Are women less corrupt in business? We revisit this question using firm-level data from the World Bank's Enterprise Surveys, which measure firms' experience of corruption and the gender of their owners and top managers. We find that women in positions of influence are associated with less corruption: female-owned businesses pay less in bribes and corruption is seen as less of an obstacle in companies where women are represented in top management. By providing evidence that women are, ethically at least, good for business our research contributes to the literature on development, gender equality, and corruption more generally.JEL Classification: D73, G32, J16, M14
This paper proves that automatic translation of multilingual newspaper documents deters neither human nor computer classification of political concepts. We show how theory-driven coding of newspaper text can be automated in several languages by monolingual researchers. Supervised machine learning is successfully applied to text in English from British, Spanish, and German sources. The paper has three main findings. First, results from human coding directly in a foreign language do not differ from coding computer-translated text. Second, humans can code translated text as well as they can code untranslated prose in their mother tongue. Third, machine learning based on translated Spanish and German training sets can reproduce human coding as accurately as a system learning from English training sets. �
Political economists disagree about the extent to which markets monitor politics in advanced economies. Some argue that investors are interested in a handful of macroeconomic indicators, while others say that markets also watch political competition closely. We argue that political competition drives variation in the government bond market more than information about economic policy. Using a new automatic classifier, we code the content of millions of newspaper paragraphs about the UK from 1986 to 2012. We then test the impact of news on government debt. We find that political news is correlated with bond prices and that macroeconomic policy news is not. Our results suggest that the market passes daily judgement on politics, not merely cleaving to seldomreleased official statistics or focusing on occasional events like elections.
Election coverage is often assumed to be different to everyday political coverage. We argue that this depends on political institutions. In majoritarian countries, where elections choose governments, election coverage should decisively move towards political competition and away from policy. In consensual countries, where coalitions are based on policy negotiations, there should be a less pronounced shift towards political competition and away from policy. To test this argument, we use an automatic coding system to study 0.9 billion words in Die Welt for 12 years and in the Financial Times for 30 years. The results support our institutional hypothesis.
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