uroot2 |
type=arg (default=“panic”) | Type of unit root test: PANIC - Bai and Ng (2004) (“panic”), CIPS - Pesaran (2007) (“cips”). Note: (1) when performing PANIC testing, factor selection, MQ, ADF lag selection, VAR lag selection (possibly), long-run variance (possibly), and p-value simulation options are relevant. (2) when perform CIPS testing, ADF lag selection options are relevant. |
exog=arg (default=“constant”) | Exogenous deterministic variables to include for each cross-section: “none” (no deterministic variables), “constant” (only a constant), “trend” (both a constant and trend). |
prompt | Force the dialog to appear from within a program. |
p | Print results. |
adflagmethod=arg (default=“sic”) | Method for selecting lag length (number of first difference terms) to be included in the Dickey-Fuller test regression or number of lags in the AR spectral density estimator: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “msaic” (Modified Akaike), “msic” (Modified Schwarz), “mhqc” (Modified Hannan-Quinn), “tstat” (Ng-Perron first backward significant t-statistic). |
adflag=integer | Use-specified fixed lag. |
adfmaxlag=integer | Maximum lag length to consider when performing automatic lag length selection. Note: default is Schwert’s rule: let for and let ; then the default maximum lag is given by |
adflagpval=arg (default=0.1) | Probability value for use in the t-statistic automatic lag selection method (“lagmethod = tstat”). |
fsmethod=arg (default=“bn”) | Factor retention selection method: “bn” (Bai and Ng (2002)), “ah” (Ahn and Horenstein (2013)), “simple” (simple eigenvalue methods), “user” (user-specified value). Note the following: (1) If using simple methods, the minimum eigenvalue and cumulative proportions may be specified using “minigen=” and “cproport=”. (2) If setting “fsmethod=user” to provide a user-specified value, you must specify the value with “r=”. |
r=arg (default=1) | User-specified number of factors to retain (for use when “fsmethod=user”). |
mineigen=arg (default=0) | Minimum eigenvalue to retain factor (when “fsmethod=simple”). |
cproport=arg (default=1.0) | Cumulative proportion of eigenvalue total to attain (when “fsmethod=simple”). |
mfmethod=arg | Maximum number of factors used by selection methods: “schwert” (Schwert’s rule, default), “ah” (Ahn and Horenstein’s (2013) suggestion), “rootsize” (), “size” (), “user” (user specified value). (1) For use with all factor retention methods apart from user-specified (“fsmethod=user”). (2) If setting “mfmethod=user”, you may specify the maximum number of factors using “rmax=”. (3) Schwert’s rule sets the maximum number of factors using the rule: let for and let ; then the default maximum lag is given by |
rmax=arg (default=all) | User-specified maximum number of factors to retain (for use when “mfmethod=user”). |
fsic=arg (default=avg) | Factor selection criterion when “fsmethod=bn”: “icp1” (ICP1), “icp2” (ICP2), “icp3” (ICP3), “pcp1” (PCP1), “pcp2” (PCP1), “pcp3” (ICP3), “avg” (average of all criteria ICP1 through PCP3). Factor selection criterion when “fsmethod=ah”: “er” (eigenvalue ratio), “gr” (growth ratio), “avg” (average of eigenvalue ratio and growth ratio). Factor selection when “fsmethod=simple”: “min” (minimum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “max” (maximum of: minimum eigenvalue, cumulative eigenvalue proportion, and maximum number of factors), “avg” (average the optimal number of factors as specified by the min and max rule, then round to the nearest integer). |
demeantime | Demeans observations across time prior to factor selection procedures. |
sdizetime | Standardizes observations across time prior to factor selection procedures. |
demeancross | Demeans observations across cross-sections prior to factor selection procedures. |
sdizecross | Standardizes observations across cross-sections prior to factor selection procedures. |
varlagmethod=arg (default=“sic”) | Method for selecting lag length (number of first difference terms) to be included in the test statistic VAR: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn), “msaic” (Modified Akaike), “msic” (Modified Schwarz), “mhqc” (Modified Hannan-Quinn), “tstat” (Ng-Perron first backward significant t-statistic). |
varlag=integer | Use-specified fixed lag. |
varmaxlag=integer | Maximum lag length to consider when performing automatic lag length selection. Note: default is Schwert’s rule: let for and let ; then the default maximum lag is given by |
lag=arg | Lag specification: integer (user-specified number of lags), “a” (automatic selection). |
infosel=arg (default=“aic”) | Information criterion for automatic selection: “aic” (Akaike), “sic” (Schwarz), “hqc” (Hannan-Quinn) (if “lag=a”). |
maxlag=integer | Maximum lag-length for automatic selection (optional) (if “lag=a”). The default is an observation-based maximum of . |
kern=arg (default=“bart”) | Kernel shape: “none” (no kernel), “bart” (Bartlett), “bohman” (Bohman), “daniell” (Daniel), “parzen” (Parzen), “parzriesz” (Parzen-Riesz), “parzgeo” (Parzen-Geometric), “parzcauchy” (Parzen-Cauchy), “quadspec” (Quadratic Spectral), “trunc” (Truncated), “thamm” (Tukey-Hamming), “thann” (Tukey-Hanning), “tparz” (Tukey-Parzen), “user” (User-specified; see “kernwgt=” below). |
kernwgt=vector | User-specified kernel weight vector (if “kern=user”). |
bw=arg (default=”nwfixed”) | Bandwidth: “fixednw” (Newey-West fixed), “andrews” (Andrews automatic), “neweywest” (Newey-West automatic), number (User-specified bandwidth). |
nwlag=integer | Newey-West lag-selection parameter for use in nonparametric bandwidth selection (if “bw=neweywest”). |
bwoffset=integer (default=0) | Apply integer offset to bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”). |
bwint | Use integer portion of bandwidth chosen by automatic selection method (“bw=andrews” or “bw=neweywest”). |
mcreps=integer | Number of Monte Carlo replications. |
asymplen=integer | Asymptotic length of series. |
seed=number | Specifies the random number generator seed |
rng=arg | Specifies the type of random number generator. The key can be; improved Knuth generator (“kn”), improved Mersenne Twister (“mt”), Knuth’s (1997) lagged Fibonacci generator used in EViews 4 (“kn4”) L’Ecuyer’s (1999) combined multiple, recursive generator (“le”), Matsumoto and Nishimura’s (1998) Mersenne Twister used in EViews 4 (“mt4”). |