Browsing by Author "Gatty Sangama, Andrés"

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    Essays on Sudden Stops in Capital Inflows: Determinants and Optimal Responses
    (2025) Gatty Sangama, Andrés; Kohn, David; Pontificia Universidad Católica de Chile. Instituto de Economía
    Sudden stops in capital inflows are disruptive and costly events that can cause redistributive effects. In the first chapter, I explore the role of inequality in the design of optimal capital controls. To do so, I set up a small open production economy model with collateral constraints and two types of agents that are heterogeneous in income and borrowing capacities. I use the model to study the response of the economy to exogenous shocks that produce a tightening of the collateral constraint and sudden stops (reversals in the current account). I then solve the constrained solution of a Social Planner’s problem, which aims to avoid sudden stops and achieve redistribution. I find that inequality implies differentiated capital controls between high income and low income agents. While in normal times taxes are higher for high income households to prevent overborrowing, the planner allows low income households to borrow more to enable some redistribution. When the economy faces a sudden stop, taxes for all agents are reduced to nearly zero. Then, I design a uniform, constant capital control that allows achieving this optimal outcome. In the second chapter, I investigate the effect of extreme natural disasters on sudden stops in capital inflows (current account reversals), both empirically and quantitatively. Using a cross-country quarterly dataset, I find that the occurrence of a disaster increases the probability of a sudden stop in Emerging Economies. On average, during a disaster, in addition to a cut-off in capital inflows, these economies experience a contraction in output and other components of demand. I then extend a standard Real Business Cycle (RBC) model with collateral constraints to incorporate extreme natural disasters and examine their interaction with sudden stops. The model successfully replicates the patterns observed in the data and shows that the risk of sudden stops increases during natural disasters due to capital destruction and productivity loss. In ddition, the model captures a fact also observed in the data, sudden stops tend to be more severe when they coincide with natural disasters.