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The authors would like to thank Ulric Erickson von Allmen, María Gonzalez, Rodrigo Valdes and the participants of a seminar at the Central Bank of Uruguay in December 2010 for their very helpful comments. We also thank the excellent work of Karlye Dilts in compiling the databases, as well as the help from María Gutierrez and Lucía Castro in editing the charts and tables of the paper.
See Mishkin (1996) for an in-depth discussion on the main channels of monetary policy transmission.
Uruguay does not have yet a full-fledged IT regime, as the country only recently began transitioning towards this monetary arrangement. This transition took place in early 2005, when the country started to conduct monetary policy with the objective of meeting a pre-announced inflation target. In addition, after September 2007 Uruguay adopted the policy rate as the main instrument for monetary policy. Previously, monetary policy was essentially run by setting objectives on monetary aggregates to meet the inflation target.
A significant number of papers study the monetary policy transmission in both advanced and emerging countries using VAR models as we do here (see Kim and Roubini, 2000; Peersman and Smets, 2001; and Leiderman et al, 2006).
For an analysis on the recent de-dollarization trends in Peru and Uruguay see García-Escribano and Sosa (2011).
The 2010 Art IV Staff Report for Uruguay also discusses the fact that Uruguay’s output volatility tends to be high relative to a number of selected peer countries.
This fact is partially explained by the evolution of certain prices in Uruguay that are somewhat controlled by economic authorities, notably transport prices and a number of selected utilities. These particularities have limited to some extent the variability of the inflation rate in the country.
Policy rates are taken from the website of each central bank, and reflect a target publicly announced by the central bank on the overnight interbank interest rate of each country.
These results should be treated with some caution since the sample period of the estimation in the case of Uruguay is particularly short. In any case, the results obtained here are broadly consistent with other studies that show a low pass through from the interbank rate to active and passive interest rates in the country.
For robustness, estimations are compared with those obtained from a structural VAR model using an identification structure similar to that proposed in Kim and Roubini (2000), without showing major differences in results.
In the case of New Zealand, information is mostly available on quarterly basis. Quarterly data have been converted to monthly data by taking a linear trend between each pair of consecutive quarters. At the time of running the estimations, quarterly data was available through 2010Q3.
Rossini and Vega (2006) point out that the presence of balance sheet effects may explain why economic activity seems to expand after an increase in the policy rate when considering Peruvian data.
The three-month response of inflation was chosen to account for the delay between the period in which the policy rate is changed and its final effect on inflation.
The credit-to-output ratio of each particular point in the scatter plot coincides with the stock of credit available at the end of the sample period of the associated rolling VAR.
Due to data availability it was not possible to run the exercise considering only the deposits in local currency of the private sector for both Peru and Uruguay