Global Political Ties and the Global Financial Cycle
Gene Ambrocio, Iftekhar Hasan, Xiang Li
IWH Discussion Papers,
No. 23,
2023
Abstract
We study the implications of forging stronger political ties with the US on the sensitivities of stock returns around the world to a global common factor – the global financial cycle. Using voting patterns at the United Nations as a measure of political ties with the US along with various measures of the global financial cycle, we document evidence indicating that stronger political ties with the US amplify the sensitivities of stock returns in developing countries to the global financial cycle. We explore several channels and find that a deepening of financial linkages along with a reduction in information asymmetries and an amplification of sentiment are potentially important factors behind this result.
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Three Essays on Cross-Firm Interactions
William McShane
PhD Thesis, Otto-von-Guericke-Universität Magdeburg,
2023
Abstract
Competition in the U.S. appears to have declined. One contributing factor may have been heterogeneity in the availability of credit during the financial crisis. I examine the impact of product market peer credit constraints on long-run competitive outcomes and behavior among non-financial firms. I use measures of lender exposure to the financial crisis to create a plausibly exogenous instrument for product market credit availability. I find that credit constraints of product market peers positively predict growth in sales, market share, profitability, and markups. This is consistent with the notion that firms gained at the expense of their credit constrained peers. The relationship is robust to accounting for other sources of inter-firm spillovers, namely credit access of technology network and supply chain peers. Further, I find evidence of strategic investment, i.e. the idea that firms increase investment in response to peer credit constraints to commit to deter entry mobility. This behavior may explain why temporary heterogeneity in the availability of credit appears to have resulted in a persistent redistribution of output across firms.
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"Let Me Get Back to You" — A Machine Learning Approach to Measuring NonAnswers
Andreas Barth, Sasan Mansouri, Fabian Wöbbeking
Management Science,
No. 10,
2023
Abstract
Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal nonanswers in earnings call questions and answers (Q&A). We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls.
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