Analysis

[1] "機械受注統計調査:非製造業業種別受注額(季調系列・月次)(単位:億円):運輸業・郵便業:内閣府"
         Jan     Feb     Mar     Apr     May     Jun     Jul     Aug     Sep     Oct     Nov     Dec
2005                          468.65  532.28  459.00  595.96  667.98  738.60  761.16  837.94  645.42
2006  633.13  666.47  695.93  829.98  947.62 1015.52  916.27  684.47  767.31  611.63  722.15  755.44
2007  744.14  780.30  663.81  580.36  647.03  470.88  801.43  968.75  652.59  943.65  958.90  964.05
2008 1558.00  729.44  815.81  859.61 1303.73 1104.26  733.37  565.11  736.45  665.22  627.02  681.14
2009  720.24  791.02 1163.96  754.61  507.97  554.67  525.02  610.66  633.79  536.74  532.66  729.01
2010  525.04  479.47  696.97  775.94  621.98  545.01  543.38  679.38  507.15  683.49  500.03  477.38
2011  608.92  563.88  554.35  431.53  419.53  744.05  790.53  541.58  677.52  494.83 1009.16  566.82
2012  509.96  583.56  445.22  486.94  493.43  557.02  619.42  672.70  702.73  639.09  718.07  546.60
2013  683.58  572.04  850.67  553.92  972.80  653.88  582.30  756.25  641.49  661.69  774.30  552.56
2014  724.90 1058.29  794.26 1028.73  776.30  609.37  712.52  721.14  751.56 1036.81  796.15  858.88
2015  968.61  663.59  808.36 1183.34  757.66  706.81  673.21  572.63  745.07 1517.49  823.32  829.97
2016  765.21  954.22  854.74  905.63 1043.16 1311.43 1056.49 1274.78 1415.19  944.99  790.79 1080.19
2017  797.17  962.06  764.01  844.55  691.32  755.47 1136.43  768.93  751.03  879.67  886.42  909.57
2018  997.96  850.52  924.25  716.49  837.58  872.51  997.09 1776.39  719.25  746.42  932.62  950.45
2019  713.33 1048.95 1208.54 1317.88  923.94 1768.81  958.30 1108.04 1106.87                        
  • 民主党政権


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-175.63  -86.60  -39.54   84.87  410.21 

Coefficients:
            Estimate Std. Error t value            Pr(>|t|)    
(Intercept) 582.5210    39.4369  14.771 <0.0000000000000002 ***
ID            0.6317     1.7184   0.368               0.715    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 120.8 on 37 degrees of freedom
Multiple R-squared:  0.003639,  Adjusted R-squared:  -0.02329 
F-statistic: 0.1351 on 1 and 37 DF,  p-value: 0.7153



    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 = 1.9934, p-value = 0.4234
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 0.12549, df = 1, p-value = 0.7232



    Box-Ljung test

data:  lm_residuals
X-squared = 0.00018303, df = 1, p-value = 0.9892
  • 第二次安倍内閣~


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-326.18 -135.12  -51.09   42.56  759.65 

Coefficients:
            Estimate Std. Error t value             Pr(>|t|)    
(Intercept)  706.999     49.410  14.309 < 0.0000000000000002 ***
ID             4.555      1.047   4.351            0.0000401 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 220.3 on 79 degrees of freedom
Multiple R-squared:  0.1933,    Adjusted R-squared:  0.1831 
F-statistic: 18.93 on 1 and 79 DF,  p-value: 0.00004011



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.18519, p-value = 0.1245
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.9181, p-value = 0.3137
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 3.0148, df = 1, p-value = 0.08251



    Box-Ljung test

data:  lm_residuals
X-squared = 0.13954, df = 1, p-value = 0.7087
  • 白川日銀総裁


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-203.57 -112.13  -28.53   61.62  573.16 

Coefficients:
            Estimate Std. Error t value            Pr(>|t|)    
(Intercept)  733.556     43.567  16.837 <0.0000000000000002 ***
ID            -2.985      1.263  -2.364              0.0215 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 165.2 on 57 degrees of freedom
Multiple R-squared:  0.08928,   Adjusted R-squared:  0.0733 
F-statistic: 5.588 on 1 and 57 DF,  p-value: 0.02152



    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 = 1.1709, p-value = 0.0002376
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 3.1305, df = 1, p-value = 0.07684



    Box-Ljung test

data:  lm_residuals
X-squared = 4.9104, df = 1, p-value = 0.0267
  • 黒田日銀総裁~


Call:
lm(formula = value ~ ID)

Residuals:
    Min      1Q  Median      3Q     Max 
-325.29 -134.23  -60.97   40.33  760.31 

Coefficients:
            Estimate Std. Error t value             Pr(>|t|)    
(Intercept)  723.062     51.095  14.151 < 0.0000000000000002 ***
ID             4.508      1.124   4.011              0.00014 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 223.5 on 76 degrees of freedom
Multiple R-squared:  0.1747,    Adjusted R-squared:  0.1639 
F-statistic: 16.09 on 1 and 76 DF,  p-value: 0.0001401



    Two-sample Kolmogorov-Smirnov test

data:  lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.16667, p-value = 0.2297
alternative hypothesis: two-sided



    Durbin-Watson test

data:  value ~ ID
DW = 1.8903, p-value = 0.2728
alternative hypothesis: true autocorrelation is greater than 0



    studentized Breusch-Pagan test

data:  value ~ ID
BP = 2.5485, df = 1, p-value = 0.1104



    Box-Ljung test

data:  lm_residuals
X-squared = 0.20876, df = 1, p-value = 0.6477
  • 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