Abstract
The authors provide an empirical assessment of the relationship between tourism specialization and economic growth by updating the findings of previous papers written on this issue. They use data for more than 150 countries, covering different time spans between 1980 and 2005. Contrary to previous findings (for example, Brau et al, 2004 and 2007), tourism-based countries did not grow at a higher rate than non-tourism-based countries, except for the 1980–1990 period for which, however, the data on international tourism were not fully reliable.
Estimating visitor spending through the segmentation approach has several advantages in terms of policy evaluation, user management and sampling design. This approach generally relies on visitor surveys to estimate two parameters, average spending per segment and segment share, so that total visitation can be apportioned to each subgroup. Equivalently, this approach is to estimate the weighted average spending by taking into consideration the relative shares of each user segment. This paper first provides a statistical formula to compute the variance of weighted average spending by taking into account the stochastic nature of spending and segment shares. Second, simulation analysis is adopted to compare the accuracy and precision of the spending estimator based on different study designs. The results show that conducting additional short surveys to obtain information on user segments provides two advantages. First, it helps to reduce non-response bias since certain visitor groups have higher ratios of unreturned questionnaires, incomplete data or non-participation. Second, it helps to decrease the variance of the estimator so that the upper and lower bound of the confidence interval can be narrowed. The level of variance reduction will depend on the relative segment shares, the average spending, cases that are obtained, spending variation and the probability of giving full spending information across segments. The implications for survey design are offered in light of the results.
This study examines the impact of the Federal Reserve (Fed) monetary policy on US hospitality stock returns. Specifically, this research paper investigates the stock performance of US hospitality firms under different Fed monetary policy regimes. Hospitality companies include gambling firms, lodging companies and restaurants. Changes in the discount rate and federal funds rate are used to measure shifts in the Fed monetary policy and to classify the full monetary policy period as either a restrictive or an expansive monetary policy environment. An expansive monetary condition is a period with a decrease in the discount or federal funds rate; a restrictive monetary environment experiences an increase in the discount or federal funds rate. Empirical test results reveal that the influence of the two monetary policy indicators on hospitality stock returns varies to a great extent. The stock returns of US restaurants are related significantly to changes in the federal funds rate. However, changes in the discount rate generally have no strong impact on US hospitality stock returns.