Testing the Exogeneity of Argentine Devaluation and Default Risks in Retrospect*

This paper studies the relationship between devaluation and default risks during Argentina's convertibility regime. Before default and devaluation occurred, a harder variant of the currency regime was under discussion. An often‐suggested argument among the supporters of dollarization was that the probability of default could have been reduced by removing fears of devaluation. For this to be true, default risk must be dependent on the devaluation risk. Long‐run relationships and ‘exogeneity’ are examined using a ‘cointegrating vector’ system approach. The results show that only devaluation risk can be modelled on default risk. No empirical evidence is found in favour of dollarization. Moreover, these conclusions are maintained when the information set is expanded to include the Latin American risk and Argentine macroeconomic variables.     

THE MONETARY METHOD AND THE SIZE OF THE SHADOW ECONOMY: A CRITICAL ASSESSMENT

A widely applied approach to measure the size of the shadow economy, known as the "monetary method" or the "currency approach," is based on econometric estimates of the demand for money. These estimates are used to get the currency held by economic agents in excess of the amount they need to finance registered transactions. This excess of currency multiplied by the income-velocity of circulation (assumed to be equal in the registered and shadow economies) gives a measure of the hidden GDP. This paper shows that the monetary method only produces coherent estimates if the income-elasticity of the demand for currency is one and suggests a way to correct the estimated size of the shadow economy when such elasticity is not one. The correction is applied to existent measures for different countries.     

Out‐of‐sample testing price discovery in commodity markets: the case of soybeans

Price discovery, a central function of futures markets, has been usually tested in‐sample by studying the common stochastic trend between spot and futures prices. Instead, to evaluate futures as anticipatory prices, we develop a forecast approach to out‐of‐sample test price discovery in a multivariate framework. We apply it to the soybeans market. Results indicate futures prices as the best available “predictors” of future spot prices, although this finding holds only on average and for certain periods, other models show forecasting gains.