macroeconomic forecasting using bayesian vector autoregressive approach
Клики: 281
ID: 257842
2017
Метрики качества и эффективности статьи
Общее качество
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Вовлечённость читателей
Emerging Content
30.0
/100
281 просмотры
65 читатели
Оценка качества ИИ
Не проанализировано
Readership in this journal
EmergingRanked #7 of 27 articles by views in oversight and controls of the us environmental protection agency
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Аннотация
There are many arguments that can be advanced to support the forecasting activities of business entities. The underlying argument in favor of forecasting is that managerial decisions are significantly dependent on proper evaluation of future trends as market conditions are constantly changing and require a detailed analysis of future dynamics. The article discusses the importance of using reasonable macro-econometric tool by suggesting the idea of conditional forecasting through a Vector Autoregressive (VAR) modeling framework. Under this framework, a macroeconomic model for Georgian economy is constructed with the few variables believed to be shaping business environment. Based on the model, forecasts of macroeconomic variables are produced, and three types of scenarios are analyzed - a baseline and two alternative ones. The results of the study provide confirmatory evidence that suggested methodology is adequately addressing the research phenomenon and can be used widely by business entities in responding their strategic and operational planning challenges. Given this set-up, it is shown empirically that Bayesian Vector Autoregressive approach provides reasonable forecasts for the variables of interest.
| Ссылочный ключ |
tutberidze2017vsnik.macroeconomic
Используйте этот ключ для автоцитирования в рукописи при использовании
SciMatic Manuscript Manager или Thesis Manager
|
|---|---|
| Авторы | ;D. Tutberidze;D. Japaridze |
| Журнал | oversight and controls of the us environmental protection agency |
| Год | 2017 |
| DOI |
10.17721/1728-2667.2017/191-2/7
|
| URL | |
| Ключевые слова |
Цитирования
Цитирования не найдены. Чтобы добавить цитирование, свяжитесь с администратором по адресу info@scimatic.org
Комментарии
Комментариев пока нет. Будьте первым, кто прокомментирует эту статью.