Forecasting China's industrial output using a spatial Bayesian vector autoregressive model

Donald J. Lacombe and Nyakundi Michieka ()

Growth and Change, 2018, vol. 49, issue 4, 712-742

Abstract: This paper forecasts cement, steel, and TV production in China's top industrial provinces using a Bayesian prior that incorporates both time and spatial dependence as proposed by LeSage and Cashell (2015). Results indicate that growth in cement production will increase following the 3‐year slump experienced between 2013 and 2016 in the five provinces in our sample. Average growth rates for steel production between 2017 and 2018 are similar to those experienced in 1999 and 2008. Our findings indicate that forecast accuracy for TV production demonstrate the superior forecasting characteristics of the hybrid prior.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/grow.12251

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: https://EconPapers.repec.org/RePEc:bla:growch:v:49:y:2018:i:4:p:712-742

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0017-4815

Access Statistics for this article

Growth and Change is currently edited by Dan Rickman and Barney Warf

More articles in Growth and Change from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().