ISTE’MOL NARXLARI INDEKSINI MODELLASHTIRISH VA PROGNOZLASHNI TAKOMILLASHTIRISH YO‘NALISHLARI
DOI:
https://doi.org/10.5281/zenodo.19786941Keywords:
iste’mol narxlari indeksi, modellashtirish, prognozlash, regressiya, vaqt qatorlari, segmentar yondashuv, ssenariyli prognozlash, import narxlari, logistika xarajatlari, tariflarAbstract
Maqolada iste’mol narxlari indeksini modellashtirish va prognozlashni takomillashtirishning ilmiy-uslubiy
yo‘nalishlari tahlil qilingan. Tadqiqotda vaqt qatorlari dekompozitsiyasi, segmentar regressiya, tashqi omillar integratsiyasi
va ssenariyli prognozlash yondashuvlari yagona metodik platformada birlashtirilgan. Taklif etilgan model oziq-ovqat, nooziqovqat
va xizmatlar segmentlari indekslari, import narxlari, logistika xarajatlari hamda tartibga solinadigan tariflar orqali INI
dinamikasini izohlash va variantli prognozlar tuzish imkonini beradi. Natijada umumiy indeksni faqat ekstrapolyatsiya
qilish emas, balki uning ichki tuzilmasi va tashqi uzatish kanallari bilan birgalikda baholash prognozlashning tahliliy va
boshqaruv qiymatini oshirishi asoslangan
References
O‘zbekiston Respublikasi Prezidenti huzuridagi Statistika agentligi. Tovarlar va xizmatlarning iste’mol
narxlari (tariflari) kuzatuvini tashkil etish hamda iste’mol narxlari indeksini hisoblash bo‘yicha uslubiy nizom.
Toshkent, 2024.
International Monetary Fund, ILO, OECD, Eurostat, UNECE, World Bank. Consumer Price Index
Manual: Concepts and Methods. Washington, DC: IMF, 2020.
Kelly P. Uzbekistan Republic. Consumer Price Index Mission Technical Assistance Report (11–15
October 2021). International Monetary Fund, 2021.
Guerreiro V. Uzbekistan Republic. Consumer Price Index Mission Technical Assistance Report (9–13
May 2022). International Monetary Fund, 2022.
ESCAP. Modernizing Consumer Price Index Compilation in Uzbekistan: Leveraging Big Data and
Digital Technologies. Stats Brief. Bangkok: UN ESCAP, 2025.
United Nations Economic Commission for Europe. Generic Statistical Business Process Model
(GSBPM), Version 5.2. Geneva: UNECE, 2025.
United Nations Economic Commission for Europe. Generic Statistical Information Model (GSIM): User
Guide. Geneva: UNECE, 2013.
Fox K. J., Levell P., O’Connell M. Inflation Measurement with High-Frequency Data. Journal of Business
& Economic Statistics, 2026, Vol. 44, No. 1, pp. 383–396.
International Monetary Fund. Consumer Price Index Manual: Theory. Washington, DC: IMF, 2025.
[10] Eurostat. Harmonised Index of Consumer Prices (HICP) Methodological Manual. Luxembourg:
Publications Office of the European Union, 2024.
ESCAP. Alternative data sources for price statistics: Uzbekistan’s experience in modernizing consumer
price statistics. Bangkok: UN ESCAP, 2025.
European Central Bank. Nowcasting consumer price inflation using high-frequency scanner data. ECB
Working Paper No. 2930. Frankfurt am Main: ECB, 2024.
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