Monte Carlo Critical Values for Reverse-Regression Recovery Dating

radf_recovery_cv(n, minw = NULL, nrep = 1000L, seed = NULL, lag = 0)

Computes critical values for the reverse-regression BSADF statistic that radf_recovery uses. They are calibrated to the null limiting distribution of that statistic (Theorem 1 of Phillips & Shi 2014) and not to the standard forward boundary of radf_mc_cv. The simulated null path is reversed before the recursive computation, because reversal induces an endogeneity that has no analogue in the forward regression (see the Details of radf_recovery).

Arguments

n	A positive integer. The sample size.
minw	A positive integer. The minimum window size (default = $(0.01 + 1.8/\sqrt{T})T$, where T denotes the sample size).
nrep	A positive integer. The number of Monte Carlo simulations.
seed	An object specifying if and how the random number generator (rng) should be initialized. It is either NULL or an integer, which is passed to set.seed before the simulation. If you set it, the value is saved as the "seed" attribute of the returned value. The default, NULL, leaves the state of the rng unchanged and returns .Random.seed as the "seed" attribute. Results are reproducible across the parallel and the non-parallel option when you use the same seed.
lag	A non-negative integer. Number of lags in the auxiliary regression, as in radf.

Value

A list of class radf_cv with a single element, bsadf_cv. It is a matrix of critical values (columns 90%, 95%, 99%) with one row for each reverse-time position, aligned in the same way as the bsadf_cv of radf_mc_cv is aligned to radf()$bsadf.

cv <- radf_recovery_cv(n = 100, minw = 20, nrep = 200)
range(cv$bsadf_cv)
#> [1] -0.2061245  1.8926854