Crescenzi, Mark J.C. & Bailee Donahue, 2017. ``Rediscovering Reputation Through Theory and Evidence" in Oxford Research Encyclopedia of Politics, ed. William Thompson. New York: Oxford University Press.
Crescenzi, Mark J.C. & Bailee Donahue, 2017. ``Reputation in International Relations" in Oxford Bibliographies in International Relations, ed. Patrick James. New York: Oxford University Press. (Annotated Bibliography)
Advisors: Mark J.C. Crescenzi (Chair), Navin Bapat, Layna Mosley, Cameron Ballard-Rosa, Stephen Gent
In my, I analyze the impact of dysfunctional borders on cross-border trade. I pose three questions: 1) what are the consequences of dysfunctional borders and their settlement on the margins of trade; 2) which commodities are disproportionately impacted by dysfunctional border regimes due to the intensity with which they rely on cross-border information networks; 3) under what conditions do economic actors re-establish cross-border economic ties following the settlement of a border. To answer these questions, I develop a novel measurement of trade exclusivity and use granular-trade data to expand data on the intensity with which goods rely on cross-border networks to trade. Using a combination of machine learning, statistical inference, and qualitative case studies, I am able to improve our understanding of how dysfunctional border regimes and their resolution regulate cross-border economic activity and cross-border economic networks.
Papers in Preparation
Bailee Donahue, "Risk and Rebuilding in Economic Cooperation: Reinvestment Challenges After Border Settlement" from Dissertation
The settlement of border disputes often increases trade between states. Analysis of aggregate bilateral trade flows, however, hides important variation in the relative risk and costliness associated with the trade of different commodities across borders. Why are some trade ties easier to re-establish than others in the aftermath of a dispute? We know from prior research that economic networks coordinate around borders, and that border changes can disrupt these networks, but some networks are more fragile than others. Highly differentiated commodities pose greater risk and costlier investment to traders seeking to re-establish cross-border networks following a settlement as they rely on higher levels of interpersonal contact between exporters and importers. When commodities depend upon economic networks that are easily disrupted, economic agents will perceive increased risk. This risk makes firms less likely to trade in highly differentiated commodities in the immediate aftermath of a border settlement. On the other hand, commodities less reliant on cross-border networks are less likely to be disrupted if borders are destabilized post-settlement. In turn, one important determinant of risk involves the heterogeneity of the commodity and the economic network associated with its cross-border exchange. To examine the above argument, I use product-level trade data that spans the period of 1962 to 2016 and territorial settlements data from 1962 to 2001. This analysis helps us to better understand the ways in which both trade and evaluations of risk evolve after the resolution of border disputes.
Donahue, Bailee & Mark J.C. Crescenzi, "Weathering the Storm: Discordant Learning About Reputations for Reliability"
In this paper, we investigate how reputations change, and whether states can cultivate reputational reserves that insulate them from unwanted reputation dynamics. Specifically, we examine how reputations for reliability are lost when states violate alliance terms. Can a well-established reputation insulate states from being labeled as unreliable when they violate an alliance contract? This paper develops a theory of discordant learning that predicts that a good reputation for reliability will act as a buffer that allows the violating state to weather the storm of minor crises without paying a reputational cost, whereas states with fragile reputations for reliability are more likely to be punished if they exhibit incongruent behavior. High levels of incongruence, however, such as a major alliance violation during a high-profile war, can trigger an over-correction in a state's reputation. Thus, a state with a stable and good reputation for reliability may absorb a greater reputational cost relative to a state with a fragile or moderate reputation if it exhibits highly incongruent behavior (i.e., the bigger they are the harder they fall). We employ a scenario-based survey experiment to test these expectations. Our analysis will help us understand when to expect a loss in state-reputation, and has implications for when reputation loss can influence alliance formation and conflict behavior.
Donahue, Bailee, Rob Williams & Mark J.C. Crescenzi, "Unsettled Borders in a Market Context"
Border disputes between states can be very costly and disruptive, including major disruptions in trade. From an aggregate perspective, scholars traditionally expect these costs and disruptions to place pressure on states to avoid or resolve these disputes quickly. This view, however, risks oversimplification of the quality of trade and the economic actors driving that trade. We investigate the consequences of complex trade relations on border disputes. Variation in the composition of trade, whether characterized by comparative advantage trade, inter-industry trade, or intra-industry trade, generates variation in the presence and intensity of domestic pressure to avoid or resolve border disputes. We examine the effects of this variation on dispute behavior using an original dataset that combines product-level trade data (spanning from 1962-2001) with ICOW territorial claims data. The use of product-level trade data allows for the analysis of substitutability options which may reduce exit costs and make it easier to escalate border disputes. This analysis helps us better understand the choice to forego trade due to border disputes, and furthers our understanding of the economic impact of unsettled borders.
Donahue, Bailee, "A Tree-Based Approach to Predicting Sanctions Success"
What features best predict the success of economic sanctions? Further, how do different historical periods interact with these features to increase or decrease their relative importance? Tree-based modeling does not impose a functional form on the data generating process and accommodates complex interactions among features. I argue that this method is well-suited to investigating the periodization of sanctions success. Using the Threat and Imposition of Economic Sanctions (TIES) data, I employ a tree-based approach to predicting sanctions success to evaluate these questions.