mdl() calls main functions of the mbreaks package to execute the following
estimation procedures:
dotest() conducts Sup F tests of 0 versus m breaks and Double Max tests
doseqtests() conducts the sequential Sup F tests of l versus l+1 breaks
doorder() conducts the number of breaks selection from 1 to m
breaks using information critera: {'KT','BIC','LWZ'}
dosequa() conducts the number of breaks selection by sequential tests
from 1 to m breaks using sequential Sup F tests
dofix() conducts structural break model estimation with fixn breaks
All the procedures automatically identify if the model is either i) pure structural
breaks model or ii) partial structural breaks model
mdl(
y_name,
z_name = NULL,
x_name = NULL,
data,
eps1 = 0.15,
m = 5,
prewhit = 1,
robust = 1,
hetdat = 1,
hetvar = 1,
hetomega = 1,
hetq = 1,
maxi = 10,
eps = 1e-05,
fixn = -1,
fixb = 0,
betaini = 0,
printd = 0,
const = 1,
signif = 2,
h = NULL
)A list that contains the following:
sbtests: class sbtests of Sup F tests of 0 versus m breaks and Double Max tests
seqtests: class seqtests of sequential Sup F test of l versus l+1 breaks
BIC: class model of structural break model with estimated number of breaks by BIC criterion
LWZ: class model of structural break model with estimated number of breaks by LWZ criterion
KT: class model of structural break model with estimated number of breaks by KT criterion
sequa: class model of structural break model with estimated number of breaks by sequential tests
fix: class model of structural break model with pre-specified fixn number of breaks
Note: All default values of error assumptions (robust,
hetdat, hetvar, hetq) are set to 1. The implications on
the structure of model's errors related to individual settings are explained within
the arguments section for each option.
name of dependent variable in the data set
name of independent variables in the data set which coefficients are allowed to change
across regimes. default is vector of 1 (Mean-shift model)
name of independent variables in the data set which coefficients are constant across
regimes. default is NULL
the data set for estimation
value of trimming (in percentage) for the construction
and critical values. Minimal segment length h will be set
at default = int(eps1*T) (T is total sample size).
eps1=0.05 Maximal value of m = 10
eps1=0.10 Maximal value of m = 8
eps1=.15 Maximal value of m = 5
eps1=.20 Maximal value of m = 3
eps1=.25 Maximal value of m = 2
eps1=0 This option allows users to explicitly specify
minimum segment length h parameters. However, this option will not
be allowed for testing and testing related functions
The default value is set at 0.15
Maximum number of structural changes allowed. If not specify,
m will be set to default value matching eps1 input
set to 1 to apply AR(1) prewhitening prior to estimating
the long run covariance matrix.
set to 1 to allow for heterogeneity
and autocorrelation in the residuals, 0 otherwise.
The method used is Andrews(1991) automatic bandwidth with AR(1) approximation with quadratic
kernel. Note: Do not set to 1 if lagged dependent variables are
included as regressors.
option for the construction of the F tests. Set to 1 if want to
allow different moment matrices of the regressors across segments.
If hetdat = 0, the same moment matrices are assumed for each segment
and estimated from the ful sample. It is recommended to set
hetdat=1 if number of regressors x > 0.
option for the construction of the F tests.Set to 1
if users want to allow for the variance of the residuals to be different across segments.
If hetvar=0, the variance of the residuals is assumed constant
across segments and constructed from the full sample. hetvar=1 when robust =1)
used in the construction of the confidence intervals for the break
dates. If hetomega=0, the long run covariance matrix of zu is
assumed identical across segments (the variance of the errors u if robust=0)
used in the construction of the confidence intervals for the break
dates. If hetq=0, the moment matrix of the data is assumed identical
across segments
number of maximum iterations for recursive calculations of finding
global minimizers.default = 10 (For partial change model ONLY)
convergence criterion for recursive calculations (For partial change model ONLY)
number of pre-specified breaks. default = -1. It will be replaced
automatically to 2 if no specification is given (For partial change model ONLY)
option to use fixed initial input \(\beta\). If 1,
the model will use values given in betaini. If 0, betaini is skipped
Initial \(beta_0\) to use in estimation (Must be a p x 1 matrix, where p is number of x variables)
Print option for model estimation. default = 0, to
suppress intermediate outputs printing to console
indicates whether the regression model include an intercept changing across regimes. Default value is 1
significance level used to sequential test to select number of breaks.
4: 1% level
3: 2.5% level
2: 5% level
1: 10% level
Minimum segment length of regime considered in estimation. If users want to specify a particular value, please set eps1=0
dotest(), doseqtests(), doorder(), dosequa(), and dofix()
which are functions called by mdl().
US_rate = mdl('rate',data=real)
nkpc_lbs = mdl('inf',c('inflag','lbs','inffut'),data=nkpc,prewhit = 0)
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