Abstract
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.