ᥛᥫᥒᥰ ᥑᥥᥱ

ᥛᥫᥒᥰ ᥑᥥᥱ
ᥛᥫᥒᥰ ᥑᥥᥱ; Lua error in package.lua at line 80: module 'Module:Lang/data/iana scripts' not found.; Lua error in package.lua at line 80: module 'Module:Lang/data/iana scripts' not found. (Pinyin);
	ᥟᥣ ᥘᥣᥛᥱ ᥛᥤᥐ ᥛᥣᥭᥴ
	ᥑᥣᥛᥰ ᥓᥪᥒ ᥛᥫᥒᥰ: "March of the Volunteers"
	ᥟᥩᥒᥲᥖᥤᥲ ᥛᥫᥒᥰ ᥑᥥᥱ (green) ASEAN ᥢᥬᥰ (dark grey) – [Legend]
ᥐᥨᥢᥰ ᥑᥫᥰ	Han (၉၁.၉.9%), ᥓᥩᥢᥰ (၁.၃၀%), ᥛᥣᥢᥱ ᥠᥨᥰ (၀.၈၆%), ᥝᥤᥱ ᥐᥣᥱ (၀.၇၉%), ᥙᥣᥢᥰ ᥔᥥᥰ (၀.၇၉%), ᥛᥦᥝᥱ ᥓᥪᥰ (၀.၇၂%), ᥕᥤᥴ (၀.၆၅%), ᥗᥧᥴ ᥓᥣᥰ (၀.၆၂%), ᥛᥧᥢᥱ ᥐᥨᥝᥰ (၀.၄၇%), ᥖᥤ ᥝᥦᥖᥳ (၀.၄၄%), ᥝᥧᥱ ᥕᥤᥰ (၀.၄၄%), ᥐᥣᥝ ᥘᥤᥴ (၀.၁၅%),
ᥛᥥᥝᥰ ᥛᥫᥒᥰ	ᥙᥫᥒ ᥙᥣᥭᥰ ᥛᥫᥒᥰ ᥙᥣᥱ ᥖᥤᥱ ᥘᥥᥝ၊ ᥛᥫᥒᥰ ᥓᥩᥛ ᥓᥪᥒ ᥔᥨᥝᥱ ᥡᥥᥱ ᥘᥤᥖᥳ
ᥟᥥᥱ ᥘᥤᥳ ᥕᥣᥱ ᥟᥢᥴ
• ᥞᥨᥛ	9,640,821 km² (3,704,427 sq mi) (ᥓᥢᥳ: 3/4)
• ᥘᥩᥒ ᥔᥖ ᥞᥨᥝᥴ ᥘᥙᥳ ᥐᥨᥢᥰ	140/km² (363/sq mi)
GDP (PPP)	ᥘᥣᥛᥰ 2020
• ᥞᥨᥛ	$29.471 trillion (ᥓᥢᥳ- 1st)
• Per capita	$20,984 (ᥓᥢᥳ - 67th)
GDP (nominal)	ᥘᥣᥛᥰ2020
• ᥞᥨᥛᥲ	$15.269 trillionᥗᥦᥛᥰ ᥙᥣ ᥘᥥᥐᥳ:Refn (ᥓᥢᥳ- 2nd)
• Per capita	$10,872 (ᥓᥢᥳ - 67th)
Gini (2018)	ᥗᥦᥛᥰ ᥙᥣ ᥘᥥᥐᥳ:IncreaseNegative 46.7; ᥔᥧᥒᥴ
HDI (2018)	0.758; ᥔᥧᥒᥴ · 85th
ᥒᥪᥢᥰ ᥖᥩᥒᥰ	Renminbi (yuan; ¥) (CNY)
ᥑᥣᥝᥰ ᥕᥣᥛᥰ ᥘᥣᥲ ᥘᥤᥢ	China Standard Time (UTC+8)
ᥙᥫᥒ ᥝᥢᥰ ᥖᥤ	yyyy-mm-dd; or yyyy年m月d日; (CE; CE-1949);
ᥙᥫᥒ ᥔᥣᥭᥴ ᥘᥨᥖ	ᥛᥪᥰ ᥑᥣᥴ
ᥑᥨᥖ ᥖᥥᥱ ᥘᥤᥱ ᥜᥨᥒᥰ	+86
Internet TLD	.cn; .中国; .中國;

ᥛᥫᥒᥰ ᥑᥥᥱ

ᥓᥪᥒ ᥛᥫᥒᥰ ᥓᥩᥛ ᥓᥪᥒ ᥐᥨᥢᥰ ᥛᥫᥒᥰ ᥙᥣᥢᥱ ᥙᥩᥒ ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥭᥳ ᥐᥣ ᥖᥤ ᥟᥥᥰ ᥡᥫᥝᥰ ᥝᥢᥰ ᥟᥩᥐᥱ ᥘᥢᥳ ᥛᥢᥰ ᥙᥥᥢ ᥓᥪᥒ ᥛᥫᥒᥰ ᥟᥢ ᥕᥬᥱ ᥖᥤ ᥔᥧᥖᥱ ᥔᥥᥴ၊ ᥘᥬᥰ ᥘᥨᥐ ᥙᥧᥢᥳ ᥖᥤ ᥙᥣᥱ ᥘᥭᥳ ᥓᥛᥰ ᥛᥢᥰ ᥙᥥᥢ ᥓᥪᥒ ᥛᥫᥒᥰ ᥟᥢ ᥕᥬᥱ ᥔᥥᥴ ᥙᥫᥢ ᥖᥤᥳ ᥔᥣᥛᥴ ᥟᥛᥱ ᥘᥢᥴ ᥗᥤᥳ ᥔᥤᥱ။ ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥭᥳ ᥞᥨᥝᥴ ᥘᥙᥳ ᥐᥨᥢᥰ ᥛᥢᥰ ᥛᥤᥰ 1300 ᥘᥣᥢᥳ ᥔᥥᥴ ᥙᥥᥢ ᥓᥪᥒ ᥛᥫᥒᥰ ᥟᥢ ᥞᥨᥝᥴ ᥘᥙᥳ ᥐᥨᥢᥰ ᥘᥛᥴ ᥔᥥᥴ ᥙᥫᥢ ᥐᥩᥲ ᥓᥬ ᥕᥝᥳ။ ᥙᥥᥢ ᥛᥫᥒᥰ ᥟᥢ ᥙᥣᥱ ᥖᥤᥱ ᥑᥩᥛᥱ ᥛᥣᥱ ᥢᥤᥖᥳ ᥚᥩᥒᥰ ᥒᥛᥰ။ ᥛᥤᥰ ᥟᥪᥒᥱ ᥖᥒᥰ ᥔᥥᥒᥲ (22)ᥟᥢ၊ ᥘᥦᥢ ᥛᥤᥰ ᥔᥧᥢᥱ ᥐᥣᥢᥰ ᥙᥩᥒ ᥞᥣᥒᥰ ᥑᥨᥝᥴ (5)ᥟᥢ၊ ᥝᥥᥒᥰ ᥒᥝᥲ ᥓᥪᥒ ᥟᥢ ᥙᥣᥢᥱ ᥙᥩᥒ ᥘᥩᥒ ᥘᥫᥛ ᥘᥭᥲ (4)ᥟᥢ (ᥙᥫᥭᥲ ᥓᥤᥢᥰ၊ ᥗᥦᥢᥰ ᥓᥤᥒᥰ၊ ᥡᥣᥒᥱ ᥑᥣᥭᥰ၊ ᥠᥨᥒᥱ ᥠᥤᥒᥳ)ᥘᥦᥲ ᥘᥦᥢ ᥐᥣᥢᥰ ᥙᥩᥒ ᥑᥪᥐᥳ ᥑᥣᥭᥰ (2)ᥟᥢ (ᥞᥩᥒ ᥐᥩᥒ ᥘᥦᥲ ᥛᥣ ᥐᥣᥝᥰ)။ ᥝᥥᥒᥰ ᥒᥝᥲ ᥓᥪᥒ ᥛᥫᥒᥰ ᥑᥥᥱ ᥙᥥᥢ ᥝᥥᥒᥰ ᥙᥫᥭᥲ ᥓᥤᥢ။

ᥓᥥ ᥟᥪᥒᥱ ᥓᥪᥒ ᥛᥫᥒᥰ ᥓᥩᥛ ᥓᥪᥒ ᥐᥨᥢᥰ ᥛᥫᥒᥰ ᥙᥣᥢᥱ ᥙᥩᥒ ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥭᥳ ᥓᥪᥒ ᥙᥩᥰ ᥞᥨᥛ ᥙᥣᥰ ᥖᥒᥰ ᥗᥭᥱ ᥝᥢᥱ ᥘᥭᥴ ᥖᥥᥴ ᥛᥤᥰ ᥓᥥ ᥟᥪᥒᥱ (23)ᥖᥩᥢ။ ᥗᥭᥱ ᥝᥢᥱ ᥖᥥᥳ ᥕᥧᥱ ᥖᥤ ᥓᥪᥒ ᥛᥫᥒᥰ ᥓᥩᥛ ᥓᥪᥒ ᥐᥨᥢᥰ ᥛᥫᥒᥰ ᥙᥣᥢᥱ ᥙᥩᥒ ᥛᥫᥒᥰ ᥑᥥᥱ ᥔᥥᥴ ᥟᥧᥙᥱ ᥙᥫᥒᥱ ᥚᥩᥒᥰ ᥒᥛᥰ။ ᥐᥥᥝᥱ ᥐᥙᥱ ᥘᥨᥭᥲ ᥐᥣᥙ ᥚᥩᥒᥰ ᥒᥛᥰ ᥟᥧᥙᥱ ᥙᥫᥒᥱ ᥗᥭᥱ ᥝᥢᥱ ᥔᥥᥴ ᥘᥬᥰ ᥐᥥ ᥓᥪᥒ ᥛᥫᥒᥰ ᥓᥩᥛ ᥓᥪᥒ ᥐᥨᥢᥰ ᥛᥫᥒᥰ ᥙᥣᥢᥱ ᥙᥩᥒ ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥦᥲ ᥖᥒᥰ ᥗᥭᥱ ᥝᥢᥱ ᥖᥪᥐᥳ ᥛᥤᥰ ᥘᥩᥒ ᥗᥥᥒᥴ ᥐᥢ ᥕᥧᥱ။ ᥘᥩᥐ ᥔᥥᥴ (23) ᥓᥥ ᥟᥪᥒᥱ ᥕᥝᥳ ᥘᥢᥳ ᥕᥒᥰ ᥛᥤᥰ ᥓᥥ ᥟᥪᥒᥱ ᥙᥣᥢᥱ ᥙᥩᥒ ᥞᥣᥒᥰ ᥑᥨᥝᥴ (5)ᥛᥫᥒᥰ၊ ᥝᥥᥒᥰ ᥒᥝᥲ ᥓᥪᥒ ᥟᥢ ᥙᥣᥢᥱ ᥙᥩᥒ ᥘᥩᥒ ᥘᥫᥛ ᥘᥭᥲ (4)ᥟᥢ၊ ᥘᥦᥢ ᥘᥤᥢ ᥘᥭᥲ ᥔᥧᥢᥱ ᥑᥪᥐᥳ ᥑᥣᥭᥰ ᥖᥣᥱ ᥐᥣᥢᥰ ᥙᥩᥒ (2)ᥟᥢ။ ᥓᥥ ᥟᥪᥒᥱ (22)ᥟᥢ၊ ᥓᥥ ᥟᥪᥒᥱ ᥙᥣᥢᥱ ᥙᥩᥒ ᥞᥣᥒᥰ ᥑᥨᥝᥴ (5)ᥛᥫᥒᥰ၊ ᥝᥥᥒᥰ ᥒᥝᥲ ᥓᥪᥒ ᥟᥢ ᥙᥣᥢᥱ ᥙᥩᥒ ᥘᥩᥒ ᥘᥫᥛ ᥘᥭᥲ (4) ᥟᥢ ᥑᥝᥴ ᥓᥫᥰ ᥘᥭᥳ ᥛᥣᥰ ᥞᥨᥛ ᥐᥢ ᥔᥥᥴ ᥞᥩᥒᥳ ᥝᥣ"ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥨᥒᥴ"(Mainland China) ᥘᥭᥴ ᥕᥝᥳ။

ᥓᥥ ᥟᥪᥒᥱ (24) ᥟᥢ

ᥓᥥ ᥟᥪᥒᥱ ᥟᥣᥢᥰ ᥞᥨᥭᥰ - Anhui (安徽)
ᥓᥥ ᥟᥪᥒᥱ ᥜᥧᥱ ᥓᥦᥢᥱ - Fujian (福建)
ᥓᥥ ᥟᥪᥒᥱ ᥐᥣᥢ ᥔᥧᥲ - Gansu (甘肅)
ᥓᥥ ᥟᥪᥒᥱ ᥐᥩᥢᥰ ᥖᥨᥒ - Guangdong (廣東)
ᥓᥥ ᥟᥪᥒᥱ ᥐᥨᥭᥲ ᥓᥫᥝ - Guizhou (貴州)
ᥓᥥ ᥟᥪᥒᥱ ᥞᥣᥭᥱ ᥢᥣᥢᥱ - Hainan (海南)
ᥓᥥ ᥟᥪᥒᥱ ᥑᥫᥱ ᥙᥫᥭᥲ - Hebei (河北)
ᥓᥥ ᥟᥪᥒᥱ ᥞᥫᥭᥰ ᥘᥨᥒᥴ ᥓᥦᥒ - Heilongjiang (黑龍江)
ᥓᥥ ᥟᥪᥒᥱ ᥑᥫᥴ ᥢᥣᥢᥴ - Henan (河南)
ᥓᥥ ᥟᥪᥒᥱ ᥑᥧ ᥙᥥᥲ - Hubei (湖北)
ᥓᥥ ᥟᥪᥒᥱ ᥑᥧᥴ ᥢᥣᥢᥴ - Hunan (湖南)
ᥓᥥ ᥟᥪᥒᥱ ᥓᥦᥒ ᥔᥧ - Jiangsu (江蘇)
ᥓᥥ ᥟᥪᥒᥱ ᥓᥦᥒ ᥡᥤ - Jiangxi (江西)
ᥓᥥ ᥟᥪᥒᥱ ᥓᥤ ᥘᥤᥢᥴ - Jilin (吉林)
ᥓᥥ ᥟᥪᥒᥱ ᥘᥦᥝᥴ ᥢᥤᥒᥴ - Liaoning (遼寧)
ᥓᥥ ᥟᥪᥒᥱ ᥡᥤᥒ ᥞᥣᥭᥴ - Qinghai (青海)
ᥓᥥ ᥟᥪᥒᥱ ᥡᥣᥢ ᥡᥤ - Shaanxi (陝西) (ᥜᥣᥒᥳ ᥘᥣᥭᥰ ᥟᥩᥐᥱ ᥔᥥᥒᥴ)
ᥓᥥ ᥟᥪᥒᥱ ᥡᥣᥢ ᥖᥨᥒ - Shandong (山東)
ᥓᥥ ᥟᥪᥒᥱ ᥔᥣᥢ ᥡᥤᥰ - Shanxi (山西) (ᥜᥣᥒᥳ ᥘᥣᥭᥰ ᥟᥩᥐᥱ ᥔᥥᥒᥴ။)
ᥓᥥ ᥟᥪᥒᥱ ᥔᥪᥲ ᥡᥩᥢ - Sichuan (四川)
ᥓᥥ ᥟᥪᥒᥱ ᥗᥭᥱ ᥝᥣᥢᥱ - Taiwan (臺灣) (ᥕᥧᥱ ᥖᥤ ᥛᥫᥒᥰ ᥑᥥᥱ ᥘᥨᥒᥴ ᥔᥥᥴ ᥚᥩᥒᥰ ᥒᥛᥰ)
ᥓᥥ ᥟᥪᥒᥱ ᥕᥤᥢᥳ ᥢᥣᥢᥳ - Yunnan (雲南)
ᥓᥥ ᥟᥪᥒᥱ ᥓᥫᥴ ᥓᥦᥒ - Zhejiang (浙江)

ᥙᥫᥒ ᥟᥤᥒ

↑ The Hong Kong Dollar is used in Hong Kong and Macau while the Macanese pataca is used in Macau only.
↑ Motor vehicles and metros drive on the right in mainland China. Hong Kong and Macau use left-hand traffic except several parts of metro lines. The majority of the country's trains drive on the left.

↑ ^1.0 ^1.1 ^1.2 ^1.3 World Economic Outlook Database, October 2019. International Monetary Fund.
↑ China Economic Update, December 2019: Cyclical Risks and Structural Imperatives. World Bank. “The Gini coefficient, a measure of overall income inequality, declined to 0.462 in 2015, and has since risen to 0.467 in 2018 (Figure 27). Higher income inequality is partly driven by unequal regional income distribution. The eastern coastal regions have been the driver of China's rapid growth, due to its geographic location and the early introduction of reforms. As a result, the eastern coastal region is now home to 38 percent of the population, and its per capita GDP was 77 percent higher than that of the central, western, and northeastern regions in 2018. This gap widened further in the first three quarters of 2019. This is in part due to a disproportionate slowdown in interior provinces, which are more dependent on commodities and heavy industry. The slowdown has been negatively affected by structural shifts, especially necessary cuts in overcapacity (Figure 28).”
↑ Human Development Report 2019 (PDF) (in en). United Nations Development Programme (10 December 2019). Archived from the original on 30 April 2020။ Retrieved on 10 December 2019။

[4] The Hong Kong Dollar is used in Hong Kong and Macau while the Macanese pataca is used in Macau only.

[5] Motor vehicles and metros drive on the right in mainland China. Hong Kong and Macau use left-hand traffic except several parts of metro lines. The majority of the country's trains drive on the left.

[IMFWEOCN-1] 1.0 ^1.1 ^1.2 ^1.3 World Economic Outlook Database, October 2019. International Monetary Fund.

[GINI-2] China Economic Update, December 2019: Cyclical Risks and Structural Imperatives. World Bank. “The Gini coefficient, a measure of overall income inequality, declined to 0.462 in 2015, and has since risen to 0.467 in 2018 (Figure 27). Higher income inequality is partly driven by unequal regional income distribution. The eastern coastal regions have been the driver of China's rapid growth, due to its geographic location and the early introduction of reforms. As a result, the eastern coastal region is now home to 38 percent of the population, and its per capita GDP was 77 percent higher than that of the central, western, and northeastern regions in 2018. This gap widened further in the first three quarters of 2019. This is in part due to a disproportionate slowdown in interior provinces, which are more dependent on commodities and heavy industry. The slowdown has been negatively affected by structural shifts, especially necessary cuts in overcapacity (Figure 28).”

[UNHDR-3] Human Development Report 2019 (PDF) (in en). United Nations Development Programme (10 December 2019). Archived from the original on 30 April 2020။ Retrieved on 10 December 2019။

[1]

[2]

[3]

[lower-alpha 1]

[lower-alpha 2]