Exchange rate volatility and India's cross-border trade: A pooled mean group and nonlinear cointegration approach

Sharma, Chandan; Pal, Debdatta

doi:10.1016/j.econmod.2018.05.016

Cited by 43 publications

(47 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There has been limited use of exchange rate volatility in tourism demand models, and its role is found to be very mixed and unclear when used along with relative prices (e.g., Webber 2001; De Vita and Kyaw 2013; Martins, Gan, and Ferreira-Lopes 2017). Some recent studies (Sharma and Pal 2018) have shown it is not the exchange rate but the volatility in exchange rate that affects international transaction and trade. Motivated by such findings, we test the effect of nominal and real exchange rate volatility on tourism demand in India.…”

Section: Resultsmentioning

confidence: 99%

“…In a similar line, by using a Quantile-Quantile approach, Shahzad et al (2017) find that positive influence of tourism activity on economic growth varies across quantiles among top 10 tourist destination countries. Similarly, international trade is also found to be nonlinearly linked with exchange rate volatility (e.g., Sharma and Pal 2018). Therefore, it seems plausible that tourism demand would also react in an asymmetric manner to volatile exchange rates.…”

Section: Introductionmentioning

confidence: 99%

“…NARDL is an extension of the ARDL of Pesaran, Shin, and Smith (2001) in the context of asymmetric relationship. While there is increasing use of the NARDL model in the field of international economics (Sharma and Pal 2018) as well as natural resources (e.g., Pal and Mitra 2015, 2016), to our knowledge, this study is one of the earliest attempts using NARDL framework for uncovering the complex asymmetric association of tourism demand with a volatile exchange rate.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Sharma

Pal

2019

Journal of Travel Research

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Sharma

Pal

2019

Journal of Travel Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Bahmani-Oskooee et al (2016) observe no impact of exchange rate volatility on trade of Pakistan. According to Sharma and Pal (2018), exchange rate volatility has a dampening effect on exports of India. Bahmani-Oskooee and Gehlan (2018) studied the impact of exchange rate volatility, world income and real effective exchange rate on exports and imports of 12 African countries and the result indicates mixed impacts of volatility on exports and imports.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Impact of Exchange Rate Volatility, Inflation and Economic Output on International Trade of India

Arora

Rakhyani

2020

The Indian Economic Journal

View full text Add to dashboard Cite

Four models have been constructed separately for exports of goods, imports of goods, exports of services and imports of services to explore the impact of exchange rate volatility, inflation and economic output on India’s foreign trade. AutoRegressive Distributed Lag (ARDL) bounds test run on monthly data over the period of 2011–2020 reports that in the long run, growth in production positively impacts the trade in goods and services. Rise in level of prices negatively impacts the exports of goods. In the short run, a rise in volatility brings a decline in the imports of goods but in the long run, it has a positive impact on the exports of goods. Volatile exchange rate has no impact on trade in services. An increase in inflation in the short run leads to a rise in the imports of goods but brings a decline in the trade of services.

show abstract

“…There are also many studies that have been done in this regard and have reached different results (Asteriou et al, 2016;Sharma and Pal, 2018;Senadza and Diaba, 2017;Šimáková, 2014). When maritime studies related to this topic were examined, few studies were found.…”

Section: Introductionmentioning

confidence: 99%

What Triggers the ISTFIX Bubbles?

Açık¹,

Başer²,

Ertürk³

2018

Uluslararası Ekonomi Ve Yenilik Dergisi

View full text Add to dashboard Cite

The aim of this study is to determine the factors that influence the probability of price bubble formation in the İstanbul Freight Index (ISTFIX). In this direction, firstly the price bubbles were determined by generalized sup augmented Dickey-Fuller (GSADF) test. Following the GSADF test, a logit regression model was established by creating dummy variables from bubble dates and it was tried to determine the factors affecting bubble formation. The dataset consists of 354 weekly observations and covers the dates between 18.03.2011 and 31.12.2017. According to the results, 4 bubble periods with lengths ranging from 6 to 12 weeks were detected. In the logit model, it was found that "euro" and "fuel price" variables increase the probability of bubble formation and the marginal effect of "euro" is much higher.

show abstract

Exchange rate volatility and India's cross-border trade: A pooled mean group and nonlinear cointegration approach

Cited by 43 publications

References 62 publications

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Exchange Rate Volatility and Tourism Demand in India: Unraveling the Asymmetric Relationship

Investigating the Impact of Exchange Rate Volatility, Inflation and Economic Output on International Trade of India

What Triggers the ISTFIX Bubbles?

Contact Info

Product

Resources

About