2023年計(jì)量經(jīng)濟(jì)學(xué)報(bào)告

計(jì)量經(jīng)濟(jì)學(xué)報(bào)告固定資產(chǎn)投資的計(jì)量經(jīng)濟(jì)學(xué)模型

一、解釋模型

固定資產(chǎn)對(duì)一個(gè)企業(yè)來(lái)說(shuō)是其主要的勞動(dòng)手段，它的價(jià)值是逐漸地轉(zhuǎn)移到所生產(chǎn)的產(chǎn)品上去.企業(yè)同時(shí)又是重要的市場(chǎng)主體，因此對(duì)固定資產(chǎn)的投資間接得影響到了一個(gè)經(jīng)濟(jì)體的產(chǎn)出.這里主要對(duì)gdp及國(guó)有經(jīng)濟(jì)固定資產(chǎn)投資額（x1），集體經(jīng)濟(jì)固定資產(chǎn)投資額（x2），個(gè)體經(jīng)濟(jì)固定資產(chǎn)投資額（x3），進(jìn)行計(jì)量經(jīng)濟(jì)學(xué)多元線性回歸模型分析.

原始數(shù)據(jù)如下：?jiǎn)挝唬▋|元）

obsgdpx1x2

19804517.8745.946

19814860.3667.5115.2

19825301.8845.3174.3

19835957.4952156.3

19847206.71185.2238.7

19858989.11680.5327.5

198610201.42079.4391.8

198711954.42448.8547

198814922.33020711.7

198916917.82808.2570

199018598.42986.3529.5

199121662.53713.8697.8

199226651.95498.71359.4

199334560.57925.92317.3

199557494.910898.23289.4

199666850.512006.23651.5

199773142.713091.73850.9

199876967.215369.34192.

2由以上數(shù)據(jù)得到如下ls估計(jì)結(jié)果，

dependentvariable：gdp

method：leastsquares

date：12/30/07time：10：52

sample：19801998

includedobservations：19variablecoefficientstd.errort-statisticprob.

c632.0385787.85220.8022300.4349

x10.4084461.0983520.3718720.7152

x26.9935122.9834202.3441260.0333

x311.194781.8313866.1127360.0000r-squared0.996478meandependentvar27022.51x3119178.3210.8321.8409535.2649.4759.91022.11032.21001.21182.912221476.21970.62560.23211.23429.43744.4

adjustedr-squareds.e.ofregressionsumsquaredresidloglikelihooddurbin-watsonstat

0.995774s.d.dependentvar1612.032akaikeinfocriterion38979701schwarzcriterion-165.0339f-statistic1.219467prob（f-statistic）

24797.6217.7930417.991871414.7900.000000

顯然x1的t檢驗(yàn)為非顯著性檢驗(yàn)，故將x1與x2合并為一個(gè)解釋變量。也就是將國(guó)有經(jīng)濟(jì)與集體經(jīng)濟(jì)固定資產(chǎn)投資額的和看作為公有經(jīng)濟(jì)固定資產(chǎn)投資額（x1+x2）.令x1+x2=x1'得到如下檢驗(yàn)結(jié)果：

dependentvariable：gdpmethod：leastsquaresdate：12/30/07time：10：53sample：19801998includedobservations：19

variablecx1+x2x3

r-squaredadjustedr-squareds.e.ofregressionsumsquaredresidloglikelihooddurbin-watsonstat

coefficient-200.07932.13308910.14031

std.error633.13990.3291901.802497

t-statistic-0.3160116.4798085.625704

prob.0.75610.00000.000027022.5124797.6217.8523718.001491918.9160.000000

0.995848meandependentvar0.995329s.d.dependentvar1694.728akaikeinfocriterion45953627schwarzcriterion-166.5975f-statistic1.138010prob（f-statistic）

，從而得到多元線性回歸方程：gdp=-200.0793+2.133089﹡x1'+10.14031﹡x3

二、模型檢驗(yàn)1.統(tǒng)計(jì)學(xué)檢驗(yàn)

t－statistic檢驗(yàn)，顯著水平0.05，其臨界值為tα/2=2.11，顯然6.472744及5.625704遠(yuǎn)遠(yuǎn)大于它，其解釋變量的prob均為0.0000，即從統(tǒng)計(jì)學(xué)檢驗(yàn)的角度上講解釋變量的選取是有意義的.

f－statistic檢驗(yàn)及擬合優(yōu)度r-squared檢驗(yàn)，r-squared值越接近于1，則f值越大，這里的r-squared值為0.995329，大于0.9擬合優(yōu)度比較高，因此f—statistic檢驗(yàn)亦通過(guò).2.計(jì)量經(jīng)濟(jì)學(xué)檢驗(yàn)

a.異方差性檢驗(yàn)：

whiteheteroskedasticitytest：f-statisticobs*r-squared

testequation：

dependentvariable：resid^2method：leastsquaresdate：12/30/07time：10：55sample：19801998includedobservations：19

variablecx1+x2（x1+x2）^2（x1+x2）*x3

x3x3^2

r-squaredadjustedr-squareds.e.ofregressionsumsquaredresidloglikelihooddurbin-watsonstat

coefficient2475097.-505.63910.444067-4.429261-289.824412.02527

std.error1758485.1727.6610.5569105.8494908934.68616.41130

0.553341probability3.334076probability

t-statistic1.407517-0.2926730.797376-0.757205-0.0324380.732744

0.7336340.648629

prob.0.18270.77440.43960.46240.97460.47672418612.2725196.32.8585433.156780.5533410.73363

40.175478meandependentvar-0.141646s.d.