Modelling Exchange Rate Fluctuation on Tourism Demand

Abstract

Kenya's tourism industry represents an indispensable growth engine, contributing over 10% of Gross Domestic Product. Exchange rate swings affect affordability and destination price competitiveness, but tourists are sensitive. Academic research on this link in Kenya is limited. This research uses Vector Autoregressive (VAR) modelling of monthly data from 2012-2021 to examine currency rate influences on Kenya's foreign tourist demand. The exchange rate and tourism demand data were obtained from the ministry of tourism and central bank of Kenya respectively. Including currency rate swings, arrivals, and receipts evaluated dynamic sensitivities. The estimated 5-lag VAR model exhibited stability and joint significance after lag order selection per information criterion. Exchange rates improved Granger causality analysis prediction. Currency appreciations reduced tourist demand, according to innovation accounting tools. US Dollar (USD) and Euro movements drove prediction mistakes more than global or regional rivals. USD strength will gradually depreciate the shilling over the next 36 months, although regional tourism will help. Findings formalize exchange rate risks' outsized tourist impact on Kenya, supporting predictive analytics, strategic planning, and policy to protect this crucial economic sector.

Keywords

• vector autoregressive
• kenya's tourism industry
• exchange rate fluctuation
• gross domestic product