Asymmetric oil price transmission to the purchasing power of the U.S. dollar: A multiple threshold NARDL modelling approach
Debdatta Pal and
Subrata Kumar Mitra
Resources Policy, 2019, vol. 64, issue C
This paper studies, whether the responses of the purchasing power of the U.S. dollar asymmetric to crude oil price fluctuations? A multiple threshold nonlinear autoregressive distributed lag model (MTNARDL) is developed to address this question. Working on the monthly data from January 1990 to June 2019, this study shows a short-run asymmetric transmission of oil price fluctuations into the purchasing power of the U.S. dollar. The results of the MTNARDL model apprehend, more minutely, the magnitude of variations in purchasing power in response to minor to major change in the oil price. It finds corroborative evidence for more rapid response of the purchasing power to the upward oil price shocks than to the downward movement in the oil price. This implies that the purchasing power of the U.S. dollar experiences sharp reduction with the rise in the oil price, nonetheless, the advantage of a drop in the oil price is not entirely transmitted to the purchasing power as its correction takes much longer period than expected.
Keywords: Oil price; Purchasing power of the U.S. dollar; Nonlinear impact; Multiple threshold nonlinear ARDL (search for similar items in EconPapers)
JEL-codes: C22 Q43 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:64:y:2019:i:c:s0301420719302314
Access Statistics for this article
Resources Policy is currently edited by R. G. Eggert
More articles in Resources Policy from Elsevier
Bibliographic data for series maintained by Haili He ().