Erda Wang

The Economic Impact of Tourism in Xinghai Park, China: A Travel Cost Value Analysis Using Count Data Regression Models

Using the travel cost method, the authors measure the recreational trip value of Xinghai Park in Dalian, China. They compare non-linear, truncated Poisson and truncated negative-binomial count data models to estimate recreational trip demand. The economic values of recreational trips in terms of consumer surplus (CS) are derived from each model. They estimate the CS values at between RMB ¥493 (US

Empirically-Based Crop Insurance for China: A Pilot Study in the Down-middle Yangtze River Area of China

64) to RMB ¥562 (US

Valuing outdoor recreation activities using a meta-analysis model in China: an empirical study

73) per trip, resulting in a total social welfare estimate in the range from RMB ¥1.08 billion to RMB ¥1.23 billion (US

Simulation of Hail and Soil Type Effects on Crop Yield Losses in Kansas, USA

140 million to US

Valuing forest park attributes by giving consideration to the tourist satisfaction

160 million in 2007).

The effects of improving coastal park attributes on the recreation demand—A case study in Dalian China:

Factors that caused slow growth in crop insurance participation and its ultimate failure in China were multi-faceted including high agricultural production risk, low participation rate, inadequate public awareness, high loss ratio, insufficient and interrupted government financial support. Thus, a clear and present need for data driven analyses and empirically-based risk management exists in China. In the present investigation, agricultural production data for two crops (corn, rice) in five counties in Jiangxi Province and Hunan province for design of a pilot crop insurance program in China. A crop insurance program was designed which (1) provides 75% coverage, (2) a 55% premium rate reduction for the farmer compared to catastrophic coverage most recently offered, and uses the currently approved governmental premium subsidy level. Thus a safety net for Chinese farmers that help maintain agricultural production at a level of self-sufficiency that costs less than half the current plans requires one change to the program: ≥80% of producers must participate in an area.

Factors contributing to tourists' length of stay in Dalian northeastern China — A survival model analysis

This paper analyses a large dataset based on empirical non-market valuation study results reported in the USA. The dataset is used to estimate a meta-regression model that is applied to predict the corresponding recreation activity values in China. The convergent validity of the meta-analytical international benefit transfer is tested against observed recreation activity values in China. In the process, a relative percentage error indicator, paired t-test and the Wilcoxon signed-rank test are used. The mean benefit transfer error is 18.74%, an acceptable value for international transfer.

Crop Insurance Premium Design Based on Survival Analysis Model

Abstract Computer simulation was used for predictive analysis of the effects of weather and soil type on crop yield in the U.S. crop insurance program. The Environmental Policy Integrated Climate (EPIC) model was modified to include hail weather events, which completed the modifications necessary to simulate the four most frequent causes of crop yield loss (hail, excessive wet, excessive cold, and excessive dry) associated with soil type in Kansas, USA. At the region level, per hectare yields were simulated for corn, wheat, soybean, and sorghum. We concluded that it was possible to predict crop yields through computer simulation with greater than 93% accuracy. The hail damage model test indicated EPIC could predict hail-soil-induced yield losses reasonably well ( R 2 > 0.6). The investigation of soil type influence on dryland sorghum and wheat production indicated that Wymore silty clay loam soil and Kenoma silt loam produced the highest sorghum yields statistically; Kuma silt loam, Roxbury silt loam, Crete silty clay loam, and Woodson silt soils produced the second highest sorghum yields statistically; and Richfiled silt loam, Wells loam, and Canadian sandy loam produced the lowest sorghum yields. By contrast, wheat production showed less sensitivity to soil type variation. The less sensitive response of wheat yields to the soil type could be largely due to the unconsidered small-scale variability of soil features.

Valuing Urban Landscape Using Subjective Well-Being Data: Empirical Evidence from Dalian, China

Despite the economic valuation of forest park resources has triggered a great deal of interest to the research community and park management, up to now no attention has been paid to the effect of psychological factors such as tourist satisfaction, which could potentially play a considerable role in contributing to the park resource valuation. This article attempts to fill this niche by carrying out a study on the economic valuation of the Xian-Ren-Tai National Forest Park in China, taking consideration of the tourist satisfaction. In the process, the choice experiment survey was used for data collection. Then, both conditional logit (CL) and random parameter logit models were used in parameter estimations to examine the factors that could potentially impact on the tourists’ willingness to pay. Results indicate that the tourists attach the greatest importance to the park’s natural environment and traffic conditions, and yet the level of tourists’ satisfaction on their tourism experience plays a big part in explaining the valuation results. Tourists who uphold a high level of satisfaction tend to pay more for the park attribute improvement than those with less satisfaction ones. The estimated compensating variation of the overall current park attributes has reached ¥184.95 per person per trip, of which 12.83% shall be attributable to the tourist satisfaction.

Valuing natural and non-natural attributes for a national forest park using a choice experiment method

In this study, we use an estimation method of combining revealed preference (RP) with stated preference (SP) to measure the effects of park attribute improvement on the tourism demand and recreation benefits. Three categories of attributes are taken into account including nature, management, and economics. Five model estimations are made using RP, SP, and pooled data, respectively. The random effects negative binomial model is used with the SP data, and the mixed negative binomial model is used with the pooled data. The economic value of each specific park attribute improvement is measured by visitors’ marginal willingness to pay that directly addresses the issues of optimal attribute combinations beyond the observed range and scenarios. We survey a sample of the participants on the sites to obtain both revealed and stated behavior data for trips based on a management-relevant park attribute improvement and different park attribute combinations. Recreation demand models are used to derive total consumer surplus. The results indicate that the congestion reduction in the park has a relatively weak effect on the tourist demand, whereas trash reduction and improved seawater visibility appear to have the most important value to the tourists. Furthermore, the estimated consumer surplus at the present park conditions is about US