全球主要經(jīng)濟(jì)體表現(xiàn)及經(jīng)濟(jì)復(fù)蘇格局展望

1、各國(guó) GDP 總體損失情況幾乎無(wú)一例外與應(yīng)對(duì)疫情措施的嚴(yán)格程度密切相關(guān)除個(gè)別國(guó)家外，疫情危機(jī)幾乎是造成全球大多數(shù)經(jīng)濟(jì)體 2020 年 GDP 嚴(yán)重 損失的最主要單一因素。這一因素對(duì)各國(guó)的經(jīng)濟(jì)沖擊，主要源于防控疫情的 限制性隔離及封鎖措施，對(duì)幾乎所有國(guó)家的經(jīng)濟(jì)部門均產(chǎn)生了顯著負(fù)面影響。我們采用了全球 27 個(gè)經(jīng)濟(jì)體作為研究樣本。樣本涵蓋了全球十大經(jīng)濟(jì)體、歐盟十大經(jīng)濟(jì)體、金磚國(guó)家、亞洲十大經(jīng)濟(jì)體以及部分具有代表性的獨(dú)聯(lián)體國(guó)家。樣本國(guó)家覆蓋了全球GDP 的 81%以及全球人口的 62%左右。本文中，GDP 損失指的是IMF預(yù)測(cè)的GDP 增速與 2020 年實(shí)際增長(zhǎng)率之間的差值。 大多數(shù)國(guó)家采取的主要

2、防疫措施是對(duì)人口實(shí)施隔離和交通限制，其導(dǎo)致的消費(fèi)和供給急劇減弱成為疫情沖擊經(jīng)濟(jì)的主要渠道。我們注意到，除必需商品和服務(wù)外，市場(chǎng)對(duì)其他消費(fèi)品和服務(wù)的需求下滑導(dǎo)致生產(chǎn)和服務(wù)供應(yīng)商產(chǎn)出下降，中間產(chǎn)品需求亦明顯收縮。0土耳其越南中國(guó)-5瑞士哈薩克斯坦-10英國(guó)西班牙印度-15菲律賓-20404550556065702020年隔離防控措施嚴(yán)格程度均值GDP 損失，%圖 1 2020 年抗疫措施的平均嚴(yán)格程度與絕大多數(shù)國(guó)家 GDP 損失具有明顯關(guān)聯(lián)Spain資料來(lái)源：各國(guó)統(tǒng)計(jì)當(dāng)局，東方金誠(chéng)和ACRA 計(jì)算除個(gè)別國(guó)家外，大多數(shù)國(guó)家的經(jīng)濟(jì)損失或多或少與強(qiáng)制隔離措施的嚴(yán)格程度保持一致(圖 1)。數(shù)據(jù)顯示，盡管隔

3、離措施較為嚴(yán)格，但中國(guó)、土耳其、越南和哈薩克斯坦這四個(gè)國(guó)家遭受的經(jīng)濟(jì)損失要比其他國(guó)家小得多，而瑞士盡管防疫限制要求相對(duì)寬松，經(jīng)濟(jì)萎縮程度卻明顯偏離均值。疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 根據(jù)樣本各國(guó)官方公布的 2020 年實(shí)際 GDP 增速數(shù)據(jù)（個(gè)別暫未公布全年數(shù)據(jù)的國(guó)家，采用估算數(shù)值）與采取防疫隔離措施前預(yù)測(cè)經(jīng)濟(jì)增速之前的差異，我們可以估算 2020 年由于新冠疫情相關(guān)限制措施造成的GDP 損失。值得一提的是，上述四個(gè) GDP 損失低于均值的國(guó)家中，越南(2.9%)、中國(guó) (2.3%)和土耳其(1.8%)三個(gè)國(guó)家盡管 2020 年全年

4、經(jīng)濟(jì)增速低于年初預(yù)期，但仍實(shí)現(xiàn)了正增長(zhǎng)，而哈薩克斯坦國(guó)內(nèi)生產(chǎn)總值則下降 2.6%。總體來(lái)看，雖然這些國(guó)家的經(jīng)濟(jì)快速發(fā)展步伐去年有所收斂，但經(jīng)濟(jì)損失仍明顯低于其他國(guó)家。中國(guó)經(jīng)濟(jì)在 2020 年經(jīng)歷了前所未有的挑戰(zhàn)后仍實(shí)現(xiàn)了正增長(zhǎng)，主要得益于其對(duì)新冠肺炎擴(kuò)散的高效遏制、其他經(jīng)濟(jì)體對(duì)中國(guó)特定商品的外部需求、針對(duì)基礎(chǔ)設(shè)施投資的財(cái)政刺激，以及高度發(fā)展的電子商務(wù)市場(chǎng)；對(duì)土耳其而言，相對(duì)廉價(jià)的低利率信貸被大量注入經(jīng)濟(jì)，在一定程度上掩蓋了防疫隔離措施的負(fù)面沖擊；就越南而言，有效遏制疫情蔓延、制造業(yè)的擴(kuò)張，以及與歐盟簽署的自由貿(mào)易協(xié)定，均對(duì)其維持國(guó)內(nèi)生產(chǎn)總值增長(zhǎng)發(fā)揮了重要作用；而哈薩克斯坦經(jīng)濟(jì)損失較小的原因主要

5、是制造業(yè)的增長(zhǎng)，特別是新生產(chǎn)設(shè)施的投入(如汽車部門)，以及政府對(duì)建筑業(yè)的支持。與樣本中的其他國(guó)家相比，瑞士政府實(shí)施的疫情封鎖限制措施并不嚴(yán)格，其因抗疫而造成的損失高于預(yù)期，主要與其易受外部沖擊的小型開放經(jīng)濟(jì)體 特征有關(guān)。不過(guò)，單就GDP 損失而言，瑞士與作為其主要貿(mào)易伙伴的其他歐洲 國(guó)家相比，國(guó)內(nèi)生產(chǎn)總值下滑并不明顯。從估算結(jié)果來(lái)看，2020 年，疫情給主要經(jīng)濟(jì)體平均帶來(lái) 7.1 個(gè)百分點(diǎn)的 GDP 損失。圖 2 數(shù)據(jù)顯示，各國(guó)經(jīng)濟(jì)損失幅度存在較大差異部分國(guó)家成功實(shí)現(xiàn)了GDP 正增長(zhǎng)，而部分經(jīng)濟(jì)體損失程度顯著高于均值。樣本國(guó)家中，經(jīng)濟(jì)損失幅度最大的國(guó)家是印度(-14.8%)、菲律賓(-15.7

6、%)、西班牙(-12.7%)和英國(guó)(-11.5%)。與此同時(shí)，這些國(guó)家抗疫限制措施的嚴(yán)格程度也在最高之列(圖 1)。疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 圖 2 各國(guó) 2020 年經(jīng)濟(jì)損失程度存在較大差異10864GDP損失實(shí)際增速疫情前IMF預(yù)測(cè)值20-2-4-6-8-10-12-14-16土耳其白俄羅斯中國(guó)越南 韓國(guó) 瑞典 瑞士 俄羅斯日本 荷蘭 美國(guó) 波蘭 德國(guó) 加拿大巴西哈薩克斯坦新加坡印度尼西亞南非澳大利亞意大利 法國(guó)馬來(lái)西亞英國(guó)西班牙印度尼西亞菲律賓-18資料來(lái)源：各國(guó)統(tǒng)計(jì)當(dāng)局，IMF，東方金誠(chéng)和ACRA 計(jì)算從圖2 可以看出，

7、主要經(jīng)濟(jì)體中，早期受疫情沖擊的西歐國(guó)家由于病毒持續(xù)蔓延傳播，全年大部分時(shí)間將處于疫情負(fù)面影響之中，因此GDP 損失較為明顯。這些國(guó)家中，除瑞典在 2020 年上半年一直沒有采取封閉隔離等防疫措施外，其余大部分采取了嚴(yán)格的防疫隔離舉措。實(shí)際GDP 增長(zhǎng)數(shù)據(jù)顯示，東亞國(guó)家總體上在疫情初期防控方面成果較為顯著。東歐和獨(dú)聯(lián)體國(guó)家由于防控疫情方面的中等表現(xiàn)以及與西歐國(guó)家的經(jīng)濟(jì)結(jié)構(gòu)性差異西歐國(guó)家服務(wù)業(yè)占比更高，全年GDP 增長(zhǎng)表現(xiàn)大多處于所有研究對(duì)象的中部區(qū)間。就經(jīng)濟(jì)活動(dòng)而言，與 2019 年相比，2020 年總體上受到負(fù)面沖擊最大的行業(yè)(圖 3)主要是交通運(yùn)輸業(yè)(-10.7%)、建筑業(yè)(-7.4%)、采

8、礦業(yè)(-7.4%)和服務(wù)業(yè)(-7.7%)。制造業(yè)和零售業(yè)盡管也受到了防疫限制措施的沖擊，不過(guò) 2020 年下半年，這兩大行業(yè)在各國(guó)均有不同程度反彈。疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 此外，由于歐佩克+相關(guān)國(guó)家限產(chǎn)協(xié)議的達(dá)成，自 2020 年 5 月開啟的減產(chǎn)對(duì)石油和天然氣主要出口國(guó)造成一定影響，在其礦業(yè)、石油產(chǎn)品制造業(yè)以及批發(fā)交易額等數(shù)據(jù)中有明顯體現(xiàn)。圖 3 用箱形圖展示了不同行業(yè)的生產(chǎn)指數(shù)分布情況。十字叉表示均值，矩形內(nèi)的橫線表示中位數(shù)，矩形表示分布中的上、下四分位數(shù)。每個(gè)圓圈代表一個(gè)國(guó)家。圖 3 抗疫隔離措施影響下，交通運(yùn)輸行業(yè)總體

9、上受到的負(fù)面沖擊最為顯著季調(diào)生產(chǎn)指數(shù)，2020 年與 2019 年均值比較，%采礦業(yè)制造業(yè)公用事業(yè)建筑業(yè)零售業(yè)交通運(yùn)輸業(yè) 其他服務(wù)業(yè)資料來(lái)源：各國(guó)統(tǒng)計(jì)當(dāng)局，IMF，東方金誠(chéng)和ACRA 計(jì)算零售業(yè)表現(xiàn)與隔離措施的嚴(yán)格程度具有一定關(guān)聯(lián)。2020 年第一波疫情期 間，部分國(guó)家最嚴(yán)格防疫措施的執(zhí)行一度導(dǎo)致了約 50%的零售業(yè)交易萎縮，而 采取中等強(qiáng)度隔離措施的國(guó)家中，部分將零售交易下滑程度控制在了個(gè)位數(shù)，甚至個(gè)別國(guó)家未現(xiàn)明顯收縮。而在第二波疫情沖擊下，零售業(yè)的衰退幅度未 有第一波期間顯著。在其他行業(yè)中，制造業(yè)也是較易受到影響的行業(yè)之一。其中，受疫情沖擊影響較小的國(guó)家大多擁有特殊的制造業(yè)特征（例如新加坡

10、），主要領(lǐng)域（例如生物醫(yī)藥和制藥）表現(xiàn)幾乎不受新冠疫情的影響。事實(shí)上，盡管 2020年各國(guó)制造業(yè)的平均表現(xiàn)并不令人樂(lè)觀，但在第二波疫情沖擊期間，多數(shù)國(guó)家已在不同程度上恢復(fù)了制造業(yè)活動(dòng)。統(tǒng)計(jì)數(shù)據(jù)顯示，樣本中受防疫隔離措施影響較大潛在經(jīng)濟(jì)損失高于平均水平的國(guó)家主要具有以下四方面結(jié)構(gòu)性特征：疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 對(duì)外來(lái)旅游依賴度較高，在國(guó)際收支中通常表現(xiàn)為具有較大外部旅游資金凈流入的國(guó)家（例如西班牙）；醫(yī)療救治能力不足或醫(yī)療服務(wù)資源分配不均的國(guó)家，通常死亡率 更高，需要采取更嚴(yán)格和趨于長(zhǎng)期的隔離舉措（例如英國(guó)、巴西、意大利）；制造

11、業(yè)中投資性商品生產(chǎn)更多的國(guó)家（例如德國(guó)、瑞士）；零售貿(mào)易和金融服務(wù)的線上滲透及運(yùn)用較低的國(guó)家。部分樣本國(guó)家得益于成功的應(yīng)對(duì)政策、特殊的經(jīng)濟(jì)產(chǎn)業(yè)結(jié)構(gòu)和出口結(jié)構(gòu)，抑或較為寬松的政府抗疫管控措施，這些因素對(duì)沖了部分潛在經(jīng)濟(jì)損失。新冠疫情關(guān)鍵節(jié)點(diǎn)回顧與防疫應(yīng)對(duì)措施分析2020 年 3 月 11 日，世界衛(wèi)生組織宣布新冠肺炎疫情具備“大流行”特征。在隨后的十天里，諸多國(guó)家報(bào)告了感染病例，多數(shù)國(guó)家積極采取了限制性措 施以遏制病毒傳播。至 3 月 20 日，超過(guò) 100 個(gè)國(guó)家的限制措施嚴(yán)格程度達(dá)到了牛津大學(xué)新冠疫情政府響應(yīng)追蹤系統(tǒng)（ Oxford COVID-19 Government Response

12、Tracker）中的 50 分以上。也就是說(shuō)，大量學(xué)校關(guān)閉，公共集會(huì)、 旅行和交通活動(dòng)受到嚴(yán)格限制。4 月中旬，該指數(shù)均值達(dá)到疫情發(fā)生以來(lái)的階 段性高點(diǎn)攀升至 80 附近（圖 4）。10080隔離措施嚴(yán)格程度指數(shù)三月六月202160均值40200五月四月12010000000000圖 4 大多數(shù)國(guó)家在 2020 年 4 月采取了最嚴(yán)格的隔離措施資料來(lái)源：牛津大學(xué)新冠疫情政府響應(yīng)追蹤系統(tǒng)，東方金誠(chéng)和 ACRA 計(jì)算疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 伴隨疫情趨穩(wěn)，6 月下旬后，越來(lái)越多國(guó)家開始明顯放開限制措施。不過(guò)，隨著 2020 年秋季之

13、后尤其是 10 月之后第二波疫情的出現(xiàn)，大多數(shù)國(guó)家開始 恢復(fù)限制性措施。德國(guó)、英國(guó)、荷蘭等歐洲國(guó)家，更是由于變異毒株引發(fā)的 新一輪疫情恐慌和擔(dān)憂，自 2020 年底以來(lái)顯著提高了與防疫有關(guān)的限制措施 嚴(yán)格程度。疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 疫苗接種進(jìn)程可能導(dǎo)致各國(guó) 2021 年經(jīng)濟(jì)復(fù)蘇表現(xiàn)有所差異2020 年秋季第二波疫情爆發(fā)期間，感染病例數(shù)量曾急劇增加。在研究樣本國(guó)家中，受影響最大的國(guó)家包括瑞士、英國(guó)，以及西班牙（圖 5）。盡管與 2020 年上半年相比，第二波疫情期間防控措施的嚴(yán)格程度有所降低，對(duì)經(jīng)濟(jì)的負(fù)面沖擊有所減輕，但與此同

14、時(shí)，抑制病毒傳播的條件也在放松。2021 年 2 月以來(lái)，多數(shù)國(guó)家新增感染病例數(shù)量大幅減少，由此我們推斷第二波疫情已接近尾聲。不過(guò)，由于諸多國(guó)家疫苗接種率依然較低，全球范圍內(nèi)的群體免疫仍困難重重，加之病毒變異帶來(lái)的影響，歐洲、印度等經(jīng)濟(jì)體正有第三波疫情趨勢(shì)，未來(lái)全球范圍內(nèi)疫情演變?nèi)源嬖谧償?shù)。盡管各國(guó)之間的新冠疫情統(tǒng)計(jì)數(shù)據(jù)存在差異，尤其是各國(guó)病例檢測(cè)對(duì)人口的覆蓋范圍不 同，因此進(jìn)行跨國(guó)比較實(shí)際上存在一定困難，但我們認(rèn)為，各國(guó)確診病例數(shù)量與病毒傳播情況具有一致性。圖 5 新增病例數(shù)據(jù)顯示，第二波疫情嚴(yán)重程度遠(yuǎn)超預(yù)想每百萬(wàn)人每日新增病例數(shù)量，七天移動(dòng)平均瑞士英國(guó)西班牙 波蘭美國(guó)10009008007

15、006005004003002001000 資料來(lái)源：牛津大學(xué)“用數(shù)據(jù)看世界”，東方金誠(chéng)和 ACRA 計(jì)算按目前全球新冠疫情及疫苗接種情況而言，討論終結(jié)疫情為時(shí)尚早。截至 2021 年 4 月 10 日數(shù)據(jù)顯示，以色列和阿聯(lián)酋的新冠疫苗接種比率處于世界領(lǐng)先地位，分別達(dá)到每百人 118 劑和 91 劑。研究樣本國(guó)家中，截至 2021 年 4 月 10 日數(shù)據(jù)顯示，英國(guó)和美國(guó)接種比率與全球領(lǐng)先者的差距較小，分別是每百人 58 劑和 55 劑(圖 6)。不過(guò)，全球平均接種比率僅為每百人 10 劑，遠(yuǎn)未達(dá)到解除疫情封鎖措施所需的接種水平。領(lǐng)先國(guó)家與平均接種率之間的差距，主要是由于疫苗接種進(jìn)度不同，而這

16、取決于民眾對(duì)可用疫苗的信任、人口規(guī)模，以及疫苗供應(yīng)的充足性。圖 6 研究樣本中，英國(guó)和美國(guó)的疫苗接種比率處于領(lǐng)先地位（截至 2021 年 4 月 10 日）以色列和阿聯(lián)酋的疫苗接種率顯著領(lǐng)先，不過(guò)，這兩個(gè)國(guó)家均不在我們的研究樣本中。Israel United Arab Emirates United Kingdom United States SingaporeSpain Turkey GermanyItaly France Canada Poland SwitzerlandSweden NetherlandsBrazil China World Russia India Indonesia

17、Australia MalaysiaKorea KazakhstanJapan PhilippinesBelarus South AfricaVietnam020406080100120140Recovered per 100 peopleDoses per 100 people資料來(lái)源：牛津大學(xué)“用數(shù)據(jù)看世界”考慮到目前多數(shù)國(guó)家的疫苗接種進(jìn)度，在接種進(jìn)展緩慢的國(guó)家，不排除將出現(xiàn)更嚴(yán)重的第三波疫情的可能。接下來(lái)，各國(guó)人口抵御新冠病毒的能力或表現(xiàn)出差異，我們預(yù)計(jì) 2021 年，各國(guó)隔離措施的嚴(yán)格程度也會(huì)存在較大不同，在全球范圍內(nèi)一致開展防疫隔離行動(dòng)的可能性不大。各國(guó)的經(jīng)濟(jì)反彈表現(xiàn)，與如何遏制疫情

18、對(duì)經(jīng)濟(jì)的沖擊有關(guān)，這將在很大程度上取決于疫苗接種進(jìn)展，因此可能引發(fā)今年全球不均衡的經(jīng)濟(jì)復(fù)蘇格局。April 15, 2021Overall GDP loss strongly correlated with the strictness of the counter-pandemic measures with few exceptions 11The vaccination process is likely to differentiate countries economic activity in 2021 16 Erzin RostislavJunior Analyst, Sover

19、eign Ratings and Macroeconomic Analysis Group+7 (495) 139-0492, ext. 172 HYPERLINK mailto:rostislav.erzinacra-ratings.ru rostislav.erzinacra-ratings.ruDmitry KulikovAssociate Director, Sovereign Ratings and Macroeconomic Analysis Group+7 (495) 139-0480, ext. 122 HYPERLINK mailto:dmitry.kulikovacra-r

20、atings.ru dmitry.kulikovacra-ratings.ruXiaoli CONGAnalyst, Research and Development Department HYPERLINK mailto:congxiaoli congxiaoliMedia contactsAlexey Churilov Manager for External Communications, ACRA+7 (495) 139-0480, ext. 169 HYPERLINK mailto:alexey.churilovacra-ratings.ru alexey.churilovacra-

21、ratings.ruRuixue LIHead of Branding Management, Golden Credit Rating+86 108-343-5967 HYPERLINK mailto:liruixue liruixueCOVID-19-related quarantines caused GDP to fall in most countries, whereas the cure for the pandemic is likely to be responsible for an uneven recoveryOverview of major world econom

22、ies performance in 2020 and outlook for 2021The overall GDP loss strongly correlated with the strictness of counter-pandemic measures. This is true for the majority of countries, which together represent 81% of global GDP and 62% of the worldspopulation, bar some exceptions. On average, lockdowns an

23、d restrictive measures resulted in 7.1 pp of GDP contraction, with variations depending on countries economic structures and the severity of quarantine measures.Among the most affected sectors were transport, construction, mining, and services. Less affected were retail and manufacturing, which rebo

24、unded to a varying extent during the second half of 2020.The majority of countries imposed quarantine measures in a coordinated manner. Coronavirus-related restrictions were in place during almost all of 2020 in major economies, reaching their lowestpoint in summer and then bouncing back to a higher

25、 level in terms of severity when the second wave of COVID-19 began in autumn. During the first wave, April was the month with the strictest quarantine measures in most of the countries.Vaccination programs are likely to be implemented in an uneven manner and with harmful implications for the economi

26、es. A third global wave of the coronavirus pandemic is quite possible, and it maybe more harmful for countries which have a slower pace of vaccination and are further away from reaching herd immunity. The different pace of vaccination globally may delay the formation of herd immunity in some countri

27、es, making future economic recovery and budget consolidation highly uneven.ACRA and Golden Credit Rating plan to publish a number of joint research papers covering the impact of the COVID-19 pandemic on economic activity and public finance. This is the first paper of the series. See also our joint r

28、esearch papers on the structure of the Russian and Chinese bond markets (Parts 1, 2, 3).Overall GDP loss strongly correlated with the strictness of the counter- pandemic measures with few exceptionsIn this research we will describe a sample of 27 countries which represents the top 10 economies in th

29、e world, top 10 in the EU, all the BRICS countries, top 10 in Asia, and some of the CIS. This sample of countries covers 81% of global GDP and 62% of global population.GDP loss is defined as the difference between the real GDP growth rate forecasted by the IMF and the factual growth rate achieved in

30、 2020.The unique feature of the 2020 crisis is a single factor that explains the severity of GDP loss in the majority of countries globally, bar some exceptions. This factor is the restrictive measures designed to tackle the spread of COVID-19 that had a significant negative impact on almost all eco

31、nomic sectors.This impact was mainly felt as a result of reduced consumption and supply, underpinned by self-isolation regimes as one of the major restrictive measures imposed on the population in many countries. Lower demand for consumer goods and services (apart from the essential ones) led to an

32、output contraction among goods producers and service providers. As a result, contractors producing intermediate goods also saw lower demand.0TurkeyVietnamChina-5SwitzerlandKazakhstan-10United KingdomSpainIndia-15Philippines-2040455055606570Average stringency over 2020GDP loss, %Figure 1. There is a

33、clear relationship between the average stringency of counter- pandemic measures over 2020 and GDP loss with few exceptionsSpainSources: national statistical offices, ACRA, Golden Credit RatingFor the majority of countries, economic losses were more or less consistent with the stringency of imposed q

34、uarantine measures (Fig. 1). However, there were some exceptions. Despite having comparably high severity of quarantine measures, four countries China, Turkey, Vietnam and Kazakhstan suffered much less economic losses than others, while Switzerland underwent a larger contraction.We estimated the GDP

35、 loss associated with COVID restrictions in 2020 by comparing the difference between the factual (or at least estimated based on the first three quarters) real GDP growth rates for the countries considered in our analysis and the forecasts available before the date when quarantine measures were intr

36、oduced.Out of the four countries mentioned above, three Vietnam (2.9%), China (2.3%) and Turkey (1.8%) managed to maintain positive growth rates, but at a lower level than initially expected, while Kazakhstans economy contracted by -2.6%. Economic expansion, though relatively modest, helped them to

37、reduce economic losses.China managed to avoid a fall in GDP thanks to its highly effective containment of the spread of COVID-19, external demand for specific Chinese goods, fiscal stimuli aimed at infrastructure investments, and a developed e-commerce market. In Turkey, relatively cheap credit was

38、massively infused into the economy. This was a countervailing factor for the quarantine measures. In the case of Vietnam, the effective containment of the pandemics spread and growth in the manufacturing sector, additionally boosted by the free trade agreement which was signed with the EU in summer

39、2020, played an important role. The smaller losses of Kazakhstan can be explained by the growth in manufacturing industries caused in particular by opening new production facilities (e.g., the automotive sector), as well as the governments efforts to stimulate construction.Switzerlands higher-than-e

40、xpected losses explained by quarantine stringency in comparison to other countries in our sample can be attributed to the fact that it is a small open economy susceptible to external shocks. Nonetheless, when compared to other European states, who are its major trading partners, the GDP growth slump

41、 of this country is not as sharp.We have estimated that the average GDP loss in 2020 caused by pandemic-related restrictions was 7.1 pp. This average conceals the extremes: there are some countries that managed to grow despite the economic damage done by COVID-19 as mentioned before, whereas others

42、were hit much harder than the average (Fig. 2).The most harm was inflicted on such countries as India (-14.8%), the Philippines (- 15.7%), Spain (-12.7%), and the United Kingdom (-11.5%). These countries had the highest level of strictness of measures imposed out of the countries considered in our s

43、ample (Fig. 1).疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 Figure 2. Economic losses during 2020 turned out to be very different across countries108GDP lossFactualPre-crisis IMF forecast6420-2-4-6-8-10-12-14-16Turkey Belarus China VietnamKorea Sweden SwitzerlandRussia Japan Netherlands United Stat

44、esPoland Germany Canada Brazil Kazakhstan Singapore Indonesia South Africa AustraliaItaly France MalaysiaUnited KingdomSpain India Philippines-18Sources: national statistical offices, ACRA, Golden Credit RatingOverall, as can be seen in Fig. 2, Western European countries were hit by the pandemic ear

45、ly and therefore lived with the coronaviruss economic consequences for more of the year, which brought some of them to the upper side of the GDP loss spectra in 2020. In addition, they tended to apply strict quarantine measures, except Sweden with its no-quarantine policy in the first half of the ye

46、ar.East Asian countries on average were more successful in containing the spread of the coronavirus during the first months of the pandemic, which is reflected in their higher real GDP figures. Eastern European and CIS countries mostly lay in the middle of the spectra, reflecting both average succes

47、s in containing the disease and economic structure differences compared to Western Europe, where the service sector occupies larger share.As for economic activities, on average the most affected industries in 2020 compared to 2019 (Fig. 3) turned out to be transport (-10.7%), construction (-7.4%), m

48、ining (-7.4%), and services (-7.7%). Manufacturing and retail trade were also hit by the restrictive measures, but they managed to bounce back to a varying extent in different countries during the second half of 2020.The major oil and gas exporters were hit by the measures imposed by the OPEC+ deal,

49、 in particular the curb on oil production starting from May 2020. The repercussions of the deal are reflected in mining sector data, the oil product manufacturing subsector, and the wholesale turnover numbers in these countries.疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 Figure 3. The transport se

50、ctor on average suffered the most from quarantine measures imposed over 2020Production index, SA, average of 2020 to average of 2019, %Mining ManufacturingUtilities ConstructionRetailTransportOther servicesFig. 3 describes the production index dynamics distribution using a candle bar chart. The cros

51、ses denote average values; lines within the rectangles denote median values; while the rectangles denote two medium quartiles in a distribution. Each circle represents a single country.Sources: national statistical offices, ACRA, Golden Credit RatingThe performance of the retail sector in 2020 refle

52、cts to a certain extent the severity of the quarantine measures. During the first wave, the countries with the strictest measures saw an almost 50% contraction in turnover, whereas the countries with an intermediate level of strictness in some cases saw single-digit or even no contraction. However,

53、during the second wave the contraction in the sector was not as striking as during the first one.Among other sectors, manufacturing was also susceptible to the restrictions. The countries that did not fit this pattern were those with unique manufacturing industry characteristics (for example, Singap

54、ore), where the major segments (e.g., biomedicine and pharmaceuticals) were basically unaffected by COVID-19. Nonetheless, during the second wave, most of the countries more or less restored their manufacturing activities, though the average figures for 2020 are still rather negative.When summarizin

55、g available statistics we identified at least four structural features which could have pushed countries potential economic losses caused by the COVID- 19 pandemic above the average:Higher than average dependence on external tourism, as reflected in huge positive net external money flows from this a

56、ctivity in the balance of payments (e.g., Spain);Inadequate capacity of healthcare facilities or uneven access to medical services, which in most cases led to higher death rates and stricter and longer quarantines (e.g., the United Kingdom, Brazil, and Italy);Elevated share of investment-oriented go

57、ods produced within a countrysmanufacturing sector (e.g., Germany and Switzerland);Historically low share of online business in retail trade and financial services.In some cases, potential losses were mitigated by successful policies, fortunate economic or export structure, or less political willing

58、ness to curb the pandemic.疫情沖擊造成多數(shù)國(guó)家 GDP 負(fù)增長(zhǎng)，不同應(yīng)對(duì)進(jìn)程將導(dǎo)致經(jīng)濟(jì)復(fù)蘇分化 2021 年 4 月 A brief history of the pandemic and the counter-pandemic measuresOn March 11, 2020, the World Health Organization announced that COVID-19 is a pandemic. Over the next 10 days, the majority of countries actively introduced restri

59、ctive measures to curb its spread, since infection cases were reported in almost all of them. By March 20, in more than 100 countries these measures had reached the 50- point mark on the scale of the Oxford COVID-19 Government Response Tracker, indicating that a great deal of public gatherings had b

60、een banned, schools were closed, and travel was severely restricted. In mid-April the tracker climbed to around the 80- point mark on average, the highest point reached during the pandemic so far (Fig. 4).From June 22 onwards an increasing number of countries started to relax their restrictive measu