Central bank authorities base implementation of monetary policy on an analysis of multiple variables known as monetary policy indicators. In a small open economy such as Chile, these indicators may include in-flation misalignments, unemployment, GDP growth, money growth, the current account balance, exchange rate volatility and international re-serves. A neural network approach is used to establish the correspond-ing weights considered by the Board of the Central Bank of Chile dur-ing the period 1995-2003. GDP growth and the difference between the actual and the target inflation were found to be among the variables of greatest weight in the monetary policy decision-making process of the Central Bank of Chile during this period.
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Article provided by Ilades-Georgetown University, Economics Department in its journal Revista de Analisis Economico.
Find related papers by JEL classification: E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
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