--------------- TSP at 13:07:27 on 31-Dec-2009 --------------- ------------------------------------- | this copy licensed | | for use by: | | TSP 5.1/OxMetrics 11/09#51AGT1109 | ------------------------------------- TSP Version 5.1 11/16/09 TSP/OxMetrics 4MB Copyright (c) 2009 TSP International ALL RIGHTS RESERVED 12/31/09 1:07 PM In case of questions or problems, see your local TSP consultant or send a description of the problem and the associated TSP output to: TSP International P.O. Box 61015 Palo Alto, CA 94306 USA PROGRAM COMMAND *************************************************************** 1 options double ; 2 name gir2 2 'Generalized Impulse Response - example with KPSW data/model' ; 2 ? 2 ? (second example, using LSQ and SOLVE to compute the IRs) 2 ? Follows Pesaran, H. Hashem and Shin, Yongcheol (1998), 2 ? Generalized Impulse Response Analysis in Linear Multivariate 2 ? Regression, Economics Letters 58, 17-29. 2 ? - paper downloaded from H. Hashem Pesaran's web page 2 ? - KPSW data downloaded from Mark Watson's web page 2 ? by Clint Cummins 3/7/2002 2 ? 2 load ; 3 y = log(ey) ; 4 cons = log(ec) ; 5 in = log(ein) ; 6 smpl 48:1 88:4 ; ? sample for estimation 7 trend t ; 8 cint = 1 ; ? do not use C as intercept, because the intercept 9 ? must be set to zero for IRs. 9 9 ? Fill in these next 4 variables, and the remaining commands 9 ? below will not need to be modified. 9 9 list ys y cons in ; 10 list xs cint t ; 11 set maxlag=4 ; 12 set horiz=51 ; 13 13 title 'GIR - generalized impulse response' ; 14 title 'IRs computed with VAR command' ; 15 15 ? This part is optional ; included for verifying the alternative calculation 15 ? using LSQ and SOLVE. 15 var(terse,nlag=maxlag,shock=chol,nhoriz=horiz) ys | xs ; 16 var(terse,nlag=maxlag,shock=stddev,nhoriz=horiz) ys | xs ; 17 var(terse,nlag=maxlag,shock=unit,nhoriz=horiz) ys | xs ; 18 18 ? Shock for GIR (invariant to ordering of variables) 18 ? We are using the VAR(SHOCK=matrix) option to compute the IR, and TSP looks for the shocks 18 ? in the rows of this matrix, so the TSP shock matrix is the transpose of the shock matrix 18 ? given by Pesaran and Shin. 18 18 ? Normalizing diagonal matrix 18 mat rsdi = sqrt(diag(@covu)") ; 19 mat shgir = (@covu*rsdi)' ; 20 print shgir ; 21 var(terse,nlag=maxlag,shock=shgir,nhoriz=horiz) ys | xs ; 22 copy @impres gir ; 23 23 ? Don't use terse option if you want plots. 23 var(nlag=maxlag,shock=gen,nhoriz=horiz) ys | xs ; 24 select .not.miss(@iry_cons) ; 25 plot @iry_cons @iry_consLB95% @iry_consUB95% ; 26 26 end ; EXECUTION ******************************************************************************* 2 ? Data is loaded here 2 noprint ; Current sample: 1947:1 to 1988:4 Current sample: 1948:1 to 1988:4 GIR - generalized impulse response ================================== IRs computed with VAR command ============================= Log likelihood = 1554.89 Estimated Standard Variable Coefficient Error t-statistic P-value Y(-1) .891636 .110032 8.10342 [.000] Y(-2) -.040600 .134712 -.301387 [.764] Y(-3) -.027832 .135452 -.205474 [.837] Y(-4) -.081163 .110764 -.732761 [.465] CONS(-1) .325983 .145477 2.24079 [.027] CONS(-2) -.093956 .186342 -.504212 [.615] CONS(-3) -.153634 .182575 -.841484 [.401] CONS(-4) .142164 .145851 .974723 [.331] IN(-1) .136072 .054900 2.47853 [.014] IN(-2) -.121448 .079002 -1.53726 [.126] IN(-3) -.033505 .075129 -.445968 [.656] IN(-4) .030695 .051103 .600640 [.549] CINT -.042359 .130281 -.325134 [.746] T .419361E-04 .128792E-03 .325611 [.745] Y(-1) .125140 .069818 1.79237 [.075] Y(-2) -.133751 .085478 -1.56475 [.120] Y(-3) -.162773 .085947 -1.89386 [.060] Y(-4) .134572 .070282 1.91474 [.057] CONS(-1) .849446 .092308 9.20229 [.000] CONS(-2) .337746 .118238 2.85648 [.005] CONS(-3) -.083755 .115848 -.722971 [.471] CONS(-4) -.072322 .092546 -.781471 [.436] IN(-1) -.360804E-02 .034835 -.103574 [.918] IN(-2) -.016380 .050129 -.326755 [.744] IN(-3) .052740 .047671 1.10634 [.270] IN(-4) -.055964 .032426 -1.72590 [.086] CINT -.160091 .082666 -1.93659 [.055] T .986245E-04 .817213E-04 1.20684 [.229] Y(-1) .593027 .212069 2.79639 [.006] Y(-2) -.600527 .259635 -2.31297 [.022] Y(-3) -.186934 .261061 -.716055 [.475] Y(-4) -.777275E-03 .213479 -.364099E-02 [.997] CONS(-1) .095436 .280382 .340379 [.734] CONS(-2) .210575 .359144 .586325 [.559] CONS(-3) .067869 .351884 .192873 [.847] CONS(-4) -.027531 .281104 -.097940 [.922] IN(-1) 1.12591 .105811 10.6407 [.000] IN(-2) -.322583 .152264 -2.11857 [.036] IN(-3) .068687 .144799 .474363 [.636] IN(-4) -.028236 .098493 -.286683 [.775] CINT -.180497 .251096 -.718836 [.473] T -.777044E-04 .248225E-03 -.313040 [.755] Log likelihood = 1554.89 Estimated Standard Variable Coefficient Error t-statistic P-value Y(-1) .891636 .110032 8.10342 [.000] Y(-2) -.040600 .134712 -.301387 [.764] Y(-3) -.027832 .135452 -.205474 [.837] Y(-4) -.081163 .110764 -.732761 [.465] CONS(-1) .325983 .145477 2.24079 [.027] CONS(-2) -.093956 .186342 -.504212 [.615] CONS(-3) -.153634 .182575 -.841484 [.401] CONS(-4) .142164 .145851 .974723 [.331] IN(-1) .136072 .054900 2.47853 [.014] IN(-2) -.121448 .079002 -1.53726 [.126] IN(-3) -.033505 .075129 -.445968 [.656] IN(-4) .030695 .051103 .600640 [.549] CINT -.042359 .130281 -.325134 [.746] T .419361E-04 .128792E-03 .325611 [.745] Y(-1) .125140 .069818 1.79237 [.075] Y(-2) -.133751 .085478 -1.56475 [.120] Y(-3) -.162773 .085947 -1.89386 [.060] Y(-4) .134572 .070282 1.91474 [.057] CONS(-1) .849446 .092308 9.20229 [.000] CONS(-2) .337746 .118238 2.85648 [.005] CONS(-3) -.083755 .115848 -.722971 [.471] CONS(-4) -.072322 .092546 -.781471 [.436] IN(-1) -.360804E-02 .034835 -.103574 [.918] IN(-2) -.016380 .050129 -.326755 [.744] IN(-3) .052740 .047671 1.10634 [.270] IN(-4) -.055964 .032426 -1.72590 [.086] CINT -.160091 .082666 -1.93659 [.055] T .986245E-04 .817213E-04 1.20684 [.229] Y(-1) .593027 .212069 2.79639 [.006] Y(-2) -.600527 .259635 -2.31297 [.022] Y(-3) -.186934 .261061 -.716055 [.475] Y(-4) -.777275E-03 .213479 -.364099E-02 [.997] CONS(-1) .095436 .280382 .340379 [.734] CONS(-2) .210575 .359144 .586325 [.559] CONS(-3) .067869 .351884 .192873 [.847] CONS(-4) -.027531 .281104 -.097940 [.922] IN(-1) 1.12591 .105811 10.6407 [.000] IN(-2) -.322583 .152264 -2.11857 [.036] IN(-3) .068687 .144799 .474363 [.636] IN(-4) -.028236 .098493 -.286683 [.775] CINT -.180497 .251096 -.718836 [.473] T -.777044E-04 .248225E-03 -.313040 [.755] Log likelihood = 1554.89 Estimated Standard Variable Coefficient Error t-statistic P-value Y(-1) .891636 .110032 8.10342 [.000] Y(-2) -.040600 .134712 -.301387 [.764] Y(-3) -.027832 .135452 -.205474 [.837] Y(-4) -.081163 .110764 -.732761 [.465] CONS(-1) .325983 .145477 2.24079 [.027] CONS(-2) -.093956 .186342 -.504212 [.615] CONS(-3) -.153634 .182575 -.841484 [.401] CONS(-4) .142164 .145851 .974723 [.331] IN(-1) .136072 .054900 2.47853 [.014] IN(-2) -.121448 .079002 -1.53726 [.126] IN(-3) -.033505 .075129 -.445968 [.656] IN(-4) .030695 .051103 .600640 [.549] CINT -.042359 .130281 -.325134 [.746] T .419361E-04 .128792E-03 .325611 [.745] Y(-1) .125140 .069818 1.79237 [.075] Y(-2) -.133751 .085478 -1.56475 [.120] Y(-3) -.162773 .085947 -1.89386 [.060] Y(-4) .134572 .070282 1.91474 [.057] CONS(-1) .849446 .092308 9.20229 [.000] CONS(-2) .337746 .118238 2.85648 [.005] CONS(-3) -.083755 .115848 -.722971 [.471] CONS(-4) -.072322 .092546 -.781471 [.436] IN(-1) -.360804E-02 .034835 -.103574 [.918] IN(-2) -.016380 .050129 -.326755 [.744] IN(-3) .052740 .047671 1.10634 [.270] IN(-4) -.055964 .032426 -1.72590 [.086] CINT -.160091 .082666 -1.93659 [.055] T .986245E-04 .817213E-04 1.20684 [.229] Y(-1) .593027 .212069 2.79639 [.006] Y(-2) -.600527 .259635 -2.31297 [.022] Y(-3) -.186934 .261061 -.716055 [.475] Y(-4) -.777275E-03 .213479 -.364099E-02 [.997] CONS(-1) .095436 .280382 .340379 [.734] CONS(-2) .210575 .359144 .586325 [.559] CONS(-3) .067869 .351884 .192873 [.847] CONS(-4) -.027531 .281104 -.097940 [.922] IN(-1) 1.12591 .105811 10.6407 [.000] IN(-2) -.322583 .152264 -2.11857 [.036] IN(-3) .068687 .144799 .474363 [.636] IN(-4) -.028236 .098493 -.286683 [.775] CINT -.180497 .251096 -.718836 [.473] T -.777044E-04 .248225E-03 -.313040 [.755] SHGIR 1 2 3 1 0.011655 0.0037898 0.014506 2 0.0059727 0.0073954 0.010818 3 0.0075264 0.0035617 0.022463 Log likelihood = 1554.89 Estimated Standard Variable Coefficient Error t-statistic P-value Y(-1) .891636 .110032 8.10342 [.000] Y(-2) -.040600 .134712 -.301387 [.764] Y(-3) -.027832 .135452 -.205474 [.837] Y(-4) -.081163 .110764 -.732761 [.465] CONS(-1) .325983 .145477 2.24079 [.027] CONS(-2) -.093956 .186342 -.504212 [.615] CONS(-3) -.153634 .182575 -.841484 [.401] CONS(-4) .142164 .145851 .974723 [.331] IN(-1) .136072 .054900 2.47853 [.014] IN(-2) -.121448 .079002 -1.53726 [.126] IN(-3) -.033505 .075129 -.445968 [.656] IN(-4) .030695 .051103 .600640 [.549] CINT -.042359 .130281 -.325134 [.746] T .419361E-04 .128792E-03 .325611 [.745] Y(-1) .125140 .069818 1.79237 [.075] Y(-2) -.133751 .085478 -1.56475 [.120] Y(-3) -.162773 .085947 -1.89386 [.060] Y(-4) .134572 .070282 1.91474 [.057] CONS(-1) .849446 .092308 9.20229 [.000] CONS(-2) .337746 .118238 2.85648 [.005] CONS(-3) -.083755 .115848 -.722971 [.471] CONS(-4) -.072322 .092546 -.781471 [.436] IN(-1) -.360804E-02 .034835 -.103574 [.918] IN(-2) -.016380 .050129 -.326755 [.744] IN(-3) .052740 .047671 1.10634 [.270] IN(-4) -.055964 .032426 -1.72590 [.086] CINT -.160091 .082666 -1.93659 [.055] T .986245E-04 .817213E-04 1.20684 [.229] Y(-1) .593027 .212069 2.79639 [.006] Y(-2) -.600527 .259635 -2.31297 [.022] Y(-3) -.186934 .261061 -.716055 [.475] Y(-4) -.777275E-03 .213479 -.364099E-02 [.997] CONS(-1) .095436 .280382 .340379 [.734] CONS(-2) .210575 .359144 .586325 [.559] CONS(-3) .067869 .351884 .192873 [.847] CONS(-4) -.027531 .281104 -.097940 [.922] IN(-1) 1.12591 .105811 10.6407 [.000] IN(-2) -.322583 .152264 -2.11857 [.036] IN(-3) .068687 .144799 .474363 [.636] IN(-4) -.028236 .098493 -.286683 [.775] CINT -.180497 .251096 -.718836 [.473] T -.777044E-04 .248225E-03 -.313040 [.755] Vector AutoRegression ===================== Dependent variables: Y CONS IN Number of lags = 4 Exogenous variables: CINT T Current sample: 1948:1 to 1988:4 Number of observations: 164 Number of trials for IR confidence intervals: 200 Residual covariance matrix Y CONS IN Y 0.00013584 CONS 0.000044171 0.000054692 IN 0.00016907 0.000080007 0.00050460 Schwarz B.I.C. = -1424.73 Log likelihood = 1554.89 Estimated Standard Variable Coefficient Error t-statistic P-value Y(-1) .891636 .110032 8.10342 [.000] Y(-2) -.040600 .134712 -.301387 [.764] Y(-3) -.027832 .135452 -.205474 [.837] Y(-4) -.081163 .110764 -.732761 [.465] CONS(-1) .325983 .145477 2.24079 [.027] CONS(-2) -.093956 .186342 -.504212 [.615] CONS(-3) -.153634 .182575 -.841484 [.401] CONS(-4) .142164 .145851 .974723 [.331] IN(-1) .136072 .054900 2.47853 [.014] IN(-2) -.121448 .079002 -1.53726 [.126] IN(-3) -.033505 .075129 -.445968 [.656] IN(-4) .030695 .051103 .600640 [.549] CINT -.042359 .130281 -.325134 [.746] T .419361E-04 .128792E-03 .325611 [.745] Y(-1) .125140 .069818 1.79237 [.075] Y(-2) -.133751 .085478 -1.56475 [.120] Y(-3) -.162773 .085947 -1.89386 [.060] Y(-4) .134572 .070282 1.91474 [.057] CONS(-1) .849446 .092308 9.20229 [.000] CONS(-2) .337746 .118238 2.85648 [.005] CONS(-3) -.083755 .115848 -.722971 [.471] CONS(-4) -.072322 .092546 -.781471 [.436] IN(-1) -.360804E-02 .034835 -.103574 [.918] IN(-2) -.016380 .050129 -.326755 [.744] IN(-3) .052740 .047671 1.10634 [.270] IN(-4) -.055964 .032426 -1.72590 [.086] CINT -.160091 .082666 -1.93659 [.055] T .986245E-04 .817213E-04 1.20684 [.229] Y(-1) .593027 .212069 2.79639 [.006] Y(-2) -.600527 .259635 -2.31297 [.022] Y(-3) -.186934 .261061 -.716055 [.475] Y(-4) -.777275E-03 .213479 -.364099E-02 [.997] CONS(-1) .095436 .280382 .340379 [.734] CONS(-2) .210575 .359144 .586325 [.559] CONS(-3) .067869 .351884 .192873 [.847] CONS(-4) -.027531 .281104 -.097940 [.922] IN(-1) 1.12591 .105811 10.6407 [.000] IN(-2) -.322583 .152264 -2.11857 [.036] IN(-3) .068687 .144799 .474363 [.636] IN(-4) -.028236 .098493 -.286683 [.775] CINT -.180497 .251096 -.718836 [.473] T -.777044E-04 .248225E-03 -.313040 [.755] Dependent variable: Y Mean of dep. var. = -4.37480 R-squared = .996996 Std. dev. of dep. var. = .203995 Adjusted R-squared = .996736 Sum of squared residuals = .020376 LM het. test = 3.75339 [.053] Variance of residuals = .135841E-03 Durbin-Watson = 1.97390 Std. error of regression = .011655 F (block exog.) = 4.09216 [.000] Impulse Response of Y to generalized shocks in Y CONS IN 1 0.011655 0.0059727 0.0075264 2 0.013601 0.0092084 0.010928 3 0.014256 0.010473 0.011738 4 0.012398 0.010036 0.0099674 5 0.0092682 0.0097650 0.0079098 6 0.0062304 0.0085902 0.0053258 7 0.0034195 0.0075955 0.0029313 8 0.0011237 0.0066767 0.0010896 9 -0.00034847 0.0058138 -0.00031905 10 -0.0012650 0.0051896 -0.0012084 11 -0.0016282 0.0047044 -0.0016682 12 -0.0015980 0.0043333 -0.0018472 13 -0.0013500 0.0040845 -0.0018028 14 -0.00096794 0.0038902 -0.0016413 15 -0.00055473 0.0037433 -0.0014283 16 -0.00017067 0.0036263 -0.0011992 17 0.00016025 0.0035193 -0.00098859 18 0.00041801 0.0034214 -0.00080704 19 0.00060484 0.0033261 -0.00065818 20 0.00072910 0.0032308 -0.00054276 21 0.00080028 0.0031367 -0.00045530 22 0.00083153 0.0030426 -0.00039103 23 0.00083371 0.0029492 -0.00034510 24 0.00081594 0.0028570 -0.00031261 25 0.00078601 0.0027659 -0.00029010 26 0.00074926 0.0026764 -0.00027463 27 0.00070963 0.0025887 -0.00026395 28 0.00066983 0.0025026 -0.00025652 29 0.00063145 0.0024185 -0.00025109 30 0.00059550 0.0023364 -0.00024682 31 0.00056246 0.0022564 -0.00024309 32 0.00053245 0.0021786 -0.00023947 33 0.00050542 0.0021031 -0.00023566 34 0.00048118 0.0020299 -0.00023150 35 0.00045944 0.0019590 -0.00022690 36 0.00043992 0.0018905 -0.00022183 37 0.00042228 0.0018244 -0.00021632 38 0.00040623 0.0017607 -0.00021045 39 0.00039150 0.0016992 -0.00020428 40 0.00037782 0.0016399 -0.00019792 41 0.00036501 0.0015828 -0.00019146 42 0.00035287 0.0015278 -0.00018497 43 0.00034127 0.0014747 -0.00017853 44 0.00033012 0.0014236 -0.00017220 45 0.00031933 0.0013742 -0.00016603 46 0.00030886 0.0013266 -0.00016004 47 0.00029867 0.0012807 -0.00015426 48 0.00028874 0.0012364 -0.00014870 49 0.00027907 0.0011937 -0.00014335 50 0.00026965 0.0011524 -0.00013823 51 0.00026048 0.0011125 -0.00013331 LB95% Y_Y UB95% 1 0.0097250 0.011655 0.012518 2 0.010264 0.013601 0.016685 3 0.010351 0.014256 0.018250 4 0.0082910 0.012398 0.017665 5 0.0050032 0.0092682 0.015486 6 0.0019463 0.0062304 0.013347 7 -0.00023933 0.0034195 0.010775 8 -0.0028085 0.0011237 0.0080726 9 -0.0046997 -0.00034847 0.0062657 10 -0.0061518 -0.0012650 0.0056391 11 -0.0068573 -0.0016282 0.0051872 12 -0.0074926 -0.0015980 0.0045144 13 -0.0075988 -0.0013500 0.0045301 14 -0.0068670 -0.00096794 0.0042067 15 -0.0055944 -0.00055473 0.0046287 16 -0.0049268 -0.00017067 0.0051669 17 -0.0042419 0.00016025 0.0052484 18 -0.0032137 0.00041801 0.0051647 19 -0.0027391 0.00060484 0.0049920 20 -0.0025522 0.00072910 0.0048462 21 -0.0022995 0.00080028 0.0060173 22 -0.0021535 0.00083153 0.0059795 23 -0.0019736 0.00083371 0.0050309 24 -0.0017148 0.00081594 0.0050454 25 -0.0017098 0.00078601 0.0050454 26 -0.0017125 0.00074926 0.0050130 27 -0.0016123 0.00070963 0.0049573 28 -0.0015019 0.00066983 0.0046977 29 -0.0014565 0.00063145 0.0043558 30 -0.0015193 0.00059550 0.0044124 31 -0.0015167 0.00056246 0.0044626 32 -0.0014218 0.00053245 0.0043900 33 -0.0013396 0.00050542 0.0042361 34 -0.0015215 0.00048118 0.0040735 35 -0.0015566 0.00045944 0.0039056 36 -0.0013728 0.00043992 0.0037348 37 -0.0010249 0.00042228 0.0037132 38 -0.00099502 0.00040623 0.0037378 39 -0.0010283 0.00039150 0.0037572 40 -0.00095457 0.00037782 0.0037727 41 -0.00094236 0.00036501 0.0037853 42 -0.00092495 0.00035287 0.0037956 43 -0.00090330 0.00034127 0.0050192 44 -0.00087829 0.00033012 0.0050679 45 -0.00084775 0.00031933 0.0050390 46 -0.00082098 0.00030886 0.0050100 47 -0.00078970 0.00029867 0.0049810 48 -0.00075713 0.00028874 0.0049519 49 -0.00072970 0.00027907 0.0039767 50 -0.00070907 0.00026965 0.0038629 51 -0.00068705 0.00026048 0.0038733 LB95% Y_CONS UB95% 1 0.0038318 0.0059727 0.0076460 2 0.0060715 0.0092084 0.011679 3 0.0066098 0.010473 0.014290 4 0.0055585 0.010036 0.014776 5 0.0058177 0.0097650 0.015084 6 0.0052156 0.0085902 0.014895 7 0.0049628 0.0075955 0.013715 8 0.0042380 0.0066767 0.012104 9 0.0031172 0.0058138 0.011142 10 0.0024622 0.0051896 0.0095510 11 0.0014830 0.0047044 0.0091967 12 0.00070811 0.0043333 0.0082272 13 0.00019002 0.0040845 0.0083879 14 -0.00043060 0.0038902 0.0082410 15 -0.00081532 0.0037433 0.0079434 16 -0.00075501 0.0036263 0.0081856 17 -0.00085602 0.0035193 0.0084931 18 -0.00080806 0.0034214 0.0082209 19 -0.00027535 0.0033261 0.0082392 20 -4.09132D-06 0.0032308 0.0079978 21 0.000061876 0.0031367 0.0076197 22 0.00013494 0.0030426 0.0076018 23 0.00030833 0.0029492 0.0074434 24 0.00026968 0.0028570 0.0074179 25 0.00029142 0.0027659 0.0074474 26 0.00027224 0.0026764 0.0074690 27 0.00022352 0.0025887 0.0074839 28 0.00021639 0.0025026 0.0074931 29 0.00011388 0.0024185 0.0074980 30 0.00012999 0.0023364 0.0074997 31 0.00012598 0.0022564 0.0074992 32 2.70050D-06 0.0021786 0.0074572 33 -0.00015691 0.0021031 0.0073646 34 -0.00020285 0.0020299 0.0072669 35 -0.00019193 0.0019590 0.0071775 36 -0.00017835 0.0018905 0.0070826 37 -0.00016311 0.0018244 0.0069860 38 -0.00014701 0.0017607 0.0068885 39 -0.00012235 0.0016992 0.0067897 40 -0.00010453 0.0016399 0.0067089 41 -0.000085359 0.0015828 0.0068494 42 -0.000084647 0.0015278 0.0074927 43 -0.000071208 0.0014747 0.0074955 44 -0.000062728 0.0014236 0.0074986 45 -0.000050076 0.0013742 0.0075019 46 -0.000028206 0.0013266 0.0075053 47 -3.86933D-06 0.0012807 0.0075088 48 -0.000017898 0.0012364 0.0075124 49 -0.000016104 0.0011937 0.0075159 50 -0.000010863 0.0011524 0.0075194 51 -6.53931D-06 0.0011125 0.0075228 LB95% Y_IN UB95% 1 0.0052961 0.0075264 0.0090776 2 0.0077529 0.010928 0.013580 3 0.0077486 0.011738 0.015131 4 0.0063660 0.0099674 0.014057 5 0.0040080 0.0079098 0.012691 6 0.0017622 0.0053258 0.010127 7 -0.00046402 0.0029313 0.0085856 8 -0.0024442 0.0010896 0.0063803 9 -0.0040733 -0.00031905 0.0047369 10 -0.0051741 -0.0012084 0.0038871 11 -0.0060492 -0.0016682 0.0032037 12 -0.0068994 -0.0018472 0.0026357 13 -0.0072544 -0.0018028 0.0023586 14 -0.0067462 -0.0016413 0.0021634 15 -0.0063826 -0.0014283 0.0022024 16 -0.0054607 -0.0011992 0.0022336 17 -0.0049537 -0.00098859 0.0022090 18 -0.0047509 -0.00080704 0.0023933 19 -0.0041665 -0.00065818 0.0024621 20 -0.0035776 -0.00054276 0.0020198 21 -0.0031242 -0.00045530 0.0020971 22 -0.0026678 -0.00039103 0.0023398 23 -0.0023909 -0.00034510 0.0023282 24 -0.0022025 -0.00031261 0.0024073 25 -0.0021023 -0.00029010 0.0024634 26 -0.0019241 -0.00027463 0.0024996 27 -0.0018790 -0.00026395 0.0023587 28 -0.0018707 -0.00025652 0.0019677 29 -0.0018872 -0.00025109 0.0019775 30 -0.0019180 -0.00024682 0.0019395 31 -0.0019544 -0.00024309 0.0019779 32 -0.0019895 -0.00023947 0.0019107 33 -0.0020184 -0.00023566 0.0017552 34 -0.0021900 -0.00023150 0.0015486 35 -0.0021985 -0.00022690 0.0015207 36 -0.0021448 -0.00022183 0.0015333 37 -0.0021019 -0.00021632 0.0015467 38 -0.0020680 -0.00021045 0.0015612 39 -0.0019761 -0.00020428 0.0015767 40 -0.0019386 -0.00019792 0.0015930 41 -0.0018967 -0.00019146 0.0016099 42 -0.0017979 -0.00018497 0.0016271 43 -0.0018058 -0.00017853 0.0016445 44 -0.0017977 -0.00017220 0.0021526 45 -0.0017571 -0.00016603 0.0021639 46 -0.0016709 -0.00016004 0.0021753 47 -0.0016293 -0.00015426 0.0021865 48 -0.0015900 -0.00014870 0.0021977 49 -0.0015531 -0.00014335 0.0022088 50 -0.0015184 -0.00013823 0.0021538 51 -0.0014859 -0.00013331 0.0017855 Dependent variable: CONS Mean of dep. var. = -4.61054 R-squared = .998920 Std. dev. of dep. var. = .215868 Adjusted R-squared = .998826 Sum of squared residuals = .820381E-02 LM het. test = .333382 [.564] Variance of residuals = .546921E-04 Durbin-Watson = 2.02315 Std. error of regression = .739541E-02 F (block exog.) = 2.85573 [.006] Impulse Response of CONS to generalized shocks in Y CONS IN 1 0.0037898 0.0073954 0.0035617 2 0.0046254 0.0069904 0.0038863 3 0.0050295 0.0085527 0.0043885 4 0.0038758 0.0083460 0.0041087 5 0.0032916 0.0078961 0.0030509 6 0.0019296 0.0074282 0.0019394 7 0.00096647 0.0068183 0.00091968 8 0.00015899 0.0061418 -0.000063453 9 -0.00044559 0.0056470 -0.00071234 10 -0.00072421 0.0051412 -0.0011661 11 -0.00079474 0.0047615 -0.0014128 12 -0.00070856 0.0044649 -0.0014721 13 -0.00049242 0.0042175 -0.0014286 14 -0.00023858 0.0040331 -0.0013080 15 0.000028134 0.0038811 -0.0011486 16 0.00027553 0.0037500 -0.00098529 17 0.00047955 0.0036375 -0.00082847 18 0.00063866 0.0035309 -0.00069161 19 0.00075017 0.0034291 -0.00057900 20 0.00081834 0.0033298 -0.00048922 21 0.00085180 0.0032308 -0.00042139 22 0.00085736 0.0031327 -0.00037162 23 0.00084304 0.0030352 -0.00033608 24 0.00081562 0.0029385 -0.00031160 25 0.00078020 0.0028431 -0.00029492 26 0.00074108 0.0027493 -0.00028364 27 0.00070112 0.0026573 -0.00027589 28 0.00066223 0.0025673 -0.00027020 29 0.00062564 0.0024796 -0.00026561 30 0.00059193 0.0023943 -0.00026142 31 0.00056130 0.0023115 -0.00025719 32 0.00053371 0.0022312 -0.00025266 33 0.00050892 0.0021535 -0.00024771 34 0.00048665 0.0020784 -0.00024228 35 0.00046656 0.0020058 -0.00023642 36 0.00044831 0.0019358 -0.00023016 37 0.00043161 0.0018683 -0.00022360 38 0.00041616 0.0018031 -0.00021681 39 0.00040173 0.0017403 -0.00020990 40 0.00038813 0.0016798 -0.00020294 41 0.00037519 0.0016214 -0.00019601 42 0.00036280 0.0015651 -0.00018918 43 0.00035086 0.0015109 -0.00018248 44 0.00033930 0.0014585 -0.00017596 45 0.00032809 0.0014080 -0.00016965 46 0.00031719 0.0013593 -0.00016356 47 0.00030658 0.0013123 -0.00015769 48 0.00029625 0.0012669 -0.00015206 49 0.00028621 0.0012231 -0.00014665 50 0.00027645 0.0011808 -0.00014145 51 0.00026698 0.0011399 -0.00013647 LB95% CONS_Y UB95% 1 0.0024674 0.0037898 0.0047023 2 0.0026506 0.0046254 0.0060754 3 0.0027435 0.0050295 0.0075005 4 0.0015294 0.0038758 0.0072767 5 0.00054033 0.0032916 0.0069155 6 -0.0010791 0.0019296 0.0060289 7 -0.0021051 0.00096647 0.0054330 8 -0.0032649 0.00015899 0.0048784 9 -0.0042994 -0.00044559 0.0041689 10 -0.0048895 -0.00072421 0.0041597 11 -0.0049333 -0.00079474 0.0041413 12 -0.0052184 -0.00070856 0.0040821 13 -0.0051121 -0.00049242 0.0041987 14 -0.0046844 -0.00023858 0.0042145 15 -0.0040056 0.000028134 0.0043379 16 -0.0035668 0.00027553 0.0042781 17 -0.0029817 0.00047955 0.0042137 18 -0.0025900 0.00063866 0.0041588 19 -0.0022703 0.00075017 0.0043341 20 -0.0022035 0.00081834 0.0046587 21 -0.0021346 0.00085180 0.0046682 22 -0.0019705 0.00085736 0.0045930 23 -0.0019900 0.00084304 0.0047419 24 -0.0019054 0.00081562 0.0048801 25 -0.0017216 0.00078020 0.0050087 26 -0.0016785 0.00074108 0.0051278 27 -0.0016698 0.00070112 0.0045257 28 -0.0015546 0.00066223 0.0045777 29 -0.0014095 0.00062564 0.0046254 30 -0.0014132 0.00059193 0.0046706 31 -0.0013286 0.00056130 0.0047145 32 -0.0012796 0.00053371 0.0047584 33 -0.0012324 0.00050892 0.0046250 34 -0.0012392 0.00048665 0.0044235 35 -0.0011689 0.00046656 0.0042195 36 -0.0011313 0.00044831 0.0040148 37 -0.0011153 0.00043161 0.0038121 38 -0.0010990 0.00041616 0.0036121 39 -0.0010826 0.00040173 0.0035860 40 -0.00096793 0.00038813 0.0035894 41 -0.00093699 0.00037519 0.0035918 42 -0.00090333 0.00036280 0.0035939 43 -0.00086739 0.00035086 0.0044892 44 -0.00082960 0.00033930 0.0045434 45 -0.00080418 0.00032809 0.0044701 46 -0.00078323 0.00031719 0.0043989 47 -0.00076104 0.00030658 0.0043294 48 -0.00073787 0.00029625 0.0036199 49 -0.00071397 0.00028621 0.0036279 50 -0.00068963 0.00027645 0.0036370 51 -0.00066511 0.00026698 0.0036472 LB95% CONS_CONS UB95% 1 0.0060392 0.0073954 0.0080130 2 0.0052820 0.0069904 0.0086267 3 0.0059952 0.0085527 0.010610 4 0.0057998 0.0083460 0.010856 5 0.0053632 0.0078961 0.011485 6 0.0049617 0.0074282 0.011562 7 0.0046632 0.0068183 0.011425 8 0.0039459 0.0061418 0.010555 9 0.0031944 0.0056470 0.010190 10 0.0026226 0.0051412 0.0085125 11 0.0016944 0.0047615 0.0081317 12 0.0013606 0.0044649 0.0082138 13 0.0010791 0.0042175 0.0082745 14 0.00086166 0.0040331 0.0083704 15 0.00062377 0.0038811 0.0082729 16 0.00045558 0.0037500 0.0079890 17 0.00032402 0.0036375 0.0077339 18 0.00040788 0.0035309 0.0076353 19 0.00046855 0.0034291 0.0074074 20 0.00038600 0.0033298 0.0073094 21 0.00027680 0.0032308 0.0077319 22 0.00010590 0.0031327 0.0078419 23 0.000068934 0.0030352 0.0078885 24 0.00021058 0.0029385 0.0079087 25 0.00026421 0.0028431 0.0079229 26 0.00019652 0.0027493 0.0079320 27 0.000042174 0.0026573 0.0079371 28 -0.00017259 0.0025673 0.0079391 29 -0.000098781 0.0024796 0.0079391 30 -0.000098413 0.0023943 0.0079378 31 -0.00016105 0.0023115 0.0079360 32 -0.00020664 0.0022312 0.0079340 33 -0.00023771 0.0021535 0.0079324 34 -0.00024178 0.0020784 0.0073485 35 -0.00021767 0.0020058 0.0065495 36 -0.00019329 0.0019358 0.0062777 37 -0.00016936 0.0018683 0.0063222 38 -0.00014640 0.0018031 0.0064427 39 -0.00012482 0.0017403 0.0071691 40 -0.00010438 0.0016798 0.0079379 41 -0.000071406 0.0016214 0.0079409 42 -0.000043184 0.0015651 0.0079441 43 -0.000025275 0.0015109 0.0079476 44 -0.000021808 0.0014585 0.0079512 45 -0.000018233 0.0014080 0.0079548 46 -0.000014713 0.0013593 0.0079585 47 -0.000011367 0.0013123 0.0079622 48 -9.24764D-06 0.0012669 0.0079658 49 -5.49398D-06 0.0012231 0.0079694 50 -3.04675D-06 0.0011808 0.0079729 51 -9.44605D-07 0.0011399 0.0079763 LB95% CONS_IN UB95% 1 0.0020729 0.0035617 0.0047515 2 0.0021707 0.0038863 0.0056205 3 0.0019777 0.0043885 0.0065824 4 0.0019227 0.0041087 0.0071632 5 0.00072455 0.0030509 0.0064292 6 -0.00033335 0.0019394 0.0056234 7 -0.0014122 0.00091968 0.0050011 8 -0.0022683 -0.000063453 0.0038895 9 -0.0032284 -0.00071234 0.0029140 10 -0.0042283 -0.0011661 0.0023096 11 -0.0050683 -0.0014128 0.0019391 12 -0.0050226 -0.0014721 0.0019443 13 -0.0050253 -0.0014286 0.0018903 14 -0.0049042 -0.0013080 0.0018224 15 -0.0046491 -0.0011486 0.0018597 16 -0.0046440 -0.00098529 0.0018274 17 -0.0041636 -0.00082847 0.0018716 18 -0.0035170 -0.00069161 0.0018266 19 -0.0030041 -0.00057900 0.0018725 20 -0.0027836 -0.00048922 0.0017522 21 -0.0025343 -0.00042139 0.0020175 22 -0.0024078 -0.00037162 0.0016854 23 -0.0022078 -0.00033608 0.0016522 24 -0.0020232 -0.00031160 0.0017092 25 -0.0018796 -0.00029492 0.0017230 26 -0.0017612 -0.00028364 0.0015707 27 -0.0017582 -0.00027589 0.0018484 28 -0.0017477 -0.00027020 0.0020427 29 -0.0017347 -0.00026561 0.0015202 30 -0.0017230 -0.00026142 0.0015349 31 -0.0022266 -0.00025719 0.0015485 32 -0.0022384 -0.00025266 0.0015847 33 -0.0022430 -0.00024771 0.0016232 34 -0.0022390 -0.00024228 0.0016585 35 -0.0022261 -0.00023642 0.0016232 36 -0.0022045 -0.00023016 0.0016205 37 -0.0021753 -0.00022360 0.0016371 38 -0.0021396 -0.00021681 0.0016542 39 -0.0020990 -0.00020990 0.0016717 40 -0.0020548 -0.00020294 0.0016894 41 -0.0020084 -0.00019601 0.0017072 42 -0.0017745 -0.00018918 0.0017251 43 -0.0017766 -0.00018248 0.0017430 44 -0.0017784 -0.00017596 0.0018928 45 -0.0017803 -0.00016965 0.0019085 46 -0.0017797 -0.00016356 0.0019235 47 -0.0017387 -0.00015769 0.0019377 48 -0.0016998 -0.00015206 0.0019513 49 -0.0016629 -0.00014665 0.0018529 50 -0.0016279 -0.00014145 0.0018719 51 -0.0015946 -0.00013647 0.0018911 Dependent variable: IN Mean of dep. var. = -5.95244 R-squared = .989479 Std. dev. of dep. var. = .210082 Adjusted R-squared = .988567 Sum of squared residuals = .075690 LM het. test = .146018 [.702] Variance of residuals = .504598E-03 Durbin-Watson = 2.01529 Std. error of regression = .022463 F (block exog.) = 3.34864 [.001] Impulse Response of IN to generalized shocks in Y CONS IN 1 0.014506 0.010818 0.022463 2 0.023606 0.016428 0.030095 3 0.024205 0.019105 0.029720 4 0.020453 0.019309 0.025766 5 0.014310 0.017204 0.019151 6 0.0072293 0.014688 0.012292 7 0.0010469 0.011823 0.0061140 8 -0.0035885 0.0092437 0.0011503 9 -0.0065856 0.0072101 -0.0022543 10 -0.0079114 0.0056355 -0.0043043 11 -0.0079916 0.0045614 -0.0052345 12 -0.0072013 0.0038846 -0.0053242 13 -0.0058925 0.0034780 -0.0049030 14 -0.0044027 0.0032778 -0.0041980 15 -0.0029412 0.0031920 -0.0033936 16 -0.0016482 0.0031655 -0.0026176 17 -0.00059950 0.0031662 -0.0019329 18 0.00019324 0.0031662 -0.0013727 19 0.00074465 0.0031561 -0.00094135 20 0.0010903 0.0031318 -0.00062583 21 0.0012747 0.0030917 -0.00040840 22 0.0013394 0.0030386 -0.00026772 23 0.0013226 0.0029749 -0.00018406 24 0.0012550 0.0029030 -0.00014101 25 0.0011596 0.0028255 -0.00012506 26 0.0010532 0.0027441 -0.00012623 27 0.00094694 0.0026603 -0.00013728 28 0.00084739 0.0025753 -0.00015308 29 0.00075827 0.0024901 -0.00017027 30 0.00068102 0.0024054 -0.00018666 31 0.00061568 0.0023218 -0.00020092 32 0.00056149 0.0022399 -0.00021236 33 0.00051719 0.0021601 -0.00022069 34 0.00048137 0.0020826 -0.00022592 35 0.00045257 0.0020077 -0.00022825 36 0.00042939 0.0019356 -0.00022800 37 0.00041061 0.0018662 -0.00022557 38 0.00039513 0.0017996 -0.00022138 39 0.00038205 0.0017356 -0.00021584 40 0.00037062 0.0016743 -0.00020934 41 0.00036027 0.0016154 -0.00020222 42 0.00035057 0.0015588 -0.00019478 43 0.00034120 0.0015045 -0.00018724 44 0.00033197 0.0014522 -0.00017978 45 0.00032274 0.0014019 -0.00017252 46 0.00031347 0.0013534 -0.00016556 47 0.00030414 0.0013067 -0.00015894 48 0.00029477 0.0012616 -0.00015268 49 0.00028541 0.0012181 -0.00014678 50 0.00027609 0.0011761 -0.00014122 51 0.00026687 0.0011355 -0.00013597 LB95% IN_Y UB95% 1 0.0097156 0.014506 0.017744 2 0.016680 0.023606 0.027924 3 0.016947 0.024205 0.030130 4 0.011901 0.020453 0.029999 5 0.0066833 0.014310 0.025104 6 0.000094810 0.0072293 0.019258 7 -0.0071466 0.0010469 0.013064 8 -0.013119 -0.0035885 0.0086688 9 -0.015909 -0.0065856 0.0049335 10 -0.019238 -0.0079114 0.0037192 11 -0.021083 -0.0079916 0.0029747 12 -0.021376 -0.0072013 0.0022965 13 -0.020027 -0.0058925 0.0016913 14 -0.017356 -0.0044027 0.0029635 15 -0.014648 -0.0029412 0.0045325 16 -0.011038 -0.0016482 0.0055468 17 -0.0088915 -0.00059950 0.0064069 18 -0.0076544 0.00019324 0.0070026 19 -0.0063352 0.00074465 0.0071022 20 -0.0050020 0.0010903 0.0070985 21 -0.0043636 0.0012747 0.0071153 22 -0.0037431 0.0013394 0.0087759 23 -0.0033175 0.0013226 0.0090850 24 -0.0030851 0.0012550 0.0079683 25 -0.0029589 0.0011596 0.0070691 26 -0.0033022 0.0010532 0.0066466 27 -0.0032490 0.00094694 0.0053989 28 -0.0031607 0.00084739 0.0052483 29 -0.0034517 0.00075827 0.0053179 30 -0.0032346 0.00068102 0.0053760 31 -0.0031638 0.00061568 0.0052619 32 -0.0031246 0.00056149 0.0054023 33 -0.0033332 0.00051719 0.0045953 34 -0.0034060 0.00048137 0.0045351 35 -0.0031775 0.00045257 0.0044840 36 -0.0031080 0.00042939 0.0045249 37 -0.0029676 0.00041061 0.0047920 38 -0.0022531 0.00039513 0.0045118 39 -0.0018784 0.00038205 0.0043150 40 -0.0014422 0.00037062 0.0046036 41 -0.0013717 0.00036027 0.0043799 42 -0.0013705 0.00035057 0.0041835 43 -0.0012931 0.00034120 0.0041362 44 -0.0012245 0.00033197 0.0040876 45 -0.0011942 0.00032274 0.0040379 46 -0.0011650 0.00031347 0.0039876 47 -0.0010784 0.00030414 0.0039371 48 -0.0010252 0.00029477 0.0038867 49 -0.0010011 0.00028541 0.0038367 50 -0.00098896 0.00027609 0.0034702 51 -0.0010331 0.00026687 0.0034731 LB95% IN_CONS UB95% 1 0.0067241 0.010818 0.014292 2 0.010008 0.016428 0.021847 3 0.011135 0.019105 0.028460 4 0.011393 0.019309 0.028201 5 0.0099793 0.017204 0.028354 6 0.0086163 0.014688 0.026435 7 0.0071420 0.011823 0.023117 8 0.0049702 0.0092437 0.018096 9 0.0018299 0.0072101 0.015941 10 -0.00041794 0.0056355 0.013805 11 -0.0026233 0.0045614 0.011925 12 -0.0048375 0.0038846 0.010532 13 -0.0055819 0.0034780 0.010096 14 -0.0067877 0.0032778 0.0096551 15 -0.0066962 0.0031920 0.0084170 16 -0.0059492 0.0031655 0.0083352 17 -0.0055036 0.0031662 0.0089244 18 -0.0045619 0.0031662 0.0088823 19 -0.0037439 0.0031561 0.0088935 20 -0.0026790 0.0031318 0.0094303 21 -0.0029323 0.0030917 0.0097639 22 -0.0020462 0.0030386 0.010157 23 -0.0015794 0.0029749 0.010127 24 -0.0018516 0.0029030 0.0097949 25 -0.0021196 0.0028255 0.0097691 26 -0.0018429 0.0027441 0.0097479 27 -0.0015265 0.0026603 0.0091682 28 -0.0016224 0.0025753 0.0086139 29 -0.0023721 0.0024901 0.0085874 30 -0.0023879 0.0024054 0.0085698 31 -0.0022981 0.0023218 0.0076834 32 -0.0017905 0.0022399 0.0076440 33 -0.0020454 0.0021601 0.0075993 34 -0.0018962 0.0020826 0.0076496 35 -0.0018001 0.0020077 0.0077749 36 -0.0018475 0.0019356 0.0078748 37 -0.0014923 0.0018662 0.0079497 38 -0.0012667 0.0017996 0.0080034 39 -0.0011246 0.0017356 0.0080413 40 -0.0011054 0.0016743 0.0080698 41 -0.0010868 0.0016154 0.0080951 42 -0.0011226 0.0015588 0.0081220 43 -0.0010619 0.0015045 0.0084757 44 -0.0010322 0.0014522 0.0084809 45 -0.0010141 0.0014019 0.0084864 46 -0.00099589 0.0013534 0.0084919 47 -0.00097773 0.0013067 0.0084973 48 -0.00068633 0.0012616 0.0085026 49 -0.00035886 0.0012181 0.0085075 50 -0.00033753 0.0011761 0.0085570 51 -0.00031716 0.0011355 0.0086243 LB95% IN_IN UB95% 1 0.018424 0.022463 0.024495 2 0.023610 0.030095 0.033737 3 0.022095 0.029720 0.036453 4 0.018321 0.025766 0.034603 5 0.012596 0.019151 0.029227 6 0.0062469 0.012292 0.023257 7 0.00016446 0.0061140 0.015852 8 -0.0056351 0.0011503 0.010797 9 -0.011356 -0.0022543 0.0079971 10 -0.014643 -0.0043043 0.0047640 11 -0.015323 -0.0052345 0.0032381 12 -0.015730 -0.0053242 0.0032654 13 -0.015974 -0.0049030 0.0022408 14 -0.015006 -0.0041980 0.0022032 15 -0.012883 -0.0033936 0.0022243 16 -0.011362 -0.0026176 0.0023244 17 -0.0094319 -0.0019329 0.0039812 18 -0.0083399 -0.0013727 0.0054882 19 -0.0068399 -0.00094135 0.0055374 20 -0.0059210 -0.00062583 0.0045277 21 -0.0054649 -0.00040840 0.0050267 22 -0.0040496 -0.00026772 0.0058432 23 -0.0034611 -0.00018406 0.0056704 24 -0.0033559 -0.00014101 0.0051999 25 -0.0034614 -0.00012506 0.0044531 26 -0.0036715 -0.00012623 0.0036306 27 -0.0032850 -0.00013728 0.0036928 28 -0.0029488 -0.00015308 0.0033031 29 -0.0031207 -0.00017027 0.0033640 30 -0.0029270 -0.00018666 0.0029693 31 -0.0027773 -0.00020092 0.0028842 32 -0.0034690 -0.00021236 0.0028966 33 -0.0037125 -0.00022069 0.0028417 34 -0.0035157 -0.00022592 0.0021173 35 -0.0032407 -0.00022825 0.0022063 36 -0.0026941 -0.00022800 0.0020370 37 -0.0025029 -0.00022557 0.0018723 38 -0.0025075 -0.00022138 0.0018912 39 -0.0025189 -0.00021584 0.0018442 40 -0.0024656 -0.00020934 0.0017688 41 -0.0022710 -0.00020222 0.0019533 42 -0.0019632 -0.00019478 0.0019747 43 -0.0017040 -0.00018724 0.0019959 44 -0.0018768 -0.00017978 0.0020170 45 -0.0020639 -0.00017252 0.0020380 46 -0.0019594 -0.00016556 0.0020589 47 -0.0016158 -0.00015894 0.0020799 48 -0.0011947 -0.00015268 0.0021010 49 -0.0011582 -0.00014678 0.0021223 50 -0.0011273 -0.00014122 0.0021438 51 -0.0011010 -0.00013597 0.0020344 *** WARNING in command 24 Procedure SELECT: Missing values for series ====> @IRY_CONS: 113 Current sample: 1948:1 to 1960:3 ******************************************************************************* END OF OUTPUT FOR USER GIR2 TOTAL NUMBER OF WARNING MESSAGES FOR MISSING VALUES:1 TOTAL NUMBER OF WARNING MESSAGES: 1 MEMORY USAGE: ITEM: DATA ARRAY TOTAL MEMORY UNITS: (4-BYTE WORDS) (MEGABYTES) MEMORY ALLOCATED : 500000 4.0 MEMORY ACTUALLY REQUIRED : 214851 3.0 CURRENT VARIABLE STORAGE : 13964