Analysis

[1] "労働力調査:完全失業率(%):季節調整値:男: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                                             3.2
2000 3.5 3.6 3.4 3.4 3.1 3.3 3.6 3.3 3.5 3.4 3.3 3.5
2001 3.4 3.1 3.5 3.5 3.3 3.7 3.6 3.6 3.6 4.2 4.8 4.4
2002 4.1 4.3 4.1 4.1 4.0 3.8 4.2 4.7 4.7 4.4 4.2 4.3
2003 4.2 4.0 3.8 4.1 4.4 4.2 3.8 4.1 4.4 3.9 3.5 3.3
2004 3.5 3.8 3.9 3.8 3.8 4.0 3.8 3.0 3.2 3.1 3.3 3.5
2005 3.3 3.2 3.3 3.1 3.1 3.2 3.1 3.3 2.9 3.3 3.3 3.0
2006 3.4 3.3 3.1 3.0 3.1 3.0 3.2 3.2 2.9 2.9 3.3 3.1
2007 2.9 2.9 2.9 2.8 2.7 2.7 2.7 2.8 3.0 3.1 2.8 2.8
2008 3.0 3.1 2.8 2.8 3.0 3.0 2.9 2.9 3.0 2.9 3.2 3.6
2009 3.1 3.5 3.8 4.0 4.2 3.6 4.0 4.2 4.0 4.2 4.0 3.9
2010 4.0 4.1 4.4 4.3 3.7 4.0 4.0 4.2 4.2 3.9 3.9 4.0
2011 4.1 3.6 3.6 3.9 3.7 4.0 3.8 3.4 3.5 3.6 3.5 3.4
2012 3.4 3.3 3.5 3.3 3.6 3.9 3.5 3.5 3.3 3.0 3.3 3.2
2013 3.2 3.7 3.6 3.5 3.4 3.0 3.3 3.5 3.3 3.7 3.3 2.9
2014 3.0 2.7 2.8 3.2 2.8 2.7 3.0 2.8 3.0 3.0 2.9 3.0
2015 3.0 2.8 2.9 2.5 2.7 3.0 3.0 2.9 2.8 2.6 2.8 2.9
2016 2.9 3.0 2.7 2.5 2.7 2.7 2.2 2.6 2.5 2.5 2.5 2.4
2017 2.3 2.5 2.4 2.5 2.8 2.4 2.4 2.4 2.4 2.2 2.4 2.4
2018 2.3 2.1 2.1 2.3 1.9 2.1 2.2 2.1 2.0 2.2 2.0 2.0
2019 1.6 1.8 2.3 2.3 2.1 2.1 2.3 2.0 1.9 2.2        
  • 民主党政権


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.33638 -0.14850 -0.01134  0.13898  0.48963 

Coefficients:
            Estimate Std. Error t value             Pr(>|t|)    
(Intercept)  4.23671    0.06379  66.416 < 0.0000000000000002 ***
ID          -0.02504    0.00278  -9.009      0.0000000000729 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1954 on 37 degrees of freedom
Multiple R-squared:  0.6868,    Adjusted R-squared:  0.6784 
F-statistic: 81.15 on 1 and 37 DF,  p-value: 0.00000000007295



    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 = 1.4967, p-value = 0.03702
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.0021354, df = 1, p-value = 0.9631



    Box-Ljung test

data:  lm_residuals
X-squared = 2.6363, df = 1, p-value = 0.1044
  • 第二次安倍内閣~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.46732 -0.13358  0.02086  0.10324  0.51366 

Coefficients:
              Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.3639566  0.0437862   76.83 <0.0000000000000002 ***
ID          -0.0177621  0.0009165  -19.38 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1964 on 80 degrees of freedom
Multiple R-squared:  0.8244,    Adjusted R-squared:  0.8222 
F-statistic: 375.6 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 = 0.085366, p-value = 0.9286
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.3897, p-value = 0.001551
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 1.6084, df = 1, p-value = 0.2047



    Box-Ljung test

data:  lm_residuals
X-squared = 7.0457, df = 1, p-value = 0.007945
  • 白川日銀総裁


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.76249 -0.28492 -0.03399  0.34680  0.74990 

Coefficients:
              Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.6643483  0.1075505  34.071 <0.0000000000000002 ***
ID          -0.0006195  0.0031177  -0.199               0.843    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.4078 on 57 degrees of freedom
Multiple R-squared:  0.0006922, Adjusted R-squared:  -0.01684 
F-statistic: 0.03949 on 1 and 57 DF,  p-value: 0.8432



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.18644, p-value = 0.2582
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.41148, p-value = 0.000000000000001678
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 15.815, df = 1, p-value = 0.00006985



    Box-Ljung test

data:  lm_residuals
X-squared = 36.885, df = 1, p-value = 0.000000001253
  • 黒田日銀総裁~


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.47590 -0.12311  0.02663  0.09770  0.53678 

Coefficients:
              Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  3.2840312  0.0435528   75.40 <0.0000000000000002 ***
ID          -0.0172590  0.0009459  -18.25 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1917 on 77 degrees of freedom
Multiple R-squared:  0.8122,    Adjusted R-squared:  0.8097 
F-statistic: 332.9 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 = 0.10127, p-value = 0.8161
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.4163, p-value = 0.002715
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.84816, df = 1, p-value = 0.3571



    Box-Ljung test

data:  lm_residuals
X-squared = 5.9124, df = 1, p-value = 0.01504
  • 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