ПРОГНОЗИРОВАНИЕ ЭКОНОМИЧЕСКОГО РОСТА РА С ПОМОЩЬЮ ФАКТОРНОЙ ВЕКТОРНОЙ АВТОРЕГРЕССИОННОЙ МОДЕЛЕИ

Авагян Гаяне; Карапетян Нарек; Мхитарян Лусине

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2 Sb'u Sims C., Macroeconomics and Reality, Econometrica, Vol. 48, No. 1,1980, t2 48:

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5 Sb'u Blanchard O., Quah D., The Dynamic Effects of Aggregate Demand and Supply Disturbances, American Economic Association is collaborating with JSTOR to digitize, preserve and extend access to The American Economic Review. American Economic Association, 1989, Vol. 79(4), tg 655-673, September, https://uh.edu/~bsorense/BlanchardQuah1989.pdf:

6 Sb'u Blanchard O., Perotti R., An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output. Quarterly Journal of Economics, November 2002, 117(4), tg 1329-1368, https://econpapers.repec.org/article/oupqjecon/default8.htm:

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8 Sb'u Koop G., Potter S., Forecasting in Large Macroeconomic Panels using Bayesian Model Averaging, No 04/16, Discussion Papers in Economics from Division of Economics, School of Business, University of Leicester,

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https://www.armstat.am/am/?nid=14, https://www.cba.am/am/SitePages/statmonetaryfinancial.aspx, https://www.investing.com, https://data.worldbank.org/, https://www.imf.org/en/Data:

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1. Pwqfltljiull bl|., Uuil|pnintlinbuwl|wtj L) Luti |xi lu in b u n Llîtl b p Jnr}b[-libp: Piujbujwti i|bl|innpiuj|iti iui|innnbq.pbu|iwtibp (BVAR), N 5(143), «<iujiuuiniuti. ä>|itiiutiutjbp U tl|nljnü|iL|LU», diujfiu, 2012:

7. Ir^yiutl C, Uiul|pninbinbuiul|wb l|Lub|llLULnbunLÜ, bp., «Stiinbuw-

8. Blanchard 0., Perotti R., An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output. Quarterly Journal of Economics, November 2002,117(4), https://econ papers, repec.org/article/ou pqjecon/defau It8. htm.

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https://uh.edu/~bsorense/BlanchardQuah1989.pdf.

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ГАЯНЕ АВАГЯН

Доцент кафедры макроэкономики АГЭУ,

кандидат экономических наук

НАРЕК КАРАПЕТЯН

Аспирант кафедры финансов АГЭУ

ЛУСИНЕ МХИТАРЯН

Кандидат экономических наук

Прогнозирование экономического роста РА с помощью факторной векторной авторегрессионной модели-

Прогнозы экономического роста имеют решающее значение как для лиц, определяющих макроэкономическую политику, так и для различных хозяйствующих субъектов. В статье рассматриваются факторные векторные авторегрессионные модели (РАУАР), представлена разработанная нами модель векторной авторегрессии для прогнозирования экономиичес-кого роста РА. Представлены результаты прогнозов, которые отражают возможную траекторию восстановления экономики Армении после шока СОУЮ-19 в рамках определенных предположений о восстановлении экономики стран-партнеров и международных товарных рынков, а также указаны существующие неопределенности. Проведенный анализ показал, что экономика РА имеет достаточный потенциал для быстрого восстановления, который может быть реализован при отсутствии внешних шоков. Подходы, использованные в исследовании, могут быть полезны специалистам по прогнозированию экономического роста, а результаты могут быть интересны более широкой аудитории.

Ключевые слова временные ряды, структурная модель, временной лаг, факторный анализ, главный компонент.

056, С32

GAYANE AVAGYAN

Associate Professor at the Chair of Macroeconomics at ASUE,

PhD in Economics

NAREK KARAPETYAN

PhD Student at the Chair of Finance at ASUE

LUSINE MKHITARYAN

PhD in Economics

Projection of RA Economic Growth through a Factor-Augmented Vector Autoregressive Model.- Projection of economic growth is crucial both for macroeconomic policy makers and different economic agents. In the paper we discuss factor-augmented vector autoregressive (FAVAR) models and our model for forecasting RA economic growth and the results of the projections. Particularly, they describe possible recovery of RA economy after the COVID-19 shock - under judgments regarding economic partners' growth rates and global commodity markets. We also outline uncertainties around the projections. The conducted analysis revealed that RA economy has strong potential for a fast recovery, which can be materialized in the absence of external shocks. We believe that our approach to growth projections can be applied by experts in this field, and the results can be interesting also for the broader public.

Key words: time series, structural model, time lag, factor analysis, principal component. JEL: Q56, C32

ПРОГНОЗИРОВАНИЕ ЭКОНОМИЧЕСКОГО РОСТА РА С ПОМОЩЬЮ ФАКТОРНОЙ ВЕКТОРНОЙ АВТОРЕГРЕССИОННОЙ МОДЕЛЕИ Текст научной статьи по специальности «Экономика и бизнес»

Аннотация научной статьи по экономике и бизнесу, автор научной работы — Авагян Гаяне, Карапетян Нарек, Мхитарян Лусине

Похожие темы научных работ по экономике и бизнесу , автор научной работы — Авагян Гаяне, Карапетян Нарек, Мхитарян Лусине

PROJECTION OF RA ECONOMIC GROWTH THROUGH A FACTOR-AUGMENTED VECTOR AUTOREGRESSIVE MODEL

Текст научной работы на тему «ПРОГНОЗИРОВАНИЕ ЭКОНОМИЧЕСКОГО РОСТА РА С ПОМОЩЬЮ ФАКТОРНОЙ ВЕКТОРНОЙ АВТОРЕГРЕССИОННОЙ МОДЕЛЕИ»