Analysis
[1] "景気動向指数個別系列:先行系列:新規求人数(除学卒)(人):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 508316
2000 535617 528372 538001 555144 564639 585988 605865 610257 615264 624621 637409 634688
2001 615461 618640 604612 611569 604371 599274 601079 583771 576815 562524 560059 555381
2002 562867 574291 584478 587126 600442 597383 595328 606017 610380 615006 608816 619766
2003 631081 633411 645082 640289 644419 653360 674017 682251 696374 707533 718043 739086
2004 727646 708340 728859 742912 742782 756655 758830 762017 775746 796232 824611 803400
2005 800057 800017 818414 821530 829649 834263 832003 834107 834544 829994 855905 841041
2006 852862 865769 844771 858312 869166 861830 867435 863916 857953 830677 855417 856829
2007 825291 842244 844035 836212 823085 819578 810943 799197 779312 769743 748010 733423
2008 738734 741011 687760 702162 702404 684611 670503 669081 645485 634327 623862 646836
2009 603284 525404 523109 516148 493498 509473 513653 512577 525120 524960 525780 532497
2010 529683 515424 537858 542156 557609 571488 575767 590956 599830 616858 619941 616063
2011 627421 635217 599542 623808 635577 643256 667304 671104 675209 692019 700299 702410
2012 706425 710037 716249 724667 735556 733296 734553 744934 738931 737931 742311 745455
2013 750781 774550 775531 766816 780614 794192 797506 800444 816314 819874 811925 825575
2014 852362 827686 825784 844984 829644 833406 833746 829938 833538 828575 838352 844312
2015 868013 839582 823788 847212 852504 855864 869209 870118 871639 894332 890336 884997
2016 897626 907127 872140 901378 914532 906562 917058 912568 920949 920906 920400 938650
2017 938304 938848 931597 937423 945346 956523 954503 971134 964972 962865 973921 996450
2018 957306 974537 981150 983720 973666 977335 969651 968758 968853 969084 965689 964901
2019 990914 997446 957235 969912 1010637 973112 957810 963439 928972
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-30830 -8058 3716 9528 19556
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 511321.3 4302.1 118.85 <0.0000000000000002 ***
ID 6613.9 187.5 35.28 <0.0000000000000002 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13180 on 37 degrees of freedom
Multiple R-squared: 0.9711, Adjusted R-squared: 0.9704
F-statistic: 1245 on 1 and 37 DF, p-value: < 0.00000000000000022
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.25641, p-value = 0.1547
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.66164, p-value = 0.0000002169
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.14126, df = 1, p-value = 0.707
Box-Ljung test
data: lm_residuals
X-squared = 16.239, df = 1, p-value = 0.00005584
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-79925 -9313 4031 13842 45956
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 783629.83 4485.86 174.69 <0.0000000000000002 ***
ID 2781.07 95.04 29.26 <0.0000000000000002 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 20000 on 79 degrees of freedom
Multiple R-squared: 0.9155, Adjusted R-squared: 0.9145
F-statistic: 856.2 on 1 and 79 DF, p-value: < 0.00000000000000022
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.098765, p-value = 0.8277
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.62241, p-value = 0.00000000000008349
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 7.6041, df = 1, p-value = 0.005824
Box-Ljung test
data: lm_residuals
X-squared = 27.077, df = 1, p-value = 0.0000001955
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-91745 -50065 3313 30522 165428
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 533633.5 16152.7 33.037 < 0.0000000000000002 ***
ID 3342.5 468.2 7.138 0.00000000187 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 61250 on 57 degrees of freedom
Multiple R-squared: 0.472, Adjusted R-squared: 0.4627
F-statistic: 50.96 on 1 and 57 DF, p-value: 0.000000001871
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.16949, p-value = 0.3674
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.079754, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 26.179, df = 1, p-value = 0.0000003112
Box-Ljung test
data: lm_residuals
X-squared = 49.313, df = 1, p-value = 0.000000000002182
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-78130 -10495 4471 13889 46305
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 795546.73 4512.48 176.30 <0.0000000000000002 ***
ID 2712.25 99.25 27.33 <0.0000000000000002 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19740 on 76 degrees of freedom
Multiple R-squared: 0.9076, Adjusted R-squared: 0.9064
F-statistic: 746.8 on 1 and 76 DF, p-value: < 0.00000000000000022
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.11538, p-value = 0.6802
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.64475, p-value = 0.000000000000717
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 8.2961, df = 1, p-value = 0.003973
Box-Ljung test
data: lm_residuals
X-squared = 25.216, df = 1, p-value = 0.0000005127
