Analysis

[1] "労働力調査:完全失業率(%):季節調整値:男女計: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                                             3.1
2000 3.3 3.3 3.3 3.3 3.1 3.2 3.4 3.2 3.4 3.2 3.1 3.3
2001 3.1 3.1 3.2 3.2 3.1 3.5 3.3 3.4 3.6 3.8 4.3 4.0
2002 3.9 4.0 3.9 4.0 4.0 3.7 3.8 4.3 4.2 4.1 3.8 3.9
2003 3.8 3.6 3.7 3.7 3.8 3.8 3.8 3.6 3.7 3.5 3.4 3.3
2004 3.5 3.7 3.6 3.5 3.4 3.5 3.5 3.1 3.1 3.1 3.2 3.3
2005 3.1 3.0 3.0 3.0 3.1 3.1 3.0 3.1 3.0 3.0 3.1 3.0
2006 3.3 3.0 2.8 2.8 2.9 2.9 2.9 2.9 2.8 3.0 3.1 2.9
2007 2.7 2.8 2.8 2.7 2.6 2.6 2.8 2.8 2.8 2.9 2.7 2.8
2008 2.8 3.0 2.9 3.0 3.0 3.0 2.7 2.7 2.9 2.9 3.1 3.4
2009 3.3 3.5 3.8 3.9 4.1 3.7 3.9 4.2 4.3 4.0 4.0 3.9
2010 3.9 3.8 4.0 4.0 3.6 3.9 4.0 4.1 4.1 3.7 3.6 3.7
2011 3.8 3.7 3.4 3.4 3.5 3.9 3.9 3.4 3.2 3.4 3.7 3.5
2012 3.5 3.3 3.6 3.3 3.5 3.6 3.4 3.3 3.1 3.2 3.2 3.2
2013 3.0 3.4 3.2 3.4 3.4 2.9 3.1 3.3 3.2 3.6 3.3 3.0
2014 3.0 2.9 3.1 3.3 2.8 2.9 3.1 3.0 3.1 2.9 2.7 2.9
2015 2.8 2.8 2.7 2.6 2.6 2.8 2.9 2.9 2.9 2.6 2.8 2.9
2016 2.9 2.7 2.6 2.5 2.7 2.6 2.2 2.3 2.3 2.4 2.5 2.3
2017 2.3 2.5 2.4 2.4 2.8 2.4 2.3 2.2 2.3 2.3 2.3 2.3
2018 2.2 2.0 2.1 2.2 1.8 2.0 2.2 2.2 2.0 2.1 1.9 2.0
2019 1.9 1.8 2.3 2.2 1.9 2.0 2.2 1.9 1.9 2.1        
  • 民主党政権


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.33943 -0.12080 -0.02038  0.09918  0.31874 

Coefficients:
             Estimate Std. Error t value             Pr(>|t|)    
(Intercept)  4.041296   0.056020  72.140 < 0.0000000000000002 ***
ID          -0.020911   0.002441  -8.566       0.000000000261 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1716 on 37 degrees of freedom
Multiple R-squared:  0.6648,    Adjusted R-squared:  0.6557 
F-statistic: 73.38 on 1 and 37 DF,  p-value: 0.0000000002607



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.12821, p-value = 0.9114
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.472, p-value = 0.03082
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.014394, df = 1, p-value = 0.9045



    Box-Ljung test

data:  lm_residuals
X-squared = 2.9222, df = 1, p-value = 0.08737
  • 第二次安倍内閣~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.36112 -0.10644  0.00652  0.10526  0.46879 

Coefficients:
              Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.3075881  0.0372908    88.7 <0.0000000000000002 ***
ID          -0.0176380  0.0007805   -22.6 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1673 on 80 degrees of freedom
Multiple R-squared:  0.8646,    Adjusted R-squared:  0.8629 
F-statistic: 510.6 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 = 0.097561, p-value = 0.8332
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.5021, p-value = 0.007886
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.41593, df = 1, p-value = 0.519



    Box-Ljung test

data:  lm_residuals
X-squared = 4.0204, df = 1, p-value = 0.04495
  • 白川日銀総裁


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.8969 -0.2520 -0.0127  0.3297  0.7288 

Coefficients:
             Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.602338   0.102734  35.065 <0.0000000000000002 ***
ID          -0.001829   0.002978  -0.614               0.541    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.3896 on 57 degrees of freedom
Multiple R-squared:  0.006576,  Adjusted R-squared:  -0.01085 
F-statistic: 0.3773 on 1 and 57 DF,  p-value: 0.5415



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.084746, p-value = 0.9854
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.31225, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 17.729, df = 1, p-value = 0.00002546



    Box-Ljung test

data:  lm_residuals
X-squared = 41.522, df = 1, p-value = 0.0000000001165
  • 黒田日銀総裁~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.35897 -0.10910  0.00884  0.09991  0.45871 

Coefficients:
              Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.2663096  0.0378108   86.39 <0.0000000000000002 ***
ID          -0.0178603  0.0008212  -21.75 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1664 on 77 degrees of freedom
Multiple R-squared:   0.86, Adjusted R-squared:  0.8582 
F-statistic:   473 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 = 0.11392, p-value = 0.6878
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.4572, p-value = 0.004858
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.24207, df = 1, p-value = 0.6227



    Box-Ljung test

data:  lm_residuals
X-squared = 5.2088, df = 1, p-value = 0.02247
  • 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