Finance - Theses
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ItemComputational complexity of decisions: Quantifying computational hardness and its effects on human computation( 2021)Humans are presented daily with decisions that require solving complex problems. In many cases, solving these problems is computationally hard. This raises a tension between the computational capacity of the agent and the computational requirements of a task. Whilst the underlying invariants of this mechanism remain unclear in cognition, they have been widely studied in computer science. I build on theoretical and empirical work in computational complexity, which characterizes the intrinsic computational hardness of problems. I first present an adaptation of this theoretical framework for the study of human cognition by introducing a set of metrics of hardness of instances of problems. I do this in a way that is independent of any algorithm or computational model and that can be generalized to other problems. Based on this, I explore empirically, in a set of lab experiments, how these task-independent metrics of hardness affect human problem-solving. I do this at two levels of analysis. Firstly, I study how these metrics affect human performance at the behavioral level in three canonical computational problems: the knapsack problem, the traveling salesperson problem and the Boolean satisfiability problem. Secondly, I examine the relation between computational hardness and the neural processes associated with problem-solving, employing ultra-high field functional MRI. I find that the metrics of intrinsic hardness put forward here predict human performance and time-on-task across the three computational problems in a similar way. Moreover, I identify the neural correlates of computational hardness in the knapsack task, a complex problem-solving task. I show that this framework can be used for the study of the neural underpinnings of problem-solving by providing a generic definition of cognitive demand. The results of these studies provide support for the conceptual premise that the quantification of intrinsic hardness is fundamental in the development of more refined theories of human decision-making and its neural underpinnings. Critically, they provide a framework to study how humans adapt to computational complexity and how intrinsic hardness of tasks affect the reliability of human decision-making. This could inform public policy by identifying which decisions over products involve solving problems that require computational resources beyond those available to an agent, and how this affects decisions.
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ItemEssays on Political Economy of Finance( 2021)This thesis explores mechanisms that connect firms to politicians, as well as new channels through which firms benefit from being politically connected, under different ecopolitical environments. It contains three essays examining various aspects of finance at its intersection with political science. The first essay exploits Donald Trump’s nonpolitical background and surprise election victory to identify the value of sudden presidential ties among S&P 500 firms. In our setting firms did not choose to become politically connected, so we identify treatment effects comparatively free of selection bias prevalent in this literature. Firms with presidential ties enjoyed greater abnormal returns around the 2016 election. Since Trump’s inauguration, connected firms had better performance, received more government contracts, and were less subject to unfavorable regulatory actions. We rule out a number of confounding factors, including industry designation, sensitivity to Republican platforms, campaign finance, and lobbying expenditures. The second essay finds that borrowers from the same state as the Chairman of the US Senate Banking Committee, whom I term "connected", are able to borrow at spreads 14 basis points lower than other borrowers. Connected borrowers’ contributions toward the Chairman are influenced by their cost of loans, but the same is not true for nonconnected borrowers. Findings suggest the Chairman is incentivized by reelection to actively help connected borrowers obtain cheaper loans. Banks that offer a larger fraction of connected loans enjoy higher future excess stock returns. Results are consistent with the existence of a quid pro quo relationship triangle between firms, banks, and politicians. The third essay examines how changes in local political leadership affect firms’ gover- nance structures. Using a novel dataset, I document that following the appointment of a new city-level Chinese Communist Party (CCP) secretary, local firms increase (decrease) the fraction of directors who share a common birthplace with the incoming (departing) secretary. This appears to be a channel through which Chinese firms establish political connections. Firms with a higher percentage of birthplace-connected directors exhibit higher abnormal returns around secretary appointments. These firms enjoy superior accounting performances and attract institutional fund flows. I reject an alternative hypothesis that these directors are appointed to company boards on the "orders" of the politician, rather than actively recruited by firms.