:

:

. , 30% .

:

,

1 , . .

, %

1 , .

1 3280 48,20 61 0,313
2 2920 43,10 54 0,413
3 5140 60,70 70 0,268
4 4630 60,10 67 0,310
5 4950 59,40 71 0,309
6 5000 52,50 74 0,288
7 2790 44,00 45 0,357
8 4340 54,20 68 0,247
9 4160 53,20 65 0,305
10 2660 46,40 51 0,376
11 2960 47,10 52 0,351
12 3230 46,10 57 0,356
13 3480 53,90 58 0,312
14 3230 53,40 52 0,415
15 2370 39,40 44 0,411
16 2610 40,20 50 0,380
17 3000 45,50 52 0,326
18 2960 41,40 49 0,341
19 3100 47,80 53 0,398
20 2720 46,30 57 0,405

. . , . , d. . , : , ( n .)

, 1 , . d = Nx - Ny

d2

x y

Nx

Ny

3280 0,313 8 13 -5 25
2920 0,413 15 2 13 169
5140 0,268 1 19 -18 324
4630 0,31 4 15 -11 121
4950 0,309 3 16 -13 169
5000 0,288 2 18 -16 256
2790 0,357 16 8 8 64
4340 0,247 5 20 -15 225
4160 0,305 6 17 -11 121
2660 0,376 18 7 11 121
2960 0,351 13,5 10 3,5 12,25
3230 0,356 9,5 9 0,5 0,25
3480 0,312 7 14 -7 49
3230 0,415 9,5 1 8,5 72,25
2370 0,411 20 3 17 289
2610 0,38 19 6 13 169
3000 0,326 12 12 0 0
2960 0,341 13,5 11 2,5 6,25
3100 0,398 11 5 6 36
2720 0,405 17 4 13 169
n = 20

∑ d 2 =

2398
ρ = -0,803

, .. .

1 , .. 1 , . d = Nx - Ny

d2

x y

Nx

Ny

48,2 0,313 9 13 -4 16
43,1 0,413 17 2 15 225
60,7 0,268 1 19 -18 324
60,1 0,31 2 15 -13 169
59,4 0,309 3 16 -13 169
52,5 0,288 8 18 -10 100
44 0,357 16 8 8 64
54,2 0,247 4 20 -16 256
53,2 0,305 7 17 -10 100
46,4 0,376 12 7 5 25
47,1 0,351 11 10 1 1
46,1 0,356 14 9 5 25
53,9 0,312 5 14 -9 81
53,4 0,415 6 1 5 25
39,4 0,411 20 3 17 289
40,2 0,38 19 6 13 169
45,5 0,326 15 12 3 9
41,4 0,341 18 11 7 49
47,8 0,398 10 5 5 25
46,3 0,405 13 4 9 81
n = 20

∑ d 2 =

2202
ρ = -0,656

, , 1 .



, %

1 , . d = Nx - Ny

d2

x y

Nx

Ny

61 0,313 7 13 -6 36
54 0,413 11 2 9 81
70 0,268 3 19 -16 256
67 0,31 5 15 -10 100
71 0,309 2 16 -14 196
74 0,288 1 18 -17 289
45 0,357 19 8 11 121
68 0,247 4 20 -16 256
65 0,305 6 17 -11 121
51 0,376 16 7 9 81
52 0,351 13 10 3 9
57 0,356 9 9 0 0
58 0,312 8 14 -6 36
52 0,415 13 1 12 144
44 0,411 20 3 17 289
50 0,38 17 6 11 121
52 0,326 13 12 1 1
49 0,341 18 11 7 49
53 0,398 12 5 7 49
57 0,405 9 4 5 25
n = 20

∑ d 2 =

2260
ρ = -0,699

.

, 1 , .. d = Nx - Ny

d2

x y

Nx

Ny

3280 48,2 8 9 -1 1
2920 43,1 15 17 -2 4
5140 60,7 1 1 0 0
4630 60,1 4 2 2 4
4950 59,4 3 3 0 0
5000 52,5 2 8 -6 36
2790 44 16 16 0 0
4340 54,2 5 4 1 1
4160 53,2 6 7 -1 1
2660 46,4 18 12 6 36
2960 47,1 13,5 11 2,5 6,25
3230 46,1 9,5 14 -4,5 20,25
3480 53,9 7 5 2 4
3230 53,4 9,5 6 3,5 12,25
2370 39,4 20 20 0 0
2610 40,2 19 19 0 0
3000 45,5 12 15 -3 9
2960 41,4 13,5 18 -4,5 20,25
3100 47,8 11 10 1 1
2720 46,3 17 13 4 16
n = 20

∑ d 2 =

172
ρ = 0,871

1 , .. 1 .

, , % d = Nx - Ny

d2

x y

Nx

Ny

3280 61 8 7 1 1
2920 54 15 11 4 16
5140 70 1 3 -2 4
4630 67 4 5 -1 1
4950 71 3 2 1 1
5000 74 2 1 1 1
2790 45 16 19 -3 9
4340 68 5 4 1 1
4160 65 6 6 0 0
2660 51 18 16 2 4
2960 52 13,5 13 0,5 0,25
3230 57 9,5 9 0,5 0,25
3480 58 7 8 -1 1
3230 52 9,5 13 -3,5 12,25
2370 44 20 20 0 0
2610 50 19 17 2 4
3000 52 12 13 -1 1
2960 49 13,5 18 -4,5 20,25
3100 53 11 12 -1 1
2720 57 17 9 8 64
n = 20

∑ d 2 =

142
ρ = 0,893

, , 89,3 % ( ).

1 , .. , % d = Nx - Ny

d2

x y

Nx

Ny

48,2 61 9 7 2 4
43,1 54 17 11 6 36
60,7 70 1 3 -2 4
60,1 67 2 5 -3 9
59,4 71 3 2 1 1
52,5 74 8 1 7 49
44 45 16 19 -3 9
54,2 68 4 4 0 0
53,2 65 7 6 1 1
46,4 51 12 16 -4 16
47,1 52 11 13 -2 4
46,1 57 14 9 5 25
53,9 58 5 8 -3 9
53,4 52 6 13 -7 49
39,4 44 20 20 0 0
40,2 50 19 17 2 4
45,5 52 15 13 2 4
41,4 49 18 18 0 0
47,8 53 10 12 -2 4
46,3 57 13 9 4 16
n = 20

∑ d 2 =

244
ρ = 0,817

1 . , .

, , , , . .

Stata 7.

:

. corr ud korm ves sst

(obs=20)

| ud korm ves sst

-------------+------------------------------------

ud | 1.0000

korm | 0.8851 1.0000

ves | 0.9401 0.8290 1.0000

sst | -0.7875 -0.6497 -0.7587 1.0000

  ud ,

  korm 1 ,

  ves ,

  sst 1 .

, (r = - 0,79), (r = - 0,76), (r = - 0,65). (r = 0,89), (r = 0,94), (r = 0,83). , , 8 %. 1 %.

:

. pwcorr ud korm ves sst

| ud korm ves sst

-------------+------------------------------------

ud | 1.0000

korm | 0.8851 1.0000

ves | 0.9401 0.8290 1.0000

sst | -0.7875 -0.6497 -0.7587 1.0000

.

.

, .

1 , . , 1 .

:


1


, .

:

. reg sst lnud korm ves

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.37

Model | .031800232 3 .010600077 Prob > F = 0.0005

Residual | .016350718 16 .00102192 R-squared = 0.6604

-------------+------------------------------ Adj R-squared = 0.5968

Total | .04815095 19 .002534261 Root MSE = .03197

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud | -.2305787 .1162704 -1.98 0.065 -.4770609 .0159036

korm | .0026417 .0025775 1.02 0.321 -.0028223 .0081057

ves | -.0000138 .0024772 -0.01 0.996 -.0052651 .0052376

_cons | 2.088534 .7538614 2.77 0.014 .4904194 3.686649

------------------------------------------------------------------------------

F- , lnud, korm, ves t- P- 0.065, 0.321 0.996. , .

:

. reg sst lnud1 korm1 ves1

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.32

Model | .031744654 3 .010581551 Prob > F = 0.0005

Residual | .016406296 16 .001025393 R-squared = 0.6593

-------------+------------------------------ Adj R-squared = 0.5954

Total | .04815095 19 .002534261 Root MSE = .03202

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 14.46292 6.110319 2.37 0.031 1.509625 27.41622

korm1 | -5.633853 5.967609 -0.94 0.359 -18.28462 7.016912

ves1 | .6831225 6.892859 0.10 0.922 -13.92909 15.29533

_cons | -1.33304 .6029802 -2.21 0.042 -2.611301 -.0547791

------------------------------------------------------------------------------

- 0,659 F- . korm1, ves1 t- P- 0.359 0.922. , .

. :

. reg sst lnud korm1 ves1

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.09

Model | .031497211 3 .01049907 Prob > F = 0.0006

Residual | .016653739 16 .001040859 R-squared = 0.6541

-------------+------------------------------ Adj R-squared = 0.5893

Total | .04815095 19 .002534261 Root MSE = .03226

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud | -.2065493 .0898758 -2.30 0.035 -.3970775 -.0160212

korm1 | -5.156249 5.939941 -0.87 0.398 -17.74836 7.435864

ves1 | 1.094516 6.895036 0.16 0.876 -13.52231 15.71134

_cons | 2.109487 .8816345 2.39 0.029 .2405058 3.978469

------------------------------------------------------------------------------

, R- , F- , korm1, ves1 P- 0.398 0.876 t- . .

:

. reg sst lnud1 korm ves1

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.60

Model | .032029999 3 .010676666 Prob > F = 0.0004

Residual | .016120951 16 .001007559 R-squared = 0.6652

-------------+------------------------------ Adj R-squared = 0.6024

Total | .04815095 19 .002534261 Root MSE = .03174

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 15.74117 6.497854 2.42 0.028 1.966333 29.516

korm | .0027978 .0025644 1.09 0.291 -.0026386 .0082341

ves1 | .0207899 6.780318 0.00 0.998 -14.35284 14.39442

_cons | -1.732706 .8136604 -2.13 0.049 -3.457589 -.0078235

------------------------------------------------------------------------------

R- - 0,665, F- . korm, ves1 P- 0.291 0.998 t- . .

:

. reg sst lnud1 korm1 ves

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.31

Model | .031738225 3 .010579408 Prob > F = 0.0005

Residual | .016412725 16 .001025795 R-squared = 0.6591

-------------+------------------------------ Adj R-squared = 0.5952

Total | .04815095 19 .002534261 Root MSE = .03203

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 14.53007 7.378598 1.97 0.066 -1.111856 30.172

korm1 | -5.544031 5.927707 -0.94 0.364 -18.11021 7.022147

ves | -.0001462 .002454 -0.06 0.953 -.0053485 .005056

_cons | -1.322613 .969369 -1.36 0.191 -3.377583 .7323579

------------------------------------------------------------------------------

, , , lnud1, korm1, ves t- .

:

. reg sst lnud lnud2 korm korm2 ves ves2

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 6, 13) = 4.52

Model | .032557159 6 .005426193 Prob > F = 0.0109

Residual | .015593791 13 .001199522 R-squared = 0.6761

-------------+------------------------------ Adj R-squared = 0.5267

Total | .04815095 19 .002534261 Root MSE = .03463

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud | -5.729043 9.44621 -0.61 0.555 -26.13634 14.67825

lnud2 | .341597 .5910669 0.58 0.573 -.9353253 1.618519

korm | .0132344 .0388671 0.34 0.739 -.0707327 .0972016

korm2 | -.0001134 .0004041 -0.28 0.783 -.0009865 .0007596

ves | .0150622 .0364293 0.41 0.686 -.0636385 .0937629

ves2 | -.0001446 .0003466 -0.42 0.683 -.0008934 .0006042

_cons | 23.57414 36.19652 0.65 0.526 -54.62369 101.772

------------------------------------------------------------------------------

, t- .

:

. reg sst lnud2 korm2 ves2

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 3, 16) = 10.39

Model | .031819188 3 .010606396 Prob > F = 0.0005

Residual | .016331762 16 .001020735 R-squared = 0.6608

-------------+------------------------------ Adj R-squared = 0.5972

Total | .04815095 19 .002534261 Root MSE = .03195

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud2 | -.0150021 .0079436 -1.89 0.077 -.0318418 .0018377

korm2 | .000028 .0000263 1.07 0.302 -.0000277 .0000838

ves2 | 2.49e-06 .0000227 0.11 0.914 -.0000457 .0000507

_cons | 1.258054 .4178871 3.01 0.008 .3721731 2.143935

------------------------------------------------------------------------------

t- . .

. , . , .

. sw reg sst lnud korm ves korm1 ves1 lnud2 korm2 ves2,pe(0.05)

begin with empty model

p = 0.0000 < 0.0500 adding lnud

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 1, 18) = 31.70

Model | .030711968 1 .030711968 Prob > F = 0.0000

Residual | .017438982 18 .000968832 R-squared = 0.6378

-------------+------------------------------ Adj R-squared = 0.6177

Total | .04815095 19 .002534261 Root MSE = .03113

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud | -.1672727 .0297095 -5.63 0.000 -.22969 -.1048553

_cons | 1.703191 .241499 7.05 0.000 1.19582 2.210561

------------------------------------------------------------------------------

. F- , lnud t- . 63,78 % sst . 2,72 % 0,17 %.

. sw reg sst lnud1 korm ves korm1 ves1 lnud2 korm2 ves2,pe(0.05)

begin with empty model

p = 0.0000 < 0.0500 adding lnud1

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 1, 18) = 32.04

Model | .030830369 1 .030830369 Prob > F = 0.0000

Residual | .017320581 18 .000962254 R-squared = 0.6403

-------------+------------------------------ Adj R-squared = 0.6203

Total | .04815095 19 .002534261 Root MSE = .03102

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 11.2229 1.982717 5.66 0.000 7.057366 15.38843

_cons | -1.038311 .2443161 -4.25 0.000 -1.5516 -.5250216

------------------------------------------------------------------------------

. F- , lnud1 t- . 64,03 % sst .

. :

R- R-

σ

0.6378 0.6177 -13,9896 -6,89499 0,0302959

0.6403 0.6203 -14,0032 -6,90180 0,03019289

, .

:

. regdw sst lnud1,t(lnud1) force

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 1, 18) = 32.04

Model | .030830369 1 .030830369 Prob > F = 0.0000

Residual | .017320581 18 .000962254 R-squared = 0.6403

-------------+------------------------------ Adj R-squared = 0.6203

Total | .04815095 19 .002534261 Root MSE = .03102

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 11.2229 1.982717 5.66 0.000 7.057366 15.38843

_cons | -1.038311 .2443161 -4.25 0.000 -1.5516 -.5250216

------------------------------------------------------------------------------

Durbin-Watson Statistic = 2.460766

- 2,46 ( ), , ( ). , .

:

. fit sst lnud1

Source | SS df MS Number of obs = 20

-------------+------------------------------ F( 1, 18) = 32.04

Model | .030830369 1 .030830369 Prob > F = 0.0000

Residual | .017320581 18 .000962254 R-squared = 0.6403

-------------+------------------------------ Adj R-squared = 0.6203

Total | .04815095 19 .002534261 Root MSE = .03102

------------------------------------------------------------------------------

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 11.2229 1.982717 5.66 0.000 7.057366 15.38843

_cons | -1.038311 .2443161 -4.25 0.000 -1.5516 -.5250216

------------------------------------------------------------------------------

. rvfplot, c(m)

, . -:

. hettest

Cook-Weisberg test for heteroskedasticity using fitted values of sst

Ho: Constant variance

chi2(1) = 0.01

Prob > chi2 = 0.9328

- , .

-, :

. newey sst lnud1, lag(0) force

Regression with Newey-West standard errors Number of obs = 20

maximum lag : 0 F( 1, 18) = 60.26

Prob > F = 0.0000

------------------------------------------------------------------------------

| Newey-West

sst | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

lnud1 | 11.2229 1.445712 7.76 0.000 8.18557 14.26023

_cons | -1.038311 .1784612 -5.82 0.000 -1.413244 -.6633776

------------------------------------------------------------------------------

.

, : ,

(sst- 1 , ) ;

lnud- , .

1 , . , , . 1.4457, 0.1785.          [ 8.1856 ; 14.2602 ],       [ -1.4132 ; -0.6634 ].

, 30 % . 3476.5 . 30 % 4519.45 . , : lnud = 8.416. , , 0,296 . 1 .


 
2011 , .