Essays in International Finance

This dissertation consists of three essays in international finance. The first two essays study emerging market sovereign risk with a focus on local currency denominated sovereign bonds. The third essay examines econometric tools for robust inference in the presence of missing observations, an issue frequently encountered by researchers in international finance.;Most emerging market sovereign borrowing is now denominated in local currencies. In Chapter 1, we introduce a new measure of sovereign risk, the local currency credit spread, defined as the synthetic dollar spread on a local currency bond after using cross currency swaps to hedge the currency risk of promised cash flows. Compared with traditional sovereign risk measures based on foreign currency denominated debt, we find that local currency credit spreads have lower means, lower cross-country correlations, and are less sensitive to global risk factors. We rationalize these findings with a model allowing for different degrees of integration between domestic and external debt markets.;Chapter 2 documents new empirical evidence on the rapid growth of foreign ownership of emerging market local currency sovereign debt over the past decade. We study risk of nominal bonds without hedging away the currency risk. We show that local currency nominal bond risks differ across countries and are highly correlated with sovereign credit default swap spreads on foreign currency external debt. Using data on investors’ forecasts of inflation and growth, we find that perceived differences in the cyclicality of monetary policy help explain the cross-sectional and time series variation in nominal bond risk as well as the development of local currency debt markets. Guided by these observed empirical patterns, we develop a simple general equilibrium model with an endogenous issuance decision between local and foreign currency debt.;Chapter 3 proposes two simple consistent heteroskedasticity and autocorrelation consistent covariance estimators for time series with missing data. First, we develop the Amplitude Modulated estimator by applying the Newey-West estimator and treating the missing observations as nonserially correlated. Secondly, we develop the Equal Spacing estimator by applying the Newey-West estimator to the series formed by treating the data as equally spaced. We show asymptotic consistency of both estimators for inference purposes and discuss finite sample variance and bias tradeoff.