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Western Hemisphere > Argentina

You are looking at 1 - 2 of 2 items for :

  • Type: Journal Issue x
  • Bayesian Analysis: General x
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Cover IMF Working Papers
Global Trade and the Dollar
Ms. Emine Boz
,
Ms. Gita Gopinath
, and
Mikkel Plagborg-Møller
We document that the U.S. dollar exchange rate drives global trade prices and volumes. Using a newly constructed data set of bilateral price and volume indices for more than 2,500 country pairs, we establish the following facts: 1) The dollar exchange rate quantitatively dominates the bilateral exchange rate in price pass-through and trade elasticity regressions. U.S. monetary policy induced dollar fluctuations have high pass-through into bilateral import prices. 2) Bilateral non-commodities terms of trade are essentially uncorrelated with bilateral exchange rates. 3) The strength of the U.S. dollar is a key predictor of rest-of-world aggregate trade volume and consumer/producer price inflation. A 1 percent U.S. dollar appreciation against all other currencies in the world predicts a 0.6–0.8 percent decline within a year in the volume of total trade between countries in the rest of the world, controlling for the global business cycle. 4) Using a novel Bayesian semiparametric hierarchical panel data model, we estimate that the importing country’s share of imports invoiced in dollars explains 15 percent of the variance of dollar pass-through/elasticity across country pairs. Our findings strongly support the dominant currency paradigm as opposed to the traditional Mundell-Fleming pricing paradigms.
Keywords:
WP; software package; U.S. dollar; exchange rate; Bayesian semiparametrics; bilateral trade; dominant currency; exchange rate pass-through; hierarchical Bayes; panel data; trade elasticity; invoicing share; dollar pass-through; pass-through coefficient; log growth; price pass-through; Exchange rates; Currencies; Exchange rate adjustments; Import prices; Imports; Global
Cover IMF Working Papers
Measuring Contagion with a Bayesian Time-Varying Coefficient Model
Mr. Alessandro Rebucci
and
Mr. Matteo Ciccarelli
We propose using a Bayesian time-varying coefficient model estimated with Markov chain-Monte Carlo methods to measure contagion empirically. The proposed measure works in the joint presence of heteroskedasticity and omitted variables and does not require knowledge of the timing of the crisis. It distinguishes contagion not only from interdependence but also from structural breaks and can be used to investigate positive as well as negative contagion. The proposed measure appears to work well using both simulated and actual data.
Keywords:
WP; contagion; Gibbs sampling; heteroskedasticity; omitted variable bias; time-varying coefficient models; Chilean peso; U.S. dollar; cross-market correlation; OLS estimate; estimation procedure; correlation coefficient; cross-market linkage; foreign exchange market reaction; Currency markets; Currencies; Metal prices; Public expenditure review; Exchange rates; Global