Economics at your fingertips  

The Use of Business Expectations in the Short-Term Forecasting of Economic Activity in Ukraine

Roman Lysenko () and Nataliia Kolesnichenko
Additional contact information
Roman Lysenko: National Bank of Ukraine
Nataliia Kolesnichenko: National Bank of Ukraine

No 02/2018, Working Papers from National Bank of Ukraine

Abstract: This paper focuses on the predictive capability of business outlook survey findings in forecasting changes in Ukraine’s real GDP, and in its consumption and investment components. Survey findings have been generalized through the use of principal component analysis. The business outlook index compiled by the National Bank of Ukraine is used as an alternative measure. To forecast GDP and its components, we employ ARDL and VAR models, which factor in the estimated principal components, the business outlook index, and the business outlook survey findings for construction investment over the next 12 months. In estimating the predictive capability of the models, we use pseudo-out-of-sample forecasting. A comparison with actual data shows that annual GDP and consumption growth are best forecast in the current period by applying business outlook survey findings that have been generalized using a principal component analysis, and the first difference of the business outlook index.

Keywords: business expectations; GDP; short-term forecasting (search for similar items in EconPapers)
JEL-codes: E27 E58 E71 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2018-06
New Economics Papers: this item is included in nep-cis, nep-for, nep-mac and nep-tra
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Working Papers from National Bank of Ukraine Contact information at EDIRC.
Bibliographic data for series maintained by Research Unit ().

Page updated 2023-09-24
Handle: RePEc:ukb:wpaper:02/2018