We are grateful to Chris Anderson and Taehoon Kim for outstanding research assistance. In recent work (Gopinath and Stein (2017)) we explore how a currency like the dollar can become entrenched as a dominant global currency, focusing on the two-way feedback between trade invoicing and banking structure. The basic idea is that when a larger share of a country's imports are invoiced in dollars, its citizens have a greater demand for dollar-denominated safe claims. This in turn leads the local banking sector to become more dollarized, in the sense of funding itself more with dollar-denominated liabilities. Here we extend the framework of that paper to consider the implications for central-bank reserve holdings. We show that when a country's banks are more heavily dollar funded, this induces the central bank-in its role as lender of last resort-to hold a larger stockpile of dollar reserves. 1 We also provide some suggestive evidence which is consistent with this hypothesis. I. The Model We model the behavior of three sets of agents in a representative emerging-market country: households, banks, and the central bank. There are two dates, 0 and 1. The time-0 exchange rate 0 ε (in units of local currency per dollar) is normalized to 1. The time-1 exchange rate 1 ε is (1+z) with probability p = 0.5, and is (1-z) with probability (1-p) = 0.5. The parameter z is thus a proxy for the volatility of the exchange rate. In the event that 1 (1) z ε = + , i.e. that the local currency depreciates against the dollar, there is a probability q of a banking crisis which requires the central bank to bail out a fraction of the banking sector. Thus banking crises are correlated with a weaker domestic currency; this is a key assumption of the model. 1 Other papers that analyze central-bank reserve holdings from the perspective of a lender of last resort include Obstfeld, Shambaugh and Taylor (2010) and Bocola and Lorenzoni (2017).
CITATION STYLE
Kiss, I. Z., Berthouze, L., Miller, J. C., & Simon, P. L. (2017). Mapping Out Emerging Network Structures in Dynamic Network Models Coupled with Epidemics (pp. 267–289). https://doi.org/10.1007/978-981-10-5287-3_12
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