Essays in finance

Mäckle, Kai

Preview

PDF
dissertation_km.pdf - Published
Download (4MB)

URN:	urn:nbn:de:bsz:180-madoc-726919
Document Type:	Doctoral dissertation
Year of publication:	2026
Place of publication:	Mannheim
University:	Universität Mannheim
Evaluator:	Ruenzi, Stefan
Date of oral examination:	2026
Publication language:	English
Institution:	Business School > Internat. Finanzierung (Ruenzi 2009-)
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject:	000 Generalities
Keywords (English):	short-termism , carbon emissions , structural estimation , social networks , opioid epidemic , innovation , patents , patent bundling
Abstract:	This dissertation examines three independent questions. Chapter 1 asks whether managerial short-termism distorts corporate carbon emissions. Firms that just meet analyst earnings forecasts exhibit carbon emissions growth eight to nine percentage points higher than firms that just miss, consistent with earnings management. A structurally estimated model of heterogeneous firms shows that removing short-term incentives would lower profits by 0.43% but cut emissions by 2.19%. This amounts to about 142 million tons of CO2, which is comparable to total U.S. aviation emissions in 2022. The implied cost per ton is well below standard estimates of the social cost of carbon, suggesting that short-termism is welfare-reducing. Chapter 2, co-authored with Stefan Ruenzi, studies whether friendship networks contribute to the spread of the U.S. opioid epidemic. We show that counties more socially proximate to high-overdose areas experience significantly higher overdose deaths, an effect identified using two quasi-natural experiments, while cohesive local social networks attenuate these spillovers. Chapter 3, co-authored with Larissa Ginzinger, Markus Huggenberger, and Stefan Ruenzi, shows that most patents are granted in bundles, and that this bundling explains much of the correlation between market-based patent value measures and forward citations, raising doubts about using stock-market reactions to value individual patents.