Exchange Rate Regime Analysis for the Indian Rupee

نویسندگان

  • Achim Zeileis
  • Ajay Shah
  • Ila Patnaik
چکیده

We investigate the Indian exchange rate regime starting from 1993 when trading in the Indian rupee began up to the end of 2007. This reproduces the analysis from Zeileis, Shah, and Patnaik (2010) which includes a more detailed discussion. 1 Analysis Exchange rate regime analysis is based on a linear regression model for cross-currency returns. A large data set derived from exchange rates available online from the US Federal Reserve at http://www.federalreserve.gov/releases/h10/Hist/ is provided in the FXRatesCHF data set in fxregime. > library("fxregime") > data("FXRatesCHF", package = "fxregime") It is a“zoo” series containing 25 daily time series from 1971-01-04 to 2010-02-12. The columns correspond to the prices for various currencies (in ISO 4217 format) with respect to CHF as the unit currency. India is an expanding economy with a currency that has been receiving increased interest over the last years. India is in the process of evolving away from a closed economy towards a greater integration with the world on both the current account and the capital account. This has brought considerable stress upon the pegged exchange rate regime. Therefore, we try to track the evolution of the INR exchange rate regime since trading in the INR began in about 1993 up to the end of 2007. The currency basket employed consists of the most important floating currencies (USD, JPY, EUR, GBP). Because EUR can only be used for the time after its introduction as official euro-zone currency in 1999, we employ the exchange rates of the German mark (DEM, the most important currency in the EUR zone) adjusted to EUR rates. The combined returns are denoted DUR below in FXRatesCHF: > inr <fxreturns("INR", frequency = "weekly", + start = as.Date("1993-04-01"), end = as.Date("2008-01-04"), + other = c("USD", "JPY", "DUR", "GBP"), data = FXRatesCHF) Weekly rather than daily returns are employed to reduce the noise in the data and alleviate the computational burden of the dating algorithm of order O(n).

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تاریخ انتشار 2009