R: Reserve demand curve predicted values

curvepred {curvir}

R Documentation

Reserve demand curve predicted values

Description

Provides the predicted values for the reserve demand curve of choice. For general use prefer the predict() function, which handles the constant internally.

Usage

curvepred(x, w, type = "logistic", dummy = NULL)

Arguments

`x`	A matrix with the inputs. If there is a constant in the estimated curve, then the first column in `x` should be the constant. Next column should be the excess reserves. Additional regressor follow (optional).
`w`	The vector of weights for the desired curve. Estimated using the `curveopt` function.
`type`	The type of the reserve demand curve. This can be any of `logistic`, `redLogistic`, `fixLogistic`, `doubleExp`, `exponential`, `fixExponential`, `arctan`, `linear`. See details in `curve`
`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`.

Details

For a description of the parametric curves, see the provided reference. Below we list their functions:

logisitc (Logistic)

r_i = \alpha + \kappa / (1 - \beta e^{g(\bm{C}_i)}) + \varepsilon_i
redLogistic (Reduced logistic)

r_i = \alpha + 1 / (1 - \beta e^{g(\bm{C}_i)}) + \varepsilon_i
fixLogistic (Fixed logistic)

r_i = \alpha + 1 / (1 - e^{g(\bm{C}_i)}) + \varepsilon_i
doubleExp (Double exponential)

r_i = \alpha + \beta e^{\rho e^{g(\bm{C}_i)}} + \varepsilon_i
exponential (Exponential)

r_i = \alpha + \beta e^{g(\bm{C}_i)} + \varepsilon_i
fixExponential (Fixed exponential)

r_i = \beta e^{g(\bm{C}_i)} + \varepsilon_i
arctan (Arctangent)

r_i = \alpha + \beta \arctan ( g(\bm{C}_i)) + \varepsilon_i
linear (Linear)

r_i = g(\bm{C}_i) + \varepsilon_i

And g(\bm{C}) = c + \bm{C} w_g, where \alpha, \beta, \kappa, \rho are curve parameters, c is a constant togglable by constant, \bm{C} are the regressors including the excess reserves. w_g their coefficients, and finally \varepsilon_i is the error term of the curve.

Value

Returns a vector of the predicted values.

Author(s)

Nikolaos Kourentzes, nikolaos@kourentzes.com

References

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