QISHLOQ, O`RMON VA BALIQCHILIK XO`JALIGI TARMOG’I YALPI QO’SHILGAN QIYMATINING SHAKLLANISHIGA INVESTITSIYALARNING TA’SIRINI BAHOLASH

INVESTITSIYALARNING TA’SIRINI BAHOLASH

N.J. Nurmatov

Termiz davlat universiteti katta o’qituvchisi

nurmatovn@tersu.uz

Annotatsiya. Mazkur maqolada qishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi qo’shilgan qiymatining shakllanishiga investitsiyalarnng ta’siri regression tahlil usuli orqali tadqiq etilgan. 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 ishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi qo’shilgan qiymatiga investitsiyalarning ta’sirini baholash maqsadida 2010-2023 yillarga mo’ljallangan ma’lumotlar www.surxonstat.uz saytidan olindi (1-jadal).

1-jadval

Surxondaryo viloyati qishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi

qo’shilgan qiymati hamda investitsiyalar hajmi ko’rsatkichlari1

Yillar 𝒚 𝒙 Yillar 𝒚 𝒙

2010 1519,7 655,3 2017 7351,3 3 551,0

2011 2819,4 802,9 2018 9169,3 7 240,6

2012 3373,7 980,3 2019 10680,8 11 835,1 1 Surxondaryo viloyati Statistika boshqarmasi www.surxonstat.uz sayti

2013 3580,4 1 371,0 2020 11610,2 10 068,2

2014 4444,8 1 509,1 2021 13811,5 12 037,8

2015 5375,9 1 843,6 2022 15934,1 11 569,4

2016 5831,4 2 142,4 2023 19448,5 17 956,0

Investitsiyalarning qishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi qo’shilgan qiymatiga qisqa va uzoq muddatli ta’sirini baholashda avtoregressiya modellari qo’l keladi. 𝐴𝑅(1) + 𝑥 avtoregressiya modeli umumiy ko’rinishi quyidagicha:

𝑦𝑡 = 𝑎 + 𝑏0 ∙ 𝑥𝑡 + 𝑐1 ∙ 𝑦𝑡−1 + 𝑒𝑡 (1)

Odatda (1) kabi model parametrlarini hisoblashda instrumental o’zgaruvchilar usulidan foydalaniladi. Ma’lumki, instrumental o'zgaruvchilar usuli (Instrumental variables) - bu modelda ishtirok etmaydigan qo'shimcha instrumental o'zgaruvchilardan foydalanishga asoslangan regressiya modellarining parametrlarini baholash usuli hisoblanadi2. Dastlab, instrumental o‘zgaruvchini baholovchi model tuzish talab etiladi.

𝑦̂𝑡−1 = 𝑑0 + 𝑑1 ⋅ 𝑥𝑡−1 (2)

(2) modelni baholash uchun natijaviy hamda omil belgilarning 𝑡 − 1 davr uchun laglarini aniqlashimiz zarur (2-jadval).

2-jadval

Surxondaryo viloyati q qishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi qo’shilgan qiymati va asosiy kapitalga o‘zlashtirilgan investitsiyalar hajmi

ko’rsatkichlarning 𝒕 − 𝟏 davrdagi qiymatlari3

Yillar 𝒚𝒕 𝒙𝒕 𝒚𝒕−𝟏 𝒙𝒕−𝟏

2010 1519,7 655,3 - - 2 https://ru.wikipedia.org/wiki/Метод_инструментальных_переменных 3 Surxondaryo viloyati Statistika boshqarmasi www.surxonstat.uz sayti

2011 2819,4 802,9 1519,7 655,3

2012 3373,7 980,3 2819,4 802,9

2013 3580,4 1 371,0 3373,7 980,3

2014 4444,8 1 509,1 3580,4 1 371,0

2015 5375,9 1 843,6 4444,8 1 509,1

2016 5831,4 2 142,4 5375,9 1 843,6

2017 7351,3 3 551,0 5831,4 2 142,4

2018 9169,3 7 240,6 7351,3 3 551,0

2019 10680,8 11 835,1 9169,3 7 240,6

2020 11610,2 10 068,2 10680,8 11 835,1

2021 13811,5 12 037,8 11610,2 10 068,2

2022 15934,1 11 569,4 13811,5 12 037,8

2023 19448,5 17 956,0 15934,1 11 569,4

Gretl dasturida OLS usulidan foydalanib, 2-jadvaldagi lag ko’rsatkichlarining (2) ko’rinishidagi chiziqli regression bog‘lanish shaklini baholaymiz (3-jadval).

3-jadval

Regression tahlil natijalari4

Model 1: OLS, using observations 2011-2023 (T = 13)

Dependent variable: yt-1 4 Muallif ishlanmasi

const 2737.82 604.913 4.526 0.0009 ***

xt-1 0.913181 0.0890842 10.25 <0.0001 ***

Mean dependent var 7346.346 S.D. dependent var 4538.483

Sum squared resid 23423142 S.E. of regression 1459.238

R-squared 0.905236 Adjusted R-squared 0.896621

F(1, 11) 105.0781 P-value(F) 5.77e-07

Log-likelihood −112.0741 Akaike criterion 228.1481

Schwarz criterion 229.2780 Hannan-Quinn 227.9159

rho 0.343082 Durbin-Watson 1.080189 Test statistic: Chi-square(2) = 2.7532 with p-value = 0.252436

𝑦̂𝑡−1 instrumental o‘zgaruvchini aniqlovchi regressiya tenglamasining umumiy ko‘rinishi

𝑦̂𝑡−1 = 2737,82 + 0,913181 ⋅ 𝑥𝑡−1 (3)

Ushbu (3) model bo’yicha Fisherning F mezonining hisoblangan qiymati 𝐹ℎ𝑖𝑠 = 105,0781 ga teng. Bu esa 𝑑𝑓1 = 𝑚 = 1 va 𝑑𝑓2 = 𝑛 − 𝑚 − 1 = 11 erkinlik darajasida hamda, 𝛼 = 0,05 ahamiyatlilik darajasidagi Fisherning jadval qiymati 𝐹𝑗𝑎𝑑 = 4.84 dan katta. Shuningdek (3) modelning parametrlari bo‘yicha Styudentning t mezoni qiymatlari 𝑡𝑑0 = 10,25 𝑡𝑑1 = 4,526ga teng, bu esa 𝛼 = 0,05 ahamiyatlilik darajasi hamda 𝑑𝑓 = 𝑛 − 𝑚 = 12 erkinlik darajasida Styudentning t mezoni jadval qiymati 𝑡𝑗𝑎𝑑 = 2,179 dan katta. Shu sababli model statistik ahamiyatga ega hisoblanadi.

𝑦̂𝑡−1 instrumental o‘zgaruvchining nazariy qiymatlarini aniqlaymiz. (4-jadval).

4-jadval

Instrumental o’zgaruvchining nazariy qiymatlari5

Yillar 𝒚𝒕 𝒙𝒕 𝒚𝒕−𝟏 𝒙𝒕−𝟏 𝒚̂ 𝒕−𝟏

2010 1519,7 655,3 - - -

2011 2819,4 802,9 1519,7 655,3 3336,229

2012 3373,7 980,3 2819,4 802,9 3471,014

2013 3580,4 1 371,0 3373,7 980,3 3633,012

2014 4444,8 1 509,1 3580,4 1 371,0 3989,785

2015 5375,9 1 843,6 4444,8 1 509,1 4115,943

2016 5831,4 2 142,4 5375,9 1 843,6 4421,372

2017 7351,3 3 551,0 5831,4 2 142,4 4694,23

2018 9169,3 7 240,6 7351,3 3 551,0 5980,526

2019 10680,8 11 835,1 9169,3 7 240,6 9349,797

2020 11610,2 10 068,2 10680,8 11 835,1 13545,41

2021 13811,5 12 037,8 11610,2 10 068,2 11931,91

2022 15934,1 11 569,4 13811,5 12 037,8 13730,51

2023 19448,5 17 956,0 15934,1 11 569,4 13302,77 4-jadvaldagi 𝑦𝑡, 𝑥𝑡 hamda 𝑦̂𝑡−1 o‘zgaruvchilar ishtirokida (1) modelni baholash mumkin. Buning uchun yana Gretl imkoniyatlaridan foydalandik. Biroq tajribalarda model parametrlari statistik ahamiyatga ega bo’lmadi. Shu sababli, o’zgarmas qatnashmagan model turini baholashga qaror qildik (5-jadval). 5 Surxondaryo viloyati Statistika boshqarmasi www.surxonstat.uz sayti

5-jadval

Avtoregressiya modelini baholash natijalari6

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

Dependent variable: y

x 0.476001 0.210408 2.262 0.0449 **

yt1_fitted 0.736086 0.202084 3.642 0.0039 ***

Mean dependent var 8725.485 S.D. dependent var 5283.307

Sum squared resid 30154236 S.E. of regression 1655.685

Uncentered R-squared 0.977237 Centered R-squared 0.909977

F(2, 11) 236.1200 P-value(F) 9.22e-10

Log-likelihood −113.7160 Akaike criterion 231.4319

Schwarz criterion 232.5618 Hannan-Quinn 231.1997

Rho 0.620963 Durbin-Watson 0.792156

Test statistic: Chi-square(2) = 2.99073

with p-value = 0.224167

3-jadvalga ko’ra avtoregressiya tenglamamiz:

𝑦𝑡 = 0,476001𝑥𝑡 + 0,736086𝑦𝑡−1 (4) 6 Muallif ishlanmasi

ko‘rinishga ega bo‘ladi. 5-jadvaldan model parametrlari statistik ahamiyatga egaligi, modelning o’zi esa Fisherning F mezoniga ko’ra iqtisodiy jarayonga mosligini ko’rish mumkin. Xi-kvadrat testi natijalari (𝑝 − 𝑞𝑖𝑦𝑚𝑎𝑡 > 0,05) esa qoldiqlar normal taqsimlanganligini ko’rsatmoqda.

(4) modeldan ko‘rinib turibdiki qisqa muddatli multiplikator 𝑏0 = 0,476001 ga, uzoq muddatli multiplikator 𝑏 = 𝑏𝑜

1−𝑐 = 0,0476001

1−0,736086 = 1,803623 ga teng.

Xulosa qilib aytsak, 𝑥𝑡 - asosiy kapitalga o‘zlashtirilgan investitsiyalar hajmining 1 mlrd so‘mga ortishi 𝑦𝑡- qishloq, o`rmon va baliqchilik xo`jaligi tarmog’i yalpi qo’shilgan qiymatini o‘rtacha 0,476001 mlrd so‘mga oshiradi. 𝑥𝑡 ning 1 mlrd so‘mga oshishi, 𝑦𝑡 ni uzoq muddatda 0,546096 mlrd so‘mga oshishiga sabab bo’ladi.

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