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Assessing the Macroeconomic Determinants of International Tourist Arrival in India: An ARDL Bounds Testing Approach.

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Titel: Assessing the Macroeconomic Determinants of International Tourist Arrival in India: An ARDL Bounds Testing Approach.
Autoren: Singh AK; Chandigarh University, Sahibzada Ajit Singh Nagar, Punjab, India., Oyelakin IO; INTI International University, Nilai, Negeri Sembilan, Malaysia., Kushwah RS; University of Delhi, New Delhi, Delhi, India., Bharti S; Manipal Academy of Higher Education, Manipal, Karnataka, India., Paatlan S; Chandigarh University, Sahibzada Ajit Singh Nagar, Punjab, India., Mahusain MA; Taylor's University, Subang Jaya, Selangor, Malaysia., Alturki KH; Qassim University, Buraydah, Al Qassim, Saudi Arabia., Singh AK; Chandigarh University, Sahibzada Ajit Singh Nagar, Punjab, India.
Quelle: F1000Research [F1000Res] 2025 Nov 05; Vol. 14, pp. 1215. Date of Electronic Publication: 2025 Nov 05 (Print Publication: 2025).
Publikationsart: Journal Article
Sprache: English
Info zur Zeitschrift: Publisher: F1000 Research Ltd Country of Publication: England NLM ID: 101594320 Publication Model: eCollection Cited Medium: Internet ISSN: 2046-1402 (Electronic) Linking ISSN: 20461402 NLM ISO Abbreviation: F1000Res Subsets: MEDLINE
Imprint Name(s): Original Publication: London : F1000 Research Ltd
MeSH-Schlagworte: Tourism* , Economic Development* , Travel*, India ; Humans ; Models, Economic
Abstract: Competing Interests: No competing interests were disclosed.
Background: Tourism is a vital component of economic development, particularly in emerging economies like India, where international tourist arrivals contribute significantly to foreign exchange earnings, employment generation, and regional growth. While prior research has explored various determinants of tourism demand, limited empirical studies have assessed the macroeconomic underpinnings of ITA using time series models capable of handling mixed integration orders. This study investigates the short-run and long-run effects of international tourist arrivals on GDP, FDI, and inflation in India.
Methods: This study uses the Autoregressive Distributed Lag bounds testing approach on annual data spanning from 1995 to 2022. The Augmented Dickey-Fuller (ADF) test was conducted to determine the stationarity properties of the time series data, after which the optimal lag structure for the ARDL model was identified using the Akaike Information Criterion (AIC). The model was built on a time series dataset spanning 1995 to 2022, and the empirical results provide both statistically significant findings and interpretive depth that are relevant to policy and theory.
Results: The findings of this study confirm a statistically significant and positive relationship between GDP and international tourist arrivals in both the short and long run. The ARDL (1,2,0,2) model demonstrated strong explanatory power (Adjusted R² = 0.9565), and the bounds test confirmed the presence of cointegration among the variables. However, FDI and inflation were found to be statistically insignificant in influencing ITA. The error correction term was negative and empirically significant, indicating that approximately 51% of the disequilibrium adjusts each year toward long-run equilibrium.
Conclusion: This study highlights GDP as the primary macroeconomic driver of international tourism demand in India, with implications for economic planning and tourism policy. While FDI and inflation were not significant in this model, their potential indirect effects needs further investigation.
(Copyright: © 2025 Singh AK et al.)
References: Waste Manag Res. 2025 Oct;43(10):1605-1624. (PMID: 40168019)
Contributed Indexing: Keywords: economic growth; foreign direct investment; gross domestic product; inflation; international tourist arrivals; tourism
Entry Date(s): Date Created: 20251201 Date Completed: 20251201 Latest Revision: 20251203
Update Code: 20251203
PubMed Central ID: PMC12658354
DOI: 10.12688/f1000research.170280.1
PMID: 41322053
Datenbank: MEDLINE
Beschreibung
Abstract:Competing Interests: No competing interests were disclosed.<br />Background: Tourism is a vital component of economic development, particularly in emerging economies like India, where international tourist arrivals contribute significantly to foreign exchange earnings, employment generation, and regional growth. While prior research has explored various determinants of tourism demand, limited empirical studies have assessed the macroeconomic underpinnings of ITA using time series models capable of handling mixed integration orders. This study investigates the short-run and long-run effects of international tourist arrivals on GDP, FDI, and inflation in India.<br />Methods: This study uses the Autoregressive Distributed Lag bounds testing approach on annual data spanning from 1995 to 2022. The Augmented Dickey-Fuller (ADF) test was conducted to determine the stationarity properties of the time series data, after which the optimal lag structure for the ARDL model was identified using the Akaike Information Criterion (AIC). The model was built on a time series dataset spanning 1995 to 2022, and the empirical results provide both statistically significant findings and interpretive depth that are relevant to policy and theory.<br />Results: The findings of this study confirm a statistically significant and positive relationship between GDP and international tourist arrivals in both the short and long run. The ARDL (1,2,0,2) model demonstrated strong explanatory power (Adjusted R² = 0.9565), and the bounds test confirmed the presence of cointegration among the variables. However, FDI and inflation were found to be statistically insignificant in influencing ITA. The error correction term was negative and empirically significant, indicating that approximately 51% of the disequilibrium adjusts each year toward long-run equilibrium.<br />Conclusion: This study highlights GDP as the primary macroeconomic driver of international tourism demand in India, with implications for economic planning and tourism policy. While FDI and inflation were not significant in this model, their potential indirect effects needs further investigation.<br /> (Copyright: © 2025 Singh AK et al.)
ISSN:2046-1402
DOI:10.12688/f1000research.170280.1