbn=978-0-991-53680-1}}
! <small>Population<br>(millions)</small>
* {{cite book|url=https://books.google.com/books?id=mW5QMQAACAAJ|title=Դու ասում ես, որ Աստված օրհնի քեզ փռշտալու և զկրտալու համար|year=2017|publisher=Clear Productions, Incorporated|isbn=978-0-991-53688-7}}
! <small>[[List of countries by GDP (nominal) per capita|Nominal<br>GDP per<br>Capita]]<br>(thousands<br>[[USD]])</small>
! Largest<br>city
|-
|1
| '''{{flag|California}}'''
| {{USA}}
| [[North America]]
| align="right"|3,183
| 2019<ref name="bea">{{Cite web |url=https://www.bea.gov/system/files/2019-04/qgdpstate0519_4.pdf|title=Archived copy |access-date=2019-02-28 |archive-url=https://web.archive.org/web/20190228192007/https://www.bea.gov/system/files/2019-02/qgdpstate0219.pdf |archive-date=2019-02-28 |url-status=dead }}</ref>
| align="right"|39.5
| align="right"|80
| [[Los Angeles]]
|-
|2
| {{flag|Texas}}
| {{USA}}
|[[North America]]
| align="right"|1,819
| 2018<ref name="bea" />
| align="right"|28.3
| align="right"|64
| [[Houston]]
|-
|3
| {{flag|New York}}
| {{USA}}
| [[North America]]
| align="right"|1,751
| 2019<ref name="bea" />
| align="right"|19.5
| align="right"|90
| [[New York City]]
|-
|4
| '''[[Guangdong]]'''
| {{CHN}}
| [[Asia]]
| align="right"|1,560
| 2019<ref name="China2019">GDP-2019 by Chinese provinces is quarterly data ({{cite web|url=http://data.stats.gov.cn/english/easyquery.htm?cn=E0102|title=Regional - quarterly by province (preliminary estimate) - China NBS National data|website=data.stats.gov.cn/english/index.htm|date=2019-04-07 }}). the average exchange rate is CNY 6.9 per US dollar (according to the ''Statistical Communiqué of P.R. China on the 2019 National Economic and Social Development'', {{cite web|url=http://www.stats.gov.cn/english/PressRelease/202002/t20200228_1728917.html|title=Statistical Communiqué of P.R. China on the 2018 National Economic and Social Development|website=data.stats.gov.cn/english/index.htm|date=2019-04-07}})</ref>
| align="right"|113.5
| align="right"|13
| [[Guangzhou]]
|-
|5
| [[Jiangsu]]
| {{CHN}}
| [[Asia]]
| align="right"|1,444
| 2019<ref name="China2019"/>
| align="right"|80.4
| align="right"|18
| [[Suzhou]]
|-
|6
| {{flag|Florida}}
| {{USA}}
| [[North America]]
| align="right"|1,059
| 2018<ref name="bea" />
| align="right"|20.6
| align="right"|50
| [[Jacksonville]]
|-
|7
| [[Shandong]]
| {{CHN}}
| [[Asia]]
| align="right"|1,030
| 2019<ref name="China2019"/>
| align="right"|100.5
| align="right"|12
| [[Qingdao]]
|-
|8
| '''{{flag|Tokyo}}'''
| {{JPN}}
| [[Asia]]
| align="right"|1,000
| 2018<ref>
{{cite web |url= https://www.metro.tokyo.lg.jp/tosei/hodohappyo/press/2020/02/10/10.html |title= 都民経済計算（都内総生産等）30年度速報・元年度見込｜東京都 |publisher= [[Tokyo Metropolitan Government]] |access-date= April 28, 2020 |language = ja}}</ref>
| align="right"|13.9
| align="right"|72
| [[Tokyo]]
|-
|9
| {{flag|Illinois}}
| {{USA}}
| [[North America]]
| align="right"|909
| 2019<ref name=":1">{{Cite web|url=https://www.bea.gov/system/files/2020-04/qgdpstate0420.pdf|title=Gross Domestic Product by State|website=US Bureau of Economic Analysis|archive-url=https://www.bea.gov/system/files/2020-04/qgdpstate0420.pdf|archive-date=2017-12-01|url-status=live}}</ref>
| align="right"|12.7
| align="right"|72
| [[Chicago]]
|-
|10
| [[Zhejiang]]
| {{CHN}}
| [[Asia]]
| align="right"|904
| 2019<ref name="China2019"/>
| align="right"|57.4
| align="right"|15
| [[Hangzhou]]
|-
|11
| '''{{flag|Île-de-France}}'''
| {{FRA}}
| [[Europe]]
| align="right"|866
| 2018<ref name="ReferenceA">https://ec.europa.eu/eurostat/documents/2995521/10474907/1-05032020-AP-EN.pdf</ref>
| align="right"|12.2
| align="right"|70
| [[Paris]]
|-
|12
| {{flag|Pennsylvania}}
| {{USA}}
| [[North America]]
| align="right"|803
| 2018<ref name=":0">{{Cite web|url=https://www.bea.gov/system/files/2019-04/qgdpstate0519_4.pdf|title=US State GDP 2018|archive-url=https://web.archive.org/web/20170513043122/https://www.bea.gov/newsreleases/regional/gdp_state/2017/pdf/qgsp0517.pdf|archive-date=2017-05-13|url-status=live}}</ref>
| align="right"|12.8
| align="right"|63
| [[Philadelphia]]
|-
|13
| '''{{flag|North Rhine-Westphalia}}'''
| {{GER}}
| [[Europe]]
| align="right"|795
| 2016<ref name=GermanyRef>{{cite web|title=Germany GDP-2012 and 2013 figures |url=http://www.statistik-portal.de/statistik-portal/en/en_jb27_jahrtab65.asp |quotation='''Germany Federal Statistical Office'''; National accounts – Gross domestic product; Annual average exchange rate is US$ 1.11 to EUR€ 1 in 2015 |website=Statistik-portal.de |accessdate=2017-03-30 |url-status=dead |archiveurl=https://web.archive.org/web/20110524080845/http://www.statistik-portal.de/Statistik-Portal/en/en_jb27_jahrtab65.asp |archivedate=2011-05-24 }}</ref>
| align="right"|17.9
| align="right"|42
| [[Cologne]]
|-
|14
| '''[[Seoul Capital Area]]'''
| {{KOR}}
| [[Asia]]
| align="right"|770
| 2017<ref name="index.go.kr">{{cite web|url=http://kostat.go.kr/portal/korea/kor_nw/1/13/2/index.board?bmode=read&aSeq=372162|title=2017년 지역소득(잠정)|website=www.kostat.go.kr}}</ref>
| align="right"|25.5
| align="right"|30
| [[Seoul]]
|-
|15
| [[Henan]]
| {{CHN}}
| [[Asia]]
| align="right"|726
| 2018<ref name="China2018">GDP-2018 by Chinese provinces is quarterly data ({{cite web|url=http://data.stats.gov.cn/english/easyquery.htm?cn=B01|title=Regional - quarterly by province (preliminary estimate) - China NBS National data|website=data.stats.gov.cn/english/index.htm|date=2019-04-07 }}). the average exchange rate is CNY 6.6174 per US dollar (according to the ''Statistical Communiqué of P.R. China on the 2018 National Economic and Social Development'', {{cite web|url=http://www.stats.gov.cn/english/PressRelease/201902/t20190228_1651335.html|title=Statistical Communiqué of P.R. China on the 2018 National Economic and Social Development|website=data.stats.gov.cn/english/index.htm|date=2019-04-07}})</ref>
| align="right"|95.5
| align="right"|8
| [[Zhengzhou]]
|-
|16
| {{flag|Bavaria}}
| {{GER}}
| [[Europe]]
| align="right"|677
| 2016<ref name=GermanyRef/>
| align="right"|12.8
| align="right"|50
| [[Munich]]
|-
|17
| '''{{flag|Ontario}}'''
| {{CAN}}
| [[North America]]
| align="right"|662
| 2018<ref>{{cite web |url=http://www.fin.gov.on.ca/en/economy/ecupdates/update.html |title=Ontario Economic Update |website=Fin.gov.on.ca |date=2017-03-24 |accessdate=2017-03-30 |archive-url=https://web.archive.org/web/20170515101513/http://www.fin.gov.on.ca/en/economy/ecupdates/update.html |archive-date=2017-05-15 |url-status=live }}</ref>
| align="right"|14.1
| align="right"|45
| [[Toronto]]
|-
|18
| '''{{flag|Greater London}}'''
| {{GBR}}
| [[Europe]]
| align="right"|650
| 2018<ref>https://www.ons.gov.uk/economy/grossdomesticproductgdp/bulletins/regionaleconomicactivitybygrossdomesticproductuk/1998to2018/pdf</ref>
| align="right"|8.9
| align="right"|73
| [[London]]
|-
|19
| {{flag|Ohio}}
| {{USA}}
| [[North America]]
| align="right"|649
| 2017<ref name=":0" />
| align="right"|11.6
| align="right"|56
| [[Columbus, Ohio|Columbus]]
|-
|20
| [[Sichuan]]
| {{CHN}}
| [[Asia]]
| align="right"|615
| 2018<ref name="China2018"/>
| align="right"|82.8
| align="right"|7
| [[Chengdu]]
|-
|21
| [[Hubei]]
| {{CHN}}
| [[Asia]]
| align="right"|595
| 2018<ref name="China2018"/>
| align="right"|58.2
| align="right"|10
| [[Wuhan]]
|-
|22
| {{flag|New Jersey}}
| {{USA}}
| [[North America]]
| align="right"|589
| 2016<ref name=":0" />
| align="right"|8.9
| align="right"|68
| [[Newark, New Jersey|Newark]]
|-
|23
| '''{{flag|São Paulo}}'''
| {{BRA}}
| [[South America]]
| align="right"|583
| 2018<ref name="Newsletter 3">{{cite web|title=PIB TRIMESTRAL DO ESTADO DE SÃO PAULO|url=http://www.seade.gov.br/produtos/midia/2018/02/PIB_Trim_4_2017.pdf|df=dmy-all}}</ref>
| align="right"|45.5
| align="right"|17
| [[São Paulo]]
|-
|24
| [[Kyushu region]]
| {{JPN}}
| [[Asia]]
| align="right"|572
| 2012
| align="right"|13.0
| align="right"|45
| [[Fukuoka]]
|-
|25
| {{flag|Baden-Württemberg}}
| {{GER}}
| [[Europe]]
| align="right"|568
| 2016<ref name=GermanyRef/>
| align="right"|10.9
| align="right"|49
| [[Stuttgart]]
|-
|26
| [[Shanghai]]
| {{CHN}}
| [[Asia]]
| align="right"|553
| 2019<ref name="China2019"/>
| align="right"|21.5
| align="right"|24
| [[Shanghai]]
|-
|27
| [[Hunan]]
| {{CHN}}
| [[Asia]]
| align="right"|550
| 2018<ref name="China2018"/>
| align="right"|68.4
| align="right"|8
| [[Changsha]]
|-
|28
| [[Hebei]]
| {{CHN}}
| [[Asia]]
| align="right"|544
| 2018<ref name="China2018"/>
| align="right"|73.3
| align="right"|7
| [[Shijiazhuang]]
|-
|29
| [[Fujian]]
| {{CHN}}
| [[Asia]]
| align="right"|541
| 2018<ref name="China2018"/>
| align="right"|38.9
| align="right"|13
| [[Fuzhou]]
|-
|30
| {{flag|Georgia (U.S. state)|name=Georgia}}
| {{USA}}
| [[North America]]
| align="right"|533
| 2016<ref name=":0" />
| align="right"|10.3
| align="right"|49
| [[Atlanta]]
|-
|31
| {{flag|North Carolina}}
| {{USA}}
| [[North America]]
| align="right"|527
| 2016<ref name=":0" />
| align="right"|10.1
| align="right"|50
| [[Charlotte, North Carolina|Charlotte]]
|-
|32
| {{flag|Massachusetts}}
| {{USA}}
| [[North America]]
| align="right"|516
| 2016<ref name=":0" />
| align="right"|6.8
| align="right"|76
| [[Boston]]
|-
|33
| [[Beijing]]
| {{CHN}}
| [[Asia]]
| align="right"|513
| 2019<ref name="China2019"/>
| align="right"|21.5
| align="right"|24
| [[Beijing]]
|-
|34
| {{flag|Michigan}}
| {{USA}}
| [[North America]]
| align="right"|505
| 2017<ref name=":0" />
| align="right"|10.0
| align="right"|50
| [[Detroit]]
|-
|35
| {{flag|Virginia}}
| {{USA}}
| [[North America]]
| align="right"|501
| 2016<ref name=":0" />
| align="right"|8.4
| align="right"|56
| [[Virginia Beach, Virginia|Virginia Beach]]
|-
|36
| {{flag|Washington}}
| {{USA}}
| [[North America]]
| align="right"|477
| 2016<ref name=":0" />
| align="right"|7.3
| align="right"|62
| [[Seattle]]
|-
|37
| '''{{flag|New South Wales}}'''
| {{AUS}}
| [[Australia]]
| align="right"|462
| 2017<ref name="AustraliaRef">{{cite web|url=http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/5220.0|title=Main Features - Main Features|first=c=AU; o=Commonwealth of Australia; ou=Australian Bureau of|last=Statistics|website=www.abs.gov.au|access-date=2013-12-21|archive-url=https://web.archive.org/web/20131209131355/http://www.abs.gov.au/AUSSTATS/abs@.nsf/mf/5220.0|archive-date=2013-12-09|url-status=live}}</ref>
| align="right"|8.0
| align="right"|61
| [[Sydney]]
|-
|38
| [[Anhui]]
| {{CHN}}
| [[Asia]]
| align="right"|453
| 2018<ref name="China2018"/>
| align="right"|62.3
| align="right"|7
| [[Hefei]]
|-
|39
| '''{{flag|Lombardy}}'''
| {{ITA}}
| [[Europe]]
| align="right"|439
| 2014<ref name="dati.istat.it">{{cite web |author=OECD |url=http://dati.istat.it/?lang=en |title=Istat Statistics |publisher=Dati.istat.it |date=2015-03-17 |accessdate=2017-03-30 |archive-url=https://web.archive.org/web/20170330042119/http://dati.istat.it/?lang=en |archive-date=2017-03-30 |url-status=live }}</ref>
| align="right"|10.0
| align="right"|47
| [[Milan]]
|-
|40
| '''[[Maharashtra]]'''
| {{IND}}
| [[Asia]]
| style="text-align:right;"|420
| 2019<ref>{{cite web|url=http://www.prsindia.org/uploads/media/State%20Budget%202018-19/Maharashtra%20Budget%20Analysis%202018-19.pdf|title=Maharashtra Budget Analysis 2018-19|website=PRS Legislative Research|access-date=2018-06-02|archive-url=https://web.archive.org/web/20180315003728/http://www.prsindia.org/uploads/media/State%20Budget%202018-19/Maharashtra%20Budget%20Analysis%202018-19.pdf|archive-date=2018-03-15|url-status=dead}}</ref>
| align="right"|112.4
| align="right"|4
| [[Mumbai]]
|-
|41
| {{flag|Maryland}}
| {{USA}}
| [[North America]]
| align="right"|414
| 2018<ref name=":0" />
| align="right"|6.0
| align="right"|69
| [[Baltimore]]
|-
|42
| [[Liaoning]]
| {{CHN}}
| [[Asia]]
| align="right"|383
| 2018<ref name="China2018"/>
| align="right"|43.7
| align="right"|9
| [[Shenyang]]
|-
|43
| [[Shaanxi]]
| {{CHN}}
| [[Asia]]
| align="right"|369
| 2018<ref name="China2018"/>
| align="right"|38.3
| align="right"|10
| [[Xi'an]]
|-
|44
| {{flag|Hong Kong}}
| {{CHN}}
| [[Asia]]
| align="right"|373
| 2019<ref>https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/weorept.aspx?sy=1990&ey=2019&scsm=1&ssd=1&sort=country&ds=.&br=1&pr1.x=29&pr1.y=8&c=546%2C532&s=NGDP%2CNGDPD%2CPPPGDP&grp=0&a=</ref>
| align="right"|7.5
| align="right"|49
| [[Hong Kong]]
|-
|45
| {{flag|Victoria}}
| {{AUS}}
| [[Australia]]
| align="right"|353
| 2017<ref name="AustraliaRef"/>
| align="right"|6.2
| align="right"|60
| [[Melbourne]]
|-
|46
| {{flag|Indiana}}
| {{USA}}
| [[North America]]
| align="right"|347
| 2016<ref name=":0" />
| align="right"|6.6
| align="right"|50
| [[Indianapolis]]
|-
|47
| [[Chongqing]]
| {{CHN}}
| [[Asia]]
| align="right"|342
| 2019<ref name="China2018"/>
| align="right"|30.5
| align="right"|11
| [[Chongqing]]
|-
|48
| {{flag|Minnesota}}
| {{USA}}
| [[North America]]
| align="right"|341
| 2016<ref name=":0" />
| align="right"|5.5
| align="right"|60
| [[Minneapolis]]
|-
|49
| {{flag|Tennessee}}
| {{USA}}
| [[North America]]
| align="right"|334
| 2016<ref name=":0" />
| align="right"|6.7
| align="right"|47
| [[Nashville, Tennessee|Nashville]]
|-
|50
| [[Chugoku Region]]
| {{JPN}}
| [[Asia]]
| align="right"|333
| 2012<ref name="esri.cao.go.jp"/>
| align="right"|7.6
| align="right"|46
| [[Hiroshima]]
|-
|51
| [[Jiangxi]]
| {{CHN}}
| [[Asia]]
| align="right"|332
| 2018<ref name="China2018"/>
| align="right"|46.1
| align="right"|7
| [[Nanchang]]
|-
|52
| {{flag|Colorado}}
| {{USA}}
| [[North America]]
| align="right"|330
| 2016<ref name=":0" />
| align="right"|5.5
| align="right"|58
| [[Denver]]
|-
|53
| {{flag|Hesse}}
| {{GER}}
| [[Europe]]
| align="right"|325
| 2015<ref name="GermanyRef" />
| align="right"|6.2
| align="right"|48
| [[Frankfurt]]
|-
|54
| {{flag|Lower Saxony}}
| {{GER}}
| [[Europe]]
| align="right"|319
| 2015<ref name="GermanyRef" />
| align="right"|7.8
| align="right"|37
| [[Hanover]]
|-
|55
| {{flag|Wisconsin}}
| {{USA}}
| [[North America]]
| align="right"|314
| 2016<ref name=":0" />
| align="right"|5.8
| align="right"|50
| [[Milwaukee]]
|-
|56
| {{flag|Quebec}}
| {{CAN}}
| [[North America]]
| align="right"|313
| 2016<ref name="www5.statcan.gc.ca">{{cite web |url=http://www5.statcan.gc.ca/cansim/a46?lang=eng&childId=3840038&CORId=3764&viewId=3 |title=CANSIM - 384-0038 - Gross domestic product, expenditure-based, provincial and territorial |website=Statcan.gc.ca |accessdate=2017-03-30 |archive-url=https://web.archive.org/web/20180530085938/http://www5.statcan.gc.ca/cansim/a46?lang=eng&childId=3840038&CORId=3764&viewId=3 |archive-date=2018-05-30 |url-status=dead }}</ref>
| align="right"|8.2
| align="right"|37
| [[Montreal]]
|-
|57
| {{flag|Arizona}}
| {{USA}}
| [[North America]]
| align="right"|309
| 2016<ref name=":0" />
| align="right"|6.9
| align="right"|43
| [[Phoenix, Arizona|Phoenix]]
|-
|58
| [[Guangxi]]
| {{CHN}}
| [[Asia]]
| align="right"|308
| 2018<ref name="China2018"/>
| align="right"|48.6
| align="right"|6
| [[Nanning]]
|-
|59
| {{flag|Missouri}}
| {{USA}}
| [[North America]]
| align="right"|305
| 2017<ref name=":0" />
| align="right"|6.1
| align="right"|50
| [[Kansas City]]
|-
|60
| {{flag|Queensland}}
| {{AUS}}
| [[Australia]]
| align="right"|300
| 2017<ref name="AustraliaRef"/>
| align="right"|5.0
| align="right"|66
| [[Brisbane]]
|-
|61
| {{flag|Connecticut}}
| {{USA}}
| [[North America]]
| align="right"|286
| 2019<ref name=":0" />
| align="right"|3.6
| align="right"|79
| [[Bridgeport, Connecticut|Bridgeport]]
|-
|62
| '''{{flag|Moscow}}'''
| {{RUS}}
| [[Europe]]
| align="right"|270
| 2017<ref>{{cite web|url=http://www.gks.ru/free_doc/new_site/vvp/vrp98-16.xlsx|title=Валовой региональный продукт|website=gks.ru|archive-url=https://web.archive.org/web/20180307214234/http://www.gks.ru/free_doc/new_site/vvp/vrp98-16.xlsx|archive-date=2018-03-07|url-status=live}}</ref>
| align="right"|12.6
| align="right"|21
| [[Moscow]]
|-
|63
| [[Yunnan]]
| {{CHN}}
| [[Asia]]
| align="right"|270
| 2018<ref name="China2018"/>
| align="right"|47.9
| align="right"|6
| [[Kunming]]
|-
|64
| '''{{flag|Mexico City}}'''
| {{MEX}}
| [[North America]]
| align="right"|266
| 2018<ref>https://www.mexicocity.com/v/economy</ref>
| align="right"|9.0
| align="right"|30
| [[Mexico City]]
|-
|65
| '''[[Istanbul Province|Istanbul]]'''
| {{flag|Turkey}}
| [[Europe]]
| align="right"|265
| 2017<ref>http://www.turkstat.gov.tr/PreHaberBultenleri.do;jsessionid=WvSKczfTxbnynDmp1TvLyNbz23GzhG62pX1pLNDSzrYhjjbMZVQd!-556022155?id=30888</ref>
| align="right"|15.1
| align="right"|18
| [[Istanbul]]
|-
|66
| {{flag|Auvergne-Rhône-Alpes}}
| {{FRA}}
| [[Europe]]
| align="right"|263
| 2014<ref name="ec.europa.eu">{{cite web|url=http://ec.europa.eu/eurostat/documents/2995521/7192292/1-26022016-AP-EN.pdf/602b34e8-abba-439e-b555-4c3cb1dbbe6e |title=Archived copy |accessdate=2016-02-28 |url-status=dead |archiveurl=https://web.archive.org/web/20160229124049/http://ec.europa.eu/eurostat/documents/2995521/7192292/1-26022016-AP-EN.pdf/602b34e8-abba-439e-b555-4c3cb1dbbe6e |archivedate=2016-02-29 }}</ref>
| align="right"|7.7
| align="right"|35
| [[Lyon]]
|-
|67
|[[Inner Mongolia]]
| {{CHN}}
| [[Asia]]
| align="right"|261
| 2018<ref name="China2018"/>
| align="right"|25.2
| align="right"|10
| [[Baotou]]
|-
|68
| [[Shanxi]]
| {{CHN}}
| [[Asia]]
| align="right"|254
| 2018<ref name="China2018"/>
| align="right"|36.9
| align="right"|7
| [[Taiyuan]]
|-
|69
| '''{{flag|Madrid}}'''
| {{ESP}}
| [[Europe]]
| align="right"|250
| 2017<ref name="ReferenceA"/>
| align="right"|6.5
| align="right"|38
| [[Madrid]]
|-
|70
| {{flag|Catalonia}}
| {{flag|Spain}}
| [[Europe]]
| align="right"|250
| 2017<ref name="ReferenceA"/>
| align="right"|7.5
| align="right"|34
| [[Barcelona]]
|-
|71
| {{flag|Alberta}}
| {{CAN}}
| [[North America]]
| align="right"|250
| 2016<ref name="www5.statcan.gc.ca" />
| align="right"|3.6
| align="right"|64
| [[Calgary]]
|-
|72
| [[Heilongjiang]]
| {{CHN}}
| [[Asia]]
| align="right"|247
| 2017<ref name="China2018"/>
| align="right"|37.9
| align="right"|7
| [[Harbin]]
|-
|73
|[[Tamil Nadu]]
| {{IND}}
| [[Asia]]
| style="text-align:right;" |245<!-- Converted from ₹17.26 lakh crore -->
| 2019<ref name="SDP 2018-19">{{cite web|title=State Domestic Product as of 31 March 2019|url=http://cms.tn.gov.in/sites/default/f..._e_2018_19.pdf|publisher=Ministry of Statistics and Program Implementation, Government Of India|accessdate=21 May 2017}}{{Dead link|date=April 2019 |bot=InternetArchiveBot |fix-attempted=yes }}</ref>
| align="right"|72.2
| align="right"|3
| [[Chennai]]
|-
|74
|[[Gujarat]]
| {{IND}}
| [[Asia]]
| style="text-align:right;" |242
| 2018<ref>{{cite web|url=https://www.prsindia.org/parliamenttrack/budgets/gujarat-budget-analysis-2019-2020|title=Gujarat State Budget|archive-url=https://web.archive.org/web/20190810040816/http://www.prsindia.org/parliamenttrack/budgets/gujarat-budget-analysis-2019-2020|archive-date=2019-08-10|url-status=dead|access-date=2019-09-02}}</ref>
| align="right"|63.9
| align="right"|4
| [[Ahmedabad]]
|-
|75
| {{flag|Louisiana}}
| {{USA}}
| [[North America]]
| align="right"|238
| 2016<ref name=":0" />
| align="right"|4.7
| align="right"|56
| [[New Orleans]]
|-
|76
| {{flag|Oregon}}
| {{USA}}
| [[North America]]
| align="right"|230
| 2016<ref name=":0" />
| align="right"|4.1
| align="right"|56
| [[Portland, Oregon|Portland]]
|-
|77
| [[Jilin]]
| {{CHN}}
| [[Asia]]
| align="right"|228
| 2018<ref name="China2018"/>
| align="right"|27.3
| align="right"|8
| [[Changchun]]
|-
|78
|[[Karnataka]]
| {{IND}}
| [[Asia]]
| style="text-align:right;" |226
| 2019
| align="right"|66.2
| align="right"|3
| [[Bangalore]]
|-
|79
| [[Guizhou]]
| {{CHN}}
| [[Asia]]
| align="right"|224
| 2018<ref name="China2018"/>
| align="right"|35.7
| align="right"|6
| [[Guiyang]]
|-
|80
| [[Uttar Pradesh]]
| {{IND}}
| [[Asia]]
| style="text-align:right;" |222
| 2018<ref>{{cite web|url=http://www.prsindia.org/uploads/media/State%20Budget%202018-19/Uttar%20Pradesh%20Budget%20Analysis%202018-19.pdf|title=Uttar Pradesh State Budget|access-date=2018-03-28|archive-url=https://web.archive.org/web/20180221100915/http://www.prsindia.org/uploads/media/State%20Budget%202018-19/Uttar%20Pradesh%20Budget%20Analysis%202018-19.pdf|archive-date=2018-02-21|url-status=dead}}</ref>
| align="right"|228
| align="right"|1
| [[Lucknow]]
|-
|81
| {{flag|Hokkaido}}
| {{JPN}}
| [[Asia]]
| align="right"|218
| 2012<ref name="esri.cao.go.jp">{{cite web|url=http://www.esri.cao.go.jp/jp/sna/data/data_list/kenmin/files/contents/pdf/gaiyou1.pdf |title=Archived copy |accessdate=2013-09-13 |url-status=dead |archiveurl=https://web.archive.org/web/20130913123113/http://www.esri.cao.go.jp/jp/sna/data/data_list/kenmin/files/contents/pdf/gaiyou1.pdf |archivedate=2013-09-13 }}</ref><ref name="autogenerated1">{{cite web|url=http://www.esri.cao.go.jp/jp/sna/data/data_list/sokuhou/files/2013/qe131_2/pdf/jikei_1.pdf |title=Archived copy |accessdate=2013-06-10 |url-status=dead |archiveurl=https://web.archive.org/web/20130810032926/http://www.esri.cao.go.jp/jp/sna/data/data_list/sokuhou/files/2013/qe131_2/pdf/jikei_1.pdf |archivedate=2013-08-10 }}</ref>
| align="right"|5.5
| align="right"|42
| [[Sapporo]]
|-
|82
| '''{{flag|Abu Dhabi}}'''
| {{UAE}}
| [[Asia]]
| align="right"|215
| 2014<ref>{{cite web|url=https://www.abudhabi.ae/portal/public/en/abu_dhabi_emirate/facts_figure_background?_adf.ctrl-state=pip061qpr_4&_afrLoop=18652570093766500#! |title=Abu Dhabi Emirate: Facts and Figures |website=Abudhabi.ae |date=2017-03-15 |accessdate=2017-03-30}}</ref>
| align="right"|2.7
| align="right"|80
| [[Abu Dhabi]]
|-
|83
| {{flag|Western Australia}}
| {{AUS}}
| [[Australia]]
| align="right"|214
| 2017<ref name="AustraliaRef" />
| align="right"|2.7
| align="right"|79
| [[Perth]]
|-
|84
| {{flag|South Carolina}}
| {{USA}}
| [[North America]]
| align="right"|213
| 2016<ref name=":0" />
| align="right"|5.0
| align="right"|40
| [[Charleston, South Carolina|Charleston]]
|-
|85
| {{flag|British Columbia}}
| {{CAN}}
| [[North America]]
| align="right"|210
| 2016<ref name="www5.statcan.gc.ca" />
| align="right"|4.4
| align="right"|50
| [[Vancouver]]
|-
|86
| {{flag|Alabama}}
| {{USA}}
| [[North America]]
| align="right"|208
| 2016<ref name=":0" />
| align="right"|4.9
| align="right"|43
| [[Birmingham, Alabama|Birmingham]]
|-
|87
| [[Tianjin]]
| {{CHN}}
| [[Asia]]
| align="right"|204
| 2019<ref name="China2019"/>
| align="right"|15.6
| align="right"|16
| [[Tianjin]]
|-
|88
| {{flag|Kentucky}}
| {{USA}}
| [[North America]]
| align="right"|202
| 2016<ref name=":0" />
| align="right"|4.4
| align="right"|42
| [[Louisville, Kentucky|Louisville]]
|-
|89
| '''{{flag|Jakarta}}'''
| {{IDN}}
| [[Asia]]
| align="right"|201
| 2019
| align="right"|10.5
| align="right"|19
| [[Jakarta]]
|-
|90
| {{flag|Lazio}}
| {{ITA}}
| [[Europe]]
| align="right"|200
| 2015<ref name="europa.eu">{{Cite web |url=http://ec.europa.eu/eurostat/documents/2995521/7962764/1-30032017-AP-EN.pdf/4e9c09e5-c743-41a5-afc8-eb4aa89913f6 |title=Archived copy |access-date=2018-02-03 |archive-url=https://web.archive.org/web/20170402074543/http://ec.europa.eu/eurostat/documents/2995521/7962764/1-30032017-AP-EN.pdf/4e9c09e5-c743-41a5-afc8-eb4aa89913f6 |archive-date=2017-04-02 |url-status=live }}</ref>
| align="right"|5.9
| align="right"|34
| [[Rome]]
|-
|}
 
 
 
== Ծանոթագրություններ ==
{{ծանցանկ}}
Ստացված է «https://hy.wikipedia.org/wiki/Մասնակից:Aregnaz2001/Ավազարկղ» էջից