Analysis

[1] "一般職業紹介状況:新規求人倍率:正社員:季節調整値:厚生労働省"
      Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
2004                                                   0.84 0.85
2005 0.87 0.90 0.89 0.89 0.88 0.88 0.89 0.87 0.89 0.89 0.90 0.95
2006 0.95 0.94 0.91 0.93 0.95 0.94 0.92 0.91 0.91 0.92 0.93 0.95
2007 0.90 0.91 0.92 0.91 0.91 0.90 0.89 0.89 0.87 0.88 0.89 0.89
2008 0.89 0.88 0.86 0.86 0.84 0.80 0.78 0.78 0.72 0.70 0.66 0.57
2009 0.52 0.46 0.46 0.46 0.45 0.45 0.44 0.45 0.46 0.45 0.44 0.44
2010 0.46 0.48 0.47 0.49 0.50 0.51 0.51 0.52 0.54 0.57 0.56 0.57
2011 0.60 0.60 0.58 0.59 0.58 0.59 0.64 0.63 0.67 0.68 0.71 0.70
2012 0.72 0.74 0.72 0.75 0.78 0.78 0.78 0.79 0.76 0.77 0.78 0.78
2013 0.80 0.82 0.81 0.83 0.84 0.86 0.86 0.89 0.88 0.93 0.93 0.94
2014 0.97 1.00 0.97 0.98 0.98 0.99 1.00 0.99 1.00 1.04 1.02 1.06
2015 1.07 1.04 1.07 1.09 1.08 1.09 1.12 1.11 1.14 1.13 1.16 1.18
2016 1.25 1.20 1.22 1.27 1.27 1.25 1.26 1.28 1.31 1.30 1.34 1.35
2017 1.35 1.37 1.38 1.40 1.46 1.45 1.43 1.45 1.47 1.51 1.53 1.57
2018 1.52 1.56 1.58 1.59 1.61 1.65 1.59 1.61 1.67 1.62 1.64 1.65
2019 1.64 1.69 1.69 1.68 1.64 1.64 1.62 1.68 1.61 1.68          
  • 民主党政権


Call:
lm(formula = value ~ ID)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.041389 -0.010263  0.000005  0.017162  0.037430 

Coefficients:
             Estimate Std. Error t value            Pr(>|t|)    
(Intercept) 0.4191363  0.0064368   65.12 <0.0000000000000002 ***
ID          0.0101073  0.0002805   36.04 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.01971 on 37 degrees of freedom
Multiple R-squared:  0.9723,    Adjusted R-squared:  0.9715 
F-statistic:  1299 on 1 and 37 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 = 0.10256, p-value = 0.9885
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.80055, p-value = 0.000005482
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 7.2129, df = 1, p-value = 0.007238



    Box-Ljung test

data:  lm_residuals
X-squared = 12.551, df = 1, p-value = 0.0003961
  • 第二次安倍内閣~


Call:
lm(formula = value ~ ID)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.128261 -0.026099  0.000497  0.018456  0.089282 

Coefficients:
             Estimate Std. Error t value            Pr(>|t|)    
(Intercept) 0.7795303  0.0084185   92.60 <0.0000000000000002 ***
ID          0.0118362  0.0001762   67.17 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.03777 on 80 degrees of freedom
Multiple R-squared:  0.9826,    Adjusted R-squared:  0.9824 
F-statistic:  4512 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 = 0.13415, p-value = 0.4541
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.58464, p-value = 0.000000000000006618
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 15.344, df = 1, p-value = 0.00008961



    Box-Ljung test

data:  lm_residuals
X-squared = 39.998, df = 1, p-value = 0.0000000002543
  • 白川日銀総裁


Call:
lm(formula = value ~ ID)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.14272 -0.09477 -0.02999  0.06058  0.33068 

Coefficients:
             Estimate Std. Error t value             Pr(>|t|)    
(Intercept) 0.5054588  0.0303745  16.641 < 0.0000000000000002 ***
ID          0.0038632  0.0008805   4.387            0.0000501 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.1152 on 57 degrees of freedom
Multiple R-squared:  0.2525,    Adjusted R-squared:  0.2393 
F-statistic: 19.25 on 1 and 57 DF,  p-value: 0.00005012



    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 = 0.051046, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 20.116, df = 1, p-value = 0.000007287



    Box-Ljung test

data:  lm_residuals
X-squared = 50.071, df = 1, p-value = 0.000000000001483
  • 黒田日銀総裁~


Call:
lm(formula = value ~ ID)

Residuals:
      Min        1Q    Median        3Q       Max 
-0.128789 -0.025733  0.000496  0.019557  0.089064 

Coefficients:
             Estimate Std. Error t value            Pr(>|t|)    
(Intercept) 0.8139533  0.0087299   93.24 <0.0000000000000002 ***
ID          0.0118569  0.0001896   62.54 <0.0000000000000002 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.03843 on 77 degrees of freedom
Multiple R-squared:  0.9807,    Adjusted R-squared:  0.9804 
F-statistic:  3911 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 = 0.16456, p-value = 0.2361
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 0.58138, p-value = 0.00000000000001568
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 14.186, df = 1, p-value = 0.0001656



    Box-Ljung test

data:  lm_residuals
X-squared = 38.752, df = 1, p-value = 0.0000000004812
  • 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