Abstract
This study explores the asymmetric effect of exchange rate volatility on tourism demand in India from January 2006 to April 2018. Tourism demand is captured from a twin perspective—quantity and value. While quantity is represented by foreign tourist arrival in India, earnings from foreign tourists are used to represent value. The study is unique from a methodological point of view as it makes the first ever application of the nonlinear autoregressive distributed lag model of Shin, Yu, and Greenwood-Nimmo (2014), in the tourism demand literature to capture nonlinearity simultaneously in the short- as well as long-run. Results of our analysis show that tourism demand in India responds asymmetrically to both nominal and real exchange rate volatility. Also, the long-run effects of exchange rate uncertainty are shown to be more damaging than the short-run effects. Our findings are fairly robust to alternative specifications.
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