Analysis
[1] "景気動向指数個別系列:一致系列:商業販売額(卸売業)(前年同月比)(%):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 -4.3
2000 -4.6 -1.8 -5.9 -5.6 -1.4 -1.5 -5.2 -1.0 -5.6 -0.9 -1.6 1.0
2001 -0.1 -3.7 -4.3 -3.2 -3.2 -4.2 -4.9 -6.9 -8.9 -6.9 -8.2 -9.0
2002 -8.8 -9.1 -10.2 -4.8 -4.9 -7.3 -3.8 -5.3 -4.2 -2.5 -1.2 -2.6
2003 -0.5 0.5 0.5 -0.2 0.1 1.6 -1.2 -0.4 1.3 3.9 -2.3 2.9
2004 3.5 2.3 2.1 5.0 -1.2 5.2 6.0 4.9 1.3 0.0 5.1 1.0
2005 0.6 -0.4 -4.1 -1.9 -1.7 -3.1 -4.8 0.5 -3.1 -1.9 0.4 0.9
2006 2.9 2.5 -0.5 0.9 4.5 1.7 2.3 3.0 0.0 4.0 1.1 -0.8
2007 -0.3 0.2 -2.0 2.3 4.6 2.8 3.8 2.0 0.1 4.6 4.0 2.4
2008 4.4 6.4 2.0 5.6 4.9 4.9 11.0 3.3 3.9 -1.7 -11.3 -14.3
2009 -20.3 -26.7 -29.4 -28.2 -30.8 -28.9 -30.1 -28.1 -27.2 -24.1 -18.1 -13.6
2010 -4.8 -1.1 2.8 4.4 1.9 1.7 1.2 2.5 2.7 1.5 7.3 6.3
2011 5.2 7.8 1.5 -1.3 2.4 3.8 2.9 4.9 0.7 0.9 -2.2 -2.1
2012 -3.8 -1.3 0.9 0.4 2.6 -3.6 -4.0 -4.4 -5.1 -1.8 -1.6 -2.5
2013 0.1 -1.3 -1.8 -0.1 0.5 0.1 2.0 0.4 2.7 1.8 2.4 2.9
2014 4.4 2.0 7.5 -3.0 -1.3 -0.5 -0.1 -2.8 1.3 -0.1 -4.1 -2.0
2015 -3.1 -4.0 -7.7 1.5 -4.1 1.1 -0.7 -0.8 -2.9 -1.8 -2.2 -3.9
2016 -6.2 -4.0 -6.8 -5.3 -6.7 -7.3 -7.6 -3.8 -6.0 -6.6 -1.3 -2.4
2017 -0.2 -0.4 3.2 0.9 6.3 4.4 3.1 4.3 4.0 5.1 5.7 7.0
2018 7.1 4.2 2.9 6.6 6.6 4.0 5.6 4.8 0.4 7.2 3.4 -1.0
2019 -1.3 -1.4 -2.8 -0.5 -3.9 -4.2 -1.3 -4.7 2.7
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-21.695 -2.598 1.097 3.863 8.808
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.49271 2.05625 -1.212 0.233
ID 0.08733 0.08960 0.975 0.336
Residual standard error: 6.298 on 37 degrees of freedom
Multiple R-squared: 0.02503, Adjusted R-squared: -0.001319
F-statistic: 0.9499 on 1 and 37 DF, p-value: 0.3361
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.28205, p-value = 0.08974
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.25851, p-value = 0.000000000000003856
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 7.7138, df = 1, p-value = 0.00548
Box-Ljung test
data: lm_residuals
X-squared = 20.998, df = 1, p-value = 0.000004599
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-7.6063 -2.6271 -0.2147 2.9807 8.2392
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.13858 0.88994 -1.279 0.205
ID 0.02663 0.01886 1.412 0.162
Residual standard error: 3.968 on 79 degrees of freedom
Multiple R-squared: 0.02462, Adjusted R-squared: 0.01227
F-statistic: 1.994 on 1 and 79 DF, p-value: 0.1618
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.1358, p-value = 0.4462
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.60193, p-value = 0.00000000000002609
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 3.7467, df = 1, p-value = 0.05291
Box-Ljung test
data: lm_residuals
X-squared = 40.862, df = 1, p-value = 0.0000000001633
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-21.854 -4.285 1.483 7.579 22.405
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -12.14342 2.85738 -4.250 0.0000801 ***
ID 0.24597 0.08283 2.969 0.00436 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 10.83 on 57 degrees of freedom
Multiple R-squared: 0.134, Adjusted R-squared: 0.1188
F-statistic: 8.818 on 1 and 57 DF, p-value: 0.004358
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.13559, p-value = 0.6544
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.11057, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 26.387, df = 1, p-value = 0.0000002794
Box-Ljung test
data: lm_residuals
X-squared = 52.787, df = 1, p-value = 0.0000000000003717
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-7.6032 -2.6300 -0.0667 3.1894 8.2510
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.07429 0.92418 -1.162 0.249
ID 0.02694 0.02033 1.325 0.189
Residual standard error: 4.042 on 76 degrees of freedom
Multiple R-squared: 0.02259, Adjusted R-squared: 0.009726
F-statistic: 1.756 on 1 and 76 DF, p-value: 0.1891
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.064103, p-value = 0.9975
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.59881, p-value = 0.00000000000006067
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 2.2369, df = 1, p-value = 0.1347
Box-Ljung test
data: lm_residuals
X-squared = 39.608, df = 1, p-value = 0.0000000003105