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   <subfield code="z">9781484373095</subfield>
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   <subfield code="a">1018-5941</subfield>
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   <subfield code="a">Hlatshwayo, Sandile.</subfield>
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  <datafield tag="245" ind1="1" ind2="4">
   <subfield code="a">The Measurement and Macro-Relevance of Corruption : </subfield>
   <subfield code="b">A Big Data Approach /</subfield>
   <subfield code="c">Sandile Hlatshwayo, Anne Oeking, Manuk Ghazanchyan, David Corvino.</subfield>
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   <subfield code="a">Washington, D.C. :</subfield>
   <subfield code="b">International Monetary Fund,</subfield>
   <subfield code="c">2018.</subfield>
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  <datafield tag="300" ind1=" " ind2=" ">
   <subfield code="a">1 online resource (72 pages)</subfield>
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   <subfield code="a">IMF Working Papers</subfield>
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   <subfield code="a">&lt;strong&gt;Off-Campus Access:&lt;/strong&gt; No User ID or Password Required</subfield>
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   <subfield code="a">&lt;strong&gt;On-Campus Access:&lt;/strong&gt; No User ID or Password Required</subfield>
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   <subfield code="a">Electronic access restricted to authorized BRAC University faculty, staff and students</subfield>
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   <subfield code="a">Corruption is macro-relevant for many countries, but is often hidden, making measurement of it-and its effects-inherently difficult. Existing indicators suffer from several weaknesses, including a lack of time variation due to the sticky nature of perception-based measures, reliance on a limited pool of experts, and an inability to distinguish between corruption and institutional capacity gaps. This paper attempts to address these limitations by leveraging news media coverage of corruption. We contribute to the literature by constructing the first big data, cross-country news flow indices of corruption (NIC) and anti-corruption (anti-NIC) by running country-specific search algorithms over more than 665 million international news articles. These indices correlate well with existing measures of corruption but offer additional richness in their time-series variation. Drawing on theory from the corporate finance and behavioral economics literature, we also test to what extent news about corruption and anti-corruption efforts affects economic agents' assessments of corruption and, in turn, economic outcomes. We find that NIC shocks appear to negatively impact both financial (e.g., stock market returns and yield spreads) and real variables (e.g., growth), albeit with some country heterogeneity. On average, NIC shocks lower real per capita GDP growth by 3 percentage points over a two-year period, illustrating persistence in the effect of such shocks. Conversely, there is suggestive evidence that anti-NIC efforts appear to have a sustained positive macro impact only when paired with meaningful institutional strengthening, proxied by capacity development efforts.</subfield>
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   <subfield code="a">Mode of access: Internet</subfield>
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  <datafield tag="650" ind1=" " ind2="7">
   <subfield code="a">Anti-Corruption Effort</subfield>
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   <subfield code="a">Corruption</subfield>
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   <subfield code="a">NIC Country</subfield>
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   <subfield code="a">NIC Shock</subfield>
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   <subfield code="a">Corvino, David.</subfield>
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   <subfield code="a">Ghazanchyan, Manuk.</subfield>
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   <subfield code="a">Oeking, Anne.</subfield>
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  <datafield tag="830" ind1=" " ind2="0">
   <subfield code="a">IMF Working Papers; Working Paper ;</subfield>
   <subfield code="v">No. 2018/195</subfield>
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   <subfield code="z">Full text available on IMF</subfield>
   <subfield code="u">http://elibrary.imf.org/view/journals/001/2018/195/001.2018.issue-195-en.xml</subfield>
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