npcurve {curvir}

Reserve demand non-parametric curve

Description

Fits a non-parametric reserve demand curve between excess reserves and normalised rates

Usage

npcurve(x, y, type = c("rforest", "spline"), dummy = NULL, q = NULL, ...)

Arguments

x

A matrix of explanatory variables. Excess reserve must be the first input.Additional regressor follow (optional).

y

A vector of normalised interest rates.

type

The type of the reserve demand curve. This can be any of rforecast for random forecast or spline for spline regression.

dummy

Optional input to signify a regime change (vertical shifts in the curve). Must be a vector of equal length to the rows of x. If not needed use NULL.

q

Target interval. This is a scalar below 1, for example 0.9 is the 90% interval. If NULL then no quantiles are estimated.

...

Additional arguments (unused).

Value

Returns a model of class npcurvir. This includes

• type the type of the curve.

• fit the non-parametric model for the mean.

• fitQ The non-parametric model for the quantiles.

• data a list including the y, x, and dummy used for the fitting of the curve.

• q the interval used in the fitting of the curve.

Author(s)

Nikolaos Kourentzes, [e-mail]

References

Chen, Z., Kourentzes, N., & Veyrune, R. (2023). Modeling the Reserve Demand to Facilitate Central Bank Operations. IMF Working Papers, 2023(179).

See Also

predict.npcurvir, and plot.npcurvir.

Examples

# Use ECB example data
rate <- ecb$rate
x <- ecb$x[,1,drop=FALSE]
npcurve(x,rate)