Before And After The Great Contentions: Explaining The Diffusion Of Crises With Machine Learning And Archives

This dissertation presents three articles that study crises from a sociological perspective. The first two articles studies the effects of global trade networks on financial and political crises with the implantation of big data and supervised machine learning methods on a dataset for a sample of 70 countries for the years between 1962 and 2009. Using the institutional and network theories, the first article finds support that normative pressures lead countries to commit sovereign defaults. Countries are more likely to commit sovereign default if other structurally equivalent or role equivalent countries did so in the previous year. The second article finds that role equivalent and structurally equivalent countries occupying a similar position in the global trade networks are affected similarly by revolutionary waves and experience revolutionary situations simultaneously. The third article argues that state secularization is a process involving mobilization, political tactics, and resources as opposing forces struggle over three major institutional dimensions. Examining the history of state secularization in Turkey, Mexico, and France in the aftermath of revolutions, this article demonstrates that the degree of secularization is determined by political contention. (1) The revolutionary state attempts to seize church property, which opens the way for further struggles. (2) If the church administers law through its own courts, or has an autonomous code of law, revolutionary states struggle to substitute secular courts and state-enacted law. (3) Churches often control education; a revolutionary state eventually attempts to take control of education when it mobilizes sufficient resources for the required state capacity. Taking all these dimensions together, the struggle over secularization has many partial outcomes and stopping places, and thus mixed patterns are much more typical than an ideal type transition to pure secularist modernity

Building Bridges between Pharmacists and Physicians: An Exploratory Investigation via Field, Usability Studies & Control Task Analysis To Enhance Pharmacy Management System Requirements

Miscommunication between healthcare professionals can impact patient care and is costly. The information systems used in pharmacies and hospitals can contribute to this miscommunication. The present research is an initial attempt to investigate the reasons leading to lack of communication between pharmacists and physicians. Twenty-five pharmacists were interviewed to understand how pharmacists use pharmacy management systems (PMS), as well as to explore why communication issues may occur between prescribers and pharmacists. The field study data was transcribed and interview results were organized into three categories. Next, a human factors analysis was completed to understand pharmacists’ needs and challenges with the current PMSs and finally Control Task Analysis was performed to discover weaknesses in the information systems. After discovering the usability issues with PMSs and reasons for miscommunication, mock ups were designed for a decision aid tool called Communication Summary. The intent of the Communication Summary is to enhance pharmacists’ workflow and their communication with prescribers. The mock ups were evaluated in a simulated pharmacy management task by senior pharmacy students. The results suggested that more information on pharmacist-prescriber communication may help in pharmacy management

Essays on Economic Uncertainty and Financial Markets

This thesis examines the role of economic uncertainty in investors’ decision process and analysts’ forecast bias. The first empirical chapter investigates the effect of firm-level exposure to economic uncertainty (EUE) on cross-sectional returns through differentiating the mispricing from ambiguity-premium effects. Conditional on a common mispricing index, I find that EUE induces disagreement among investors, which amplifies mispricing. The highest EUE quintile produces a significantly higher mispricing alpha than the unconditional mispricing effect. By contrast, the high-minus-low EUE portfolio in the non-mispricing group generates a significant positive premium in the sense of the ambiguity-return trade-off. The EUE-induced mispricing effect is different from existing limits of arbitrage explanations, such as idiosyncratic risk. The ambiguity premium is a new source of the risk premium that is robust to the latest risk models. The second empirical chapter studies the role of market-wide sentiment in relation to the mispricing and the ambiguity effects documented in the first study. Considering the presence of the market-wide sentiment combined with short-sale constraints, I find larger mispricing spread in stocks with high EUE following high-sentiment periods. This mispricing effect is stronger following the periods with both increasing economic uncertainty and high sentiment. It suggests that economic uncertainty indeed leaves more room for the sentiment effect in the market. The ambiguity premium in the non-mispricing group, however, is significant only following low-sentiment periods during which the mispricing effect vanishes. This is consistent with the previous finding that the market pricing is more rational when investor sentiment is relatively low. The final empirical chapter examines whether there is an effect of EUE on analysts’ optimism. Existing literature shows that equity analysts have an optimistic bias. I find that analysts are even more optimistic for stocks with higher EUE. This is especially true following periods with high economic uncertainty. This study confirms that such an increase in optimism is for incentives given that high uncertainty reduces their reputation costs by lowering the chance of them being caught for such bias. The effect is more pronounced when firm-specific information quality (measured by earnings quality and information availability at the market level) is lower, and investors are less sophisticated (measured by the proportion of institutional ownership). Finally, analysts issuing optimistic view for stocks with higher exposure to economic uncertainty impede the price efficiency in the market. The EUE-induced mispricing is significantly apparent among stocks with high optimism. This thesis contributes to the literature in several ways. First, economic uncertainty has two seemingly contradicting mechanisms in asset pricing, including the ambiguity premium and the mispricing effects. This thesis reaches a clear conclusion that both mechanisms are at work through disentangling the two effects, which has not been studied by the existing literature where these two mechanisms are studied in isolation. Second, I identify EUE as a common mispricing component across anomalies, which is different from but complements investor sentiment and arbitrage risk, contributing to existing studies by suggesting that mispricing has common components across stocks. Finally, analyst optimism for incentives exacerbates the mispricing effect of economic uncertainty. This finding complements studies which suggest that analyst bias impedes the price efficiency in the market

Can financial uncertainty forecast aggregate stock market returns?

We investigate the role of financial uncertainty in forecasting aggregate stock market returns. Our results suggest that financial uncertainty, along with its change, are more powerful predictors of excess US monthly stock market returns than 14 macroeconomic predictors commonly used in the literature. Financial uncertainty is shown to outperform short interest, which has been suggested to be the strongest known predictor of the equity risk premium. These results persist using robust econometric methods in-sample, and when forecasting out-of-sample

Heat Transfer In Naturally Ventilated Rooms: Data From Full-Scale Measurements.

Experiments were conducted in a full-scale room of the Florida Solar Energy Center (FSEC) Passive Cooling Laboratory (PCL) to determine heat-transfer coefficients from one vertical wall when the room was naturally ventilated. Such data are required for accurate predictions of heat removal rates from overheated rooms by natural and forced ventilation. The heat-transfer data are correlated to local surface airspeeds and design values are presented. Comparisons are made with other data sources