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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">77</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:0CE58996-512E-521C-907F-C2C6EA147B5F</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">Russian Journal of Economics</journal-title>
        <abbrev-journal-title xml:lang="en">RUJEC</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">2618-7213</issn>
      <issn pub-type="epub">2405-4739</issn>
      <publisher>
        <publisher-name>Non-profit partnership "Voprosy Ekonomiki"</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.32609/j.ruje.5.35506</article-id>
      <article-id pub-id-type="publisher-id">35506</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>(E63) Comparative or Joint Analysis of Fiscal and Monetary Policy &amp;amp;bull; Stabilization &amp;amp;bull; Treasury Policy</subject>
          <subject>(E65) Studies of Particular Policy Episodes</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Can emerging markets be a source of global troubles again?</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" xlink:type="simple" corresp="yes">
          <name name-style="western">
            <surname>Dabrowski</surname>
            <given-names>Marek</given-names>
          </name>
          <xref ref-type="aff" rid="A1">a</xref>
          <xref ref-type="aff" rid="A2">b</xref>
          <xref ref-type="aff" rid="A3">c</xref>
          <email xlink:type="simple">mdabrowski@hse.ru</email>
          <uri content-type="orcid">https://orcid.org/0000-0002-7960-8734</uri>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>a</label>
        <addr-line content-type="verbatim">National Research University Higher School of Economics, Moscow, Russia</addr-line>
        <institution>National Research University Higher School of Economics</institution>
        <addr-line content-type="city">Moscow</addr-line>
        <country>Russia</country>
      </aff>
      <aff id="A2">
        <label>b</label>
        <addr-line content-type="verbatim">CASE — Center for Social and Economic Research, Warsaw, Poland</addr-line>
        <institution>CASE–Center for Social and Economic Research</institution>
        <addr-line content-type="city">Warsaw</addr-line>
        <country>Poland</country>
      </aff>
      <aff id="A3">
        <label>c</label>
        <addr-line content-type="verbatim">Bruegel, Brussels, Belgium</addr-line>
        <institution>Bruegel</institution>
        <addr-line content-type="city">Brussels</addr-line>
        <country>Belgium</country>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Marek Dabrowski (<email xlink:type="simple">mdabrowski@hse.ru</email>).</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: </p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2019</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>17</day>
        <month>04</month>
        <year>2019</year>
      </pub-date>
      <volume>5</volume>
      <issue>1</issue>
      <fpage>67</fpage>
      <lpage>87</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/04FFEDF2-CDBA-5CAA-B4D4-478363C91394">04FFEDF2-CDBA-5CAA-B4D4-478363C91394</uri>
      <uri content-type="zenodo_dep_id" xlink:href="https://zenodo.org/record/2650574">2650574</uri>
      <permissions>
        <copyright-statement>Non-profit partnership “Voprosy Ekonomiki”</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/" xlink:type="simple">
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits to copy and distribute the article for non-commercial purposes, provided that the article is not altered or modified and the original author and source are credited.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>After two turbulent decades (1980s and 1990s) when emerging-market economies were frequent victims of financial crises, in the first two decades of the 21st century their macroeconomic performance improved. Nevertheless, there were three crisis episodes that hit some of these countries: (i) the spill-over effects of the global financial crisis in 2008–2009; (ii) the consequences of the decline in commodity prices in 2014–2016 for their exporters; (iii) the turbulence in Argentina and Turkey in 2018. Currency crises in Argentina and Turkey in 2018 underlined again the key role of prudent domestic policies. Early policy correction can help to prevent a crisis and avoid its economic, social and political costs. If crisis cannot be avoided, the comprehensive anti-crisis package, including up-front monetary and fiscal adjustment, should be adopted as quickly as possible to arrest market panic and reverse negative expectations.</p>
      </abstract>
      <kwd-group>
        <label>Keywords:</label>
        <kwd>emerging markets</kwd>
        <kwd>financial crisis</kwd>
        <kwd>currency crisis</kwd>
        <kwd>crisis prevention</kwd>
        <kwd>spill-over</kwd>
        <kwd>contagion</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta xlink:type="simple">
          <meta-name>JEL classification</meta-name>
          <meta-value>E63, E65</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="1. Introduction" id="SECID0E6C">
      <title>1. Introduction</title>
      <p>According to popular perception, emerging-market economies have not experienced serious macroeconomic and financial turbulence since the beginning of this century. This perception was not entirely correct because it disregarded spill-over effects of the global financial crises of 2008–2009, the consequences of the decline of oil and other commodity prices in 2014–2016, economic and financial troubles caused by violent conflicts and regional political instability (for example, Ukraine and several Arab countries) or individual cases caused by domestic macroeconomic mismanagement (Venezuela, Zimbabwe and Belarus). Finally, two large emerging-market economies and members of G20 — Argentina and Turkey — were affected by currency crises in 2018. In the case of Argentina, where the scale of experienced turbulence and underlying macroeconomic instability was much larger than in Turkey, authorities had to ask the International Monetary Fund (<abbrev xlink:title="International Monetary Fund" id="ABBRID0EFD">IMF</abbrev>) to provide a rescue program.</p>
      <p>Nevertheless, there were no serial emerging-market crises involving cross-country or even cross-regional contagion, as had occurred in the 1980s or 1990s, except for the former Soviet Union (<abbrev xlink:title="former Soviet Union" id="ABBRID0ELD">FSU</abbrev>) where such an intra-regional contagion could be observed, both in 2008–2009 and 2014–2016. Besides, victims of the 1990s crises in Latin America and Asia were only partly affected by the global financial crisis of 2008–2009. Macroeconomic and financial instability did not originate from emerging markets, but from the US and Europe.</p>
      <p>Against the above background, this paper has three major purposes. First, it analyzes factors, which decreased frequency and magnitude of emerging-market crises in the first two decades of the 21st century. Second, it looks at risk factors faced by emerging-market economies at the end of 2010s. Third, it comes back to the debate on the most effective anti-crisis policies.</p>
      <p>The paper’s structure reflects the above purposes. Section 2 presents basic definitions and the brief historical background of emerging-market crises since 1980s. Section 3 discusses changes in macroeconomic performance of emerging markets since 2000. They resulted in reduced frequency, and magnitude, of financial crises, which, however, did not disappear completely. Section 4 analyzes three recent emerging-market crisis episodes: (i) the spill-over effects of the global financial crisis in 2008–2009; (ii) the consequences of decline in commodity prices in 2014–2016 for their exporters; (iii) turbulence in Argentina and Turkey in 2018. Section 5 comments on risk factors faced by emerging-market economies at the end of the 2010s. Section 6 deals with crisis prevention and anti-crisis policies. Section 7 contains conclusions and general policy recommendations.</p>
      <p>The paper has both diagnostic and normative character and is partly based on earlier publications (see <xref ref-type="bibr" rid="B10">Dabrowski, 2010</xref>, <xref ref-type="bibr" rid="B12">2015</xref>, <xref ref-type="bibr" rid="B13">2016</xref>, <xref ref-type="bibr" rid="B14">2018</xref>).</p>
    </sec>
    <sec sec-type="2. Emerging-market crises: definitions and historic overview" id="SECID0EDE">
      <title>2. Emerging-market crises: definitions and historic overview</title>
      <sec sec-type="2.1. Definition of financial, debt and currency crises" id="SECID0EHE">
        <title>
          <italic>2.1. Definition of financial, debt and currency crises</italic>
        </title>
        <p>For the purposes of this paper, we define financial crisis as a sudden decline in confidence in the ability of a country’s government/central bank and banking sector to pay back their liabilities (on committed terms). Such a broad definition includes all types of instability related to monetary and financial systems (see <xref ref-type="bibr" rid="B43">WEO, 1998</xref>, pp. 74–76).</p>
        <p>There are three specific forms of financial crisis: (i) banking crisis; (ii) public debt crisis; (iii) balance-of-payments crisis. Banking crisis refers to actual or potential bank runs or failures that induce commercial banks to suspend the internal convertibility of their liabilities. A public debt crisis occurs when a government cannot service its foreign and/or domestic debt. A balance of payments crisis involves a structural imbalance between a deficit in the current account (absorption) and capital and financial accounts (sources of financing) that leads to a currency crisis after international reserves are exhausted. Finally, a currency crisis is defined as a sudden decline in confidence in a given currency, usually leading to a speculative attack against it. Analytically, a currency crisis can be detected by either substantial depreciation of a given currency, a decline in a country’s international reserves, or both (<xref ref-type="bibr" rid="B9">Dabrowski, 2003</xref>, p. 5).</p>
      </sec>
      <sec sec-type="2.2. Theoretical models of currency crises" id="SECID0E1E">
        <title>
          <italic>2.2. Theoretical models of currency crises</italic>
        </title>
        <p>Historically, three major generations of theoretical models followed the respective rounds of currency crises. The first-generation models were developed by <xref ref-type="bibr" rid="B23">Krugman (1979)</xref>, and <xref ref-type="bibr" rid="B19">Flood and Garber (1984)</xref>, among others, in response to a series of currency crises in Latin America in the 1970s and early 1980s and focused on the inconsistency between the exchange-rate peg and expansionary macroeconomic policies. In these models, the central bank accommodates changes in domestic money demand through purchases or sales of international reserves. Therefore, if domestic credit expansion (typically caused by monetization of a fiscal deficit) exceeds the money demand, international reserves will decline at the rate of credit expansion, ultimately leading to their depletion. Furthermore, once they understand that the collapse of an exchange-rate peg is unavoidable, economic agents will trigger speculative attacks to avoid losses or to earn speculative gains. Thus, the moment of a currency crash can be hastened relative to the pace of reserves depletion under “normal” circumstances (mechanism of multiple equilibria).</p>
        <p>In the second-generation models (see, among others, <xref ref-type="bibr" rid="B30">Obstfeld, 1994</xref>, <xref ref-type="bibr" rid="B31">1997</xref>; <xref ref-type="bibr" rid="B17">Drazen, 1999</xref>) developed after speculative attacks against the Exchange Rate Mechanism in Europe (<abbrev xlink:title="Exchange Rate Mechanism in Europe" id="ABBRID0EZF">ERM1</abbrev>) in 1992 and the Mexican peso in 1994, the government can choose between defending an exchange-rate peg and abandoning it. The latter choice could be justified, for example, by the expected output/employment losses caused by the high interest rates required to stop speculative attacks on the currency. Economic agents are not certain as to which option will be chosen, which creates uncertainty and various market-game strategies. Therefore, the behavior of economic agents is determined not only by their perception of macroeconomic fundamentals (as in the first-generation models) but also by the expected reaction of the government.</p>
        <p>The experience of the Asian crises in 1997–1998 led to a third-generation of models that focus on the moral hazard driven over-borrowing by large but poorly regulated banks, other financial institutions and non-financial corporations (<xref ref-type="bibr" rid="B28">McKinnon and Phil, 1996</xref>; <xref ref-type="bibr" rid="B24">Krugman, 1998</xref>, 1999; Corsetti et al., <xref ref-type="bibr" rid="B6">1998a</xref>, <xref ref-type="bibr" rid="B7">1998b</xref>, <xref ref-type="bibr" rid="B8">1998c</xref>). According to these models, an economic agent may expect a government rescue operation for a large bank or corporation with good political connections in the event that it faces solvency problems. Therefore, part of private sector “over-borrowing” can be understood as implicit government debt (a contingent fiscal liability), which may eventually have to be monetized.</p>
      </sec>
      <sec sec-type="2.3. Definition of emerging markets" id="SECID0ETG">
        <title>
          <italic>2.3. Definition of emerging markets</italic>
        </title>
        <p>In 1981, Antoine van Agtmael from the International Finance Corporation first used the term emerging market (<xref ref-type="bibr" rid="B18">Economist, 2017</xref>). One can find various definitions of emerging markets or emerging-market economies in economic literature. For the purpose of our analysis, we understand emerging-market economy as a middle-income economy integrated into the world economy in terms of trade, investment and financial flows but with immature/imperfect market mechanisms and institutions. That is, in practical terms, this group neither includes those economies that already graduated to the group of high-income countries (for, example, South Korea, Taiwan, Singapore, Hong Kong, the Baltic countries, Czech Republic and Slovakia) nor low-income countries with underdeveloped financial sectors (most of the African countries).</p>
      </sec>
      <sec sec-type="2.4. Emerging-market crises in 1980s, 1990s and early 2000s" id="SECID0EAH">
        <title>
          <italic>2.4. Emerging-market crises in 1980s, 1990s and early 2000s</italic>
        </title>
        <p>Although financial crises of various kinds have a long history (see Reinhart and Rogoff, 2009), in this paper we are interested in a more recent period when serious turbulences in emerging markets started to have a “serial” character, including cross-border spill-over and contagion effects and had repercussions for the entire global economy or at least individual regions. Thus, we are less interested in crises limited to individual countries and caused by their domestic economic and political problems even if they represent prominent cases of economic mismanagement (think about the situation in Venezuela or Zimbabwe).</p>
        <p>Given the above limitations, our overview starts with the series of currency and public debt crises in the early 1980s, mainly in Latin America. The crisis started in Mexico in 1982 (<xref ref-type="bibr" rid="B5">Brinke, 2013</xref>) and then spread to other countries of this region (Chile, Argentina, Uruguay and Brazil) and outside (Philippines) (<xref ref-type="bibr" rid="B4">Barkbu et al, 2012</xref>).<sup><xref ref-type="fn" rid="en1">1</xref></sup> Most of these crises were caused by imprudent fiscal and monetary policies and by currency pegs incompatible with those policies (first-generation crises). The sharp tightening of US monetary policies at the end of 1970s and early 1980s (to fight two-digit inflation) played a role of external trigger —interest rates in the US and internationally increased to a record-high level and the US$ strengthened against other major currencies.</p>
        <p>The Mexican crisis of 1994–1995 with negative spill-over effect to other Latin American countries, mainly Argentina (the so-called Tequila crisis) was the next major crisis episode, this time reflecting the second-generation model of currency crisis.</p>
        <p>Finally, the years 1997–2002 brought the largest wave of emerging-market crises, which affected more than one region. It started in Thailand in June 1997 and then spread to the Philippines, Malaysia, Indonesia and South Korea in the same year and in early 1998. As mentioned in Section 2.2, Asian financial turbulences represented the third-generation model of currency crisis (see Moreno, 1998; <xref ref-type="bibr" rid="B24">Krugman, 1998</xref>).</p>
        <p>In August 1998, the triple crisis, involving large-scale domestic currency depreciation, default on public debt and insolvency of several banks, hit Russia. In the following six months, other <abbrev xlink:title="former Soviet Union" id="ABBRID0EBAAC">FSU</abbrev> countries were also affected. Large fiscal imbalances were the primary cause of these crises; that is, these were classic cases of the first-generation model (<xref ref-type="bibr" rid="B13">Dabrowski, 2016</xref>).</p>
        <p>Then crisis spread to Brazil which had to abandon the peg of the real to US$ in January 1999. Similarly to Russia and other <abbrev xlink:title="former Soviet Union" id="ABBRID0ELAAC">FSU</abbrev> countries, fiscal imbalance was the main reason. In turn, devaluation of the real affected terms of trade of Brazil’s direct neighbors — Argentina and Uruguay. Together with their domestic fiscal imbalances, it led to triple financial crises in both countries in 2001–2002 (see <xref ref-type="bibr" rid="B41">Spiegel, 2002</xref> for Argentina and <xref ref-type="bibr" rid="B42">Taylor, 2007</xref> for Uruguay). They had to devalue their currencies in 2002 and defaulted on their sovereign debt.</p>
        <p>The Argentinian crisis was particularly messy and involved abandoning the currency board, a deep devaluation of peso, the default of banks on their liabilities to depositors and a default on public debt. The long conflict with foreign holders of government bonds was resolved only in 2016 (<xref ref-type="bibr" rid="B27">Mander and Moore, 2016</xref>; <xref ref-type="bibr" rid="B37">Reinhart, 2016</xref>).</p>
        <p>The large-scale banking and currency crisis in Turkey (2000–2001) was a culmination of at least two decades of lax monetary and fiscal policies, high inflation, and volatile growth in that country (<xref ref-type="bibr" rid="B39">Sasin, 2001</xref>). That is, it had mainly domestic roots but international contagion (and resulting capital outflow) also played an important role.</p>
      </sec>
    </sec>
    <sec sec-type="3. The period of relative calm and prosperity" id="SECID0EHBAC">
      <title>3. The period of relative calm and prosperity</title>
      <p>Financial crises in Turkey, Argentina and Uruguay in 2000–2002 were the last episodes in the large wave of emerging-market turbulences analyzed in Section 2.4. Overall, the first two decades of the 21st century brought significant changes in the macroeconomic performance of emerging-market economies.</p>
      <p><italic>First</italic>, this was the period of rapid growth of this group of countries (Fig. <xref ref-type="fig" rid="F1">1</xref>). Its pace was systematically higher than that of <abbrev xlink:title="advanced economies" id="ABBRID0EUBAC">AEs</abbrev>.<sup><xref ref-type="fn" rid="en2">2</xref></sup> However, growth was uneven across regions (Fig. <xref ref-type="fig" rid="F2">2</xref>) — the highest one in Emerging and Developing Asia (<abbrev xlink:title="Emerging and Developing Asia" id="ABBRID0EBCAC">EDA</abbrev>) and the lowest — in Latin America and Caribbean (<abbrev xlink:title="Latin America and Caribbean" id="ABBRID0EFCAC">LAC</abbrev>) and <abbrev xlink:title="former Soviet Union" id="ABBRID0EJCAC">FSU</abbrev> (in the latter — since 2008). Given its predominantly low-income status and rapid population growth, Sub-Saharan Africa (<abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0ENCAC">SSA</abbrev>) also underperformed. When we look at BRICS countries<sup><xref ref-type="fn" rid="en3">3</xref></sup> (Fig. <xref ref-type="fig" rid="F3">3</xref>), we also see differentiation of growth rates, especially in 2010s: China and India grew much faster than Brazil, Russia and South Africa.</p>
      <fig id="F1" position="float" orientation="portrait">
        <label>Fig. 1.</label>
        <caption>
          <p>World economy, annual changes in real GDP, 1980–2017 (%).</p>
          <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EFDAC">IMF</abbrev> World Economic Outlook database, October 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g001.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295024.jpg"/>
      </fig>
      <fig id="F2" position="float" orientation="portrait">
        <label>Fig. 2.</label>
        <caption>
          <p>EMDE regions, annual change in real GDP, 2000–2017 (%).</p>
          <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EZDAC">IMF</abbrev> World Economic Outlook database, October 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g002.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295025.jpg"/>
      </fig>
      <fig id="F3" position="float" orientation="portrait">
        <label>Fig. 3.</label>
        <caption>
          <p>BRICS countries, annual change in real GDP, 2000–2017 (%).</p>
          <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0ENEAC">IMF</abbrev> World Economic Outlook database, October 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g003.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295026.jpg"/>
      </fig>
      <p><italic>Second</italic>, inflation in <abbrev xlink:title="emerging market and developing economies" id="ABBRID0E1EAC">EMDEs</abbrev> has declined to one-digit level (Fig. <xref ref-type="fig" rid="F4">4</xref>) converging towards the level observed in <abbrev xlink:title="advanced economies" id="ABBRID0ECFAC">AEs</abbrev>. This has been a tremendous achievement, in particular for <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0EGFAC">LAC</abbrev> (that suffered from numerous high-inflation and hyperinflation episodes in 1970s and 1980s — see <xref ref-type="bibr" rid="B16">Dornbusch and Edwards, 1991</xref>), <abbrev xlink:title="former Soviet Union" id="ABBRID0EOFAC">FSU</abbrev>, Emerging and Developing Europe (<abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0ESFAC">EDE</abbrev>) and <abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0EWFAC">SSA</abbrev>. Nevertheless, there is differentiation of inflation performance between regions, with <abbrev xlink:title="Emerging and Developing Asia" id="ABBRID0E1FAC">EDA</abbrev>, <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0E5FAC">EDE</abbrev> and <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0ECGAC">LAC</abbrev> doing better and <abbrev xlink:title="former Soviet Union" id="ABBRID0EGGAC">FSU</abbrev>, Middle East and North Africa (<abbrev xlink:title="Middle East and North Africa" id="ABBRID0EKGAC">MENA</abbrev>) and <abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0EOGAC">SSA</abbrev> lagging behind.</p>
      <p><italic>Third</italic>, most emerging-market central banks accumulated substantial international reserves (Fig. <xref ref-type="fig" rid="F5">5</xref>) following recommendation of the <abbrev xlink:title="International Monetary Fund" id="ABBRID0E1GAC">IMF</abbrev>. This increased their resilience to external shocks, for example, during the global financial crisis of 2008–2009 and in the period of commodity price decline in 2014–2016.</p>
      <fig id="F4" position="float" orientation="portrait">
        <label>Fig. 4.</label>
        <caption>
          <p>End-of-year inflation in <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EGHAC">EMDEs</abbrev>, in percent, 2000–2017 (%).</p>
          <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EOHAC">IMF</abbrev> World Economic Outlook database, October 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g004.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295027.jpg"/>
      </fig>
      <fig id="F5" position="float" orientation="portrait">
        <label>Fig. 5.</label>
        <caption>
          <p>Total reserves of central banks in <abbrev xlink:title="emerging market and developing economies" id="ABBRID0E6HAC">EMDEs</abbrev> minus gold, 2000–2018 (US$ billion).</p>
          <p>Source: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EFIAC">IMF</abbrev> International Financial Statistics.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g005.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295028.jpg"/>
      </fig>
      <p><italic>Fourth</italic>, fiscal performance also improved, especially in the early and mid-2000s (Table <xref ref-type="table" rid="T1">1</xref>). In particular, oil and other commodity exporters built up sovereign wealth funds (<abbrev xlink:title="sovereign wealth funds" id="ABBRID0EWIAC">SWFs</abbrev>), sometimes quite substantial ones that helped many of them to cushion the negative effects of both the 2007–2009 financial shock and commodity price decline in 2014–2016. Nevertheless, fiscal improvement did not happen everywhere and was not consequent enough to eliminate the macroeconomic vulnerability of emerging markets (see Sections 4 and 5).</p>
      <table-wrap id="T1" position="float" orientation="portrait">
        <label>Table 1.</label>
        <caption>
          <p>General government gross debt in selected <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EDJAC">EMDEs</abbrev>, 2000–2017 (% of GDP).</p>
        </caption>
        <table id="TID0EJ3AE" rules="all">
          <tbody>
            <tr>
              <td rowspan="1" colspan="1">Country</td>
              <td rowspan="1" colspan="1">2000</td>
              <td rowspan="1" colspan="1">2001</td>
              <td rowspan="1" colspan="1">2002</td>
              <td rowspan="1" colspan="1">2003</td>
              <td rowspan="1" colspan="1">2004</td>
              <td rowspan="1" colspan="1">2005</td>
              <td rowspan="1" colspan="1">2006</td>
              <td rowspan="1" colspan="1">2007</td>
              <td rowspan="1" colspan="1">2008</td>
              <td rowspan="1" colspan="1">2009</td>
              <td rowspan="1" colspan="1">2010</td>
              <td rowspan="1" colspan="1">2011</td>
              <td rowspan="1" colspan="1">2012</td>
              <td rowspan="1" colspan="1">2013</td>
              <td rowspan="1" colspan="1">2014</td>
              <td rowspan="1" colspan="1">2015</td>
              <td rowspan="1" colspan="1">2016</td>
              <td rowspan="1" colspan="1">2017</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Argentina</td>
              <td rowspan="1" colspan="1">42.1</td>
              <td rowspan="1" colspan="1">49.4</td>
              <td rowspan="1" colspan="1">152.2</td>
              <td rowspan="1" colspan="1">128.7</td>
              <td rowspan="1" colspan="1">117.3</td>
              <td rowspan="1" colspan="1">79.2</td>
              <td rowspan="1" colspan="1">69.8</td>
              <td rowspan="1" colspan="1">61.0</td>
              <td rowspan="1" colspan="1">52.6</td>
              <td rowspan="1" colspan="1">53.8</td>
              <td rowspan="1" colspan="1">42.0</td>
              <td rowspan="1" colspan="1">37.5</td>
              <td rowspan="1" colspan="1">38.9</td>
              <td rowspan="1" colspan="1">41.7</td>
              <td rowspan="1" colspan="1">43.6</td>
              <td rowspan="1" colspan="1">55.1</td>
              <td rowspan="1" colspan="1">55.0</td>
              <td rowspan="1" colspan="1">57.6</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Belarus</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">9.5</td>
              <td rowspan="1" colspan="1">8.4</td>
              <td rowspan="1" colspan="1">12.7</td>
              <td rowspan="1" colspan="1">16.4</td>
              <td rowspan="1" colspan="1">21.0</td>
              <td rowspan="1" colspan="1">32.5</td>
              <td rowspan="1" colspan="1">36.8</td>
              <td rowspan="1" colspan="1">58.2</td>
              <td rowspan="1" colspan="1">36.9</td>
              <td rowspan="1" colspan="1">36.9</td>
              <td rowspan="1" colspan="1">38.8</td>
              <td rowspan="1" colspan="1">53.0</td>
              <td rowspan="1" colspan="1">53.5</td>
              <td rowspan="1" colspan="1">53.4</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Brazil</td>
              <td rowspan="1" colspan="1">65.6</td>
              <td rowspan="1" colspan="1">70.1</td>
              <td rowspan="1" colspan="1">78.9</td>
              <td rowspan="1" colspan="1">73.9</td>
              <td rowspan="1" colspan="1">70.2</td>
              <td rowspan="1" colspan="1">68.7</td>
              <td rowspan="1" colspan="1">65.9</td>
              <td rowspan="1" colspan="1">63.8</td>
              <td rowspan="1" colspan="1">61.9</td>
              <td rowspan="1" colspan="1">65.0</td>
              <td rowspan="1" colspan="1">63.1</td>
              <td rowspan="1" colspan="1">61.2</td>
              <td rowspan="1" colspan="1">62.2</td>
              <td rowspan="1" colspan="1">60.2</td>
              <td rowspan="1" colspan="1">62.3</td>
              <td rowspan="1" colspan="1">72.6</td>
              <td rowspan="1" colspan="1">78.4</td>
              <td rowspan="1" colspan="1">84.0</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Chile</td>
              <td rowspan="1" colspan="1">13.2</td>
              <td rowspan="1" colspan="1">14.5</td>
              <td rowspan="1" colspan="1">15.2</td>
              <td rowspan="1" colspan="1">12.7</td>
              <td rowspan="1" colspan="1">10.3</td>
              <td rowspan="1" colspan="1">7.0</td>
              <td rowspan="1" colspan="1">5.0</td>
              <td rowspan="1" colspan="1">3.9</td>
              <td rowspan="1" colspan="1">4.9</td>
              <td rowspan="1" colspan="1">5.8</td>
              <td rowspan="1" colspan="1">8.6</td>
              <td rowspan="1" colspan="1">11.1</td>
              <td rowspan="1" colspan="1">11.9</td>
              <td rowspan="1" colspan="1">12.7</td>
              <td rowspan="1" colspan="1">15.0</td>
              <td rowspan="1" colspan="1">17.3</td>
              <td rowspan="1" colspan="1">21.0</td>
              <td rowspan="1" colspan="1">23.6</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">China</td>
              <td rowspan="1" colspan="1">22.8</td>
              <td rowspan="1" colspan="1">24.4</td>
              <td rowspan="1" colspan="1">25.7</td>
              <td rowspan="1" colspan="1">26.6</td>
              <td rowspan="1" colspan="1">26.2</td>
              <td rowspan="1" colspan="1">26.1</td>
              <td rowspan="1" colspan="1">25.4</td>
              <td rowspan="1" colspan="1">29.0</td>
              <td rowspan="1" colspan="1">27.0</td>
              <td rowspan="1" colspan="1">34.3</td>
              <td rowspan="1" colspan="1">33.7</td>
              <td rowspan="1" colspan="1">33.6</td>
              <td rowspan="1" colspan="1">34.3</td>
              <td rowspan="1" colspan="1">37.0</td>
              <td rowspan="1" colspan="1">39.9</td>
              <td rowspan="1" colspan="1">41.1</td>
              <td rowspan="1" colspan="1">44.2</td>
              <td rowspan="1" colspan="1">47.0</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Colombia</td>
              <td rowspan="1" colspan="1">38.1</td>
              <td rowspan="1" colspan="1">41.2</td>
              <td rowspan="1" colspan="1">47.7</td>
              <td rowspan="1" colspan="1">45.2</td>
              <td rowspan="1" colspan="1">41.6</td>
              <td rowspan="1" colspan="1">38.6</td>
              <td rowspan="1" colspan="1">36.1</td>
              <td rowspan="1" colspan="1">32.7</td>
              <td rowspan="1" colspan="1">32.4</td>
              <td rowspan="1" colspan="1">35.4</td>
              <td rowspan="1" colspan="1">36.6</td>
              <td rowspan="1" colspan="1">35.8</td>
              <td rowspan="1" colspan="1">34.0</td>
              <td rowspan="1" colspan="1">37.6</td>
              <td rowspan="1" colspan="1">43.3</td>
              <td rowspan="1" colspan="1">50.4</td>
              <td rowspan="1" colspan="1">49.8</td>
              <td rowspan="1" colspan="1">49.4</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Croatia</td>
              <td rowspan="1" colspan="1">33.2</td>
              <td rowspan="1" colspan="1">34.6</td>
              <td rowspan="1" colspan="1">36.6</td>
              <td rowspan="1" colspan="1">38.1</td>
              <td rowspan="1" colspan="1">40.4</td>
              <td rowspan="1" colspan="1">41.3</td>
              <td rowspan="1" colspan="1">38.9</td>
              <td rowspan="1" colspan="1">37.7</td>
              <td rowspan="1" colspan="1">39.6</td>
              <td rowspan="1" colspan="1">48.9</td>
              <td rowspan="1" colspan="1">58.1</td>
              <td rowspan="1" colspan="1">65.0</td>
              <td rowspan="1" colspan="1">70.6</td>
              <td rowspan="1" colspan="1">81.6</td>
              <td rowspan="1" colspan="1">85.7</td>
              <td rowspan="1" colspan="1">85.3</td>
              <td rowspan="1" colspan="1">82.3</td>
              <td rowspan="1" colspan="1">77.8</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Egypt</td>
              <td rowspan="1" colspan="1">71.7</td>
              <td rowspan="1" colspan="1">79.1</td>
              <td rowspan="1" colspan="1">85.8</td>
              <td rowspan="1" colspan="1">97.1</td>
              <td rowspan="1" colspan="1">96.5</td>
              <td rowspan="1" colspan="1">98.3</td>
              <td rowspan="1" colspan="1">85.9</td>
              <td rowspan="1" colspan="1">76.3</td>
              <td rowspan="1" colspan="1">66.8</td>
              <td rowspan="1" colspan="1">69.5</td>
              <td rowspan="1" colspan="1">69.6</td>
              <td rowspan="1" colspan="1">72.8</td>
              <td rowspan="1" colspan="1">73.8</td>
              <td rowspan="1" colspan="1">84.0</td>
              <td rowspan="1" colspan="1">85.1</td>
              <td rowspan="1" colspan="1">88.5</td>
              <td rowspan="1" colspan="1">96.8</td>
              <td rowspan="1" colspan="1">103.0</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Ethiopia</td>
              <td rowspan="1" colspan="1">93.6</td>
              <td rowspan="1" colspan="1">97.3</td>
              <td rowspan="1" colspan="1">107.4</td>
              <td rowspan="1" colspan="1">103.7</td>
              <td rowspan="1" colspan="1">103.1</td>
              <td rowspan="1" colspan="1">78.2</td>
              <td rowspan="1" colspan="1">70.0</td>
              <td rowspan="1" colspan="1">46.8</td>
              <td rowspan="1" colspan="1">41.7</td>
              <td rowspan="1" colspan="1">37.8</td>
              <td rowspan="1" colspan="1">40.5</td>
              <td rowspan="1" colspan="1">45.3</td>
              <td rowspan="1" colspan="1">37.7</td>
              <td rowspan="1" colspan="1">42.9</td>
              <td rowspan="1" colspan="1">46.8</td>
              <td rowspan="1" colspan="1">54.0</td>
              <td rowspan="1" colspan="1">53.2</td>
              <td rowspan="1" colspan="1">54.2 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hungary</td>
              <td rowspan="1" colspan="1">55.0</td>
              <td rowspan="1" colspan="1">51.6</td>
              <td rowspan="1" colspan="1">54.8</td>
              <td rowspan="1" colspan="1">57.4</td>
              <td rowspan="1" colspan="1">58.3</td>
              <td rowspan="1" colspan="1">60.2</td>
              <td rowspan="1" colspan="1">64.4</td>
              <td rowspan="1" colspan="1">65.3</td>
              <td rowspan="1" colspan="1">71.2</td>
              <td rowspan="1" colspan="1">77.5</td>
              <td rowspan="1" colspan="1">80.2</td>
              <td rowspan="1" colspan="1">80.5</td>
              <td rowspan="1" colspan="1">78.4</td>
              <td rowspan="1" colspan="1">77.1</td>
              <td rowspan="1" colspan="1">76.6</td>
              <td rowspan="1" colspan="1">76.7</td>
              <td rowspan="1" colspan="1">76.0</td>
              <td rowspan="1" colspan="1">73.6</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">India</td>
              <td rowspan="1" colspan="1">73.6</td>
              <td rowspan="1" colspan="1">78.7</td>
              <td rowspan="1" colspan="1">82.9</td>
              <td rowspan="1" colspan="1">84.2</td>
              <td rowspan="1" colspan="1">83.3</td>
              <td rowspan="1" colspan="1">80.9</td>
              <td rowspan="1" colspan="1">77.1</td>
              <td rowspan="1" colspan="1">74.0</td>
              <td rowspan="1" colspan="1">74.5</td>
              <td rowspan="1" colspan="1">72.5</td>
              <td rowspan="1" colspan="1">67.5</td>
              <td rowspan="1" colspan="1">69.6</td>
              <td rowspan="1" colspan="1">69.1</td>
              <td rowspan="1" colspan="1">68.5</td>
              <td rowspan="1" colspan="1">67.8</td>
              <td rowspan="1" colspan="1">70.0</td>
              <td rowspan="1" colspan="1">69.5</td>
              <td rowspan="1" colspan="1">71.2</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Indonesia</td>
              <td rowspan="1" colspan="1">87.4</td>
              <td rowspan="1" colspan="1">73.7</td>
              <td rowspan="1" colspan="1">62.3</td>
              <td rowspan="1" colspan="1">55.6</td>
              <td rowspan="1" colspan="1">51.3</td>
              <td rowspan="1" colspan="1">42.6</td>
              <td rowspan="1" colspan="1">35.8</td>
              <td rowspan="1" colspan="1">32.3</td>
              <td rowspan="1" colspan="1">30.3</td>
              <td rowspan="1" colspan="1">26.5</td>
              <td rowspan="1" colspan="1">24.5</td>
              <td rowspan="1" colspan="1">23.1</td>
              <td rowspan="1" colspan="1">23.0</td>
              <td rowspan="1" colspan="1">24.8</td>
              <td rowspan="1" colspan="1">24.7</td>
              <td rowspan="1" colspan="1">27.5</td>
              <td rowspan="1" colspan="1">28.3</td>
              <td rowspan="1" colspan="1">28.8</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Iran</td>
              <td rowspan="1" colspan="1">11.9</td>
              <td rowspan="1" colspan="1">11.7</td>
              <td rowspan="1" colspan="1">21.6</td>
              <td rowspan="1" colspan="1">19.5</td>
              <td rowspan="1" colspan="1">16.2</td>
              <td rowspan="1" colspan="1">13.0</td>
              <td rowspan="1" colspan="1">11.9</td>
              <td rowspan="1" colspan="1">11.4</td>
              <td rowspan="1" colspan="1">9.1</td>
              <td rowspan="1" colspan="1">10.1</td>
              <td rowspan="1" colspan="1">11.7</td>
              <td rowspan="1" colspan="1">8.9</td>
              <td rowspan="1" colspan="1">12.1</td>
              <td rowspan="1" colspan="1">10.7</td>
              <td rowspan="1" colspan="1">11.8</td>
              <td rowspan="1" colspan="1">38.4</td>
              <td rowspan="1" colspan="1">47.5</td>
              <td rowspan="1" colspan="1">39.5</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Jordan</td>
              <td rowspan="1" colspan="1">100.5</td>
              <td rowspan="1" colspan="1">96.5</td>
              <td rowspan="1" colspan="1">99.7</td>
              <td rowspan="1" colspan="1">99.6</td>
              <td rowspan="1" colspan="1">91.8</td>
              <td rowspan="1" colspan="1">84.3</td>
              <td rowspan="1" colspan="1">76.3</td>
              <td rowspan="1" colspan="1">73.8</td>
              <td rowspan="1" colspan="1">60.2</td>
              <td rowspan="1" colspan="1">64.8</td>
              <td rowspan="1" colspan="1">67.1</td>
              <td rowspan="1" colspan="1">70.7</td>
              <td rowspan="1" colspan="1">80.7</td>
              <td rowspan="1" colspan="1">86.7</td>
              <td rowspan="1" colspan="1">89.0</td>
              <td rowspan="1" colspan="1">93.4</td>
              <td rowspan="1" colspan="1">95.1</td>
              <td rowspan="1" colspan="1">95.9</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Kazakhstan</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">17.6</td>
              <td rowspan="1" colspan="1">15.0</td>
              <td rowspan="1" colspan="1">11.4</td>
              <td rowspan="1" colspan="1">8.1</td>
              <td rowspan="1" colspan="1">6.7</td>
              <td rowspan="1" colspan="1">5.9</td>
              <td rowspan="1" colspan="1">6.8</td>
              <td rowspan="1" colspan="1">10.2</td>
              <td rowspan="1" colspan="1">10.7</td>
              <td rowspan="1" colspan="1">10.2</td>
              <td rowspan="1" colspan="1">12.1</td>
              <td rowspan="1" colspan="1">12.6</td>
              <td rowspan="1" colspan="1">14.5</td>
              <td rowspan="1" colspan="1">21.9</td>
              <td rowspan="1" colspan="1">19.7</td>
              <td rowspan="1" colspan="1">20.8</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Lebanon</td>
              <td rowspan="1" colspan="1">148.2</td>
              <td rowspan="1" colspan="1">163.2</td>
              <td rowspan="1" colspan="1">163.2</td>
              <td rowspan="1" colspan="1">171.4</td>
              <td rowspan="1" colspan="1">169.7</td>
              <td rowspan="1" colspan="1">179.0</td>
              <td rowspan="1" colspan="1">183.1</td>
              <td rowspan="1" colspan="1">169.0</td>
              <td rowspan="1" colspan="1">160.9</td>
              <td rowspan="1" colspan="1">144.2</td>
              <td rowspan="1" colspan="1">136.9</td>
              <td rowspan="1" colspan="1">133.9</td>
              <td rowspan="1" colspan="1">131.0</td>
              <td rowspan="1" colspan="1">136.6</td>
              <td rowspan="1" colspan="1">137.2</td>
              <td rowspan="1" colspan="1">140.9</td>
              <td rowspan="1" colspan="1">145.5</td>
              <td rowspan="1" colspan="1">146.8 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Malaysia</td>
              <td rowspan="1" colspan="1">32.9</td>
              <td rowspan="1" colspan="1">38.5</td>
              <td rowspan="1" colspan="1">40.1</td>
              <td rowspan="1" colspan="1">42.0</td>
              <td rowspan="1" colspan="1">42.6</td>
              <td rowspan="1" colspan="1">41.4</td>
              <td rowspan="1" colspan="1">40.2</td>
              <td rowspan="1" colspan="1">39.9</td>
              <td rowspan="1" colspan="1">39.9</td>
              <td rowspan="1" colspan="1">51.1</td>
              <td rowspan="1" colspan="1">51.9</td>
              <td rowspan="1" colspan="1">52.6</td>
              <td rowspan="1" colspan="1">54.6</td>
              <td rowspan="1" colspan="1">56.4</td>
              <td rowspan="1" colspan="1">56.2</td>
              <td rowspan="1" colspan="1">57.9</td>
              <td rowspan="1" colspan="1">56.2</td>
              <td rowspan="1" colspan="1">54.1 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Mexico</td>
              <td rowspan="1" colspan="1">40.3</td>
              <td rowspan="1" colspan="1">39.3</td>
              <td rowspan="1" colspan="1">41.9</td>
              <td rowspan="1" colspan="1">44.2</td>
              <td rowspan="1" colspan="1">40.8</td>
              <td rowspan="1" colspan="1">38.5</td>
              <td rowspan="1" colspan="1">37.4</td>
              <td rowspan="1" colspan="1">37.2</td>
              <td rowspan="1" colspan="1">42.5</td>
              <td rowspan="1" colspan="1">43.7</td>
              <td rowspan="1" colspan="1">42.0</td>
              <td rowspan="1" colspan="1">42.9</td>
              <td rowspan="1" colspan="1">42.7</td>
              <td rowspan="1" colspan="1">45.9</td>
              <td rowspan="1" colspan="1">48.9</td>
              <td rowspan="1" colspan="1">52.8</td>
              <td rowspan="1" colspan="1">56.8</td>
              <td rowspan="1" colspan="1">54.3</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Morocco</td>
              <td rowspan="1" colspan="1">70.2</td>
              <td rowspan="1" colspan="1">65.4</td>
              <td rowspan="1" colspan="1">64.3</td>
              <td rowspan="1" colspan="1">61.6</td>
              <td rowspan="1" colspan="1">58.9</td>
              <td rowspan="1" colspan="1">59.3</td>
              <td rowspan="1" colspan="1">54.8</td>
              <td rowspan="1" colspan="1">50.9</td>
              <td rowspan="1" colspan="1">45.4</td>
              <td rowspan="1" colspan="1">46.1</td>
              <td rowspan="1" colspan="1">49.0</td>
              <td rowspan="1" colspan="1">52.5</td>
              <td rowspan="1" colspan="1">56.5</td>
              <td rowspan="1" colspan="1">61.7</td>
              <td rowspan="1" colspan="1">63.3</td>
              <td rowspan="1" colspan="1">63.7</td>
              <td rowspan="1" colspan="1">64.9</td>
              <td rowspan="1" colspan="1">65.1</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Nigeria</td>
              <td rowspan="1" colspan="1">57.6</td>
              <td rowspan="1" colspan="1">53.1</td>
              <td rowspan="1" colspan="1">43.3</td>
              <td rowspan="1" colspan="1">42.1</td>
              <td rowspan="1" colspan="1">35.5</td>
              <td rowspan="1" colspan="1">18.9</td>
              <td rowspan="1" colspan="1">9.4</td>
              <td rowspan="1" colspan="1">8.1</td>
              <td rowspan="1" colspan="1">7.3</td>
              <td rowspan="1" colspan="1">8.6</td>
              <td rowspan="1" colspan="1">9.6</td>
              <td rowspan="1" colspan="1">12.1</td>
              <td rowspan="1" colspan="1">12.7</td>
              <td rowspan="1" colspan="1">12.9</td>
              <td rowspan="1" colspan="1">13.1</td>
              <td rowspan="1" colspan="1">16.0</td>
              <td rowspan="1" colspan="1">19.6</td>
              <td rowspan="1" colspan="1">21.8</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Pakistan</td>
              <td rowspan="1" colspan="1">76.8</td>
              <td rowspan="1" colspan="1">81.2</td>
              <td rowspan="1" colspan="1">76.1</td>
              <td rowspan="1" colspan="1">70.5</td>
              <td rowspan="1" colspan="1">63.2</td>
              <td rowspan="1" colspan="1">58.9</td>
              <td rowspan="1" colspan="1">53.7</td>
              <td rowspan="1" colspan="1">52.4</td>
              <td rowspan="1" colspan="1">57.2</td>
              <td rowspan="1" colspan="1">58.5</td>
              <td rowspan="1" colspan="1">60.6</td>
              <td rowspan="1" colspan="1">58.9</td>
              <td rowspan="1" colspan="1">63.2</td>
              <td rowspan="1" colspan="1">63.9</td>
              <td rowspan="1" colspan="1">63.5</td>
              <td rowspan="1" colspan="1">63.3</td>
              <td rowspan="1" colspan="1">67.6</td>
              <td rowspan="1" colspan="1">67.0</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Philippines</td>
              <td rowspan="1" colspan="1">61.1</td>
              <td rowspan="1" colspan="1">61.5</td>
              <td rowspan="1" colspan="1">67.5</td>
              <td rowspan="1" colspan="1">74.1</td>
              <td rowspan="1" colspan="1">73.9</td>
              <td rowspan="1" colspan="1">67.4</td>
              <td rowspan="1" colspan="1">59.7</td>
              <td rowspan="1" colspan="1">52.4</td>
              <td rowspan="1" colspan="1">52.1</td>
              <td rowspan="1" colspan="1">52.1</td>
              <td rowspan="1" colspan="1">49.7</td>
              <td rowspan="1" colspan="1">47.5</td>
              <td rowspan="1" colspan="1">47.9</td>
              <td rowspan="1" colspan="1">45.7</td>
              <td rowspan="1" colspan="1">42.1</td>
              <td rowspan="1" colspan="1">41.5</td>
              <td rowspan="1" colspan="1">39.0</td>
              <td rowspan="1" colspan="1">39.9</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Poland</td>
              <td rowspan="1" colspan="1">36.4</td>
              <td rowspan="1" colspan="1">37.1</td>
              <td rowspan="1" colspan="1">41.5</td>
              <td rowspan="1" colspan="1">46.3</td>
              <td rowspan="1" colspan="1">45.1</td>
              <td rowspan="1" colspan="1">46.4</td>
              <td rowspan="1" colspan="1">46.9</td>
              <td rowspan="1" colspan="1">44.2</td>
              <td rowspan="1" colspan="1">46.3</td>
              <td rowspan="1" colspan="1">49.4</td>
              <td rowspan="1" colspan="1">53.1</td>
              <td rowspan="1" colspan="1">54.1</td>
              <td rowspan="1" colspan="1">53.7</td>
              <td rowspan="1" colspan="1">55.7</td>
              <td rowspan="1" colspan="1">50.3</td>
              <td rowspan="1" colspan="1">51.1</td>
              <td rowspan="1" colspan="1">54.2</td>
              <td rowspan="1" colspan="1">50.6 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Romania</td>
              <td rowspan="1" colspan="1">29.4</td>
              <td rowspan="1" colspan="1">27.2</td>
              <td rowspan="1" colspan="1">27.3</td>
              <td rowspan="1" colspan="1">24.0</td>
              <td rowspan="1" colspan="1">21.0</td>
              <td rowspan="1" colspan="1">17.5</td>
              <td rowspan="1" colspan="1">12.5</td>
              <td rowspan="1" colspan="1">12.3</td>
              <td rowspan="1" colspan="1">13.0</td>
              <td rowspan="1" colspan="1">22.6</td>
              <td rowspan="1" colspan="1">30.8</td>
              <td rowspan="1" colspan="1">34.1</td>
              <td rowspan="1" colspan="1">37.7</td>
              <td rowspan="1" colspan="1">39.0</td>
              <td rowspan="1" colspan="1">40.5</td>
              <td rowspan="1" colspan="1">39.4</td>
              <td rowspan="1" colspan="1">38.8</td>
              <td rowspan="1" colspan="1">36.8</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Russia</td>
              <td rowspan="1" colspan="1">55.7</td>
              <td rowspan="1" colspan="1">44.3</td>
              <td rowspan="1" colspan="1">37.5</td>
              <td rowspan="1" colspan="1">28.3</td>
              <td rowspan="1" colspan="1">20.8</td>
              <td rowspan="1" colspan="1">14.8</td>
              <td rowspan="1" colspan="1">9.8</td>
              <td rowspan="1" colspan="1">8.0</td>
              <td rowspan="1" colspan="1">7.4</td>
              <td rowspan="1" colspan="1">9.9</td>
              <td rowspan="1" colspan="1">10.9</td>
              <td rowspan="1" colspan="1">11.2</td>
              <td rowspan="1" colspan="1">11.9</td>
              <td rowspan="1" colspan="1">13.1</td>
              <td rowspan="1" colspan="1">16.0</td>
              <td rowspan="1" colspan="1">16.3</td>
              <td rowspan="1" colspan="1">16.1</td>
              <td rowspan="1" colspan="1">15.5</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">South Africa</td>
              <td rowspan="1" colspan="1">42.2</td>
              <td rowspan="1" colspan="1">42.4</td>
              <td rowspan="1" colspan="1">35.5</td>
              <td rowspan="1" colspan="1">35.4</td>
              <td rowspan="1" colspan="1">34.4</td>
              <td rowspan="1" colspan="1">33.2</td>
              <td rowspan="1" colspan="1">31.4</td>
              <td rowspan="1" colspan="1">27.1</td>
              <td rowspan="1" colspan="1">26.5</td>
              <td rowspan="1" colspan="1">30.1</td>
              <td rowspan="1" colspan="1">34.7</td>
              <td rowspan="1" colspan="1">38.2</td>
              <td rowspan="1" colspan="1">41.0</td>
              <td rowspan="1" colspan="1">44.1</td>
              <td rowspan="1" colspan="1">47.0</td>
              <td rowspan="1" colspan="1">49.3</td>
              <td rowspan="1" colspan="1">51.6</td>
              <td rowspan="1" colspan="1">53.0</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Tunisia</td>
              <td rowspan="1" colspan="1">65.9</td>
              <td rowspan="1" colspan="1">54.7</td>
              <td rowspan="1" colspan="1">54.2</td>
              <td rowspan="1" colspan="1">55.1</td>
              <td rowspan="1" colspan="1">54.1</td>
              <td rowspan="1" colspan="1">52.4</td>
              <td rowspan="1" colspan="1">48.0</td>
              <td rowspan="1" colspan="1">44.8</td>
              <td rowspan="1" colspan="1">42.0</td>
              <td rowspan="1" colspan="1">40.7</td>
              <td rowspan="1" colspan="1">39.2</td>
              <td rowspan="1" colspan="1">43.1</td>
              <td rowspan="1" colspan="1">47.7</td>
              <td rowspan="1" colspan="1">46.8</td>
              <td rowspan="1" colspan="1">51.5</td>
              <td rowspan="1" colspan="1">55.4</td>
              <td rowspan="1" colspan="1">62.3</td>
              <td rowspan="1" colspan="1">70.3 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Turkey</td>
              <td rowspan="1" colspan="1">51.6</td>
              <td rowspan="1" colspan="1">76.1</td>
              <td rowspan="1" colspan="1">72.1</td>
              <td rowspan="1" colspan="1">65.7</td>
              <td rowspan="1" colspan="1">57.7</td>
              <td rowspan="1" colspan="1">50.8</td>
              <td rowspan="1" colspan="1">44.7</td>
              <td rowspan="1" colspan="1">38.2</td>
              <td rowspan="1" colspan="1">38.2</td>
              <td rowspan="1" colspan="1">43.9</td>
              <td rowspan="1" colspan="1">40.1</td>
              <td rowspan="1" colspan="1">36.5</td>
              <td rowspan="1" colspan="1">32.7</td>
              <td rowspan="1" colspan="1">31.4</td>
              <td rowspan="1" colspan="1">28.8</td>
              <td rowspan="1" colspan="1">27.6</td>
              <td rowspan="1" colspan="1">28.3</td>
              <td rowspan="1" colspan="1">28.3</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Ukraine</td>
              <td rowspan="1" colspan="1">43.8</td>
              <td rowspan="1" colspan="1">35.3</td>
              <td rowspan="1" colspan="1">32.3</td>
              <td rowspan="1" colspan="1">28.3</td>
              <td rowspan="1" colspan="1">23.9</td>
              <td rowspan="1" colspan="1">17.1</td>
              <td rowspan="1" colspan="1">14.3</td>
              <td rowspan="1" colspan="1">11.8</td>
              <td rowspan="1" colspan="1">19.7</td>
              <td rowspan="1" colspan="1">34.1</td>
              <td rowspan="1" colspan="1">40.6</td>
              <td rowspan="1" colspan="1">36.9</td>
              <td rowspan="1" colspan="1">37.5</td>
              <td rowspan="1" colspan="1">40.5</td>
              <td rowspan="1" colspan="1">70.3</td>
              <td rowspan="1" colspan="1">79.3</td>
              <td rowspan="1" colspan="1">81.2</td>
              <td rowspan="1" colspan="1">71.0 <sup>a)</sup></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Uruguay</td>
              <td rowspan="1" colspan="1">n/a</td>
              <td rowspan="1" colspan="1">54.9</td>
              <td rowspan="1" colspan="1">109.6</td>
              <td rowspan="1" colspan="1">111.5</td>
              <td rowspan="1" colspan="1">93.5</td>
              <td rowspan="1" colspan="1">83.9</td>
              <td rowspan="1" colspan="1">75.7</td>
              <td rowspan="1" colspan="1">68.0</td>
              <td rowspan="1" colspan="1">59.8</td>
              <td rowspan="1" colspan="1">63.1</td>
              <td rowspan="1" colspan="1">59.4</td>
              <td rowspan="1" colspan="1">58.1</td>
              <td rowspan="1" colspan="1">58.0</td>
              <td rowspan="1" colspan="1">60.2</td>
              <td rowspan="1" colspan="1">61.4</td>
              <td rowspan="1" colspan="1">64.6</td>
              <td rowspan="1" colspan="1">61.6</td>
              <td rowspan="1" colspan="1">65.7</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Vietnam</td>
              <td rowspan="1" colspan="1">31.4</td>
              <td rowspan="1" colspan="1">32.3</td>
              <td rowspan="1" colspan="1">35.2</td>
              <td rowspan="1" colspan="1">37.9</td>
              <td rowspan="1" colspan="1">37.4</td>
              <td rowspan="1" colspan="1">36.5</td>
              <td rowspan="1" colspan="1">38.4</td>
              <td rowspan="1" colspan="1">40.9</td>
              <td rowspan="1" colspan="1">39.4</td>
              <td rowspan="1" colspan="1">45.2</td>
              <td rowspan="1" colspan="1">48.1</td>
              <td rowspan="1" colspan="1">44.7</td>
              <td rowspan="1" colspan="1">48.4</td>
              <td rowspan="1" colspan="1">52.0</td>
              <td rowspan="1" colspan="1">55.0</td>
              <td rowspan="1" colspan="1">57.4</td>
              <td rowspan="1" colspan="1">59.9 <sup>a)</sup></td>
              <td rowspan="1" colspan="1">58.5 <sup>a)</sup></td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p><sup>a)</sup> The <abbrev xlink:title="International Monetary Fund" id="ABBRID0EDUAG">IMF</abbrev> staff estimate. <italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EJUAG">IMF</abbrev> World Economic Outlook database, October 2018.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Several factors facilitated the improvement in macroeconomic performance of emerging markets in the early and mid-2000s. First, this was the period of global economic boom, which increased demand for commodities produced predominantly by <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EPUAG">EMDEs</abbrev>, and their prices (Fig. <xref ref-type="fig" rid="F6">6</xref>). Part of this boom was fuelled by lax monetary policy in the US and other <abbrev xlink:title="advanced economies" id="ABBRID0EXUAG">AEs</abbrev>, which led to building up bubbles on credit, stock, housing and commodity markets (<xref ref-type="bibr" rid="B10">Dabrowski, 2010</xref>). Busting those bubbles in 2007–2008 was a major cause of the global financial crisis. Second, emerging markets, particularly in <abbrev xlink:title="Emerging and Developing Asia" id="ABBRID0E6UAG">EDA</abbrev>, <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0EDVAG">EDE</abbrev> and <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0EHVAG">LAC</abbrev>, benefited from global and regional trade liberalization in 1990s and early 2000s, which boosted their manufacturing exports and allowed for the inclusion of their producers into global value chains (<abbrev xlink:title="global value chains" id="ABBRID0ELVAG">GVCs</abbrev>). In many instances, this also helped in their structural diversification. Third, they also benefited from financial globalization, which allowed for large-scale inflow of foreign investment (Fig. <xref ref-type="fig" rid="F7">7</xref>) and improvement in resource allocation. Last but not least, most emerging markets benefited from far-reaching economic and institutional reforms in 1990s and 2000s, partly in response to the painful lessons of the previous crises. The transition from a centrally planned to a market economy in <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0ETVAG">EDE</abbrev>, <abbrev xlink:title="former Soviet Union" id="ABBRID0EXVAG">FSU</abbrev>, China and Vietnam is the most prominent case of such reforms. However, market-oriented reforms were also conducted in India, <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0E2VAG">LAC</abbrev>, <abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0E6VAG">SSA</abbrev>, and, to a lesser degree, in <abbrev xlink:title="Middle East and North Africa" id="ABBRID0EDWAG">MENA</abbrev>.</p>
      <fig id="F6" position="float" orientation="portrait">
        <label>Fig. 6.</label>
        <caption>
          <p>Commodity price indexes, 2000–2018 (2005 = 100).</p>
          <p>Source: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EQWAG">IMF</abbrev> World Economic Outlook database, April 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g006.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295029.jpg"/>
      </fig>
      <fig id="F7" position="float" orientation="portrait">
        <label>Fig. 7.</label>
        <caption>
          <p>Net direct investment flows to <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EBXAG">EMDEs</abbrev>, 2000–2017 (US$ billion).</p>
          <p><italic>Note</italic>: Sign (–) means positive net inflow to <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EJXAG">EMDEs</abbrev>. <italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EPXAG">IMF</abbrev> World Economic Outlook database, October 2018.</p>
        </caption>
        <graphic xlink:href="rujec-05-e35506-g007.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295030.jpg"/>
      </fig>
    </sec>
    <sec sec-type="4. New crisis episodes" id="SECID0EYXAG">
      <title>4. New crisis episodes</title>
      <p>In spite of policy improvement discussed in Section 3, emerging-market crises have not disappeared completely. At least three episodes deserve a closer attention: (i) the spill-over effects of the global financial crisis in 2008–2009; (ii) the consequences of decline in oil and commodity prices in 2014–2016 for their exporters; (iii) the turbulence in Argentina and Turkey in 2018.</p>
      <sec sec-type="4.1. Global financial crisis (2008–2009)" id="SECID0E4XAG">
        <title>
          <italic>4.1. Global financial crisis (2008–2009)</italic>
        </title>
        <p>While the global financial crisis of 2008–2009 originated in the US financial sector and hit predominantly <abbrev xlink:title="advanced economies" id="ABBRID0EGYAG">AEs</abbrev>, <abbrev xlink:title="emerging market and developing economies" id="ABBRID0EKYAG">EMDEs</abbrev> did not remain unaffected. After the bankruptcy of the Lehman Brothers on 15 September 2008, international liquidity and credit dried up, and capital started to fly back to the main financial centers, mostly the US. Stock markets and commodity prices declined (see Fig. <xref ref-type="fig" rid="F6">6</xref>), risk premiums for both sovereign and private borrowing grew dramatically, and many emerging-market currencies depreciated (especially in countries which run floating exchange rate regimes), threatening the massive insolvency of economic agents who borrowed in foreign currencies. Those emerging-market banks, non-banking financial institutions and non-financial corporation, which relied on financing on international financial markets, faced liquidity problems, and some of them became insolvent. In the real sphere, external demand for exported goods and labor declined (<xref ref-type="bibr" rid="B10">Dabrowski, 2010</xref>).</p>
        <p>The culmination of the shock was observed in the nine-month period between September 2008 and May 2009. As Table <xref ref-type="table" rid="T2">2</xref> shows, all emerging-market regions were affected but with dominance at <abbrev xlink:title="former Soviet Union" id="ABBRID0E3YAG">FSU</abbrev>, <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0EAZAG">EDE</abbrev> and <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0EEZAG">LAC</abbrev>. The same conclusion can be drawn if one looks at GDP (see Fig. <xref ref-type="fig" rid="F2">2</xref>) and capital flow (see Fig. <xref ref-type="fig" rid="F7">7</xref>) data. In 2009, three regions — <abbrev xlink:title="former Soviet Union" id="ABBRID0EQZAG">FSU</abbrev>, <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0EUZAG">EDE</abbrev> and <abbrev xlink:title="Latin America and Caribbean" id="ABBRID0EYZAG">LAC</abbrev> — recorded output decline while others (<abbrev xlink:title="Emerging and Developing Asia" id="ABBRID0E3ZAG">EDA</abbrev>, <abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0EA1AG">SSA</abbrev>, <abbrev xlink:title="Middle East and North Africa" id="ABBRID0EE1AG">MENA</abbrev>) continued growing albeit at a lower pace. In 2010, all emerging-market regions returned to growth.</p>
        <table-wrap id="T2" position="float" orientation="portrait">
          <label>Table 2.</label>
          <caption>
            <p>Countries most affected by the global financial crisis through financial channels (between September 2008 and May 2009).</p>
          </caption>
          <table id="TID0EZOAI" rules="all">
            <tbody>
              <tr>
                <td rowspan="1" colspan="1">Country</td>
                <td rowspan="1" colspan="1">Currency depreciation (%) against US$</td>
                <td rowspan="1" colspan="1">Bond spreads (bps) against US Treasuries or German bunds (EU)</td>
                <td rowspan="1" colspan="1">Equity market (%)</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Ukraine</td>
                <td rowspan="1" colspan="1">–59.9</td>
                <td rowspan="1" colspan="1">733</td>
                <td rowspan="1" colspan="1">–66</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Argentina</td>
                <td rowspan="1" colspan="1">–21.4</td>
                <td rowspan="1" colspan="1">735</td>
                <td rowspan="1" colspan="1">–58</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Hungary</td>
                <td rowspan="1" colspan="1">–18.9</td>
                <td rowspan="1" colspan="1">283</td>
                <td rowspan="1" colspan="1">–58</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Poland</td>
                <td rowspan="1" colspan="1">–35.2</td>
                <td rowspan="1" colspan="1">127</td>
                <td rowspan="1" colspan="1">–53</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Jamaica</td>
                <td rowspan="1" colspan="1">–20.4</td>
                <td rowspan="1" colspan="1">439</td>
                <td rowspan="1" colspan="1">–51</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Ghana</td>
                <td rowspan="1" colspan="1">–28.0</td>
                <td rowspan="1" colspan="1">448</td>
                <td rowspan="1" colspan="1">–35</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Russia</td>
                <td rowspan="1" colspan="1">–22.0</td>
                <td rowspan="1" colspan="1">144</td>
                <td rowspan="1" colspan="1">–44</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Kazakhstan</td>
                <td rowspan="1" colspan="1">–22.0</td>
                <td rowspan="1" colspan="1">167</td>
                <td rowspan="1" colspan="1">–34</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Bulgaria</td>
                <td rowspan="1" colspan="1">–1.5</td>
                <td rowspan="1" colspan="1">175</td>
                <td rowspan="1" colspan="1">–51</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Mexico</td>
                <td rowspan="1" colspan="1">–22.6</td>
                <td rowspan="1" colspan="1">73</td>
                <td rowspan="1" colspan="1">–35</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Turkey</td>
                <td rowspan="1" colspan="1">–21.7</td>
                <td rowspan="1" colspan="1">44</td>
                <td rowspan="1" colspan="1">–40</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Sri Lanka</td>
                <td rowspan="1" colspan="1">–6.6</td>
                <td rowspan="1" colspan="1">464</td>
                <td rowspan="1" colspan="1">–27</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Indonesia</td>
                <td rowspan="1" colspan="1">–8.8</td>
                <td rowspan="1" colspan="1">85</td>
                <td rowspan="1" colspan="1">–29</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Pakistan</td>
                <td rowspan="1" colspan="1">–6.3</td>
                <td rowspan="1" colspan="1">132</td>
                <td rowspan="1" colspan="1">–26</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">El Salvador</td>
                <td rowspan="1" colspan="1">-0.3</td>
                <td rowspan="1" colspan="1">176</td>
                <td rowspan="1" colspan="1">–35</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Vietnam</td>
                <td rowspan="1" colspan="1">–7.1</td>
                <td rowspan="1" colspan="1">53</td>
                <td rowspan="1" colspan="1">–33</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Lebanon</td>
                <td rowspan="1" colspan="1">-0.3</td>
                <td rowspan="1" colspan="1">57</td>
                <td rowspan="1" colspan="1">–45</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Brazil</td>
                <td rowspan="1" colspan="1">–8.4</td>
                <td rowspan="1" colspan="1">36</td>
                <td rowspan="1" colspan="1">–28</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Chile</td>
                <td rowspan="1" colspan="1">–5.5</td>
                <td rowspan="1" colspan="1">80</td>
                <td rowspan="1" colspan="1">–14</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Tunisia</td>
                <td rowspan="1" colspan="1">–7.7</td>
                <td rowspan="1" colspan="1">62</td>
                <td rowspan="1" colspan="1">–14</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Ecuador</td>
                <td rowspan="1" colspan="1">0</td>
                <td rowspan="1" colspan="1">2528</td>
                <td rowspan="1" colspan="1">–13</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Egypt</td>
                <td rowspan="1" colspan="1">–3.4</td>
                <td rowspan="1" colspan="1">–137</td>
                <td rowspan="1" colspan="1">–39</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Colombia</td>
                <td rowspan="1" colspan="1">–3.4</td>
                <td rowspan="1" colspan="1">63</td>
                <td rowspan="1" colspan="1">–10</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Malaysia</td>
                <td rowspan="1" colspan="1">-0.9</td>
                <td rowspan="1" colspan="1">81</td>
                <td rowspan="1" colspan="1">–12</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Philippines</td>
                <td rowspan="1" colspan="1">-0.1</td>
                <td rowspan="1" colspan="1">53</td>
                <td rowspan="1" colspan="1">–21</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Peru</td>
                <td rowspan="1" colspan="1">-0.4</td>
                <td rowspan="1" colspan="1">42</td>
                <td rowspan="1" colspan="1">–15</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">South Africa</td>
                <td rowspan="1" colspan="1">1.5</td>
                <td rowspan="1" colspan="1">39</td>
                <td rowspan="1" colspan="1">–20</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">China</td>
                <td rowspan="1" colspan="1">0.3</td>
                <td rowspan="1" colspan="1">–31</td>
                <td rowspan="1" colspan="1">–11</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><italic>Source</italic>: Ali et al. (2009).</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>The case of <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0EVGBG">EDE</abbrev> and <abbrev xlink:title="former Soviet Union" id="ABBRID0EZGBG">FSU</abbrev> is perhaps the most interesting. In mid-2000s, these two regions were seen by financial markets as a success story of post-communist transition, which resulted in the acceleration of capital inflows in 2005–2007. In particular, due to its EU membership/ candidacy status and expected fast-track accession to the Eurozone, <abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0E4GBG">EDE</abbrev> was seen by financial markets as a relatively “safe haven”, resulting in exceptionally low risk premiums (<xref ref-type="bibr" rid="B26">Luengnaruemitchai and Schadler, 2007</xref>). On the other hand, the global commodity boom, especially of oil, natural gas, metals and food products, boosted growth in the <abbrev xlink:title="former Soviet Union" id="ABBRID0EFHBG">FSU</abbrev> and improved its investment rating.</p>
        <p>However, financial markets overlooked numerous vulnerabilities in both regions. For example, rapid credit growth and excessive borrowing in foreign currencies led, in many instances, to deterioration of credit portfolios. Unfortunately, it became fully visible only when the crisis hit the region and previously optimistic growth prospects had to be revised. In some countries (Russia, the Baltic countries, Bulgaria and, to a lesser extent, Poland) it also led to a substantial growth of real estate prices before the crisis (<xref ref-type="bibr" rid="B3">Bakker and Klingen, 2012</xref>, p. 7, fig. 1.4).</p>
        <p>After 2008, over-optimistic assessments and expectations had to be corrected which led to the reduction (<abbrev xlink:title="Emerging and Developing Europe" id="ABBRID0ERHBG">EDE</abbrev>) or even reversion (<abbrev xlink:title="former Soviet Union" id="ABBRID0EVHBG">FSU</abbrev>) of capital flows. Several countries in both regions — Armenia, Belarus, Bosnia and Herzegovina, Georgia, Hungary, Kosovo, Kyrgyzstan, Latvia, Moldova, Romania, Serbia, Tajikistan, and Ukraine — had to ask for the <abbrev xlink:title="International Monetary Fund" id="ABBRID0EZHBG">IMF</abbrev> rescue programs to deal with the consequences resulting from a sudden cessation of capital flows.</p>
      </sec>
      <sec sec-type="4.2. Decline in commodity prices (2014–2016)" id="SECID0E4HBG">
        <title>
          <italic>4.2. Decline in commodity prices (2014–2016)</italic>
        </title>
        <p>The decline in commodity prices in 2014–2016 (see Fig. <xref ref-type="fig" rid="F6">6</xref>) generated a heavy macroeconomic shock on commodity producers and exporters. In particular, those countries whose GDP and exports were dominated by oil (the source of highest resource rents) became seriously affected. However, the negative effects were smaller as compared to the similar price decline in the mid-1980s. Better macroeconomic fundamentals (see Section 3) and accumulation of substantial monetary and fiscal buffers (large international reserves of central banks and <abbrev xlink:title="sovereign wealth funds" id="ABBRID0EKIBG">SWFs</abbrev>) in the boom period made oil and other commodity producers more resilient to negative price shock. Furthermore, in many countries these buffers were large enough to launch aggressive countercyclical fiscal and monetary policies that mitigated the negative impact on the real sector. Fig. <xref ref-type="fig" rid="F8">8</xref> shows that in most oil-producing countries growth in real GDP continued in the crisis period, albeit at slower pace.</p>
        <p>Nevertheless, there was a group of oil exporters such as Algeria, Azerbaijan, Belarus<sup><xref ref-type="fn" rid="en4">4</xref></sup>, Kazakhstan, Malaysia, Nigeria, Russia and Venezuela, which suffered from substantial depreciation of their currencies (Fig. <xref ref-type="fig" rid="F9">9</xref>), surge in inflation and banking sector problems. In the case of Venezuela and Nigeria, these were consequences of overspending in the boom period and populist economic policies, in <abbrev xlink:title="former Soviet Union" id="ABBRID0E4IBG">FSU</abbrev> countries — effect of macroeconomic and financial fragility caused by past crises and poor business climate (Dabrowski, 2016). The US and EU economic sanctions against Russia launched in 2014 in response to its annexation of Crimea and intervention in Donbas magnified the negative effect of oil price decline on this country (<xref ref-type="bibr" rid="B12">Dabrowski, 2015</xref>).</p>
        <fig id="F8" position="float" orientation="portrait">
          <label>Fig. 8.</label>
          <caption>
            <p>Oil producers: annual real GDP growth, 2013 and 2015 (%).</p>
            <p>Source: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EOJBG">IMF</abbrev> World Economic Outlook database, October 2018.</p>
          </caption>
          <graphic xlink:href="rujec-05-e35506-g008.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295031.jpg"/>
        </fig>
        <fig id="F9" position="float" orientation="portrait">
          <label>Fig. 9.</label>
          <caption>
            <p>Depreciation of oil exporters’ currencies between 30.06.2014 and 30.09.2015 (US$ per local currency unit, percentage change).</p>
            <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0ECKBG">IMF</abbrev> International Financial Statistics.</p>
          </caption>
          <graphic xlink:href="rujec-05-e35506-g009.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295032.jpg"/>
        </fig>
      </sec>
      <sec sec-type="4.3. Troubles of Argentina and Turkey (2018)" id="SECID0ELKBG">
        <title>
          <italic>4.3. Troubles of Argentina and Turkey (2018)</italic>
        </title>
        <p>In 2018, the currencies of two large emerging-market economies and members of the G20 — Argentina and Turkey — suffered from substantial depreciation. The culmination of the speculative attack came in August and September 2018. Other currencies, including the Indian rupee, Indonesian rupiah, Brazilian real, Pakistani rupee, Russian rouble and South African rand also recorded losses, but smaller ones compared to Argentina and Turkey (Fig. <xref ref-type="fig" rid="F10">10</xref>).</p>
        <p>The spreads on credit default swaps (<abbrev xlink:title="credit default swaps" id="ABBRID0E1KBG">CDS</abbrev>) for Argentinian and Turkish government bonds denominated in US dollars (Fig. <xref ref-type="fig" rid="F11">11</xref>) started to increase from the beginning of 2018, but picked up dramatically in August and September 2018 — by some 400 basis points for Argentina and 300 basis points for Turkey. Even though they decreased at the end of September and early October 2018, they continued to stay far above the pre-crisis level.</p>
        <fig id="F10" position="float" orientation="portrait">
          <label>Fig. 10.</label>
          <caption>
            <p>Depreciation of emerging-market currencies between 31.12.2017 and 30.09.2018 (US$ per local currency unit, percentage change).</p>
            <p><italic>Source</italic>: <ext-link xlink:type="simple" ext-link-type="uri" xlink:href="https://www.x-rates.com/historical/?from=USD%26amount=1%26date=2018-09-30">https://www.x-rates.com/historical/?from=USD&amp;amount=1&amp;date=2018-09-30</ext-link></p>
          </caption>
          <graphic xlink:href="rujec-05-e35506-g010.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295033.jpg"/>
        </fig>
        <fig id="F11" position="float" orientation="portrait">
          <label>Fig. 11.</label>
          <caption>
            <p><abbrev xlink:title="credit default swaps" id="ABBRID0E5LBG">CDS</abbrev> of Argentina and Turkey, 5-year US dollar denominated government bonds, 2017–2018 (basis points).</p>
            <p><italic>Source</italic>: Bloomberg database.</p>
          </caption>
          <graphic xlink:href="rujec-05-e35506-g011.jpg" position="float" orientation="portrait" xlink:type="simple" id="oo_295034.jpg"/>
        </fig>
        <p>Both countries have been characterized by numerous macro- and microeconomic vulnerabilities, which made them potential victims of market pressure.</p>
        <p>Argentina recorded high and increasing inflation and fiscal deficit, and several episodes of recession since the period of global financial crisis of 2008–2009 (Table <xref ref-type="table" rid="T3">3</xref>). This resulted from the populist policies of President Cristina Fernandez de Kirchner, who ruled the country between 2007 and 2015. These policies included excessive public spending in the years of the commodity boom; price, foreign exchange and export controls; energy subsidies; a complex and non-transparent tax system; trade protectionism; manipulation of price and GDP statistics; the undermining of central bank and judicial independence (<xref ref-type="bibr" rid="B33">OECD, 2017</xref>).</p>
        <table-wrap id="T3" position="float" orientation="portrait">
          <label>Table 3.</label>
          <caption>
            <p>Argentina and Turkey: basic macroeconomic indicators, 2007–2017.</p>
          </caption>
          <table id="TID0EEEBI" rules="all">
            <tbody>
              <tr>
                <td rowspan="1" colspan="1">Subject descriptor</td>
                <td rowspan="1" colspan="1">2007</td>
                <td rowspan="1" colspan="1">2008</td>
                <td rowspan="1" colspan="1">2009</td>
                <td rowspan="1" colspan="1">2010</td>
                <td rowspan="1" colspan="1">2011</td>
                <td rowspan="1" colspan="1">2012</td>
                <td rowspan="1" colspan="1">2013</td>
                <td rowspan="1" colspan="1">2014</td>
                <td rowspan="1" colspan="1">2015</td>
                <td rowspan="1" colspan="1">2016</td>
                <td rowspan="1" colspan="1">2017</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <italic>Argentina</italic>
                </td>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Real GDP growth, %</td>
                <td rowspan="1" colspan="1">9.0</td>
                <td rowspan="1" colspan="1">4.1</td>
                <td rowspan="1" colspan="1">–5.9</td>
                <td rowspan="1" colspan="1">10.1</td>
                <td rowspan="1" colspan="1">6.0</td>
                <td rowspan="1" colspan="1">–1.0</td>
                <td rowspan="1" colspan="1">2.4</td>
                <td rowspan="1" colspan="1">–2.5</td>
                <td rowspan="1" colspan="1">2.7</td>
                <td rowspan="1" colspan="1">–1.8</td>
                <td rowspan="1" colspan="1">2.9</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Inflation, e-o-p, %</td>
                <td rowspan="1" colspan="1">8.5</td>
                <td rowspan="1" colspan="1">7.2</td>
                <td rowspan="1" colspan="1">7.7</td>
                <td rowspan="1" colspan="1">10.9</td>
                <td rowspan="1" colspan="1">9.5</td>
                <td rowspan="1" colspan="1">10.8</td>
                <td rowspan="1" colspan="1">10.9</td>
                <td rowspan="1" colspan="1">23.9</td>
                <td rowspan="1" colspan="1">n/a</td>
                <td rowspan="1" colspan="1">n/a</td>
                <td rowspan="1" colspan="1">24.8</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">GG net lending/borrowing, % of GDP</td>
                <td rowspan="1" colspan="1">–0.1</td>
                <td rowspan="1" colspan="1">0.2</td>
                <td rowspan="1" colspan="1">–2.6</td>
                <td rowspan="1" colspan="1">–1.4</td>
                <td rowspan="1" colspan="1">–2.7</td>
                <td rowspan="1" colspan="1">–3.0</td>
                <td rowspan="1" colspan="1">–3.3</td>
                <td rowspan="1" colspan="1">–4.3</td>
                <td rowspan="1" colspan="1">–6.0</td>
                <td rowspan="1" colspan="1">–6.6</td>
                <td rowspan="1" colspan="1">–6.7</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">GG gross debt, % of GDP</td>
                <td rowspan="1" colspan="1">61.0</td>
                <td rowspan="1" colspan="1">52.6</td>
                <td rowspan="1" colspan="1">53.8</td>
                <td rowspan="1" colspan="1">42.0</td>
                <td rowspan="1" colspan="1">37.5</td>
                <td rowspan="1" colspan="1">38.9</td>
                <td rowspan="1" colspan="1">41.7</td>
                <td rowspan="1" colspan="1">43.6</td>
                <td rowspan="1" colspan="1">55.1</td>
                <td rowspan="1" colspan="1">55.0</td>
                <td rowspan="1" colspan="1">57.6</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Current account balance, % of GDP</td>
                <td rowspan="1" colspan="1">2.1</td>
                <td rowspan="1" colspan="1">1.5</td>
                <td rowspan="1" colspan="1">2.2</td>
                <td rowspan="1" colspan="1">–0.4</td>
                <td rowspan="1" colspan="1">–1.0</td>
                <td rowspan="1" colspan="1">-0.4</td>
                <td rowspan="1" colspan="1">–2.1</td>
                <td rowspan="1" colspan="1">–1.6</td>
                <td rowspan="1" colspan="1">–2.7</td>
                <td rowspan="1" colspan="1">–2.7</td>
                <td rowspan="1" colspan="1">–4.9</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <italic>Turkey</italic>
                </td>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Real GDP growth, %</td>
                <td rowspan="1" colspan="1">5.0</td>
                <td rowspan="1" colspan="1">0.8</td>
                <td rowspan="1" colspan="1">–4.7</td>
                <td rowspan="1" colspan="1">8.5</td>
                <td rowspan="1" colspan="1">11.1</td>
                <td rowspan="1" colspan="1">4.8</td>
                <td rowspan="1" colspan="1">8.5</td>
                <td rowspan="1" colspan="1">5.2</td>
                <td rowspan="1" colspan="1">6.1</td>
                <td rowspan="1" colspan="1">3.2</td>
                <td rowspan="1" colspan="1">7.4</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Inflation, e-o-p, %</td>
                <td rowspan="1" colspan="1">8.4</td>
                <td rowspan="1" colspan="1">10.1</td>
                <td rowspan="1" colspan="1">6.5</td>
                <td rowspan="1" colspan="1">6.4</td>
                <td rowspan="1" colspan="1">10.4</td>
                <td rowspan="1" colspan="1">6.2</td>
                <td rowspan="1" colspan="1">7.4</td>
                <td rowspan="1" colspan="1">8.2</td>
                <td rowspan="1" colspan="1">8.8</td>
                <td rowspan="1" colspan="1">8.5</td>
                <td rowspan="1" colspan="1">11.9</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">GG net lending/borrowing, % of GDP</td>
                <td rowspan="1" colspan="1">–1.9</td>
                <td rowspan="1" colspan="1">–2.7</td>
                <td rowspan="1" colspan="1">–5.9</td>
                <td rowspan="1" colspan="1">–3.4</td>
                <td rowspan="1" colspan="1">-0.7</td>
                <td rowspan="1" colspan="1">–1.8</td>
                <td rowspan="1" colspan="1">–1.5</td>
                <td rowspan="1" colspan="1">–1.4</td>
                <td rowspan="1" colspan="1">–1.3</td>
                <td rowspan="1" colspan="1">–2.3</td>
                <td rowspan="1" colspan="1">–2.3</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">GG gross debt, % of GDP</td>
                <td rowspan="1" colspan="1">38.2</td>
                <td rowspan="1" colspan="1">38.2</td>
                <td rowspan="1" colspan="1">43.9</td>
                <td rowspan="1" colspan="1">40.1</td>
                <td rowspan="1" colspan="1">36.5</td>
                <td rowspan="1" colspan="1">32.7</td>
                <td rowspan="1" colspan="1">31.4</td>
                <td rowspan="1" colspan="1">28.8</td>
                <td rowspan="1" colspan="1">27.6</td>
                <td rowspan="1" colspan="1">28.3</td>
                <td rowspan="1" colspan="1">28.3</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Current account balance, % of GDP</td>
                <td rowspan="1" colspan="1">–5.5</td>
                <td rowspan="1" colspan="1">–5.2</td>
                <td rowspan="1" colspan="1">–1.8</td>
                <td rowspan="1" colspan="1">–5.8</td>
                <td rowspan="1" colspan="1">–8.9</td>
                <td rowspan="1" colspan="1">–5.5</td>
                <td rowspan="1" colspan="1">–6.7</td>
                <td rowspan="1" colspan="1">–4.7</td>
                <td rowspan="1" colspan="1">–3.7</td>
                <td rowspan="1" colspan="1">–3.8</td>
                <td rowspan="1" colspan="1">–5.6</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p><italic>Source</italic>: <abbrev xlink:title="International Monetary Fund" id="ABBRID0EP3BG">IMF</abbrev> World Economic Outlook database, April 2018.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>The case of Turkey was slightly different. The country recorded high growth and ran a moderately prudent fiscal policy. However, its monetary policy was too lax — as demonstrated by increasing inflation (much higher than the levels of its main trading partners) and low interest rates (negative in real terms). Furthermore, an authoritarian trend in domestic politics led to a deterioration in economic institutions and the reversal of many reforms of the early 2000s (<xref ref-type="bibr" rid="B1">Acemoglu and Ucer, 2015</xref>). For example, the Central Bank of the Republic of Turkey (<abbrev xlink:title="Central Bank of the Republic of Turkey" id="ABBRID0EZ3BG">CBRT</abbrev>) was under pressure to avoid an increase in interest rates backed by an “unorthodox” president’s opinion that higher interest rates lead to higher inflation.</p>
        <p>The failed military coup d’état in 2016 led to massive personal purges in the judiciary and public administration, which also meant deterioration in economic governance. The new round of ethnic conflict with the Kurdish minority, engagement in the conflict in Syria, tensions with traditional allies (the US and Europe) and practical freezing of the EU accession process forced many investors to reassess geopolitical risks and prospects of deeper integration with the EU economy.</p>
        <p>In 2017–2018, both countries recorded increasing current account deficits. In Argentina, this has been the effect of fiscal imbalance and a low rate of private saving; in Turkey, it has been born of private sector over-borrowing and an investment boom. In principle, such deficits can be seen as a normal phenomenon in the world of unrestricted capital movement, in which investors seek the highest rate of return (<xref ref-type="bibr" rid="B11">Dabrowski, 2013</xref>). However, if a country has limited access to the world capital market (Argentina), if its domestic investment climate is not rated favorably and if macroeconomic policies are too expansionary (both cases), then the increasing current account deficit should serve as a warning signal and strong argument in favor of policy correction.</p>
        <p>Both Turkey and Argentina have also had reputation problems due to several macroeconomic and financial crises in their history (Reinhart and Rogoff, 2009). The most recent episodes happened in both countries not so long ago, in 2000–2002 (see Section 2.4). Widespread spontaneous dollarization reflected their continuous macroeconomic fragility even in good times.</p>
      </sec>
    </sec>
    <sec sec-type="5. Potential risk factors" id="SECID0EF4BG">
      <title>5. Potential risk factors</title>
      <p>While the aim of this paper is not to speculate whether, in the coming months and years, we will see more crisis episodes and which countries could be affected, the risk of such developments remains relatively high. This has been caused, in the first instance, by tightening of US monetary policy in 2016–2018. Although the Federal Open Market Committee of the US Federal Reserve Board suspended its tightening cycle on 20 March 2019,<sup><xref ref-type="fn" rid="en5">5</xref></sup> it is very likely that it will be resumed when inflation pressure intensifies.</p>
      <p>Historical experience tells us that increasing interest rates in the US have usually led to the US dollar strengthening, capital outflow from emerging markets, and pressure on their currencies. To resist these pressures, domestic interest rates must also be taken up, thus increasing the cost of credit to economy and the cost of servicing public debt.</p>
      <p>The increasing global economic uncertainty associated with protectionist policies, such as the Trump administration is implementing in the US, is another factor which can hit many emerging-market economies, in particular those that developed export-oriented manufacturing capacity and participate in <abbrev xlink:title="global value chains" id="ABBRID0ET4BG">GVCs</abbrev>. If the pessimistic scenario of gradual decomposition of the existing global trading system materializes (see <xref ref-type="bibr" rid="B15">Dadush and Wolff, 2019</xref>) it will destroy many <abbrev xlink:title="global value chains" id="ABBRID0E24BG">GVCs</abbrev> and create heavy adverse shock to those emerging markets, which have become deeply involved in the international division of labor. This may lead to the partial undoing of the positive effects of globalization, including income-per-capita convergence in several emerging-market economies.</p>
      <p>It is also worth reflecting that most of the factors that contributed to emerging-market boom in the first two decades of the 21st century (see Section 3) do not work any longer. This concerns, for example, positive effects of post-communist transition and economic reforms in other emerging-market regions. In most countries, the reform process stopped around mid-2000s and, in some cases, earlier reforms were even partly reversed. Two decades of good economic performance weakened pressure for further reforms and, in many instances, increased the temptation to return to imprudent policies (see Section 6).</p>
      <p>The positive effects of trade liberalization under the Uruguay Round (completed in 1994) were largely consumed by mid-2000s while new trade negotiation under the Doha Round failed. Similarly, productivity gains of the information and communication revolution that gave a strong boost to global growth between mid-1990s and mid-2000s have been much weaker thereafter (<xref ref-type="bibr" rid="B20">Gordon, 2016</xref>, pp. 601–602).</p>
      <p>The same concerns the peace dividend after the end of Cold War in 1990s, which many countries benefited from. These gains started to disappear in the early 2000s as a result of the “war on terror”. Further deterioration has been noticed in the decade of the 2010s, especially in the <abbrev xlink:title="Middle East and North Africa" id="ABBRID0EI5BG">MENA</abbrev>, <abbrev xlink:title="Sub-Saharan Africa" id="ABBRID0EM5BG">SSA</abbrev> and <abbrev xlink:title="former Soviet Union" id="ABBRID0EQ5BG">FSU</abbrev> regions. Violent conflicts and increasing geopolitical rivalry of global and regional powers negatively influence the business and investment climate, leading to higher military and security spending at the cost of other public goods such as education, health or infrastructure, and damaging trade in goods and services (especially in such security-sensitive sectors as tourism or transportation).</p>
      <p>All these risks create challenge not only for emerging-market economies. The global impact of any large-scale emerging-market crisis can be much stronger now than it was in 1980s and 1990s for the simple reason that the share of emerging markets in global GDP and global trade has increased since then.</p>
    </sec>
    <sec sec-type="6. Crisis prevention and crisis management" id="SECID0EV5BG">
      <title>6. Crisis prevention and crisis management</title>
      <p>Given a risk of new emerging-market turmoil (see Section 5) and its potentially devastating impact on the world economy, policies aimed at crisis prevention are extremely important. If a crisis happens anyway, equally important is to ensure competent management, so as to minimize its costs and the risk of cross-border spill-over or contagion. In our discussion of crisis prevention policies and crisis management, we will concentrate on the recent cases of Argentina and Turkey.</p>
      <sec sec-type="6.1. The role of early warning signals" id="SECID0E15BG">
        <title>
          <italic>6.1. The role of early warning signals</italic>
        </title>
        <p>As in many similar cases in the past, Argentina and Turkey could have avoided their 2018 crises if their policies had been corrected in time. Both were warned well in advance by international organizations such as the <xref ref-type="bibr" rid="B21">IMF (2014</xref>; <xref ref-type="bibr" rid="B22">2016</xref>) and <xref ref-type="bibr" rid="B32">OECD (2016</xref>; <xref ref-type="bibr" rid="B33">2017</xref>). Each country was advised to tighten monetary and fiscal policies in order to curb inflation, and to conduct a series of structural and regulatory reforms to improve the business climate. In addition, Argentina was advised to remove distortions of Kirchner’s era and Turkey was warned of the risk of overheating.<sup><xref ref-type="fn" rid="en6">6</xref></sup> However, either they did not follow these recommendations (Turkey) or they followed them too slowly (Argentina).</p>
        <p>There are many reasons why politicians are reluctant to correct unsustainable policies.</p>
        <p><italic>First</italic>, they are afraid that corrections mean admitting the shortcomings of previous policies — especially if they have been engaged in defending them by use of various “non-orthodox” doctrines.</p>
        <p><italic>Second</italic>, the required policy tightening often remains in conflict with the political timetable; for example, forthcoming elections. In Turkey, this was the constitutional referendum on 16 April 2017 and presidential and parliamentary elections on 24 June 2018.</p>
        <p><italic>Third</italic>, financial markets rarely react immediately to imprudent policies, especially in tranquil times. Rather, their reaction has a non-linear character, a typical case of multiple equilibria. Politicians often misinterpret such delayed reaction as the tacit approval of their policies. It creates a feeling of impunity and a temptation to continue testing market tolerance.</p>
        <p>When the market wake-up call finally comes — in the form of higher yields for government bonds, greater spreads on <abbrev xlink:title="credit default swaps" id="ABBRID0EIAAI">CDS</abbrev>, inflationary pressure, capital outflow, banking panic, or all these phenomena together — it is usually too late for minor adjustment steps. More bold and comprehensive actions are required to stop market panic and reverse negative expectations. They are costlier, economically and politically, than earlier corrective measures.</p>
      </sec>
      <sec sec-type="6.2. Fighting crisis: gradual stabilization is not a remedy" id="SECID0EMAAI">
        <title>
          <italic>6.2. Fighting crisis: gradual stabilization is not a remedy</italic>
        </title>
        <p>However, even when crisis is already at the door, governments and central banks often are not ready to act quickly and decisively, choosing instead a strategy of gradual adjustment. This is caused either by an underestimation of the real threat, or a belief that gradual changes will be politically more acceptable and involve smaller output and employment losses, or both. However, a strategy of gradual adjustment works best when policy corrections are done in advance — that is, when the macroeconomic situation is still relatively good and under control. This is also an acceptable approach in the case of more complex structural and institutional changes, under condition that the entire reform plan remains credible and will not be abandoned when the economic situation starts to improve. However, gradual adjustment does not work in an environment of speculative pressure and financial-market panic, because it lacks credibility and is unable to change market expectations. Furthermore, it extends the period of pain and delays the perception of improvement.</p>
        <p>Unfortunately, authorities of both analyzed countries were not ready to act quickly and decisively enough when the first signs of the forthcoming crisis were tangible. The <abbrev xlink:title="Central Bank of the Republic of Turkey" id="ABBRID0EWAAI">CBRT</abbrev> took its first decision to increase the one-week repo auction rate from 8.00% to 16.50% on 1 June 2018, followed by another hike to 17.75% one week later.<sup><xref ref-type="fn" rid="en7">7</xref></sup> These higher interest rates were not able to stop capital outflow and abrupt depreciation of Turkish lira in August and September, especially because they were not supported by other policy measures — in particular, in the fiscal sphere.</p>
        <p>This led to one more hike to 24% on 14 September 2018. In October 2018, yields on five-year government bonds denominated in US dollars amounted to more than 7%, and on 10-year bonds stayed around 8% (Pan and Samson, 2018). The anti-crisis actions and policy statements remained contradictory (<xref ref-type="bibr" rid="B40">Smith, 2018</xref>).</p>
        <p>Argentina’s story is even more illustrative of the ineffectiveness of gradual stabilization. President Mauricio Macri won the 2015 election on the promise to depart from the populist policies of his predecessor and restore macroeconomic stability. However, reforms that were implemented were slow and not always consistent enough, and the macroeconomic policy stance remained loose — as illustrated by Table <xref ref-type="table" rid="T3">3</xref>.</p>
        <p>After the first signs of market pressures at the end of 2017, macroeconomic policy was tightened but not enough to change expectations. Episodes of market panics were repeated several times, especially in August and September 2018. The Central Bank of the Republic of Argentina increased its key interest rate in several steps — from 27.25% in April to 72.83% on October 4<sup>th</sup> 2018<sup><xref ref-type="fn" rid="en8">8</xref></sup> — but the situation remained very fragile.</p>
        <p>Politically, the new administration wasted the window of opportunity to stabilize and reform the economy in the first two years of its term, when the blame could be put on the previous government. As result, it had to fight a crisis that was largely attributed to its own indecisive actions, and tighten policy a year before the next election and during the country’s presidency of G20.</p>
      </sec>
    </sec>
    <sec sec-type="7. Summary: lessons to be learnt" id="SECID0EVBAI">
      <title>7. Summary: lessons to be learnt</title>
      <p>The 2018 turmoil in Argentina and Turkey, still limited by historical standards, should serve as both the warning signal and source of policy lessons for both countries in trouble and others, including advanced economies, many of which walk on the edge of fiscal sustainability (examples include Japan or Italy).</p>
      <p>First, the era of extremely low interest rates in <abbrev xlink:title="advanced economies" id="ABBRID0E3BAI">AEs</abbrev> is coming to an end. This will have a strong impact on both them and emerging markets, in terms of direction of capital flows, public and private debt sustainability, financial sector stability, growth dynamics, and many others.</p>
      <p>Second, the growth recovery, which started in <abbrev xlink:title="advanced economies" id="ABBRID0ECCAI">AEs</abbrev> in 2017, could be short-lived, due to tensions in the global trade system, other geopolitical and security risks, supply-side constraints such as shrinking and ageing population and necessary tightening of monetary and fiscal policies. If growth in <abbrev xlink:title="advanced economies" id="ABBRID0EGCAI">AEs</abbrev> weakens, this will have an additional negative impact on emerging-market economies.</p>
      <p>Third, populist policies that ignore fiscal and monetary arithmetic are always of a limited lifespan. The question is only when the country will have to pay for such policies and how much.</p>
      <p>Fourth, if economic policy requires corrections, it is always better and less expensive — in economic and political terms — to introduce them sooner rather than later. If the country faces the risk of becoming a victim of market turmoil, the policy adjustment should be fast and strong enough to arrest negative trends immediately and create positive expectations.</p>
      <p>Although the above policy lessons are not new, they have to be repeated again and again. The memory of politicians is usually short as they tend to concentrate on current developments and concerns. Thus, if there have not been recently major crisis episodes, politicians tend to ignore risks and believe that “this time is different”, referring to the title of Reinhart and Rogoff’s (2009) historical analysis of financial crises.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn id="en1">
        <p>Earlier, in March 1981, the Government of Poland declared default on its debt to foreign banks. However, due to the autarkic economic model based on central planning this default did not lead to external spillovers.</p>
      </fn>
      <fn id="en2">
        <p>Following the IMF World Economic outlook database (October 2018 edition), we disaggregate the global economy into two subgroups: (1) advanced economies (AEs); and (2) emerging market and developing economies (EMDEs). The latter is a broader category than the emerging-market economies analyzed in this paper because it also covers low-income countries weakly integrated into a global economy (see Section 2.3).</p>
      </fn>
      <fn id="en3">
        <p>The BRICS acronym stands for Brazil, Russia, India, China and South Africa and was originally introduced by <xref ref-type="bibr" rid="B34">O’Neill (2001)</xref> as BRIC for Brazil. Russia, India and China (South Africa was added later).</p>
      </fn>
      <fn id="en4">
        <p>Belarus is not a producer of crude oil but it imports Russian crude oil at Russian domestic prices (lower than international ones) and then re-exports oil products at international prices.</p>
      </fn>
      <fn id="en5">
        <p>See <ext-link xlink:type="simple" ext-link-type="uri" xlink:href="https://www.federalreserve.gov/newsevents/pressreleases/monetary20190320a.htm">https://www.federalreserve.gov/newsevents/pressreleases/monetary20190320a.htm</ext-link></p>
      </fn>
      <fn id="en6">
        <p>The first signs of market vulnerability of the Turkish lira were already observed at the end of 2013 (<xref ref-type="bibr" rid="B35">O’Neill, 2018</xref>).</p>
      </fn>
      <fn id="en7">
        <p>
          <ext-link xlink:type="simple" ext-link-type="uri" xlink:href="http://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Core+Functions/Monetary+Policy/Central+Bank+Interest+Rates/1+Week+Repo">http://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Core+Functions/Monetary+Policy/Central+Bank+Interest+Rates/1+Week+Repo</ext-link>
        </p>
      </fn>
      <fn id="en8">
        <p>
          <ext-link xlink:type="simple" ext-link-type="uri" xlink:href="https://countryeconomy.com/key-rates/argentina">https://countryeconomy.com/key-rates/argentina</ext-link>
        </p>
      </fn>
    </fn-group>
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