Analysis

[1] "労働力調査:完全失業率(%):季節調整値:女:15から64歳:45から54:総務省"
     Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999                                             3.0
2000 2.9 2.9 3.1 3.2 3.0 2.9 2.9 2.9 3.2 3.0 3.0 3.0
2001 2.8 2.9 2.8 2.8 2.9 3.2 2.9 3.1 3.5 3.2 3.5 3.4
2002 3.6 3.7 3.5 3.8 4.0 3.6 3.2 3.7 3.8 3.7 3.4 3.4
2003 3.3 3.1 3.5 3.3 3.0 3.1 3.8 3.1 2.7 2.9 3.2 3.4
2004 3.5 3.6 3.2 3.2 2.8 2.8 3.1 3.1 3.0 3.0 3.0 2.9
2005 2.7 2.6 2.7 2.7 3.2 3.0 2.6 2.9 3.0 2.8 2.9 2.7
2006 3.2 2.7 2.5 2.4 2.6 3.0 2.5 2.5 2.7 3.2 2.8 2.5
2007 2.5 2.6 2.7 2.6 2.6 2.4 2.9 2.9 2.6 2.4 2.5 2.9
2008 2.6 2.8 3.1 3.3 3.0 2.8 2.6 2.5 2.8 2.9 2.9 3.3
2009 3.5 3.5 3.7 3.8 4.0 3.9 3.7 4.2 4.6 3.9 4.0 4.0
2010 3.7 3.5 3.5 3.8 3.4 3.8 4.0 4.0 3.7 3.5 3.4 3.1
2011 3.4 3.6 3.4 2.9 3.2 3.6 3.8 3.4 2.9 3.3 3.6 3.6
2012 3.8 3.4 3.7 3.3 3.4 3.3 3.4 3.0 2.9 3.3 3.1 3.1
2013 2.8 3.1 2.7 3.2 3.3 2.8 2.8 3.0 3.1 3.5 3.2 3.0
2014 2.9 3.0 3.4 3.4 2.9 3.1 3.3 3.3 3.2 2.6 2.4 2.8
2015 2.7 2.9 2.5 2.6 2.5 2.6 2.7 2.8 3.1 2.6 2.9 2.7
2016 2.9 2.5 2.5 2.4 2.5 2.5 2.2 2.0 2.0 2.2 2.5 2.1
2017 2.3 2.3 2.3 2.5 2.8 2.4 2.0 2.1 2.2 2.4 2.2 2.3
2018 2.1 2.0 2.1 2.0 1.7 1.9 2.3 2.3 2.0 1.9 1.8 2.0
2019 2.2 1.9 2.3 2.2 1.8 2.0 2.1 1.8 1.9 1.8        
  • 民主党政権


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.59625 -0.16329  0.03841  0.14622  0.45460 

Coefficients:
             Estimate Std. Error t value             Pr(>|t|)    
(Intercept)  3.814710   0.083432   45.72 < 0.0000000000000002 ***
ID          -0.016761   0.003635   -4.61            0.0000467 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.2555 on 37 degrees of freedom
Multiple R-squared:  0.3649,    Adjusted R-squared:  0.3477 
F-statistic: 21.26 on 1 and 37 DF,  p-value: 0.00004668



    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 = 1.2517, p-value = 0.004335
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.012093, df = 1, p-value = 0.9124



    Box-Ljung test

data:  lm_residuals
X-squared = 5.7985, df = 1, p-value = 0.01604
  • 第二次安倍内閣~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.46528 -0.13165 -0.02987  0.16017  0.48606 

Coefficients:
            Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.20515    0.05255   61.00 <0.0000000000000002 ***
ID          -0.01682    0.00110  -15.29 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.2357 on 80 degrees of freedom
Multiple R-squared:  0.745, Adjusted R-squared:  0.7418 
F-statistic: 233.7 on 1 and 80 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 = 0.14634, p-value = 0.3453
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.1852, p-value = 0.00003315
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 4.6407, df = 1, p-value = 0.03122



    Box-Ljung test

data:  lm_residuals
X-squared = 12.958, df = 1, p-value = 0.0003186
  • 白川日銀総裁


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.0125 -0.2367  0.0104  0.2938  1.1319 

Coefficients:
             Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.526125   0.113981  30.936 <0.0000000000000002 ***
ID          -0.003413   0.003304  -1.033               0.306    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.4322 on 57 degrees of freedom
Multiple R-squared:  0.01838,   Adjusted R-squared:  0.001156 
F-statistic: 1.067 on 1 and 57 DF,  p-value: 0.306



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.11864, p-value = 0.8052
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.45162, p-value = 0.00000000000002175
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 10.418, df = 1, p-value = 0.001248



    Box-Ljung test

data:  lm_residuals
X-squared = 34.258, df = 1, p-value = 0.000000004826
  • 黒田日銀総裁~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.47594 -0.12479 -0.03278  0.13591  0.48359 

Coefficients:
            Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.20273    0.05203   61.56 <0.0000000000000002 ***
ID          -0.01773    0.00113  -15.69 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.229 on 77 degrees of freedom
Multiple R-squared:  0.7617,    Adjusted R-squared:  0.7586 
F-statistic: 246.1 on 1 and 77 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 = 0.13924, p-value = 0.4302
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.1774, p-value = 0.00003735
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 2.4097, df = 1, p-value = 0.1206



    Box-Ljung test

data:  lm_residuals
X-squared = 13.877, df = 1, p-value = 0.0001952
  • 特記その他
  1. 時系列データの特徴(誤差構造、負数の有無その他等)に関わらず線形回帰を求めている。よってあくまでも対象とした期間における線形回帰そしてその残差の傾向を確認しているのみであり結果の外挿は出来ない。
  2. 民主党政権:2009-09-16~2012-12-25
  3. 白川方明氏の日銀総裁就任期間:2008-04-09~2013-03-19