*@M_TAR  series start end  resids
*
* Computes the Momentum-TAR unit root test. References:
*   Enders, W. and Granger C.W.J (1998), "Unit-root Tests and Asymmetric Adjustment with an Example Using
*    the Term Structure of Interest Rates", Journal of Business and Economic Statistics, 16, 304-311
*   Enders, W.(2001) "Improved critical values for the Enders-Granger unit-root test", Applied Economic
*    Letters, 8, 257-261
*
* Options:
*    Model=[MTAR]/TAR; This determines whether the Threshold Autoregressive or Momentum-TAR unit root
*      test is computed
*    LAGS=number of additional lags [0] ; LAGS indicates the degree of AR polynomial on the differences
*      to include in the regressions
*    Method=[CONSISTENT]/KNOWN; These determine whether a consistent estimate as of Chan's method (1993)
*      or the sample mean are used for estimation of the threshold.
*
*   The procedure offers the possibility of saving the residuals for diagnostic checking.
*
*
*  Sept.2005, Written by: Walter Enders and Razvan Pascalau, University of Alabama
*             rpascala@cba.ua.edu
*
*
procedure M_TAR series1 start end resids
type series series1  *resids
type integer start end
*
option choice  model 1 MTAR TAR
option choice  method 1 consistent known
option integer lags 0
*
local series  y yy dy dyy resids
local integer v1 v2  nobs
local rectangular[real] known consistent knownt consistentt
*
inquire(series=series1) v1>>start v2>>end
*
DIMENSION Known(3,13) Consistent(3,13) Knownt(3,4) Consistentt(3,13)

* critical values at 90%, 95%, 97.5%, 99%  (table 1 & 2 p. 259)

compute Known       = ||  50 , 4.21 , 5.19 , 6.15 , 7.55  $
                       | 100 , 4.11 , 5.04 , 5.96 , 7.10  $
                       | 250 , 4.08 , 4.97 , 5.83 , 6.91  $
                       ||
compute Consistent  = ||  50 , 5.02 , 6.05 , 7.09 , 8.59  $
                       | 100 , 4.81 , 5.77 , 6.73 , 7.99  $
                       | 250 , 4.70 , 5.64 , 6.51 , 7.64  $
                       ||
compute Knownt      = ||  50 , 3.27 , 4.08 , 4.91 , 6.07  $
                       | 100 , 3.18 , 3.95 , 4.72 , 5.76  $
                       | 250 , 3.09 , 3.82 , 4.54 , 5.51  $
                       ||
compute Consistentt = ||  50 , 5.15 , 6.19 , 7.25 , 8.64  $
                       | 100 , 5.08 , 6.06 , 6.93 , 8.19  $
                       | 250 , 5.11 , 6.03 , 6.88 , 8.04  $
                       ||

*
if model.eq.2 {
 *
 if method.eq.2 {
 linreg(noprint) series1 v1 v2  y ; # constant ; *demean the series
 dis 'Threshold = ' %beta

 set flag = %if(y{1}<0,0,1)
 set yplus = flag*y{1}
 set yminus = (1-flag)*y{1}
 *
  dif y v1+1 v2 dy
  if lags {
  linreg dy v1+lags+1 v2 resids ; # yplus yminus  dy{1 to lags}
    }
  else {
  linreg dy v1+1 v2 resids ; # yplus yminus
  }
  display
  display 'TAR Unit Root Test, Series' %l(series1)
  display 'Regression Run From' %datelabel(v1+lags+1) 'to' %datelabel(v2)
  *
  exclude
  # yplus yminus
  display '---------------------------------------------------------'
  display '                      With known threshold               '
  display '---------------------------------------------------------'

  compute f = %cdstat
  compute nobs = %nobs + 1
display 'critical values at' @20 '90%' @28 '95%' @36 '97.5%' @44 '99%'
    if nobs<100
     display @3 'for 50 obs.' @19 #.## knownt(1,2) @27 #.## knownt(1,3) @36 #.## knownt(1,4) $
          @43 #.## knownt(1,5)
    if nobs>100.and.nobs<250
     display @3 'for 100 obs.' @19 #.## knownt(2,2) @27 #.## knownt(2,3) @36 #.## knownt(2,4) $
          @43 #.## knownt(2,5)
    if nobs>250
     display @3 'for 250 obs.' @19 #.## knownt(3,2) @27 #.## knownt(3,3) @36 #.## knownt(3,4) $
          @43 #.## knownt(3,5)
     * now test rho1 = rho2
     display '-----------------------------------------------------------------------'
     display 'Perform the test for symmetric adjustment(rho1=rho2)'
     restrict 1
     # 1 2
     # 1 -1 0
     }
 else if method.eq.1 {
 compute rss_test = 1000000.0
 set thresh_test = series1
 order thresh_test
 compute low = v1 + fix(%nobs*.15), high = v2 - fix(%nobs*0.15)
*
 compute thresh = thresh_test(low)
 do ii = low,high
 set yy = series1 - thresh_test(ii)
 dif yy v1+1 v2 dyy
 set flag = %if(yy{1}<0,0,1)
 set y_plus = flag*yy{1}
 set y_minus = (1-flag)*yy{1}
 linreg(noprint) dyy v1+1 v2
 # y_plus y_minus
 if %rss < rss_test {
 compute rss_test = %rss
 compute thresh = thresh_test(ii)
 }
 end do ii
 dis 'Threshold = ' thresh

 *
 set yy = series1 - thresh
 set flag = %if(yy{1}<0,0,1)
 set y_plus = flag*yy{1}
 set y_minus = (1-flag)*yy{1}
 *
  dif yy v1+1 v2 dyy
  if lags {
  linreg dyy v1+lags+1 v2 resids ; # y_plus y_minus  dyy{1 to lags}
  }
  else {
  linreg dyy v1+1 v2 resids ; # y_plus y_minus
  }
  display
  display 'TAR Unit Root Test, Series' %l(series1)
  display 'Regression Run From' %datelabel(v1+lags+1) 'to' %datelabel(v2)
  exclude
  # y_plus y_minus
  display '---------------------------------------------------------'
  display '                  With consistent threshold              '
  display '---------------------------------------------------------'

  compute f = %cdstat
  compute nobs = %nobs + 1
display 'critical values at' @20 '90%' @28 '95%' @36 '97.5%' @44 '99%'
    if nobs<100
     display @3 'for 50 obs.' @19 #.## consistentt(1,2) @27 #.## consistentt(1,3) @36 #.## consistentt(1,4) $
          @43 #.## consistentt(1,5)
    if nobs>100.and.nobs<250
     display @3 'for 100 obs.' @19 #.## consistentt(2,2) @27 #.## consistentt(2,3) @36 #.## consistentt(2,4) $
          @43 #.## consistentt(2,5)
    if nobs>250
     display @3 'for 250 obs.' @19 #.## consistentt(3,2) @27 #.## consistentt(3,3) @36 #.## consistentt(3,4) $
          @43 #.## consistentt(3,5)
     * now test rho1 = rho2
     display '-----------------------------------------------------------------------'
     disply 'Perform the test for symmetric adjustment(rho1=rho2)'
     restrict 1
     # 1 2
     # 1 -1 0
        }
      }
 else if model.eq.1 {
 if method.eq.2 {
 linreg(noprint) series1 v1 v2  y ; # constant ; *demean the series
 dis 'Threshold = ' %beta
 dif y v1+1 v2 dy
 set flag = %if(dy{1}<0,0,1)
 set yplus = flag*y{1}
 set yminus = (1-flag)*y{1}
 *
 if lags {
  linreg dy v1+lags+1 v2 resids ; # yplus yminus  dy{1 to lags}
  }
  else {
  linreg dy v1+1 v2 resids ; # yplus yminus
    }
  display
  display 'M-TAR Unit Root Test, Series' %l(series1)
  display 'Regression Run From' %datelabel(v1+lags+1) 'to' %datelabel(v2)
  *
  exclude
  # yplus yminus
  display '---------------------------------------------------------'
  display '                        With known threshold             '
  display '---------------------------------------------------------'

  compute f = %cdstat
  compute nobs = %nobs + 1
display 'critical values at' @20 '90%' @28 '95%' @36 '97.5%' @44 '99%'
    if nobs<100
     display @3 'for 50 obs.' @19 #.## known(1,2) @27 #.## known(1,3) @36 #.## known(1,4) $
          @43 #.## known(1,5)
    if nobs>100.and.nobs<250
     display @3 'for 100 obs.' @19 #.## known(2,2) @27 #.## known(2,3) @36 #.## known(2,4) $
          @43 #.## known(2,5)
    if nobs>250
     display @3 'for 250 obs.' @19 #.## known(3,2) @27 #.## known(3,3) @36 #.## known(3,4) $
          @43 #.## known(3,5)
     * now test rho1 = rho2
     display '-----------------------------------------------------------------------'
     disply 'Perform the test for symmetric adjustment(rho1=rho2)'
     restrict 1
     # 1 2
     # 1 -1 0
      }
 else if method.eq.1 {
 compute rss_test = 1000000.0
 set thresh_test = series1
 order thresh_test
 compute low = v1 + fix(%nobs*.15), high = v2 - fix(%nobs*0.15)
*
 compute thresh = thresh_test(low)
 do ii = low,high
 set yy = series1 - thresh_test(ii)
 dif yy v1+1 v2 dyy
 set flag = %if(dyy{1}<0,0,1)
 set y_plus = flag*yy{1}
 set y_minus = (1-flag)*yy{1}
 linreg(noprint) dyy v1+1 v2
 # y_plus y_minus
 if %rss < rss_test {
 compute rss_test = %rss
 compute thresh = thresh_test(ii)
  }
 end do ii
 dis 'Threshold = ' thresh
*
 set yy = series1 - thresh
 dif yy v1+1 v2 dyy
 set flag = %if(dyy{1}<0,0,1)
 set y_plus = flag*yy{1}
 set y_minus = (1-flag)*yy{1}
 *
 if lags {
  linreg dyy v1+lags+1 v2 resids ; # y_plus y_minus dyy{1 to lags}
   }
  else {
  linreg dyy v1+1 v2 resids ; # y_plus y_minus
  }
  display
  display 'M-TAR Unit Root Test, Series' %l(series1)
  display 'Regression Run From' %datelabel(v1+lags+1) 'to' %datelabel(v2)
  exclude
  # y_plus y_minus
  display '---------------------------------------------------------'
  display '                     With consistent threshold           '
  display '---------------------------------------------------------'

  compute f = %cdstat
  compute nobs = %nobs + 1
display 'critical values at' @20 '90%' @28 '95%' @36 '97.5%' @44 '99%'
    if nobs<100
     display @3 'for 50 obs.' @19 #.## consistent(1,2) @27 #.## consistent(1,3) @36 #.## consistent(1,4) $
          @43 #.## consistent(1,5)
    if nobs>100.and.nobs<250
     display @3 'for 100 obs.' @19 #.## consistent(2,2) @27 #.## consistent(2,3) @36 #.## consistent(2,4) $
          @43 #.## consistent(2,5)
    if nobs>250
     display @3 'for 250 obs.' @19 #.## consistent(3,2) @27 #.## consistent(3,3) @36 #.## consistent(3,4) $
          @43 #.## consistent(3,5)
     * now test rho1 = rho2
     display '-----------------------------------------------------------------------'
     disply 'Perform the test for symmetric adjustment(rho1=rho2)'
     restrict 1
     # 1 2
     # 1 -1 0
     }
   }
end