Forecasting Inflation in Mongolia: A Dynamic Model Averaging Approach

Gan-Ochir Doojav () and Davaajargal Luvsannyam

Journal of Time Series Econometrics, 2023, vol. 15, issue 1, 27-48

Abstract: This paper investigates the use of the dynamic model averaging (DMA) approach for identifying good inflation predictors and forecasting inflation in Mongolia, one of the most commodity-dependent economies. The DMA approach allows for both a set of predictors for inflation and marginal effects of predictors to change over time. Our empirical work resulted in several novel findings. First, external variables (i.e., China’s growth, China’s inflation, and change in oil price) play an important role in forecasting inflation and change considerably over time and over forecast horizons. Second, among domestic variables, wage inflation and M2 growth are currently the best predictors for short and longer forecast horizons. Third, the use of DMA leads to substantial improvements in forecast performance, and DMA (2,15) with the chosen forgetting factors is the best performer in predicting inflation for Mongolia.

Keywords: inflation; dynamic model averaging; time-varying parameter; forecasting (search for similar items in EconPapers)
JEL-codes: C11 C22 C53 E31 E37 (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1515/jtse-2020-0021 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
Working Paper: Forecasting inflation in Mongolia: A dynamic model averaging approach (2017)
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: https://EconPapers.repec.org/RePEc:bpj:jtsmet:v:15:y:2023:i:1:p:27-48:n:4

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jtse/html

DOI: 10.1515/jtse-2020-0021

Access Statistics for this article

Journal of Time Series Econometrics is currently edited by Javier Hidalgo

More articles in Journal of Time Series Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().