Remittance Inflows and Exchange Rate in Kenya: An Empirical Investigation

M.T. Musakwa () and N.M. Odhiambo ()
Additional contact information
M.T. Musakwa: University of South Africa
N.M. Odhiambo: University of South Africa

No 2311, Working Papers from African Economic and Social Research Institute (AESRI)

Abstract: This study investigated the impact of remittances on the nominal exchange rate in Kenya, using annual time series data from 1980 to 2020. The study was motivated by the need to find out how remittances affect the exchange rate in Kenya on the back of an increase in remittance inflows in low- and middle-income countries, including Kenya. This is important as Kenya continues to build a stable macroeconomic environment that supports economic growth and other milestones specified in the Sustainable Development Goals. Using the autoregressive distributed lag approach to cointegration, the study found a positive relationship between remittances and the nominal exchange rate in both the short and long run. This implies that an increase in remittance inflows in Kenya leads to a depreciation of the currency. The study, therefore, concludes that remittance inflows in Kenya are not associated with the Dutch-disease phenomenon.

Keywords: Kenya; remittances; exchange rate; autoregressive distributed lag; appreciation; depreciation (search for similar items in EconPapers)
JEL-codes: F24 F33 (search for similar items in EconPapers)
Pages: 30
Date: 2023-12-30
References: Add references at CitEc
Citations:

Downloads: (external link)
https://aesri.org/RePEc/afa/afa-wpaper/AESRI-2311-Final.pdf Revised version, 2026 (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: https://EconPapers.repec.org/RePEc:afa:wpaper:2311

Access Statistics for this paper

More papers in Working Papers from African Economic and Social Research Institute (AESRI)
Bibliographic data for series maintained by Prof Nicholas M Odhiambo ().