blocal: Interpolate Critical Values Local to Fractional Integration...

In fracdist: Numerical CDFs for Fractional Unit Root and Cointegration Tests

Description

blocal calculates an approximation to the CDF for a particular value of the fractional integration parameter b.

Usage

blocal(nb = 31, bb, estcrit, bval)

Arguments

nb	The integer number of values of the fractional integration parameter b. The default is 31, which is the number of gridpoints between 0.5 and 2.0 in the lookup tables.
bb	The fractional integration parameter, which can take on values between 0.5 and 2.0.
estcrit	A numeric scalar that is an estimate of the critical value, a quantile, corresponding to a particular probability.
bval	A numeric vector of the fractional integration parameter b ranging between 0.5 and 2.0 to match those in the lookup tables.

Value

A numeric scalar that is the sum of regression coefficients from a response surface regression.

Note

The fractional integration parameter b must lie within the interval [0.50, 2]. If b is less than 0.5, the relevant distribution is chi-squared. A value above 2 is less common but might be avoided by differencing the data before estimating the model under consideration.

References

James G. MacKinnon and Morten Ørregaard Nielsen, "Numerical Distribution Functions of Fractional Unit Root and Cointegration Tests," Journal of Applied Econometrics, Vol. 29, No. 1, 2014, pp.161-171.

Examples

frtab <- get_fracdist_tab(iq = 3, iscon = 0)
bval <- unique(frtab[, 'bbb'])
probs <- unique(frtab[, 'probs'])
estcrit <- frtab[frtab[, 'probs'] == probs[201], 'xndf']
bedf_i <- blocal(nb = 31, bb = 0.75, estcrit, bval)

fracdist documentation built on May 25, 2021, 9:07 a.m.