MCMCpanic04             PANIC (2004) MCMC Non-Stationarity Tests on
                        Common and Idiosyncratic Components
MCMCpanic10             MCMC PANIC (2010) Sample Moment and PAC tests
                        for Idiosyncratic Component
NIPA_agg_5              NIPA Aggregate Level 5
NIPA_agg_9              NIPA Aggregate Level 9
adf                     ADF test for PANIC (2010)
adf04                   ADF test for PANIC (2004)
adfc2                   ADF critical values for PANIC (2004) demeaned
                        data
adfnc                   ADF test critical values for PANIC (2004)
                        idiosyncratic test
adfp                    Generalized Least Squares Modified
                        Dickey-Fuller t test
coint0                  Cointegration test critical values for PANIC
                        (2004)
getnfac                 Determining The Number of Factors In
                        Approximate Factor Model
glsd                    General Least Squares Detrending
lagn                    Create lags for matrix
lm1                     KPSS test critical values for PANIC (2004)
                        idiosyncratic test
minindc                 Create an Index of lowest values of each column
mydiff                  Difference a matrix
myols                   Beta Coefficients for standard OLS
nuisance                Estimate the nuisance parameters of the error
                        term
nw                      Bandwidth Selection
panic04                 PANIC (2004) Non-Stationarity Tests on Common
                        and Idiosyncratic Components
panic10                 PANIC (2010) Sample Moment and PAC tests for
                        Idiosyncratic Component
pc                      Principle Component Analysis for PANIC (2004)
pool                    Pooling Function for PANIC (2010)
poolcoint               Pooling Function for Cointegration test PANIC
                        (2004)
s2ar                    Finding optimal lag for dfgls test
trimr                   Trim dataset
