Common and idiosyncratic movements in Latin-American exchange rates

Fredy Gamboa-Estrada and José Romero

International Economics, 2022, vol. 171, issue C, 174-190

Abstract: We propose a simple theoretical and empirical approach to differentiate between common and idiosyncratic exchange rate movements in 5 Latin-American economies: Brazil, Chile, Colombia, Mexico, and Peru. Our approach allows us to distinguish the effects of a regional exchange rate common factor and macroeconomic fundamentals differentials on exchange rates. The methodology and estimation strategy are suitable for both low- and high-frequency settings. We provide evidence that the regional common factor is important to assess the dynamics of the Latin-American exchange rates. In our estimations, the relation between exchange rates and the common factor is contemporaneous and stable during the studied period.

Keywords: Exchange rate; Exchange rate in Latin-American countries; Factor model; Forecasting and simulation (search for similar items in EconPapers)
JEL-codes: F31 F37 G17 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S211070172200052X
Full text for ScienceDirect subscribers only

Related works:
Journal Article: Common and idiosyncratic movements in Latin-American exchange rates (2022)
Working Paper: Common and idiosyncratic movements in Latin-American Exchange Rates (2021)
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:eee:inteco:v:171:y:2022:i:c:p:174-190

DOI: 10.1016/j.inteco.2022.06.002

Access Statistics for this article

International Economics is currently edited by Valerie Mignon and Marcelo Olarreaga

More articles in International Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().