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on Tourism Economics |
| By: | Chang, Chia-Lin; Hsu, Hui-Kuang |
| Abstract: | This paper investigates the volatility size effects for firm performance in the Taiwan tourism industry, especially the impacts arising from the tourism policy reform that allowed mainland Chinese tourists to travel to Taiwan. Four conditional univariate GARCH models are used to estimate the volatility in the stock indexes for large and small firms in Taiwan. Daily data from 30 November 2001 to 27 February 2013 are used, which covers the period of Cross-Straits tension between China and Taiwan. The full sample period is divided into two subsamples, namely prior to and after the policy reform that encouraged Chinese tourists to Taiwan. The empirical findings confirm that there have been important changes in the volatility size effects for firm performance, regardless of firm size and estimation period. Furthermore, the risk premium reveals insignificant estimates in both time periods, while asymmetric effects are found to exist only for large firms after the policy reform. The empirical findings should be useful for financial managers and policy analysts as it provides insight into the magnitude of the volatility size effects for firm performance, how it can vary with firm size, the impacts arising from the industry policy reform, and how firm size is related to financial risk management strategy. |
| Keywords: | Tourism, firm size, conditional volatility models, volatility size effects, asymmetry, tourism policy reform. |
| JEL: | C22 C32 G18 L83 |
| Date: | 2013–03–31 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:45691&r=tur |
| By: | Liu, Xiangping (Department of Economics, School of Business, Economics and Law, Göteborg University); Taylor, Laura (Center for Environmental and Resource Economic Policy); Hamilton, Timothy (Department of Economics, University of Richmond); Grigelis, Peter (Office of Policy Analysis, U.S. Deparment of Interior) |
| Abstract: | The National Wildlife Refuge system is a network of permanently protected open space encompassing more than 150 million acres across 50 states. Maintaining such a large network of permanently protected open space can put the federal government at odds with local communities when management priorities differ from the local community’s objectives. This can be especially true in rapidly urbanizing areas where local jurisdictions voice concerns over the loss of property tax revenues and economic activity resulting from lands’ protected status. While refuge recreation and ecosystem benefits have been identified, we know little about the property value benefits accruing to local homeowners. This research quantifies the property value benefits of all refuges on the east coast that are near urban areas. Our approach is made possible through access to confidential U.S. Census data identifying property values surrounding all refuges with high geographic resolution. Results from hedonic property value models suggest that the amenity values of refuges located near urbanized areas are capitalized into the value of homes in very close proximity, averaging $11 million per refuge. These capitalized values add directly to the local tax base and are considerable complements to the annual economic value created by the refuge system. |
| Keywords: | National Wildlife Refuges; open space; amenity values; hedonic analysis |
| JEL: | Q24 Q51 Q57 Q58 |
| Date: | 2013–03–22 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:gunwpe:0562&r=tur |
| By: | Bent Flyvbjerg |
| Abstract: | Project promoters, forecasters, and managers sometimes object to two things in measuring inaccuracy in travel demand forecasting: (1) using the forecast made at the time of making the decision to build as the basis for measuring inaccuracy and (2) using traffic during the first year of operations as the basis for measurement. This paper presents the case against both objections. First, if one is interested in learning whether decisions about building transport infrastructure are based on reliable information, then it is exactly the traffic forecasted at the time of making the decision to build that is of interest. Second, although ideally studies should take into account so-called demand "ramp up" over a period of years, the empirical evidence and practical considerations do not support this ideal requirement, at least not for large-N studies. Finally, the paper argues that large samples of inaccuracy in travel demand forecasts are likely to be conservatively biased, i.e., accuracy in travel demand forecasts estimated from such samples would likely be higher than accuracy in travel demand forecasts in the project population. This bias must be taken into account when interpreting the results from statistical analyses of inaccuracy in travel demand forecasting. |
| Date: | 2013–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1303.7401&r=tur |