A Time to Heal Old Wounds of Racial Inequality in the World Foreign
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A Miraculous Ningguo City of China and Analysis of Influencing Factors of Competitive Advantage
www.ccsenet.org/jgg Journal of Geography and Geology Vol. 3, No. 1; September 2011 A Miraculous Ningguo City of China and Analysis of Influencing Factors of Competitive Advantage Wei Shui Department of Eco-agriculture and Regional Development Sichuan Agricultural University, Chengdu Sichuan 611130, China & School of Geography and Planning Sun Yat-Sen University, Guangzhou 510275, China Tel: 86-158-2803-3646 E-mail: [email protected] Received: March 31, 2011 Accepted: April 14, 2011 doi:10.5539/jgg.v3n1p207 Abstract Ningguo City is a remote and small county in Anhui Province, China. It has created “Ningguo Miracle” since 1990s. Its general economic capacity has been ranked #1 (the first) among all the counties or cities in Anhui Province since 2000. In order to analyze the influencing factors of competitive advantages of Ningguo City and explain “Ningguo Miracle”, this article have evaluated, analyzed and classified the general economic competitiveness of 61 counties (cities) in Anhui Province in 2004, by 14 indexes of evaluation index system. The result showed that compared with other counties (cities) in Anhui Province, Ningguo City has more advantages in competition. The competitive advantage of Ningguo City is due to the productivities, the effect of the second industry and industry, and the investment of fixed assets. Then the influencing factors of Ningguo’s competitiveness in terms of productivity were analyzed with authoritative data since 1990 and a log linear regression model was established by stepwise regression method. The results demonstrated that the key influencing factor of Ningguo City’s competitive advantage was the change of industry structure, especially the change of manufacture structure. -
Minimum Wage Standards in China August 11, 2020
Minimum Wage Standards in China August 11, 2020 Contents Heilongjiang ................................................................................................................................................. 3 Jilin ............................................................................................................................................................... 3 Liaoning ........................................................................................................................................................ 4 Inner Mongolia Autonomous Region ........................................................................................................... 7 Beijing......................................................................................................................................................... 10 Hebei ........................................................................................................................................................... 11 Henan .......................................................................................................................................................... 13 Shandong .................................................................................................................................................... 14 Shanxi ......................................................................................................................................................... 16 Shaanxi ...................................................................................................................................................... -
Congressional Record United States Th of America PROCEEDINGS and DEBATES of the 104 CONGRESS, FIRST SESSION
E PL UR UM IB N U U S Congressional Record United States th of America PROCEEDINGS AND DEBATES OF THE 104 CONGRESS, FIRST SESSION Vol. 141 WASHINGTON, THURSDAY, JULY 20, 1995 No. 118 House of Representatives The House met at 10 a.m. and was last day's proceedings and announces tions in need of its support. The con- called to order by the Speaker pro tem- to the House his approval thereof. gregation generously provides to these pore [Mr. EMERSON]. Pursuant to clause 1, rule I, the Jour- groups whatever it can. Reverend f nal stands approved. Hobbs and his congregation help to f bridge a critical gap to those who do DESIGNATION OF THE SPEAKER not qualify for State and Federal aid, PRO TEMPORE PLEDGE OF ALLEGIANCE and yet still require assistance. The SPEAKER pro tempore laid be- The SPEAKER. Will the gentleman I salute the generous efforts of Rev- fore the House the following commu- from Kansas [Mr. TIAHRT] come for- erend Hobbs and Hamden's Spring Glen nication from the Speaker: ward and lead the House in the Pledge Church for their selfless service to the of Allegiance. community. I thank them for their WASHINGTON, DC, Mr. TIAHRT led the Pledge of Alle- July 20, 1995. continuing commitment to these ongo- I hereby designate the Honorable BILL EM- giance as follows: ing efforts. ERSON to act as Speaker pro tempore on this I pledge allegiance to the Flag of the It is our distinct pleasure to have the day. United States of America, and to the Repub- Reverend Hobbs with us today, and we NEWT GINGRICH, lic for which it stands, one nation under God, indivisible, with liberty and justice for all. -
Huizhou's Roots in Trade Still Echo Today
Xxxxx April 1X,11, 2017 | PAGE S1-4 CHINA DAILY chinadaily.COM.CN Hefei science center to pursue technological specialization Anhui in the eyes of foreigners China Daily reporter Zhuan Ti interviewed international scholars and students at By LI YOU universities in Anhui. They expressed their feelings toward the province. [email protected] Hefei, the capital city of Anhui province, Why Anhui? I tell I am currently launched a major project on Feb 27 to con- my friends “if studying in the struct a comprehensive national science cen- Urumqi Beijing you want to see Hefei University ter by the year 2020. the real China, of Technology It will be the second comprehensive nation- come to visit and this is my al science center in China, following Shang- me in Hefei”! seventh year hai’s Zhangjiang Comprehensive National Delingha Ji'nan While Shanghai in China. In the Science Center, and also the first national is glamorous past couple of Xiuning, once one of the major bases for merchants of Huizhou, is now seeing a revival of commercial innovation platform in the central and west- and Beijing is years, I have prosperity with better transport links. ern regions of China. Ngari stately, Anhui witnessed the The signature Welcoming-Guests Pine in the Huangshan Mountains. PHOTOS PROVIDED TO CHINA DaILY The science center will focus on research Lijiang Hefei is authentic — real people living real, quick growth and development of Hefei. AN OPEN CHINA: SPLENDID ANHUI of information technology, energy, health and Shanghai hard-working lives in an environment of I feel very comfortable and at home the environment, and will seek breakthroughs enthusiasm for change and innovation. -
Clinical Characteristics and Outcomes of Hospitalised Patients with COVID-19 Treated in Hubei
Early View Original article Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicenter) and outside Hubei (non- epicenter): A Nationwide Analysis of China Wen-hua Liang, Wei-jie Guan, Cai-chen Li, Yi-min Li, Heng-rui Liang, Yi Zhao, Xiao-qing Liu, Ling Sang, Ru-chong Chen, Chun-li Tang, Tao Wang, Wei Wang, Qi-hua He, Zi-sheng Chen, Sook-San Wong, Mark Zanin, Jun Liu, Xin Xu, Jun Huang, Jian-fu Li, Li-min Ou, Bo Cheng, Shan Xiong, Zhan- hong Xie, Zheng-yi Ni, Yu Hu, Lei Liu, Hong Shan, Chun-liang Lei, Yi-xiang Peng, Li Wei, Yong Liu, Ya-hua Hu, Peng Peng, Jian-ming Wang, Ji-yang Liu, Zhong Chen, Gang Li, Zhi-jian Zheng, Shao-qin Qiu, Jie Luo, Chang-jiang Ye, Shao-yong Zhu, Lin-ling Cheng, Feng Ye, Shi-yue Li, Jin-ping Zheng, Nuo-fu Zhang, Nan-shan Zhong, Jian-xing He Please cite this article as: Liang W-hua, Guan W-jie, Li C-chen, et al. Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicenter) and outside Hubei (non-epicenter): A Nationwide Analysis of China. Eur Respir J 2020; in press (https://doi.org/10.1183/13993003.00562-2020). This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. -
Utilization of Crop Straw Resources in Anhui
1302 Bulgarian Journal of Agricultural Science, 20 (No 6) 2014, 1302-1310 Agricultural Academy UTILIZATION OF CROP STRAW RESOURCES IN ANHUI PROVINCE, EASTERN CHINA YIRU YANG1,3, XINGXIANG WANG1, TAOLIN ZHANG1,3 and DECHENG LI2* 1 Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, P. R. China 2 State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, P. R. China 3 University of Chinese Academy of Sciences, Beijing 100049, P. R. China Abstract YIRU YANG, XINGXIANG WANG, TAOLIN ZHANG and DECHENG LI, 2014. Utilization of crop straw resources in Anhui Province, Eastern China. Bulg. J. Agric. Sci., 20: 1302-1310 Returning straw to fields is one of the most effective ways of maintaining and improving soil fertility. However, straw burning is a recurring phenomenon in China. To better understand the current situation facing the utilization of straw resourc- es in Anhui Province, a total of 731 typical fields and farmers were surveyed on a provincial scale in 2011 along a national highway, provincial highway and county road. Moreover, a total of 344 fields and farmers were surveyed on a county scale in three typical counties, i.e., Mengcheng County, Dingyuan County and Xuanzhou District. The average rates of straw return- ing were generally low in Anhui Province, with 30.2% for single-middle-season rice, 16.1% for early rice, 14.3% for wheat, 2.9% for rape, 1.8% for late rice and 1.8% for maize, respectively. The average return rate of wheat in the three typical counties was 13.2%, lower than the rates of the entire province; however, the return rates of other crops in the counties were all higher than those of the entire province. -
Working Paper Series No. 2017-11
Working Paper Series No. 2017-11 New Evidence on the Impact of Sustained Exposure to Air Pollution on Life Expectancy from China’s Huai Avraham Ebenstein, Maoyong Fan, Michael Greenstone, Guojun He, and Maigeng Zhou September 2017 JEL Codes: I15, I18, Q53, Q58 Becker Friedman Institute for Research in Economics Contact: 773.702.5599 [email protected] bfi.uchicago.edu New Evidence on the Impact of Sustained Exposure to Air Pollution on Life Expectancy from China’s Huai River Policy Avraham Ebenstein, Maoyong Fan, Michael Greenstone , Guojun He, and Maigeng Zhou* September 2017 Abstract 3 This paper finds that a 10 µg/m increase in airborne particulate matter (PM10) reduces life expectancy by 0.64 years (95% CI: 0.21, 1.07). This estimate is derived from quasi-experimental variation in PM10 generated by China’s Huai River Policy, which provides free or heavily subsidized coal for indoor heating during the winter to cities north of the Huai River but not to the south. The findings are derived from a regression discontinuity design based on distance from the Huai River, and are robust to using parametric and non-parametric estimation methods, different kernel types and bandwidth sizes, and adjustment for a rich set of demographic and behavioral covariates. Furthermore, the shorter lifespans are almost entirely due to elevated rates of cardiorespiratory mortality, suggesting that PM10 is the causal factor. The estimates imply that bringing all of China into compliance with its Class I standards for PM10 would save 3.7 billion life years. * Ebenstein: Department of Environmental Economics and Management, Hebrew University of Jerusalem, [email protected]. -
Cardiovascular Mortality Associated with Low and High Temperatures: Determinants of Inter-Region Vulnerability in China
Supplementary Information Cardiovascular Mortality Associated with Low and High Temperatures: Determinants of Inter-Region Vulnerability in China Table S1. Reference values of low temperature and high temperature. Reference Reference Reference Reference Region Value of Low Value of High Region Value of Low Value of High Temperature Temperature Temperature Temperature Chaohu City 2.41 28.27 Binyang County 11.13 29.17 Yushan District 2.36 28.28 Liubei District 9.69 30.25 Daguan District 3.39 29.16 Xiufeng District 7.89 29.44 Tianchang City 1.80 27.79 Hepu County 12.69 29.33 Mengcheng County 1.00 27.32 Lingyun County 10.82 27.73 Luochengyaolaozu Jing County 3.15 28.48 9.32 29.04 Autonomous County Tianxin District 4.91 30.23 Meilan District 16.56 28.88 Liuyang City 4.64 29.38 Ding’an County 17.40 28.91 Pingjiang County 4.45 29.01 Chengguan District 0.20 17.57 Mozhugongka Wuling District 4.94 29.30 −1.34 15.56 County Suxian District 5.56 30.42 Naidong County 0.42 16.57 Hongjiang City 4.82 27.93 Jiangzi County −2.89 13.48 Fenghuang County 5.30 28.21 Milin County 1.12 16.49 Table S2. Splits of the factors for percent changes in cardiovascular mortality at low (PCL) and high (PCH) temperatures. Discretization Discretization Quantitative factors Intervals for PCL Intervals for PCH number of hospital [4.95, 21.11], (21.11, 109.38] [4.95, 30.71], (30.71, 109.38] beds per 10,000 people per capita years of education [5.18, 5.25], (5.25, 12.31] [5.18,7.00], (7.00, 12.31] %uneducated [0.49, 1.07], (1.07, 31.93] [0.49, 29.84], (29.84, 31.93] %female [46.66, -
Time and Space Model of Urban Pollution Migration: Economy-Energy-Environment Nexus Network ⇑ Gengyuan Liu A,B, , Zhifeng Yang A,B, Brian D
Applied Energy xxx (2016) xxx–xxx Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy Time and space model of urban pollution migration: Economy-energy-environment nexus network ⇑ Gengyuan Liu a,b, , Zhifeng Yang a,b, Brian D. Fath c,d, Lei Shi e, Sergio Ulgiati a,b,f a State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China b Beijing Engineering Research Center for Watershed Environmental Restoration & Integrated Ecological Regulation, Beijing 100875, China c Biology Department, Towson University, Towson, MD, USA d Dynamic Systems, IIASA, Laxenburg, Austria e State Environmental Protection Key Laboratory of Eco-industry, School of Environment, Tsinghua University, Beijing 100084, China f Department of Sciences and Technologies, Parthenope University of Naples, Centro Direzionale—Isola C4, 80143 Naples, Italy highlights 3E Networks are constructed to untangling the causal web linking urbanization and human health. Appearance of a cancer village is result of spatial-temporal distribution of human-land interaction. Incidences are not just because of surrounding cities also due to far-away city through network. Mitigation of the adverse effects of urbanization need to meet the people’s health care demands. article info abstract Article history: In recent years, news of ‘‘cancer villages” in the Huaihe River Basin filled front and back pages of news- Received 7 December 2015 papers and generated elevated concern among readers. This study aims to understand the relationship Received in revised form 28 May 2016 between the ‘‘cancer villages” and the ‘‘large cities” around them. A gravity model is constructed to ana- Accepted 29 June 2016 lyze the correlation between ‘‘big cities” and ‘‘cancer villages” in terms of indices involving economic con- Available online xxxx nections and pollution frequency. -
Remote Sensing ISSN 2072-4292 Article Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China
Remote Sens. 2013, 5, 3057-3081; doi:10.3390/rs5063057 OPEN ACCESS Remote Sensing ISSN 2072-4292 www.mdpi.com/journal/remotesensing Article Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China Xi Li 1,*, Huimin Xu 2, Xiaoling Chen 1 and Chang Li 3 1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China; E-Mail: [email protected] 2 School of Economics, Zhongnan University of Economics and Law, Wuhan 430060, China; E-Mail: [email protected] 3 College of Urban and Environmental Science, Central China Normal University, Wuhan 430079, China; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +86-27-6877-8141. Received: 18 April 2013; in revised form: 7 June 2013 / Accepted: 13 June 2013 / Published: 19 June 2013 Abstract: Historically, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) was the unique satellite sensor used to collect the nighttime light, which is an efficient means to map the global economic activities. Since it was launched in October 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) Satellite has become a new satellite used to monitor nighttime light. This study performed the first evaluation on the NPP-VIIRS nighttime light imagery in modeling economy, analyzing 31 provincial regions and 393 county regions in China. For each region, the total nighttime light (TNL) and gross regional product (GRP) around the year of 2010 were derived, and a linear regression model was applied on the data. -
Advancing the Modernization of Agriculture and Rural Areas
劥䫣デꅷ欽梠⥂紺䓎⿺屘㟯⽪ⵖ ࣾᆂ䨣㵹͇ۉ͚ప 2017 ᎡᏓ្ॷ AGRICULTURAL DEVELOPMENT BANK OF CHINA DEVELOPMENT AGRICULTURAL ⚥㕂ⱚ⚌〄㾝Ꜿ遤 "(3*$6-563"-%&7&-01.&/5#"/,0'$)*/" 㖑㖧⻌❩䋑銯㙹⼓剢㗐⻌遳歌〿 歏霢⠛溫 ч䉐Ш្ॷ 緸㖧XXXBECDDPNDO "EE":VFUBOCFJKJF4USFFU 9JDIFOH%JTUSJDU #FJKJOH $IJOB Social Responsibility Report 5FM'BY IUUQXXXBECDDPNDO ᡀಣ CONTENTS ᐧᑂ䶳 ᑧᵦ䨥偯ڇ㦐θ䪬㜡䓋 12 ̀䷅喟 02 ڡ㵹䪬㜡䓋 16 ߎΎ᱾ᡜ 04 ڕ䩛㐖᩵ 20 Ԋ䯉పუ㇛丌Ⴖڠ 06 22 ߎ㙞䉘ᩨಇ ᱾⣝Аࡃۉ͇ۉλЙ 27 ᣕ䔈ڠ 10 36 ߎࡧഌࡼ䄰ࣾᆂ 42जᠮ㐚ࣾᆂധ 56 䭱ᒂ 44 ䷻䮖䭟ᣔ 56 䶦হ㢐㾶 䲏䷻䮖ノ⤳ 58 ្ॷ䄡ᬻڕᣕ䔈 44 ᣔव㻱ᐧ䃫ڲ 45 էݥウ䯳 46 էݥࣾ㵹ᗲۢ 46 Ѕᗲۢپէݥ 46 ࣯̻էݥጯ౧ᐧ䃫 47 50 ᝤߎ 50 ᑧࡃឭᩜᦾ 50 ᮛࣷ䛾㲺ⴒ䃳 51 ⌞ࡃϑ≮व҉ 51 অጒࣾᆂ 51 ᐧ䃫ϧ䭌к 52 ࡴࣾᆂ㘪߈ 53 ⣝㕹͇Ꭵ⺼ᙌ 㦐θ䪬㜡䓋 Ꭱ喑᭜Ą̶ρą㻱ܿ⮱䛺㺮Ꭱ喑 ̭Ꭱ喑᭜ӈ㐆Ӕ㐀Ჱᕔᩦ䲖⮱⌞ࡃᎡȡ̭Ꭱ喑᭜ӈ ڒ⌞ࣾ㵹ۉ䲏㥪ڕ⮱Ί๔⺋喑ڇ䉜ᒨڒ⌞ࣾ㵹ۉ ప䛾㲺ڕప䛾㲺ጒ҉ч䃛Ƞ͚๛㏼≻ጒ҉ч䃛Ƞڕ ᱾ጒۉ᱾ጒ҉ч䃛ぶጒ҉䘕㒟喑ಇᠮ⽠͚͚๛ۉ͚๛ ߈Ⅿ䔈ጒ҉ᕨڕⅯ䔈ጒ҉ᕨധ䄰喑㥪ࣾᆂ⤳ᔢȡ ӈ͇ۉߎۉӈ㐆Ӕ㐀Ჱᕔᩦ䲖喑⼜Ხᩜᠮ͇ۉߎ ᱾⣝Аۉ᱾⣝Аࡃ喑̺ࡴߎపუᝅ⪒হ͇ۉ͇ ąࣾۉąࣾᆂ⮱㘪߈喑䔈̭ₒࣾᡒᩬゃᕔĄ̶ۉĄ̶ ͇ۉࣾᆂजᠮ㐚Ƞ⊵䮑䉘ఝȠ⣜ධ䛾㲺ౕ͇ۉ䛾㲺ౕ ⩌ᔮԊ៑ぶ䶳ഌ⮱䛺㺮҉⩕ȡ⩌ᔮԊ៑ぶ ᐧᑂ䶳ᑧڇᐧᑂ䶳ᑧᵦ䨥偯ڇ ᄦ䛾ڇᅭ倅Ꮣಇᠮڕᄦ䛾㲺⮱䶳ᄩ喑ϻᝅ⪒হڇಇᠮ 䲏ϻڕȡ͒Ⴕᩬ⇨㏗ᒸহ⠍ៀڇ⇨ڇ䲏ϻ͒ノڕៀ⠍ 㵹অጒ䔈̭ₒᴾ⿸Ąఈᩬ⇨㻱ⴖڕᩬ⇨㻱ⴖ喑Ӱ䔈 ᘼ䃳ą喑ᑧĄఈ͗㜗Ԏą喑ևݝĄఈ͗ᘼ䃳ą͗ ࣾ㵹㥪͗ϻąۉϻą喑ᣕߕ͚๛۠ゃ䘕㒟ౕ͗ ➏ప҉ͧౝ⩌ᵦȡ្ۉౝ⩌ᵦȡ➏䃝ჄᬕҬপ喑ិᩜ ሴ倅⮱⤳ᘠহθ͇喑⼜Ხែ䏘ݝߎĄ̶ሴ倅⮱⤳ᘠ ą⮱ь๔ۉą⮱ь๔䌢͚ࣨȡۉ Ύ᱾̀∕͇ͨᡜڡᡜ͇ͨ⧵̀ ♓ࣾ㵹㖇ۉą䛺◦䶳ഌȠ㪱ᑞ⣜㞯ۉࣾ㵹㖇♓Ą̶ۉ হ䉘ఝౝܧ⾮喑וহ䉘ఝౝࡧ喑๔߈ᩜᠮ㇛᷶⇦ᩣ ࣾᆂ䨣㵹͇ۉ͚ప ч䉐Ш្ॷ 40$*"-3&410/4*#*-*5:3&1035 䉱⎽ᐭ̻ࣾԊ៑ぶϔ৮喑ᣏ㉏ᣕᎬឣ䉘 ۉ͇ۉ߈ߎ㙞䉘ᩨಇ喑व㻱ᩜᠮڕ۳ 䒙䉤ぶᐼ喑̺ࡴߎۉАࡃ喑 䓴ᶒȠᩜ⣝͇ۉ᱾ധ䃫ᐧ䃫喑݈ᩜᠮ Ꭱ㉜ᩫ䉤 Ҁ㏼≻⮱䉕䛼হ᩵⢴ȡウᐧ䯱Ⴖܳ㵹喑ڕ䲏ᐧᄼᏤчȡڕߖ߈۠㘉 Ϭٰ喑Ꭱ᱘䉤҆䷊ ̴Ϭ ๔߈ᩜᠮ䯱Ⴖࡧᐧ䃫ȡड़ߕᵥᓰ㈨㐌̴ Ⴧ⽠ڕ Ϭٰȡ็ᣗᎣͫウ ᐧ䃫喑ߍᑧᢛ⇨⤳喑Ԏᖜ㈨㐌Ⴖ 喑䒰Ꭱ݊ߍٰ 䓽㵹ȡ ͇ۉ≯䉱䛾喑ᑂᄩч䉱䛾ࣺਧఋۉᣗᩜ Ꭱ㉜䃎ࣾէウ䉱 ̴Ϭٰ喑ڕ᱾喑ۉ ䷊Ꭱ᱘էݥ҆䷊ ̴ Ϭ ٰ喑 ႅ҆ ⼸Ϭٰȡ ̺ᔅ݊ᓰᐭड़ᒮ̴ 䲏䉜ᒨΊ๔⺋⮱ᐭᅭڕᎡ喑᭜ ࣾ㵹倅䉕䛼ࣾᆂ⮱䊤ₒᎡȡۉᎡ喑Ό᭜ ധ㜡߈जᠮ㐚 ⮱Ί๔⺋喑ᠶ⚔ڇ䲏䉜ᒨڕࣾ㵹ᄳۉ ప䛾㲺ጒ҉ч䃛Ƞ͚๛㏼≻ጒ҉ч䃛Ƞڕ ᣕڒ⌞⮱Ѻ㒛喑ܧ⾮ᄳ䭟ᣔ䷻䮖ᥳౕᰡߍ ڇ᱾ጒ҉ч䃛⮱䘕㒟喑ಇᠮহႹۉ䲏䷻䮖ノ⤳喑ᄦ䛺◦ࡧഌȠ䛺◦ϔ৮ ͚๛ڕ䔈 -
Minimum Wage Standards in China June 28, 2018
Minimum Wage Standards in China June 28, 2018 Contents Heilongjiang .................................................................................................................................................. 3 Jilin ................................................................................................................................................................ 3 Liaoning ........................................................................................................................................................ 4 Inner Mongolia Autonomous Region ........................................................................................................... 7 Beijing ......................................................................................................................................................... 10 Hebei ........................................................................................................................................................... 11 Henan .......................................................................................................................................................... 13 Shandong .................................................................................................................................................... 14 Shanxi ......................................................................................................................................................... 16 Shaanxi .......................................................................................................................................................