exuber (version 1.0.2)

radf: Recursive Augmented Dickey-Fuller Test

Description

radf returns the recursive univariate and panel Augmented Dickey-Fuller test statistics.

Usage

radf(data, minw = NULL, lag = 0L)

Value

A list that contains the unit root test statistics (sequence):

adf

Augmented Dickey-Fuller

badf

Backward Augmented Dickey-Fuller

sadf

Supremum Augmented Dickey-Fuller

bsadf

Backward Supremum Augmented Dickey-Fuller

gsadf

Generalized Supremum Augmented Dickey-Fuller

bsadf_panel

Panel Backward Supremum Augmented Dickey-Fuller

gsadf_panel

Panel Generalized Supremum Augmented Dickey-Fuller

And attributes:

mat

The matrix used in the estimation.

index

The index parsed from the dataset.

lag

The lag used in the estimation.

n

The number of rows.

minw

The minimum window used in the estimation.

series_names

The series names.

Arguments

data

A univariate or multivariate numeric time series object, a numeric vector or matrix, or a data.frame. The object should not have any NA values.

minw

A positive integer. The minimum window size (default = \((0.01 + 1.8/\sqrt(T))T\), where T denotes the sample size).

lag

A non-negative integer. The lag length of the Augmented Dickey-Fuller regression (default = 0L).

Details

The radf() function is vectorized, i.e., it can handle multiple series at once, to improve efficiency. This property also enables the computation of panel statistics internally as a by-product of the univariate estimations with minimal additional cost incurred.

References

Phillips, P. C. B., Wu, Y., & Yu, J. (2011). Explosive Behavior in The 1990s Nasdaq: When Did Exuberance Escalate Asset Values? International Economic Review, 52(1), 201-226.

Phillips, P. C. B., Shi, S., & Yu, J. (2015). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500. International Economic Review, 56(4), 1043-1078.

Pavlidis, E., Yusupova, A., Paya, I., Peel, D., Martínez-García, E., Mack, A., & Grossman, V. (2016). Episodes of exuberance in housing markets: in search of the smoking gun. The Journal of Real Estate Finance and Economics, 53(4), 419-449.

Examples

# \donttest{
# We will use simulated data that are stored as data
sim_data

rsim <- radf(sim_data)

str(rsim)

# We would also use data that contain a Date column
sim_data_wdate

rsim_wdate <- radf(sim_data_wdate)

tidy(rsim_wdate)

augment(rsim_wdate)

tidy(rsim_wdate, panel = TRUE)

head(index(rsim_wdate))

# For lag = 1 and minimum window = 20
rsim_20 <- radf(sim_data, minw = 20, lag = 1)
# }