Analysis
[1] "景気動向指数個別系列:先行系列:中小企業売上げ見通しDI:内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 10.9
2000 16.7 12.6 16.1 11.2 12.3 7.4 14.1 13.8 15.8 16.0 11.9 9.0
2001 6.2 3.7 -7.4 -9.2 -8.4 -11.9 -18.2 -17.4 -19.2 -23.7 -24.4 -15.0
2002 -19.1 -12.9 -8.8 -2.6 -0.9 2.2 3.6 6.1 2.0 3.0 5.8 4.5
2003 2.6 -2.5 3.7 2.5 -0.8 1.2 2.4 1.7 11.3 11.0 13.6 10.9
2004 14.9 14.6 15.1 13.6 15.2 11.3 17.8 11.8 11.1 11.5 7.5 14.5
2005 6.2 7.3 8.4 8.8 11.0 10.7 7.3 12.9 11.1 13.6 18.7 26.2
2006 19.8 19.8 19.0 17.6 17.5 11.7 10.4 14.4 12.9 16.3 16.1 16.4
2007 17.4 19.4 17.5 15.2 10.6 11.7 9.9 9.2 9.5 8.4 11.7 13.4
2008 13.1 7.4 5.7 2.1 -0.3 -1.9 -7.5 -7.0 -11.1 -17.0 -22.9 -30.6
2009 -43.3 -41.9 -36.0 -18.8 -11.6 -8.1 -6.7 -4.4 0.0 2.8 0.7 -0.5
2010 -0.4 3.9 6.6 5.1 8.0 5.6 5.9 1.9 -9.3 -3.3 -0.3 4.4
2011 7.1 14.2 10.5 -22.5 -11.5 -1.3 2.7 5.1 8.8 4.6 5.1 1.7
2012 6.4 2.4 6.3 5.7 4.4 0.4 -4.6 -7.0 -10.5 -8.8 -13.8 -8.5
2013 -10.5 1.3 2.0 3.5 7.1 5.0 9.8 7.3 10.9 14.4 15.1 17.3
2014 20.1 10.8 4.0 -11.9 -0.2 1.6 4.6 12.2 9.6 5.6 6.5 1.7
2015 0.7 1.2 6.9 4.9 7.0 7.4 3.6 2.0 4.7 2.9 4.4 6.3
2016 5.4 0.1 -2.8 -1.9 -3.0 -2.9 -2.9 1.4 -5.2 0.8 -2.1 2.1
2017 2.7 5.4 4.8 9.2 3.6 7.3 10.1 11.3 8.3 10.4 12.9 3.5
2018 11.9 10.8 11.7 7.7 13.6 9.9 7.7 4.0 9.2 7.1 9.7 7.4
2019 -1.6 -0.1 -0.8 -4.9 -7.9 -6.0 -4.4 -13.0 -9.6
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-23.423 -4.521 2.351 4.953 12.866
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.8244 2.3631 2.042 0.0484 *
ID -0.2053 0.1030 -1.994 0.0536 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.237 on 37 degrees of freedom
Multiple R-squared: 0.09703, Adjusted R-squared: 0.07263
F-statistic: 3.976 on 1 and 37 DF, p-value: 0.05356
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.20513, p-value = 0.3888
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.96713, p-value = 0.0001105
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.27095, df = 1, p-value = 0.6027
Box-Ljung test
data: lm_residuals
X-squared = 10.871, df = 1, p-value = 0.0009766
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-17.4722 -4.0577 0.0567 4.9145 14.3639
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.44645 1.46014 4.415 0.0000317 ***
ID -0.05464 0.03094 -1.766 0.0812 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.51 on 79 degrees of freedom
Multiple R-squared: 0.03799, Adjusted R-squared: 0.02581
F-statistic: 3.12 on 1 and 79 DF, p-value: 0.08122
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.08642, p-value = 0.9254
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.50647, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.064866, df = 1, p-value = 0.799
Box-Ljung test
data: lm_residuals
X-squared = 39.316, df = 1, p-value = 0.0000000003605
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-33.467 -6.190 3.558 7.773 17.337
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -12.2441 3.0324 -4.038 0.000163 ***
ID 0.2679 0.0879 3.047 0.003498 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.5 on 57 degrees of freedom
Multiple R-squared: 0.1401, Adjusted R-squared: 0.125
F-statistic: 9.285 on 1 and 57 DF, p-value: 0.003498
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.10169, p-value = 0.9239
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.37106, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 3.8151, df = 1, p-value = 0.05079
Box-Ljung test
data: lm_residuals
X-squared = 40.237, df = 1, p-value = 0.0000000002249
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-18.5282 -4.2327 -0.2147 5.0191 13.2264
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.69167 1.43198 5.371 0.000000824 ***
ID -0.08181 0.03150 -2.597 0.0113 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.263 on 76 degrees of freedom
Multiple R-squared: 0.08153, Adjusted R-squared: 0.06945
F-statistic: 6.747 on 1 and 76 DF, p-value: 0.01127
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.089744, p-value = 0.9147
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.52054, p-value = 0.0000000000000005029
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 1.2555, df = 1, p-value = 0.2625
Box-Ljung test
data: lm_residuals
X-squared = 41.653, df = 1, p-value = 0.000000000109