fxlm {fxregime} | R Documentation

## Exchange Rate Regression

### Description

Interface to `lm` for fitting exchange rate regression models (Frankel-Wei models).

### Usage

      fxlm(formula, data, ...)

### Arguments

`formula` | a `"formula"` describing the linear model to be fit. For details see below.
`data` | a `"zoo"` time series.
`...` | arguments passed to `lm`.

### Details

`fxlm` is a function for fitting exchange rate regression models also known as Frankel-Wei models. It is a simple convenience interface to `lm`: `data` is assumed to be a `"zoo"` series in which, by default, the first column is the dependent variable. If `formula` is omitted, the first column is regressed on the remaining columns in `data`. The main difference compared to plain `lm` models is that the error variance is reported as a full parameter (estimated by maximum likelihood) in the `coef` method and the `estfun` method (but currently not in the `vcov` method). Furthermore, the index (also known as the time stamps) of the underlying data set can be extracted by the `time`/`index` method.

### Value

An object of class `"fxlm"` inheriting from `"lm"`.

### References

Shah A., Zeileis A., Patnaik I. (2005), What is the New Chinese Currency Regime?, Report 23, Department of Statistics and Mathematics, Wirtschaftsuniversitaet Wien, Research Report Series, November 2005.

Zeileis A., Shah A., Patnaik I. (2008), Testing, Monitoring, and Dating Structural Changes in Maximum Likelihood Models, Report 70, Department of Statistics and Mathematics, Wirtschaftsuniversitaet Wien, Research Report Series, August 2008.

### See Also

`lm`, `fxregimes`

### Examples

    ## load package and data
    library("fxregime")
    data("FXRatesCHF", package = "fxregime")

    ## compute returns for CNY (and explanatory currencies)
    ## for one year after abolishing fixed USD regime
    cny <- fxreturns("CNY", frequency = "daily",
      start = as.Date("2005-07-25"), end = as.Date("2006-07-24"),
      other = c("USD", "JPY", "EUR", "GBP"))

    ## estimate full-sample exchange rate regression
    fm <- fxlm(CNY ~ USD + JPY + EUR + GBP, data = cny)
    coef(fm)
    summary(fm)

    ## test parameter stability (with double max test)
    scus <- gefp(fm, fit = NULL)
    plot(scus, aggregate = FALSE)
    ## which shows a clear increase in the variance in March 2006

    ## alternative tests: Andrews' supLM ...
    plot(scus, functional = supLM(0.1))
    ## ... or Nyblom-Hansen test (Cramer-von Mises type test)
    plot(scus, functional = meanL2BB)

[Package fxregime version 0.3-1 Index]