| Summary: | How do policymakers make decisions during financial market uncertainty? I develop a straightforward framework of policymaking in uncertainty. To overcome uncertainty, policymakers gather information using strategies discussed across a variety of political science disciplines. Policymakers need information to be able to make goal-oriented decisions. The information strategies actors choose are conditioned on the uncertainty problems they face. In turn, the information they receive impacts their policy decisions. My three empirical papers investigate what strategies are likely to be chosen in different types of uncertainty and how these choices affect policy decisions. My first paper, co-written with Mícheál O’Keeffe, develops a signaling game that policymakers play when they perceive data uncertainty, i.e. uncertainty about economic fundamentals. The model is supported empirically with analytic narratives of recent crises in Korea and Ireland. My following two papers deal with situations of increasing causal uncertainty, i.e. uncertainty about how actions cause outcomes. In both of these papers I use Multi-state Event History Analysis. I find that when there is high causal uncertainty policymakers tend to use learning strategies that start with international-level policy recommendations. These recommendations are then updated with the experiences of regional peers who have adopted them. Beyond creating and finding evidence for a parsimonious framework of decisionmaking in uncertainty, I make a number of other contributions to political economy. I extend the empirical tools researchers can use to understand decisions in complex choice environments. I provide evidence that making financial bureaucrats “independent" does not ensure positive outcomes. Specifically, it does not guarantee that financial bureaucrats will provide accurate information needed for effective policymaking.
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