Batch file run: D:\Documents\Books_other\Lund\code\16_03_DHSY_IIS.fl

Ox Professional version 7.00 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2013

---- PcGive 14.0B3 session started at 14:56:33 on 20-02-2014 ----

Autometrics identification block search over regressors
no. initial regressors     82  no. of observations        68
significance level      0.025  block method         standard
extension effort     standard  reduction effort     standard
backtesting              GUM0  backtesting in      A,B,C1,D1

Free variables in the GUM:
 c            c            c            c            c            y            y           
 y            y            y            y            D4p          D4p          D4p         
 I:1959(1)    I:1959(2)    I:1959(3)    I:1959(4)    I:1960(1)    I:1960(2)    I:1960(3)   
 I:1960(4)    I:1961(1)    I:1961(2)    I:1961(3)    I:1961(4)    I:1962(1)    I:1962(2)   
 I:1962(3)    I:1962(4)    I:1963(1)    I:1963(2)    I:1963(3)    I:1963(4)    I:1964(1)   
 I:1964(2)    I:1964(3)    I:1964(4)    I:1965(1)    I:1965(2)    I:1965(3)    I:1965(4)   
 I:1966(1)    I:1966(2)    I:1966(3)    I:1966(4)    I:1967(1)    I:1967(2)    I:1967(3)   
 I:1967(4)    I:1968(1)    I:1968(2)    I:1968(3)    I:1968(4)    I:1969(1)    I:1969(2)   
 I:1969(3)    I:1969(4)    I:1970(1)    I:1970(2)    I:1970(3)    I:1970(4)    I:1971(1)   
 I:1971(2)    I:1971(3)    I:1971(4)    I:1972(1)    I:1972(2)    I:1972(3)    I:1972(4)   
 I:1973(1)    I:1973(2)    I:1973(3)    I:1973(4)    I:1974(1)    I:1974(2)    I:1974(3)   
 I:1974(4)    I:1975(1)    I:1975(2)    I:1975(3)    I:1975(4)   

A. Step 1: block search for omitted regressors
  significance          0.025  diagnostics             off
  no of blocks              4  blocked by         variable
- block   3 size= 24 total=  13   8 added
- block   2 size= 24 total=  13
- block   1 size= 24 total=  13
- block   0 size= 10 total=  23  10 added
A. Step 1 (continued): 
- block   0 size= 18 total=  15  10 added
A. Step 1 (continued): 
- block   0 size= 10 total=  11   6 added

A. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size=  6 total=  11 loglik=     258.985 SC=    -6.93464

           lag  sel count    sel run     in GUM
c            4          1          1          1
y            0          1          1          1
y            1          1          1          1
y            5          1          1          1
D4p          0          1          1          1
D4p          1          1          1          1


B. Step 1: block search for omitted regressors
  significance          0.025  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  11
- block   3 size= 24 total=  11
- block   2 size= 24 total=  11
- block   1 size= 24 total=  11
- block   0 size= 10 total=  11

           lag  sel count    sel run     in GUM
c            4          2          2          1
y            0          2          2          1
y            1          2          2          1
y            5          2          2          1
D4p          0          2          2          1
D4p          1          2          2          1


C. Step 1: extended block search for omitted regressors
  significance           0.05  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  11
- block   3 size= 24 total=  11
- block   2 size= 24 total=  11
- block   1 size= 24 total=  11
- block   0 size= 10 total=  12   1 added

C. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size=  7 total=  11 loglik=     258.985 SC=    -6.93464

           lag  sel count    sel run     in GUM
c            4          2          3          1
y            0          2          3          1
y            1          2          3          1
y            5          2          3          1
D4p          0          2          3          1
D4p          1          2          3          1


D. Step 1: extended block search for omitted regressors
  significance      0.0930233  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  11
- block   3 size= 24 total=  15   4 added
- block   2 size= 24 total=  15
- block   1 size= 24 total=  15
- block   0 size= 10 total=  16   1 added

D. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size= 11 total=  11 loglik=     258.985 SC=    -6.93464

           lag  sel count    sel run     in GUM
c            4          3          4          1
y            0          3          4          1
y            1          3          4          1
y            5          3          4          1
D4p          0          3          4          1
D4p          1          3          4          1


Block search complete, estimated 396 models in  0.21
- final block size=  6 regs=  6 total=  11 loglik=     258.985

GUM( 1) Modelling c by OLS
        The dataset is: D:\Documents\Books_other\Lund\code\DHSY.xlsx
        The estimation sample is: 1959(1) - 1975(4)

                  Coefficient  Std.Error  t-value  t-prob Part.R^2
c_4                  0.743693    0.05548     13.4  0.0000   0.7592
y                    0.253798    0.03725     6.81  0.0000   0.4488
y_1                  0.209536    0.04142     5.06  0.0000   0.3099
y_5                 -0.233935    0.04518    -5.18  0.0000   0.3199
D4p                 -0.405005    0.09217    -4.39  0.0000   0.2530
D4p_1                0.236612     0.1003     2.36  0.0218   0.0889
Constant      U      0.217717     0.1185     1.84  0.0713   0.0559
CSeasonal     U    -0.0157890   0.006650    -2.37  0.0210   0.0900
CSeasonal_1   U   -0.00958981   0.002740    -3.50  0.0009   0.1769
CSeasonal_2   U   -0.00626886   0.002893    -2.17  0.0344   0.0761
D4D           U    0.00752690   0.002125     3.54  0.0008   0.1804

sigma              0.00586171  RSS             0.00195849748
R^2                  0.998021  F(10,57) =     2874 [0.000]**
Adj.R^2              0.997674  log-likelihood        258.985
no. of observations        68  no. of parameters          11
mean(c)               8.83719  se(c)                0.121529

AR 1-5 test:      F(5,52)   =  0.69013 [0.6331]  
ARCH 1-4 test:    F(4,60)   =   2.1172 [0.0897]  
Normality test:   Chi^2(2)  =  0.33189 [0.8471]  
Hetero test:      F(17,50)  =   1.3248 [0.2167]  
Chow test:        F(19,38)  =   1.1682 [0.3317]   for break after 1971(1)


---------- Autometrics: dimensions of initial GUM ----------
no. of observations        68  no. of parameters          11
no. free regressors (k1)    6  no. free components (k2)    0
no. of equations            1  no. diagnostic tests        5
Fixed regressors: 
[0] = Constant
[1] = CSeasonal
[2] = CSeasonal_1
[3] = CSeasonal_2
[4] = D4D

[0.2] Presearch reduction of initial GUM

Starting closed lag reduction at 0.21620
Removing lags(#regressors): none

Starting common lag reduction at 0.21620
Removing lags(#regressors): none

Starting common lag reduction at 0.21620 (excluding lagged y's)
Removing lags(#regressors): none

Presearch reduction in opposite order

Starting common lag reduction at 0.21620 (excluding lagged y's)
Removing lags(#regressors): none

Starting common lag reduction at 0.21620
Removing lags(#regressors): none

Starting closed lag reduction at 0.21620
Removing lags(#regressors): none

Encompassing test against initial GUM (iGUM) removes: none

Presearch reduction: none removed

[0.3] Testing GUM 0:  LRF( 6) [0.0000] kept

[1.0] Start of Autometrics tree search

Searching from GUM 0  k=   6 loglik=     258.985

Searching for contrasting terminals in terminal paths

[2.0] Selection of final model from terminal candidates: terminal 0

p-values in Final GUM and terminal model(s)
                 Final GUM
c_4             0.00000000
y               0.00000001
y_1             0.00000468
y_5             0.00000304
D4p             0.00004895
D4p_1           0.02179148
k                        6
parameters              11
loglik              258.99
AIC                -7.2937
HQ                 -7.1514
SC                 -6.9346

coefficients and diagnostic p-values in Final GUM and terminal model(s)
                 Final GUM
c_4                0.74369
y                  0.25380
y_1                0.20954
y_5               -0.23393
D4p               -0.40500
D4p_1              0.23661
k                        6
parameters              11
loglik              258.99
sigma            0.0058617
AR(5)              0.63312
ARCH(4)            0.08971
Normality          0.84709
Hetero             0.21668
Chow(70%)          0.33169

p-values of diagnostic checks for model validity
          Initial GUM     cut-off   Final GUM     cut-off Final model
AR(5)         0.63312     0.01000     0.63312     0.01000     0.63312
ARCH(4)       0.08971     0.01000     0.08971     0.01000     0.08971
Normality     0.84709     0.01000     0.84709     0.01000     0.84709
Hetero        0.21668     0.01000     0.21668     0.01000     0.21668
Chow(70%)     0.33169     0.01000     0.33169     0.01000     0.33169


Summary of Autometrics search
initial search space      2^6  final search space        2^6
no. estimated models        3  no. terminal models         0
test form                LR-F  target size      Medium:0.025
outlier detection          no  presearch reduction      lags
backtesting              GUM0  tie-breaker                SC
diagnostics p-value      0.01  search effort        standard
time                     0.26  Autometrics version      1.5e

EQ( 2) Modelling c by OLS
       The dataset is: D:\Documents\Books_other\Lund\code\DHSY.xlsx
       The estimation sample is: 1959(1) - 1975(4)

                  Coefficient  Std.Error  t-value  t-prob Part.R^2
c_4                  0.743693    0.05548     13.4  0.0000   0.7592
y                    0.253798    0.03725     6.81  0.0000   0.4488
y_1                  0.209536    0.04142     5.06  0.0000   0.3099
y_5                 -0.233935    0.04518    -5.18  0.0000   0.3199
D4p                 -0.405005    0.09217    -4.39  0.0000   0.2530
D4p_1                0.236612     0.1003     2.36  0.0218   0.0889
Constant      U      0.217717     0.1185     1.84  0.0713   0.0559
CSeasonal     U    -0.0157890   0.006650    -2.37  0.0210   0.0900
CSeasonal_1   U   -0.00958981   0.002740    -3.50  0.0009   0.1769
CSeasonal_2   U   -0.00626886   0.002893    -2.17  0.0344   0.0761
D4D           U    0.00752690   0.002125     3.54  0.0008   0.1804

sigma              0.00586171  RSS             0.00195849748
R^2                  0.998021  F(10,57) =     2874 [0.000]**
Adj.R^2              0.997674  log-likelihood        258.985
no. of observations        68  no. of parameters          11
mean(c)               8.83719  se(c)                0.121529

AR 1-5 test:      F(5,52)   =  0.69013 [0.6331]  
ARCH 1-4 test:    F(4,60)   =   2.1172 [0.0897]  
Normality test:   Chi^2(2)  =  0.33189 [0.8471]  
Hetero test:      F(17,50)  =   1.3248 [0.2167]  
Hetero-X test: not enough observations
RESET23 test:     F(2,55)   =   6.4823 [0.0030]**

Autometrics identification block search over regressors
no. initial regressors     82  no. of observations        68
significance level      0.025  block method         standard
extension effort     standard  reduction effort     standard
backtesting              GUM0  backtesting in      A,B,C1,D1

Free variables in the GUM:
 c            c            c            c            c            y            y           
 y            y            y            y            D4p          D4p          D4p         
 I:1959(1)    I:1959(2)    I:1959(3)    I:1959(4)    I:1960(1)    I:1960(2)    I:1960(3)   
 I:1960(4)    I:1961(1)    I:1961(2)    I:1961(3)    I:1961(4)    I:1962(1)    I:1962(2)   
 I:1962(3)    I:1962(4)    I:1963(1)    I:1963(2)    I:1963(3)    I:1963(4)    I:1964(1)   
 I:1964(2)    I:1964(3)    I:1964(4)    I:1965(1)    I:1965(2)    I:1965(3)    I:1965(4)   
 I:1966(1)    I:1966(2)    I:1966(3)    I:1966(4)    I:1967(1)    I:1967(2)    I:1967(3)   
 I:1967(4)    I:1968(1)    I:1968(2)    I:1968(3)    I:1968(4)    I:1969(1)    I:1969(2)   
 I:1969(3)    I:1969(4)    I:1970(1)    I:1970(2)    I:1970(3)    I:1970(4)    I:1971(1)   
 I:1971(2)    I:1971(3)    I:1971(4)    I:1972(1)    I:1972(2)    I:1972(3)    I:1972(4)   
 I:1973(1)    I:1973(2)    I:1973(3)    I:1973(4)    I:1974(1)    I:1974(2)    I:1974(3)   
 I:1974(4)    I:1975(1)    I:1975(2)    I:1975(3)    I:1975(4)   

A. Step 1: block search for omitted regressors
  significance          0.025  diagnostics             off
  no of blocks              4  blocked by         variable
- block   3 size= 24 total=  10   6 added
- block   2 size= 24 total=  10
- block   1 size= 24 total=  10
- block   0 size= 10 total=  20  10 added
A. Step 1 (continued): 
- block   0 size= 16 total=  14  10 added
A. Step 1 (continued): 
- block   0 size= 10 total=  10   6 added

A. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size=  6 total=  10 loglik=     252.322 SC=    -6.80071

           lag  sel count    sel run     in GUM
c            4          1          1          1
y            0          1          1          1
y            1          1          1          1
y            4          1          1          1
y            5          1          1          1
D4p          0          1          1          1


B. Step 1: block search for omitted regressors
  significance          0.025  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  10
- block   3 size= 24 total=  10
- block   2 size= 24 total=  10
- block   1 size= 24 total=  10
- block   0 size= 10 total=  10

           lag  sel count    sel run     in GUM
c            4          2          2          1
y            0          2          2          1
y            1          2          2          1
y            4          2          2          1
y            5          2          2          1
D4p          0          2          2          1


C. Step 1: extended block search for omitted regressors
  significance           0.05  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  10
- block   3 size= 24 total=  10
- block   2 size= 24 total=  10
- block   1 size= 24 total=  12   2 added
- block   0 size= 10 total=  12

C. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size=  8 total=  10 loglik=     252.322 SC=    -6.80071

           lag  sel count    sel run     in GUM
c            4          2          3          1
y            0          2          3          1
y            1          2          3          1
y            4          2          3          1
y            5          2          3          1
D4p          0          2          3          1


D. Step 1: extended block search for omitted regressors
  significance      0.0930233  diagnostics         delayed
  no of blocks              5  blocked by         variable
- block   4 size= 24 total=  10
- block   3 size= 24 total=  13   3 added
- block   2 size= 24 total=  13
- block   1 size= 24 total=  18   5 added
- block   0 size= 10 total=  18
D. Step 1 (continued): 
- block   0 size= 14 total=  16   6 added

D. Step 2: determination of new candidate set
  significance          0.025  diagnostics              on
- block   0 size= 12 total=  10 loglik=     252.322 SC=    -6.80071

           lag  sel count    sel run     in GUM
c            4          3          4          1
y            0          3          4          1
y            1          3          4          1
y            4          3          4          1
y            5          3          4          1
D4p          0          3          4          1


Block search complete, estimated 580 models in  0.26
- final block size=  6 regs=  6 total=  10 loglik=     252.322

GUM( 3) Modelling c by OLS
        The dataset is: D:\Documents\Books_other\Lund\code\DHSY.xlsx
        The estimation sample is: 1959(1) - 1975(4)

                  Coefficient  Std.Error  t-value  t-prob Part.R^2
c_4                  0.789766    0.07224     10.9  0.0000   0.6733
y                    0.309505    0.04062     7.62  0.0000   0.5003
y_1                  0.145715    0.04111     3.54  0.0008   0.1781
y_4                 -0.136465    0.05502    -2.48  0.0161   0.0959
y_5                 -0.129356    0.04716    -2.74  0.0081   0.1148
D4p                 -0.168813    0.03200    -5.28  0.0000   0.3243
Constant      U      0.170945     0.1366     1.25  0.2158   0.0263
CSeasonal     U    -0.0163325   0.007453    -2.19  0.0325   0.0765
CSeasonal_1   U   -0.00806004   0.003320    -2.43  0.0183   0.0922
CSeasonal_2   U   -0.00642369   0.003227    -1.99  0.0512   0.0640

sigma              0.00640922  RSS             0.00238253298
R^2                  0.997592  F(9,58) =      2670 [0.000]**
Adj.R^2              0.997219  log-likelihood        252.322
no. of observations        68  no. of parameters          10
mean(c)               8.83719  se(c)                0.121529

AR 1-5 test:      F(5,53)   =  0.70259 [0.6240]  
ARCH 1-4 test:    F(4,60)   =   2.2652 [0.0726]  
Normality test:   Chi^2(2)  =   1.0655 [0.5870]  
Hetero test:      F(15,52)  =   1.1326 [0.3528]  
Chow test:        F(19,39)  =   1.4115 [0.1777]   for break after 1971(1)


---------- Autometrics: dimensions of initial GUM ----------
no. of observations        68  no. of parameters          10
no. free regressors (k1)    6  no. free components (k2)    0
no. of equations            1  no. diagnostic tests        5
Fixed regressors: 
[0] = Constant
[1] = CSeasonal
[2] = CSeasonal_1
[3] = CSeasonal_2

[0.2] Presearch reduction of initial GUM

Starting closed lag reduction at 0.21620
Removing lags(#regressors): none

Starting common lag reduction at 0.21620
Removing lags(#regressors): none

Starting common lag reduction at 0.21620 (excluding lagged y's)
Removing lags(#regressors): none

Presearch reduction in opposite order

Starting common lag reduction at 0.21620 (excluding lagged y's)
Removing lags(#regressors): none

Starting common lag reduction at 0.21620
Removing lags(#regressors): none

Starting closed lag reduction at 0.21620
Removing lags(#regressors): none

Encompassing test against initial GUM (iGUM) removes: none

Presearch reduction: none removed

[0.3] Testing GUM 0:  LRF( 6) [0.0000] kept

[1.0] Start of Autometrics tree search

Searching from GUM 0  k=   6 loglik=     252.322

Searching for contrasting terminals in terminal paths

[2.0] Selection of final model from terminal candidates: terminal 0

p-values in Final GUM and terminal model(s)
                 Final GUM
c_4             0.00000000
y               0.00000000
y_1             0.00078498
y_4             0.01605663
y_5             0.00808982
D4p             0.00000205
k                        6
parameters              10
loglik              252.32
AIC                -7.1271
HQ                 -6.9978
SC                 -6.8007

coefficients and diagnostic p-values in Final GUM and terminal model(s)
                 Final GUM
c_4                0.78977
y                  0.30950
y_1                0.14571
y_4               -0.13647
y_5               -0.12936
D4p               -0.16881
k                        6
parameters              10
loglik              252.32
sigma            0.0064092
AR(5)              0.62397
ARCH(4)            0.07260
Normality          0.58699
Hetero             0.35281
Chow(70%)          0.17765

p-values of diagnostic checks for model validity
          Initial GUM     cut-off   Final GUM     cut-off Final model
AR(5)         0.62397     0.01000     0.62397     0.01000     0.62397
ARCH(4)       0.07260     0.01000     0.07260     0.01000     0.07260
Normality     0.58699     0.01000     0.58699     0.01000     0.58699
Hetero        0.35281     0.01000     0.35281     0.01000     0.35281
Chow(70%)     0.17765     0.01000     0.17765     0.01000     0.17765


Summary of Autometrics search
initial search space      2^6  final search space        2^6
no. estimated models        4  no. terminal models         0
test form                LR-F  target size      Medium:0.025
outlier detection          no  presearch reduction      lags
backtesting              GUM0  tie-breaker                SC
diagnostics p-value      0.01  search effort        standard
time                     0.32  Autometrics version      1.5e

EQ( 4) Modelling c by OLS
       The dataset is: D:\Documents\Books_other\Lund\code\DHSY.xlsx
       The estimation sample is: 1959(1) - 1975(4)

                  Coefficient  Std.Error  t-value  t-prob Part.R^2
c_4                  0.789766    0.07224     10.9  0.0000   0.6733
y                    0.309505    0.04062     7.62  0.0000   0.5003
y_1                  0.145715    0.04111     3.54  0.0008   0.1781
y_4                 -0.136465    0.05502    -2.48  0.0161   0.0959
y_5                 -0.129356    0.04716    -2.74  0.0081   0.1148
D4p                 -0.168813    0.03200    -5.28  0.0000   0.3243
Constant      U      0.170945     0.1366     1.25  0.2158   0.0263
CSeasonal     U    -0.0163325   0.007453    -2.19  0.0325   0.0765
CSeasonal_1   U   -0.00806004   0.003320    -2.43  0.0183   0.0922
CSeasonal_2   U   -0.00642369   0.003227    -1.99  0.0512   0.0640

sigma              0.00640922  RSS             0.00238253298
R^2                  0.997592  F(9,58) =      2670 [0.000]**
Adj.R^2              0.997219  log-likelihood        252.322
no. of observations        68  no. of parameters          10
mean(c)               8.83719  se(c)                0.121529

AR 1-5 test:      F(5,53)   =  0.70259 [0.6240]  
ARCH 1-4 test:    F(4,60)   =   2.2652 [0.0726]  
Normality test:   Chi^2(2)  =   1.0655 [0.5870]  
Hetero test:      F(15,52)  =   1.1326 [0.3528]  
Hetero-X test: not enough observations
RESET23 test:     F(2,56)   =   4.7762 [0.0122]* 
