2014年4月分の日本のマネーストック

2014年5月13日、2014年4月分の日本のマネーストックが公表されました。

そこでマネタリーベースとマネーストックの関係を確認してみましょう。

なおマネタリーベースの1次階差の単位根検定の結果、p値(=0.05359)は0.05を超え0.1未満であることを考慮の上、確認してください。 
mbm3201404

> library(tseries)

> dataset
         date       M3       MB
1    2004/4/1 1024.045 108.2958
2    2004/5/1 1024.742 108.8328
3    2004/6/1 1024.312 107.2957
4    2004/7/1 1029.688 108.5248
5    2004/8/1 1028.420 108.5653
6    2004/9/1 1024.221 108.5201
7   2004/10/1 1021.759 107.9234
8   2004/11/1 1021.473 109.4035
9   2004/12/1 1028.685 111.9769
10   2005/1/1 1029.064 112.5134
11   2005/2/1 1023.629 109.3674
12   2005/3/1 1026.453 110.3301
13   2005/4/1 1030.090 111.5568
14   2005/5/1 1027.792 111.2725
15   2005/6/1 1027.626 109.1586
16   2005/7/1 1032.622 110.1137
17   2005/8/1 1030.622 109.7890
18   2005/9/1 1029.457 110.3950
19  2005/10/1 1026.125 110.9848
20  2005/11/1 1026.469 111.0432
21  2005/12/1 1032.146 113.0466
22   2006/1/1 1031.286 114.1316
23   2006/2/1 1024.830 111.4431
24   2006/3/1 1025.365 109.2791
25   2006/4/1 1031.246 103.5779
26   2006/5/1 1026.619  94.1951
27   2006/6/1 1025.674  91.4229
28   2006/7/1 1025.906  90.5410
29   2006/8/1 1023.258  87.5607
30   2006/9/1 1022.738  86.9660
31  2006/10/1 1019.308  87.3279
32  2006/11/1 1019.945  86.2670
33  2006/12/1 1026.271  90.4664
34   2007/1/1 1026.952  90.0507
35   2007/2/1 1021.495  87.9061
36   2007/3/1 1022.937  88.4022
37   2007/4/1 1029.541  90.8926
38   2007/5/1 1026.995  88.7868
39   2007/6/1 1029.113  87.6336
40   2007/7/1 1030.599  88.4708
41   2007/8/1 1026.303  88.1473
42   2007/9/1 1025.326  87.5728
43  2007/10/1 1025.266  87.7567
44  2007/11/1 1026.290  87.1633
45  2007/12/1 1033.148  90.7835
46   2008/1/1 1034.342  89.9793
47   2008/2/1 1030.188  87.9916
48   2008/3/1 1030.991  88.3867
49   2008/4/1 1034.784  88.3589
50   2008/5/1 1033.881  87.9638
51   2008/6/1 1038.082  88.0155
52   2008/7/1 1038.358  87.8532
53   2008/8/1 1036.687  87.9433
54   2008/9/1 1034.725  88.3741
55  2008/10/1 1030.867  88.9825
56  2008/11/1 1032.926  88.8562
57  2008/12/1 1040.645  92.4351
58   2009/1/1 1043.757  93.5049
59   2009/2/1 1042.126  93.6531
60   2009/3/1 1044.532  94.4658
61   2009/4/1 1052.392  95.6238
62   2009/5/1 1052.048  94.9165
63   2009/6/1 1055.549  93.6392
64   2009/7/1 1058.155  93.2096
65   2009/8/1 1057.677  93.3355
66   2009/9/1 1056.457  92.3942
67  2009/10/1 1055.768  92.8609
68  2009/11/1 1057.479  92.2042
69  2009/12/1 1063.518  97.2143
70   2010/1/1 1066.208  98.0675
71   2010/2/1 1062.869  95.6928
72   2010/3/1 1064.878  96.4571
73   2010/4/1 1074.912  98.3836
74   2010/5/1 1076.380  98.4323
75   2010/6/1 1078.451  97.0240
76   2010/7/1 1079.908  98.9359
77   2010/8/1 1079.734  98.3995
78   2010/9/1 1078.947  97.7173
79  2010/10/1 1078.409  98.8248
80  2010/11/1 1078.622  99.1866
81  2010/12/1 1082.937 104.0238
82   2011/1/1 1085.254 103.4826
83   2011/2/1 1082.249 101.0039
84   2011/3/1 1085.747 112.7432
85   2011/4/1 1097.612 121.8934
86   2011/5/1 1099.480 114.4208
87   2011/6/1 1102.806 113.4780
88   2011/7/1 1105.613 113.7324
89   2011/8/1 1103.464 114.0447
90   2011/9/1 1103.401 114.0181
91  2011/10/1 1103.657 115.6428
92  2011/11/1 1105.766 118.4978
93  2011/12/1 1111.535 118.0195
94   2012/1/1 1113.372 118.9656
95   2012/2/1 1109.701 112.4409
96   2012/3/1 1113.658 112.4618
97   2012/4/1 1122.881 121.5003
98   2012/5/1 1120.576 117.1210
99   2012/6/1 1124.337 120.2142
100  2012/7/1 1127.124 123.5010
101  2012/8/1 1126.282 121.4626
102  2012/9/1 1126.205 124.3261
103 2012/10/1 1125.457 128.1344
104 2012/11/1 1126.384 124.4449
105 2012/12/1 1136.010 131.9837
106  2013/1/1 1138.692 131.9205
107  2013/2/1 1136.732 129.3148
108  2013/3/1 1141.673 134.7413
109  2013/4/1 1151.885 149.5975
110  2013/5/1 1152.027 154.1412
111  2013/6/1 1158.713 163.5375
112  2013/7/1 1160.992 170.3890
113  2013/8/1 1160.434 172.4437
114  2013/9/1 1161.274 181.7012
115 2013/10/1 1162.766 186.8687
116 2013/11/1 1165.727 189.7244
117 2013/12/1 1174.818 193.4594
118  2014/1/1 1178.130 200.4141
119  2014/2/1 1173.051 201.3223
120  2014/3/1 1174.475 208.5929
121  2014/4/1 1183.769 222.0795

> m3 < - dataset$M3

> mb < - dataset$MB

> adf.test(m3)

        Augmented Dickey-Fuller Test

data:  m3
Dickey-Fuller = -0.5764, Lag order = 4, p-value = 0.9771
alternative hypothesis: stationary

> dm3 < - diff(m3)

> adf.test(dm3)

        Augmented Dickey-Fuller Test

data:  dm3
Dickey-Fuller = -5.9998, Lag order = 4, p-value = 0.01
alternative hypothesis: stationary

 警告メッセージ: 
In adf.test(dm3) : p-value smaller than printed p-value

> adf.test(mb)

        Augmented Dickey-Fuller Test

data:  mb
Dickey-Fuller = 2.1351, Lag order = 4, p-value = 0.99
alternative hypothesis: stationary

 警告メッセージ: 
In adf.test(mb) : p-value greater than printed p-value

> dmb < - diff(mb)

> adf.test(dmb)

        Augmented Dickey-Fuller Test

data:  dmb
Dickey-Fuller = -3.4259, Lag order = 4, p-value = 0.05359
alternative hypothesis: stationary

> ccfvalue < - ccf(dmb,dm3,36,main="CrossCorrelation.MB&M3(both 1st diff) in Japan")

> ccfvalue

Autocorrelations of series ‘X’, by lag

   -36    -35    -34    -33    -32    -31    -30    -29    -28    -27    -26 
 0.163 -0.146 -0.205  0.071  0.015 -0.102  0.019 -0.008  0.083  0.113 -0.110 
   -25    -24    -23    -22    -21    -20    -19    -18    -17    -16    -15 
 0.012  0.301 -0.091 -0.246  0.129  0.065 -0.118  0.051 -0.024  0.107  0.164 
   -14    -13    -12    -11    -10     -9     -8     -7     -6     -5     -4 
-0.153  0.006  0.433 -0.081 -0.254  0.198  0.144 -0.021  0.181 -0.012  0.103 
    -3     -2     -1      0      1      2      3      4      5      6      7 
 0.292 -0.045  0.086  0.601 -0.029 -0.210  0.309  0.209  0.025  0.198 -0.007 
     8      9     10     11     12     13     14     15     16     17     18 
 0.078  0.252 -0.077  0.064  0.510 -0.043 -0.186  0.264  0.122 -0.005  0.124 
    19     20     21     22     23     24     25     26     27     28     29 
-0.042  0.076  0.201 -0.113  0.065  0.473 -0.028 -0.159  0.202  0.137  0.003 
    30     31     32     33     34     35     36 
 0.035 -0.096  0.016  0.175 -0.081  0.027  0.384 
> 

R Core Team (2013). R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria.
URL http://www.R-project.org/.