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The authors fitted a number of time-series econometric models to monthly visitation data of a national park to examine the effect of impaired visibility on visitation demand. Using a polynomial distributed lag model, the long-run elasticity of demand with respect to visibility in the Great Smoky Mountain National Park (GSMNP) was estimated. The GSMNP, the most visited national park in the USA, has significant air quality issues. Although the park has observed some fluctuation in visitation, the results indicate that the demand for visitation in general and for specific recreational visits are mean reverting and highly stable. Further, park visitation in a given month is significantly affected by the cumulative effect of the visibility condition in both the current and preceding months. Estimated elasticity reveals that a programme aiming to improve the average visibility by 10% (5.5 km) from the current level could result in an increase of roughly one million recreational visits annually, and that the increase would be higher for overnight visitors than for day visitors because of overnight visitors' relatively elastic demand. This demand model could assist park managers in their planning as they weigh the anticipated benefits of a visibility improvement programme against increased visitation and its associated costs.
Poudyal et al. (Mon,) studied this question.