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Role of Rules of Thumb in Forecasting Foreign Tourist Arrival: A Case Study of India

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  • Bhattacharya, Kaushik

Abstract

The paper examines forecast performances of some popular rules of thumb vis-à-vis more sophisticated time series models in the specific context of foreign tourist arrival in India. Among all forecasting approaches attempted in the study, exponential smoothing (ES) and ARIMA provided the best short-term forecasts, closely followed by autoregressive distributed lag (ADL) models. These results are largely in agreement with cross-country findings on tourism forecast. Foreign tourist arrival data in India, however, displayed a regularity that did not change substantially even in the face of major global or local events. Given the regularity, our study suggests that rules of thumb can play an important practical part in short-term forecasts of tourist arrival in India. Our study, however, reveals that forecasts from such thumb rules could be improved substantially through simple residual corrections and incorporation of other information available in the public domain.

Suggested Citation

  • Bhattacharya, Kaushik, 2011. "Role of Rules of Thumb in Forecasting Foreign Tourist Arrival: A Case Study of India," MPRA Paper 28515, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:28515
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    File URL: https://mpra.ub.uni-muenchen.de/28515/1/MPRA_paper_28515.pdf
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    References listed on IDEAS

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    1. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
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    1. repec:eee:touman:v:63:y:2017:i:c:p:201-208 is not listed on IDEAS

    More about this item

    Keywords

    Tourism; Tourist Arrival; Forecasting; Rules of Thumb; Exponential Smoothing; ARIMA; ADL;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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