Приложение №1.1
Для анализа экономического роста будем использовать следующие показатели.
Валовой национальный продукт (ВНП). ВНП — рыночная стоимость конечных товаров и услуг, произведенных в стране за год. Один из способов определения ВНП:
ВНП = C + I + G + EI , где
C - личные потребительские расходы, включающие расходы домашних хозяйств. Этот элемент является основным элементом ВНП и значительно превосходит другие его составляющие.
I - валовые инвестиции, включающие производственные капиталовложения или инвестиции в основные производственные фонды. Валовые инвестиции можно представить также как сумму чистых инвестиций (добавление к объему капитала) и инвестиций, идущих на амортизацию капитала.
G - государственные расходы - включают все затраты правительства, федеральных и местных органов власти за минусом трансфертных платежей. Государственные расходы являются расходной частью бюджета. Государственные расходы - денежные платежи правительства за товары и услуги текущего производства. Основная доходная статья государственного бюджета - налоговые поступления.
EI - чистый экспорт товаров и услуг за рубеж, рассчитываемый как разность экспорта и импорта.
Валовой внутренний продукт (ВВП) - измеряет стоимость конечной продукции, произведенной на территории данной страны за определенный период.
Чистый национальный продукт (ЧНП) - можно получить вычитая из ВНП амортизационные отчисления. Если из ЧНП вычесть чистые косвенные налоги на бизнес, получим национальный доход (НД) - показатель, представляющий суммарный доход всех жителей страны.
Располагаемый личный доход получается путем вычитания из НД взносов на социальное страхование, нераспределенной прибыли корпораций, налогов на прибыль корпораций, суммы подоходного налога с граждан. Располагаемый личный доход используется домашним хозяйством на потребление и сбережения.
Индекс потребительских цен (P) - индекс, показывающий динамику изменения цены “рыночной корзины”, т.е. цены рыночного набора потребительских товаров.
Накопленный капитал - созданные человеком ресурсы, используемые для производства товаров и услуг, которые непосредственно не удовлетворяют потребности человека; инвестиционные товары, средства производства.
Ставка на капитал - цена использования капитала. Определяется как процент, уплачиваемый заимодателем владельцу капитала за использование его денежных средств. Как правило, номинальная ставка капитала мало о чем говорит. При принятии инвестиционных решений рассчитывают реальную ставку на капитал:
,
Объем израсходованной рабочей силы - среднегодовая численность работающих (L). Численность работающий определяется в результате взаимодействия спроса на труд с его предложением.
Объем невостребованной рабочей силы - среднегодовая численность безработных (U). Обычно безработными считаются те, кто не имеет работы, но активно ищет ее и готов приступить к работе немедленно. Безработица - превышение предложения труда над спросом на труд. Уровень безработицы - это процент безработной части рабочей силы.
Совокупность занятых и безработных образует рабочую силу.
Важно понятие полной занятости - положение, при котором отсутствует циклическая безработица, т.е. вызванная спадом (фаза экономического цикла, характеризуемая недостаточностью расходов). Уровень безработицы при полной занятости называют естественным уровнем безработицы. Американские экономисты определяют естественный уровень безработицы на уровне 5-6%, в странах Западной Европы его считают на уровне 9%.
Если при наличии безработицы выше естественного уровня мы “теряем” часть ВНП, которая могла бы быть произведена при полной занятости, то при уровне безработицы ниже естественного уровня мы платим за это ростом инфляции.
Кроме того, инфляцию может вызвать повышение заработной платы, не уравновешенное противодействующими факторами, такими как увеличение объема выпускаемой продукции.
Инфляция - это повышение общего уровня цен. С помощью P можно определить уровень инфляции, как темп прироста уровня цен.
Почасовая ставка заработной платы - цена за труд в единицу времени ( час ).
Объем налогов (T) - сумма обязательных выплат, направляемых в бюджет страны хозяйствующими субъектами по ставкам, установленным правительством (налоги на бизнес и на личный доход).
Спрос на деньги (М) - желание экономических субъектов иметь в своем распоряжении определенное количество средств (кассу). Дж. М. Кейнс выделил три мотива, порождающие спрос на деньги: трансакционный мотив (деньги для сделок), мотив предосторожности (запас денег) и спекулятивный мотив (деньги как имущество). Реальную ценность денег, их покупную способность меняет изменение уровня цен.
Бюджетный дефицит является весьма важным макроэкономическим регулятором, определяемый как превышение расходов правительства над доходами.
Приложение №4.1
(1МНК-Y)
1. Multiple Regression Analysis - Yt=a0 e t KtKLtL
-----------------------------------------------------------------------------
Dependent variable: ln_Y
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -16,2063 6,17441 -2,62475 0,0210
t -0,0714664 0,0239617 -2,98253 0,0106
ln_K 3,01159 0,814084 3,69936 0,0027
ln_L -0,279649 0,683289 -0,409268 0,6890
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,207846 3 0,0692821 39,61 0,0000
Residual 0,0227406 13 0,00174928
-----------------------------------------------------------------------------
Total (Corr.) 0,230587 16
R-squared = 90,1379 percent
R-squared (adjusted for d.f.) = 87,8621 percent
Standard Error of Est. = 0,0418244
Mean absolute error = 0,0322493
Durbin-Watson statistic = 0,321689
2. Multiple Regression Analysis - Yt=a0 e t KtK
-----------------------------------------------------------------------------
Dependent variable: ln_Y
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -16,2307 5,98774 -2,71066 0,0169
t -0,071992 0,0232049 -3,10245 0,0078
ln_K 2,86814 0,712586 4,02497 0,0013
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,207553 2 0,103777 63,08 0,0000
Residual 0,0230336 14 0,00164526
-----------------------------------------------------------------------------
Total (Corr.) 0,230587 16
R-squared = 90,0109 percent
R-squared (adjusted for d.f.) = 88,5838 percent
Standard Error of Est. = 0,0405618
Mean absolute error = 0,032514
Durbin-Watson statistic = 0,284239
3. Multiple Regression Analysis - Yt=a0 e t Kt Lt (1-)
-----------------------------------------------------------------------------
Dependent variable: lnY_L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -4,07743 2,79597 -1,45832 0,1668
t -0,0237048 0,00999154 -2,37249 0,0325
lnK_L 1,88495 0,698082 2,70018 0,0173
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,0186655 2 0,00933273 4,24 0,0363
Residual 0,0308053 14 0,00220038
-----------------------------------------------------------------------------
Total (Corr.) 0,0494708 16
R-squared = 37,7303 percent
R-squared (adjusted for d.f.) = 28,8346 percent
Standard Error of Est. = 0,0469082
Mean absolute error = 0,0345754
Durbin-Watson statistic = 0,795447
4. Multiple Regression Analysis - Yt=e t Kt Lt (1-)
Multiple Regression Analysis
-----------------------------------------------------------------------------
Dependent variable: lnY_L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
t -0,00955879 0,00248354 -3,84886 0,0016
lnK_L 0,866956 0,00616049 140,728 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 207,638 2 103,819 43885,91 0,0000
Residual 0,0354849 15 0,00236566
-----------------------------------------------------------------------------
Total 207,674 17
R-squared = 99,9829 percent
R-squared (adjusted for d.f.) = 99,9818 percent
Standard Error of Est. = 0,0486381
Mean absolute error = 0,0360506
Durbin-Watson statistic = 0,610202
Приложение №4.2
(1МНК-С)
1. Multiple Regression Analysis - Сt=СyYt+Сy(1-)Yt-1
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt 0,573288 0,0595849 9,62137 0,0000
Yt_1 0,0712952 0,0613927 1,1613 0,2637
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 7,22107E7 2 3,61053E7 25339,11 0,0000
Residual 21373,3 15 1424,89
-----------------------------------------------------------------------------
Total 7,2232E7 17
R-squared = 99,9704 percent
R-squared (adjusted for d.f.) = 99,9684 percent
Standard Error of Est. = 37,7477
Mean absolute error = 29,5603
Durbin-Watson statistic = 2,06672
2. Multiple Regression Analysis - Сt=С+СyYt
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -92,8185 75,3763 -1,2314 0,2371
Yt 0,671124 0,0234949 28,5647 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1,15082E6 1 1,15082E6 815,94 0,0000
Residual 21156,2 15 1410,41
-----------------------------------------------------------------------------
Total (Corr.) 1,17197E6 16
R-squared = 98,1948 percent
R-squared (adjusted for d.f.) = 98,0745 percent
Standard Error of Est. = 37,5555
Mean absolute error = 29,0461
Durbin-Watson statistic = 2,89739
3. Multiple Regression Analysis - Сt=СyYt
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt 0,642404 0,00288459 222,702 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 7,22088E7 1 7,22088E7 49596,25 0,0000
Residual 23294,9 16 1455,93
-----------------------------------------------------------------------------
Total 7,2232E7 17
R-squared = 99,9677 percent
R-squared (adjusted for d.f.) = 99,9677 percent
Standard Error of Est. = 38,1567
Mean absolute error = 29,5398
Durbin-Watson statistic = 2,47049
4. Multiple Regression Analysis - Сt=Сy(Yt -Tt)+Сy(1-)(Yt-1 -Tt-1)
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt_Tt 0,744643 0,0729549 10,2069 0,0000
Yt_1_Tt_1 0,0949164 0,0752543 1,26128 0,2265
----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 7,22141E7 2 3,6107E7 30126,40 0,0000
Residual 17977,8 15 1198,52
-----------------------------------------------------------------------------
Total 7,2232E7 17
R-squared = 99,9751 percent
R-squared (adjusted for d.f.) = 99,9735 percent
Standard Error of Est. = 34,6196
Mean absolute error = 27,8957
Durbin-Watson statistic = 2,43725
5. Multiple Regression Analysis - Сt- (Yt - Tt) =С +i
-----------------------------------------------------------------------------
Dependent variable: CC
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -414,209 45,0525 -9,19392 0,0000
i 102,888 315,333 0,326283 0,7487
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 370,783 1 370,783 0,11 0,7487
Residual 52242,3 15 3482,82
-----------------------------------------------------------------------------
Total (Corr.) 52613,1 16
R-squared = 0,704735 percent
R-squared (adjusted for d.f.) = 0,0 percent
Standard Error of Est. = 59,0154
Mean absolute error = 42,9857
Durbin-Watson statistic = 1,56757
6. Multiple Regression Analysis - Сt-(Yt - Tt) = i
-----------------------------------------------------------------------------
Dependent variable: CC
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
i -2646,05 249,864 -10,5899 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 2,42966E6 1 2,42966E6 112,15 0,0000
Residual 346639,0 16 21664,9
-----------------------------------------------------------------------------
Total 2,77629E6 17
R-squared = 87,5143 percent
R-squared (adjusted for d.f.) = 87,5143 percent
Standard Error of Est. = 147,19
Mean absolute error = 109,845
Durbin-Watson statistic = 0,840413
7. Multiple Regression Analysis - Сt=С +СyYt+СMMt
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -68,6631 113,863 -0,603032 0,5561
Yt 0,679793 0,0384497 17,6801 0,0000
M -0,0975183 0,335686 -0,290504 0,7757
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1,15095E6 2 575473,0 383,11 0,0000
Residual 21029,5 14 1502,1
-----------------------------------------------------------------------------
Total (Corr.) 1,17197E6 16
R-squared = 98,2056 percent
R-squared (adjusted for d.f.) = 97,9493 percent
Standard Error of Est. = 38,757
Mean absolute error = 28,8135
Durbin-Watson statistic = 2,89871
8. Multiple Regression Analysis Сt=СyYt+СMMt
-----------------------------------------------------------------------------
Dependent variable: C
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt 0,683018 0,0372594 18,3314 0,0000
M -0,245345 0,224413 -1,09327 0,2915
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 7,22105E7 2 3,61052E7 25101,33 0,0000
Residual 21575,7 15 1438,38
-----------------------------------------------------------------------------
Total 7,2232E7 17
R-squared = 99,9701 percent
R-squared (adjusted for d.f.) = 99,9681 percent
Standard Error of Est. = 37,926
Mean absolute error = 30,3443
Durbin-Watson statistic = 2,75617
Приложение №4.3
(1МНК-I)
1. Multiple Regression Analysis - It= a0+a1 (Yt -Yt-1)+a2 (Kt -Kt-1)+a3 Tt+a4 it
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -149,323 83,3602 -1,7913 0,0985
Yt_Yt_1 0,0551541 0,169301 0,325775 0,7502
Kt_Kt_1 0,7052 0,32836 2,14765 0,0529
Tt 0,688613 0,0903311 7,62321 0,0000
i 187,971 149,428 1,25794 0,2323
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 181089,0 4 45272,2 65,09 0,0000
Residual 8345,79 12 695,483
-----------------------------------------------------------------------------
Total (Corr.) 189435,0 16
R-squared = 95,5944 percent
R-squared (adjusted for d.f.) = 94,1258 percent
Standard Error of Est. = 26,372
Mean absolute error = 17,41
Durbin-Watson statistic = 0,578202
2. Multiple Regression Analysis - It= a1 (Yt -Yt-1)+a2 (Kt -Kt-1)+a3 Tt+a4 it
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt_Yt_1 0,224584 0,151877 1,47873 0,1630
Kt_Kt_1 0,410243 0,307278 1,33509 0,2048
Tt 0,566731 0,0642642 8,81877 0,0000
i 89,6308 150,321 0,596261 0,5612
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 5,03826E6 4 1,25957E6 1548,05 0,0000
Residual 10577,4 13 813,649
-----------------------------------------------------------------------------
Total 5,04884E6 17
R-squared = 99,7905 percent
R-squared (adjusted for d.f.) = 99,7422 percent
Standard Error of Est. = 28,5245
Mean absolute error = 20,4332
Durbin-Watson statistic = 0,37852
3. Multiple Regression Analysis - It= a1 (Yt -Yt-1)+a2 (Kt -Kt-1)+a3 Tt
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt_Yt_1 0,185507 0,133818 1,38626 0,1874
Kt_Kt_1 0,474897 0,280814 1,69114 0,1129
Tt 0,569895 0,0625531 9,11058 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 5,03797E6 3 1,67932E6 2163,54 0,0000
Residual 10866,7 14 776,193
-----------------------------------------------------------------------------
Total 5,04884E6 17
R-squared = 99,7848 percent
R-squared (adjusted for d.f.) = 99,754 percent
Standard Error of Est. = 27,8602
Mean absolute error = 21,1396
Durbin-Watson statistic = 0,364144
4. Multiple Regression Analysis - It= a1 (Yt -Yt-1)+a2 (Kt -Kt-1)+a3 it
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt_Yt_1 -0,804533 0,24751 -3,25051 0,0058
Kt_Kt_1 2,8197 0,358031 7,87558 0,0000
i 199,121 381,455 0,522004 0,6098
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 4,97499E6 3 1,65833E6 314,35 0,0000
Residual 73855,4 14 5275,39
-----------------------------------------------------------------------------
Total 5,04884E6 17
R-squared = 98,5372 percent
R-squared (adjusted for d.f.) = 98,3282 percent
Standard Error of Est. = 72,6319
Mean absolute error = 55,4407
Durbin-Watson statistic = 1,45553
5. Multiple Regression Analysis - It= a1 (Yt -Yt-1)+a2 (Kt -Kt-1)
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Yt_Yt_1 -0,904797 0,152269 -5,9421 0,0000
Kt_Kt_1 2,99442 0,123996 24,1494 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 4,97355E6 2 2,48677E6 495,42 0,0000
Residual 75292,9 15 5019,53
-----------------------------------------------------------------------------
Total 5,04884E6 17
R-squared = 98,5087 percent
R-squared (adjusted for d.f.) = 98,4093 percent
Standard Error of Est. = 70,8486
Mean absolute error = 57,1473
Durbin-Watson statistic = 1,50741
6. Multiple Regression Analysis - It= a1 (Kt -Kt-1)+a2 it
-----------------------------------------------------------------------------
Dependent variable: II
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Kt_Kt_1 1,77351 0,200707 8,83636 0,0000
i 1161,35 307,877 3,7721 0,0018
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 4,91925E6 2 2,45962E6 284,69 0,0000
Residual 129594,0 15 8639,61
-----------------------------------------------------------------------------
Total 5,04884E6 17
R-squared = 97,4332 percent
R-squared (adjusted for d.f.) = 97,2621 percent
Standard Error of Est. = 92,9495
Mean absolute error = 63,2867
Durbin-Watson statistic = 1,85121
Приложение №4.4
(1МНК-G)
1. Regression Analysis - Linear model: Y = a + b*X
-----------------------------------------------------------------------------
Dependent variable: G
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 476,32 10,8532 43,8875 0,0000
Slope 17,2076 1,05916 16,2464 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 120809,0 1 120809,0 263,95 0,0000
Residual 6865,57 15 457,705
-----------------------------------------------------------------------------
Total (Corr.) 127675,0 16
Correlation Coefficient = 0,972742
R-squared = 94,6226 percent
Standard Error of Est. = 21,394
2. Regression Analysis - Exponential model: Y = exp(a + b*X)
-----------------------------------------------------------------------------
Dependent variable: G
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 6,19231 0,0159379 388,528 0,0000
Slope 0,0273219 0,00155538 17,5661 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,304567 1 0,304567 308,57 0,0000
Residual 0,0148055 15 0,000987031
-----------------------------------------------------------------------------
Total (Corr.) 0,319372 16
Correlation Coefficient = 0,976546
R-squared = 95,3642 percent
Standard Error of Est. = 0,031417
3. Regression Analysis - Square root-Y model: Y = (a + b*X)^2
-----------------------------------------------------------------------------
Dependent variable: G
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 21,9831 0,206202 106,609 0,0000
Slope 0,342378 0,0201233 17,014 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 47,8269 1 47,8269 289,48 0,0000
Residual 2,47827 15 0,165218
-----------------------------------------------------------------------------
Total (Corr.) 50,3052 16
Correlation Coefficient = 0,975057
R-squared = 95,0735 percent
Standard Error of Est. = 0,40647
Приложение №4.5
(1МНК-N)
Multiple Regression Analysis
-----------------------------------------------------------------------------
Dependent variable: lnN
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 4,46819 0,00886442 504,058 0,0000
t 0,0191892 0,000865079 22,1821 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,150237 1 0,150237 492,04 0,0000
Residual 0,00457998 15 0,000305332
-----------------------------------------------------------------------------
Total (Corr.) 0,154817 16
R-squared = 97,0417 percent
R-squared (adjusted for d.f.) = 96,8445 percent
Standard Error of Est. = 0,0174737
Mean absolute error = 0,0140917
Durbin-Watson statistic = 2,1418
Приложение №4.6
(1МНК-L)
1. Multiple Regression Analysis - Lt=a0+a1Wrt+a2Nt
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -33,5365 9,11292 -3,6801 0,0025
Wt 2,42986 0,601397 4,04036 0,0012
Nt 0,974601 0,0214643 45,4057 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1321,75 2 660,876 4566,74 0,0000
Residual 2,02601 14 0,144715
-----------------------------------------------------------------------------
Total (Corr.) 1323,78 16
R-squared = 99,847 percent
R-squared (adjusted for d.f.) = 99,8251 percent
Standard Error of Est. = 0,380414
Mean absolute error = 0,300556
Durbin-Watson statistic = 2,06753
2. Multiple Regression Analysis - Lt=a0+a1Wrt+a2Nt-1
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 41,6865 57,8446 0,720664 0,4830
Wt -2,14424 3,85692 -0,555945 0,5870
Nt_1 0,781756 0,134746 5,80169 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1235,54 2 617,77 98,02 0,0000
Residual 88,2373 14 6,30266
-----------------------------------------------------------------------------
Total (Corr.) 1323,78 16
R-squared = 93,3344 percent
R-squared (adjusted for d.f.) = 92,3822 percent
Standard Error of Est. = 2,51051
Mean absolute error = 2,09756
Durbin-Watson statistic = 3,09366
3. Multiple Regression Analysis - Lt=a0+a1Wrt-1+a2Nt-1
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 100,502 55,2369 1,81948 0,0903
Wt_1 -5,86132 3,54671 -1,65261 0,1207
Nt_1 0,636641 0,140015 4,54694 0,0005
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1248,31 2 624,157 115,79 0,0000
Residual 75,4638 14 5,39027
-----------------------------------------------------------------------------
Total (Corr.) 1323,78 16
R-squared = 94,2994 percent
R-squared (adjusted for d.f.) = 93,485 percent
Standard Error of Est. = 2,3217
Mean absolute error = 1,83958
Durbin-Watson statistic = 3,10535
4. Multiple Regression Analysis - Lt=a0+a1Wrt-1
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 339,808 25,4958 13,328 0,0000
Wt_1 -20,6371 2,16052 -9,5519 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1136,87 1 1136,87 91,24 0,0000
Residual 186,906 15 12,4604
-----------------------------------------------------------------------------
Total (Corr.) 1323,78 16
R-squared = 85,8809 percent
R-squared (adjusted for d.f.) = 84,9396 percent
Standard Error of Est. = 3,52993
Mean absolute error = 2,63155
Durbin-Watson statistic = 1,65549
5. Multiple Regression Analysis - Lt=a1Wrt
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Wt 8,19665 0,24381 33,619 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 157118,0 1 157118,0 1130,24 0,0000
Residual 2224,22 16 139,014
-----------------------------------------------------------------------------
Total 159343,0 17
R-squared = 98,6041 percent
R-squared (adjusted for d.f.) = 98,6041 percent
Standard Error of Est. = 11,7904
Mean absolute error = 9,75095
Durbin-Watson statistic = 0,087904
6. Multiple Regression Analysis - Lt=a2Nt-1
-----------------------------------------------------------------------------
Dependent variable: L
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Nt_1 0,942835 0,00606785 155,382 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 159237,0 1 159237,0 24143,54 0,0000
Residual 105,527 16 6,59543
-----------------------------------------------------------------------------
Total 159343,0 17
R-squared = 99,9338 percent
R-squared (adjusted for d.f.) = 99,9338 percent
Standard Error of Est. = 2,56816
Mean absolute error = 2,16163
Durbin-Watson statistic = 3,01167
Приложение №4.7
(1МНК-R)
1. Regression Analysis - Square root-X model: Y = a + b*sqrt(X)
-----------------------------------------------------------------------------
Dependent variable: R
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 0,241375 0,00164848 146,423 0,0000
Slope -0,00307213 0,000549495 -5,59083 0,0001
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,000133125 1 0,000133125 31,26 0,0001
Residual 0,0000638848 150,00000425898
-----------------------------------------------------------------------------
Total (Corr.) 0,000197009 16
Correlation Coefficient = -0,822026
R-squared = 67,5727 percent
Standard Error of Est. = 0,00206373
2. Regression Analysis - Exponential model: Y = exp(a + b*X)
-----------------------------------------------------------------------------
Dependent variable: R
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept -1,43683 0,00463488 -310,002 0,0000
Slope -0,00241579 0,000452318 -5,34091 0,0001
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,00238111 1 0,00238111 28,53 0,0001
Residual 0,0012521 15 0,0000834735
-----------------------------------------------------------------------------
Total (Corr.) 0,00363321 16
Correlation Coefficient = -0,809551
R-squared = 65,5373 percent
Standard Error of Est. = 0,00913638
3. Regression Analysis - Reciprocal-Y model: Y = 1/(a + b*X)
-----------------------------------------------------------------------------
Dependent variable: R
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 4,20686 0,0199071 211,325 0,0000
Slope 0,0103768 0,00194273 5,34131 0,0001
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,0439322 1 0,0439322 28,53 0,0001
Residual 0,0230982 15 0,00153988
-----------------------------------------------------------------------------
Total (Corr.) 0,0670304 16
Correlation Coefficient = 0,809572
R-squared = 65,5407 percent
Standard Error of Est. = 0,0392413
Приложение №4.8
(1МНК-Wn)
1. Multiple Regression Analysis - Wnt =a0+a1 Ut +a2 Pt
-----------------------------------------------------------------------------
Dependent variable: Wn
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 1,21735 0,217113 5,60697 0,0001
Ut -0,108331 0,0465807 -2,32566 0,0356
Pt 11,1307 0,240317 46,3169 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 93,3994 2 46,6997 4078,84 0,0000
Residual 0,16029 14 0,0114493
-----------------------------------------------------------------------------
Total (Corr.) 93,5597 16
R-squared = 99,8287 percent
R-squared (adjusted for d.f.) = 99,8042 percent
Standard Error of Est. = 0,107001
Mean absolute error = 0,0809055
Durbin-Watson statistic = 1,18031
2. Multiple Regression Analysis - Wnt =a0+a1 Ut /Nt +a2 Pt
-----------------------------------------------------------------------------
Dependent variable: Wn
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 1,64206 0,334579 4,90784 0,0002
Ut_Nt -13,8443 5,0766 -2,72709 0,0164
Pt 10,8246 0,130311 83,0675 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 93,4146 2 46,7073 4505,84 0,0000
Residual 0,145123 14 0,0103659
-----------------------------------------------------------------------------
Total (Corr.) 93,5597 16
R-squared = 99,8449 percent
R-squared (adjusted for d.f.) = 99,8227 percent
Standard Error of Est. = 0,101813
Mean absolute error = 0,0741444
Durbin-Watson statistic = 1,19401
3. Multiple Regression Analysis - Wn=a0+a1 (Ut-Ut-1)+a2 (Pt-Pt-1)
-----------------------------------------------------------------------------
Dependent variable: Wn
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 3,86202 1,38895 2,78053 0,0147
Ut_Ut_1 -1,65868 0,646422 -2,56594 0,0224
Pt_Pt_1 124,84 30,6956 4,06704 0,0012
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 52,3985 2 26,1992 8,91 0,0032
Residual 41,1612 14 2,94009
-----------------------------------------------------------------------------
Total (Corr.) 93,5597 16
R-squared = 56,0054 percent
R-squared (adjusted for d.f.) = 49,7205 percent
Standard Error of Est. = 1,71467
Mean absolute error = 1,26138
Durbin-Watson statistic = 1,48298
4. Multiple Regression Analysis - Wnt =a0+a1 (Ut - Ut-1)+a2 Pt
-----------------------------------------------------------------------------
Dependent variable: Wn
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 0,815714 0,103023 7,9178 0,0000
Ut_Ut_1 -0,0780526 0,0396414 -1,96897 0,0691
Pt 10,5998 0,124836 84,9098 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 93,3857 2 46,6928 3756,36 0,0000
Residual 0,174025 14 0,0124303
-----------------------------------------------------------------------------
Total (Corr.) 93,5597 16
R-squared = 99,814 percent
R-squared (adjusted for d.f.) = 99,7874 percent
Standard Error of Est. = 0,111491
Mean absolute error = 0,0805466
Durbin-Watson statistic = 1,33874
5. Multiple Regression Analysis - Wnt =a0+a1 Ut /Nt +a2 (Pt-Pt-1)
-----------------------------------------------------------------------------
Dependent variable: Wn
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -2,51005 6,48465 -0,387075 0,7045
Ut_Nt 111,292 95,815 1,16153 0,2648
Pt_Pt_1 75,8038 37,086 2,044 0,0602
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 38,3602 2 19,1801 4,86 0,0249
Residual 55,1995 14 3,94282
-----------------------------------------------------------------------------
Total (Corr.) 93,5597 16
R-squared = 41,0008 percent
R-squared (adjusted for d.f.) = 32,5724 percent
Standard Error of Est. = 1,98565
Mean absolute error = 1,46259
Durbin-Watson statistic = 0,8625
Приложение №4.9
(1МНК-M)
1. Multiple Regression Analysis - Mt = a0+a1 Yt+a2 it
-----------------------------------------------------------------------------
Dependent variable: M
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 384,542 34,0411 11,2964 0,0000
Y 0,0702233 0,00920457 7,62918 0,0000
i -571,163 78,6154 -7,26528 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 30726,8 2 15363,4 76,97 0,0000
Residual 2794,39 14 199,599
-----------------------------------------------------------------------------
Total (Corr.) 33521,2 16
R-squared = 91,6638 percent
R-squared (adjusted for d.f.) = 90,4729 percent
Standard Error of Est. = 14,128
Mean absolute error = 10,4235
Durbin-Watson statistic = 1,47565
2. Multiple Regression Analysis - Mt = a1Yt+a2 it
-----------------------------------------------------------------------------
Dependent variable: M
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Y 0,168845 0,00896047 18,8433 0,0000
i -79,7961 201,207 -0,396587 0,6973
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 4,79509E6 2 2,39754E6 1272,36 0,0000
Residual 28264,9 15 1884,33
-----------------------------------------------------------------------------
Total 4,82335E6 17
R-squared = 99,414 percent
R-squared (adjusted for d.f.) = 99,3749 percent
Standard Error of Est. = 43,4088
Mean absolute error = 31,4938
Durbin-Watson statistic = 0,276094
3. Multiple Regression Analysis - Mt = a0+a1 Yt
-----------------------------------------------------------------------------
Dependent variable: M
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 247,701 59,8318 4,13996 0,0009
Y 0,0888954 0,0186496 4,76661 0,0002
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 20191,1 1 20191,1 22,72 0,0002
Residual 13330,1 15 888,673
-----------------------------------------------------------------------------
Total (Corr.) 33521,2 16
R-squared = 60,2339 percent
R-squared (adjusted for d.f.) = 57,5828 percent
Standard Error of Est. = 29,8106
Mean absolute error = 22,2551
Durbin-Watson statistic = 0,704245
4. Multiple Regression Analysis - Mt =a1 Yt
-----------------------------------------------------------------------------
Dependent variable: M
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Y 0,165538 0,00319405 51,827 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 4,79479E6 1 4,79479E6 2686,04 0,0000
Residual 28561,3 16 1785,08
-----------------------------------------------------------------------------
Total 4,82335E6 17
R-squared = 99,4079 percent
R-squared (adjusted for d.f.) = 99,4079 percent
Standard Error of Est. = 42,2502
Mean absolute error = 31,2043
Durbin-Watson statistic = 0,354632
Приложение №4.10
(1МНК-P)
1. Multiple Regression Analysis - Pt = a1 Mt+a2 Yt
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Mt -0,00260591 0,000586055 -4,44653 0,0005
Yt 0,000680294 0,000097303 6,9915 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 11,0352 2 5,51758 562,46 0,0000
Residual 0,147145 15 0,00980966
-----------------------------------------------------------------------------
Total 11,1823 17
R-squared = 98,6841 percent
R-squared (adjusted for d.f.) = 98,5964 percent
Standard Error of Est. = 0,0990437
Mean absolute error = 0,0758373
Durbin-Watson statistic = 0,770752
2. Multiple Regression Analysis - Pt = a1 Mt-1+a2 Yt-1
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Mt_1 -0,0026135 0,000577455 -4,52589 0,0004
Yt_1 0,000694405 0,0000971771 7,14577 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 11,0243 2 5,51216 523,41 0,0000
Residual 0,15797 15 0,0105313
-----------------------------------------------------------------------------
Total 11,1823 17
R-squared = 98,5873 percent
R-squared (adjusted for d.f.) = 98,4931 percent
Standard Error of Est. = 0,102622
Mean absolute error = 0,076842
Durbin-Watson statistic = 0,803733
3. Multiple Regression Analysis - Pt = a1 Mt+a2 Yt +a3 Wnt
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Mt 0,0000384578 0,000107581 0,357477 0,7261
Yt -0,0000443431 0,0000252497 -1,75619 0,1009
Wnt 0,0993907 0,0030769 32,3022 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 11,1804 3 3,72678 26781,96 0,0000
Residual 0,00194814 14 0,000139153
-----------------------------------------------------------------------------
Total 11,1823 17
R-squared = 99,9826 percent
R-squared (adjusted for d.f.) = 99,9801 percent
Standard Error of Est. = 0,0117963
Mean absolute error = 0,00813089
Durbin-Watson statistic = 1,31544
4. Multiple Regression Analysis - Pt=a1(Mt -Mt-1)+a2(Yt-Yt-1)+a3 Wnt
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Mt_Mt_1 0,000082504 0,000224773 0,367056 0,7191
Yt_Yt_1 -8,1372E-7 0,000046574 -0,0174716 0,9863
Wnt 0,0864427 0,000695281 124,328 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 11,1753 3 3,72509 7411,47 0,0000
Residual 0,00703655 14 0,000502611
-----------------------------------------------------------------------------
Total 11,1823 17
R-squared = 99,9371 percent
R-squared (adjusted for d.f.) = 99,9281 percent
Standard Error of Est. = 0,022419
Mean absolute error = 0,0172554
Durbin-Watson statistic = 0,489844
5. Multiple Regression Analysis - Pt = a0 +a1Wnt
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT -0,0697562 0,0110653 -6,30406 0,0000
Wnt 0,0937292 0,00118083 79,3756 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,821937 1 0,821937 6300,49 0,0000
Residual 0,00195684 15 0,000130456
-----------------------------------------------------------------------------
Total (Corr.) 0,823894 16
R-squared = 99,7625 percent
R-squared (adjusted for d.f.) = 99,7467 percent
Standard Error of Est. = 0,0114217
Mean absolute error = 0,00789649
Durbin-Watson statistic = 1,44532
6. Multiple Regression Analysis - Pt = a1 Pt-1
-----------------------------------------------------------------------------
Dependent variable: Pt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Pt_1 1,05912 0,00416556 254,256 0,0000
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 11,1795 1 11,1795 64646,13 0,0000
Residual 0,00276695 16 0,000172934
-----------------------------------------------------------------------------
Total 11,1823 17
R-squared = 99,9753 percent
R-squared (adjusted for d.f.) = 99,9753 percent
Standard Error of Est. = 0,0131504
Mean absolute error = 0,0103848
Durbin-Watson statistic = 1,84639
Приложение №4.11
(1МНК-i)
Regression Analysis - Logarithmic-X model: Y = a + b*ln(X)
-----------------------------------------------------------------------------
Dependent variable: it
Independent variable: t
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Intercept 0,242931 0,015516 15,6568 0,0000
Slope -0,0797248 0,0104846 -7,60402 0,0003
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0,0220132 1 0,0220132 57,82 0,0003
Residual 0,00228428 6 0,000380713
-----------------------------------------------------------------------------
Total (Corr.) 0,0242975 7
Correlation Coefficient = -0,951834
R-squared = 90,5987 percent
Standard Error of Est. = 0,0195119
Приложение №4.13
(2МНК: 1-й шаг)
1. Multiple Regression Analysis
-----------------------------------------------------------------------------
Dependent variable: Yt
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
Nt 41,2087 10,4132 3,95735 0,0016
Kt_1 -1,40689 0,400787 -3,51032 0,0038
Yt_1 1,34085 0,243461 5,50744 0,0001
Pt_1 4030,65 1083,48 3,72011 0,0026
-----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1,7481E8 4 4,37025E7 3472,38 0,0000
Residual 163615,0 13 12585,7
-----------------------------------------------------------------------------
Total 1,74974E8 17
R-squared = 99,9065 percent
R-squared (adjusted for d.f.) = 99,8849 percent
Standard Error of Est. = 112,186
Mean absolute error = 86,6032
Durbin-Watson statistic = 2,36103
2. Multiple Regression Analysis
-----------------------------------------------------------------------------
Dependent variable: Ct
-----------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
-----------------------------------------------------------------------------
CONSTANT 8618,98 2769,64 3,11195 0,0125
t 425,382 145,573 2,92213 0,0170
Gt 1,41903 0,592216 2,39614 0,0402
Tt_1 -6,48003 2,17164 -2,98394 0,0154
Kt_1 -4,06731 0,993805 -4,09266 0,0027
Yt_1 3,88555 0,763043 5,09218 0,0007
Nt_1 21,0253 8,14253 2,58216 0,0296
Pt_1 4038,54 577,282 6,9958 0,0001
----------------------------------------------------------------------------
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 1,15433E6 7 164904,0 84,11 0,0000
Residual 17644,7 9 1960,52
-----------------------------------------------------------------------------
Total (Corr.) 1,17197E6 16
R-squared = 98,4944 percent
R-squared (adjusted for d.f.) = 97,3235 percent
Standard Error of Est. = 44,2778
Mean absolute error = 28,4383
Durbin-Watson statistic = 2,72959