The Measurement and Macro-Relevance of Corruption: A Big Data Approach

Abstract

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, crosscountry 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.

Automatizált szöveganalitika a korrupció kutatásában

“…A kvantitatív módszert használó cikkeket részletesebben is tárgyaljuk. Az NLP-re támaszkodó tanulmányokra koncentrálunk, de előbb az IMF Working Paper-jét (Hlatshwayo et al, 2018) emelnénk ki, annak szisztematikus, átfogó jellege, és az IMF mint szereplő fontossága miatt. Az írás egy, 665 millió sajtócikket tartalmazó nemzetközi gyűjteményből indul ki és a big data megközelítést követő "cross-country news flow indices of corruption" 5 (NIC) indexre támaszkodva jellemzi a korrupció mértékét, dinamikáját és országközi eltéréseit.…”

Measuring Social Unrest Using Media Reports

“…Like us, these authors use an algorithm which counts the frequency of articles that refer to geopolitical risks in leading newspapers published in the US, UK, and Canada, although in their case ProQuest Historical Newspapers and ProQuest News stream are the primary sources. Finally, Hlatshwayo et al (2018) construct a cross-country news-based flow indexes of corruption and anti-corruption by reviewing 665 million international news articles provided by Factiva. They show that shocks in the corruption index are associated to negative impacts on asset prices and economic activity.…”

Descontrole ou inflexão? A política fiscal do governo Dilma e a crise econômica

“…Tal impacto não é uma particularidade brasileira, como mostram dois estudos recentes produzidos respectivamente pelo FMI e pelo Banco Central Europeu. No primeiro, Hlatshwayo et al (2017), após construir e analisar indicadores do fluxo de notícias sobre corrupção e de notícias sobre esforços anti-corrupção na imprensa internacional, concluem que, especialmente em países em desenvolvimento, choques no primeiro indicador parecem de fato afetar negativamente e de forma persistente variáveis tanto financeiras como reais, e que choques no segundo indicador somente podem gerar resultados positivos se tiverem impacto na redução de notícias sobre corrupção e caso ocorram mudanças institucionais significativas. Já no segundo estudo, Marrazzo e Terzi (2017), após analisar o efeito de 23 pacotes amplos de reforma entre 1961 e 2000, mostram que "ondas de reformas estruturais" tendem a impactar negativamente o crescimento do PIB nos primeiros anos após sua implantação, e a produzir impactos positivos em média somente cinco anos após sua ocorrência, tempo que é geralmente maior em países em desenvolvimento.…”