QURILISH ISHLAB CHIQARISH HAJMIGA INVESTITSIYALAR TA’SIRINI EKONOMETRIK BAHOLASH

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

171

QURILISH ISHLAB CHIQARISH HAJMIGA INVESTITSIYALAR

TA’SIRINI EKONOMETRIK BAHOLASH

R.A. Xurramov

Termiz davlat universiteti o’qituvchisi

B.E. Turayev

Termiz davlat universiteti katta o’qituvchisi, i.f.f.d.

Annotatsiya.

Mazkur maqolada qurilish ishlab chiqarish hajmiga investitsiyalar

ta’sirining regression tahlili amalga oshirilgan. Avtoregressiya modeli tuzish orqali

qisqa va uzoq muddatli istiqboldagi o’zgarishlar haqida xulosalar qilingan.

Kalit so‘zlar:

model, avtoregressiya, regressiya tenglamasi, Styudent t mezoni,

Fisher, instrumental o`zgaruvchi.

Surxondaryo viloyati qurilish ishlab chiqarish hajmiga investitsiyalarning

ta’sirini baholash maqsadida 2010-2023 yillarga mo’ljallangan ma’lumotlar

www.surxonstat.uz

saytidan olindi (1-jadval).

1-jadval

Surxondaryo viloyati qurilish ishlab chiqarish hamda investitsiyalar hajmi

ko’rsatkichlari

1

Yillar

𝒚

𝒙

Yillar

𝒚

𝒙

2010

335,9

655,3

2017

1 827,0

3 551,0

2011

470,6

802,9

2018

2 879,7

7 240,6

2012

605,3

980,3

2019

3 979,7

11 835,1

2013

849,5

1 371,0

2020

4 774,7

10 068,2

1

Surxondaryo viloyati Statistika boshqarmasi

www.surxonstat.uz

sayti

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

172

2014

1 051,5

1 509,1

2021

5 868,4

12 037,8

2015

1 351,3

1 843,6

2022

6 521,9

11 569,4

2016

1 554,8

2 142,4

2023

7 353,3

17 956,0

Investitsiyalarning qurilish ishlab chiqarish hajmiga qisqa va uzoq muddatli

ta’sirini baholashda avtoregressiya modellari qo’l keladi.

𝐴𝑅(1) + 𝑥

modeli umumiy

ko’rinishi quyidagicha:

𝑦

𝑡

= 𝑎 + 𝑏

0

∙ 𝑥

𝑡

+ 𝑐

1

∙ 𝑦

𝑡−1

+ 𝑒

𝑡

(1)

Ushbu modelni hisoblash uchun dastlab instrumental o‘zgaruvchini baholovchi

model tuzish talab etiladi:

𝑦̂

𝑡−1

= 𝑑

0

+ 𝑑

1

⋅ 𝑥

𝑡−1

(2)

(2) modelni baholash uchun natijaviy hamda omil belgilarning

𝑡 − 1

davr uchun

laglarini aniqlashimiz zarur (2-jadval).

2-jadval

Surxondaryo viloyati qurilish ishlab chiqarish va asosiy kapitalga o‘zlashtirilgan

investitsiyalar hajmi ko’rsatkichlarning

𝒕 − 𝟏

davrdagi qiymatlari

2

Yillar

𝒚

𝒕

𝒙

𝒕

𝒚

𝒕−𝟏

𝒙

𝒕−𝟏

2010

335,9

655,3

-

-

2011

470,6

802,9

335,9

655,3

2012

605,3

980,3

470,6

802,9

2013

849,5

1 371,0

605,3

980,3

2014

1 051,5

1 509,1

849,5

1 371,0

2015

1 351,3

1 843,6

1 051,5

1 509,1

2016

1 554,8

2 142,4

1 351,3

1 843,6

2

Surxondaryo viloyati Statistika boshqarmasi

www.surxonstat.uz

sayti

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

173

2017

1 827,0

3 551,0

1 554,8

2 142,4

2018

2 879,7

7 240,6

1 827,0

3 551,0

2019

3 979,7

11 835,1

2 879,7

7 240,6

2020

4 774,7

10 068,2

3 979,7

11 835,1

2021

5 868,4

12 037,8

4 774,7

10 068,2

2022

6 521,9

11 569,4

5 868,4

12 037,8

2023

7 353,3

17 956,0

6 521,9

11 569,4

Gretl dasturida OLS usulidan foydalanib 2-jadvaldagi lag ko’rsatkichlarining

regression bog‘lanishini baholaymiz (3-jadval).

3-jadval

Regression tahlil natijalari

3

Model 2: OLS, using observations 2011-2023 (T = 13)

Dependent variable: yt1

Coefficient

Std. Error

t-ratio

p-value

xt-1

0.464409

0.0256488

18.11

<0.0001

***

Mean dependent var

2466.947 S.D. dependent var

2138.834

Sum squared resid

4731975 S.E. of regression

627.9580

Uncentered R-squared

0.964690 Centered R-squared

0.913800

F(1, 12)

327.8440 P-value(F)

4.44e-10

Log-likelihood

−101.6781 Akaike criterion

205.3562

Schwarz criterion

205.9211 Hannan-Quinn

205.2400

rho

0.444907 Durbin-Watson

1.079236

3

Mualliflar ishlanmasi

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

174

3-jadvaldan

𝑦̂

𝑡−1

instrumental

o‘zgaruvchini aniqlovchi regressiya

tenglamasining umumiy ko‘rinishi

𝑦̂

𝑡−1

= 0,464409 ⋅ 𝑥

𝑡−1

(3)

kabi bo’ladi.

Ushbu (3) model bo’yicha Fisherning F mezonining hisoblangan qiymati

𝐹

ℎ𝑖𝑠

=

327,844

ga teng. Bu esa

𝑑𝑓

1

= 𝑚 = 1

va

𝑑𝑓

2

= 𝑛 − 1 − 1 = 12

erkinlik darajasida

hamda,

𝛼 = 0,05

ahamiyatlilik darajasidagi Fisherning jadval qiymati

𝐹

𝑗𝑎𝑑

= 4.75

dan

katta. Shuningdek (3) modelning parametrlari bo‘yicha Styudentning t mezoni

qiymatlari

𝑡

𝑑

1

= 18,11

ga teng, bu esa

𝛼 = 0,05

ahamiyatlilik darajasi hamda

𝑑𝑓 =

𝑛 − 𝑚 = 13

erkinlik darajasida Styudentning t mezoni jadval qiymati

𝑡

𝑗𝑎𝑑

= 2,16

dan

katta. Shu sababli model statistik ahamiyatga ega hisoblanadi.

𝑦̂

𝑡−1

instrumental o‘zgaruvchining nazariy qiymatlarini aniqlaymiz. (4-jadval).

4-jadval

Instrumental o’zgaruvchining nazariy qiymatlari

4

Yillar

𝒚

𝒕

𝒙

𝒕

𝒚

𝒕−𝟏

𝒙

𝒕−𝟏

𝒚

̂

𝒕−𝟏

2010

335,9

655,3

-

-

-

2011

470,6

802,9

335,9

655,3

304,3

2012

605,3

980,3

470,6

802,9

372,9

2013

849,5

1 371,0

605,3

980,3

455,3

2014

1 051,5

1 509,1

849,5

1 371,0

636,7

2015

1 351,3

1 843,6

1 051,5

1 509,1

700,9

2016

1 554,8

2 142,4

1 351,3

1 843,6

856,2

2017

1 827,0

3 551,0

1 554,8

2 142,4

995,0

2018

2 879,7

7 240,6

1 827,0

3 551,0

1 649,1

4

Surxondaryo viloyati Statistika boshqarmasi

www.surxonstat.uz

sayti

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

175

2019

3 979,7

11 835,1

2 879,7

7 240,6

3 362,6

2020

4 774,7

10 068,2

3 979,7

11 835,1

5 496,3

2021

5 868,4

12 037,8

4 774,7

10 068,2

4 675,8

2022

6 521,9

11 569,4

5 868,4

12 037,8

5 590,4

2023

7 353,3

17 956,0

6 521,9

11 569,4

5 372,9

4-jadvaldagi

𝑦

𝑡

,

𝑥

𝑡

hamda

𝑦̂

𝑡−1

o‘zgaruvchilar ishtirokida (1) modelni baholash

mumkin. Buning uchun yana Gretl imkoniyatlaridan foydalandik. (5-jadval).

5-jadval

Regression tahlil natijalari

5

Model 2: OLS, using observations 2011-2023 (T = 13)

Dependent variable: y

Coefficient

Std. Error

t-ratio

p-value

const

346.814

187.231

1.852

0.0937

*

x

0.216391

0.0574790

3.765

0.0037

***

yt-1_fitted

0.546096

0.149724

3.647

0.0045

***

Mean dependent var

3006.744 S.D. dependent var

2422.853

Sum squared resid

1933064 S.E. of regression

439.6662

R-squared

0.972558 Adjusted R-squared

0.967070

F(2, 10)

177.2045 P-value(F)

1.56e-08

Log-likelihood

−95.85904 Akaike criterion

197.7181

Schwarz criterion

199.4129 Hannan-Quinn

197.3697

rho

0.399093 Durbin-Watson

1.173993

Test for normality of residual -

Null hypothesis: error is normally distributed

5

Mualliflar ishlanmasi

ISSN (E): 2181-4570 ResearchBib Impact Factor: 6,4 / 2023 SJIF 2024 = 5.073/Volume-2, Issue-7

176

Test statistic: Chi-square(2) = 1.99324

with p-value = 0.369125

3-jadvalga ko’ra avtoregressiya tenglamamiz:

𝑦

𝑡

= 346,814 + 0,216391𝑥

𝑡

+ 0,546096𝑦

𝑡−1

(4)

ko‘rinishga ega bo‘ladi. (4) modeldan ko‘rinib turibdiki qisqa muddatli multiplikator

𝑏

0

= 0,216391

ga, uzoq muddatli multiplikator

𝑏 =

𝑏

𝑜

1−𝑐

=

0,216391

1−0,546096

= 0,476733

ga

teng. Xulosa, shunday qilib

𝑥

𝑡

- asosiy kapitalga o‘zlashtirilgan investitsiyalar

hajmining 1 mlrd so‘mga ortishi

𝑦

𝑡

- qurilish ishlab chiqarish hajmini o‘rtacha 0,216391

mlrd so‘mga oshiradi.

𝑥

𝑡

ning uzoq muddatda 1 mlrd so‘mga oshishi esa,

𝑦

𝑡

ni

0,546096 mlrd so‘mga oshiradi.

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