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.

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The real and nominal shocks in the U.S. are identified by using long-run implications of an open economy stochastic macroeconomic model, and the effects of these shocks are observed in real GDP, effective exchange rates, and the prices for the U.S. relative to each of six other G-7 countries. While Blanchard and Quah's long-run identification strategy is used to identify the shocks, short-run implication of the model are also exploited, as a prima facie evidence, by applying appropriate sign restrictions in the VAR estimation. Consistent with the model's predictions, a positive supply shock results in an increase in relative U.S. real GDP and a real depreciation of U.S. currency whereas nominal shocks in the U.S. lead to an increase in relative U.S. real GDP and relative U.S. prices. The application of short-run dynamics with proper sign restrictions into the VAR estimation produces exchange rate overshooting following the U.S. real shocks.

This study first conducts a detailed survey on recently emerged new field in economics called new open economy macroeconomics and then carries out an empirical test of theoretical predictions of these models to observe transmission effects of Indian economic shocks in South Asia region. In the survey, the study starts with the seminal work of Obstfeld and Rogoff (1995) and then evaluates the subsequent evolution of this field. The survey reveals that the field is rapidly evolving with many dimensions added on it within a short period of time, making this field richer and betterable to perform better predictions. The estimation of Vector Autoregression model for South Asia region, on the other hand, uncovers that the effects of Indian shocks in South Asia region, have mixed results. Since the real, nominal, and financial shocks generated in India affect the economies of neighboring countries with varied extent.

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