Financing the sustainable management of Rwanda's protected areas

Rwanda's Nyungwe National Park is a biodiversity hotspot with the most endemic species in the ecoregion and the highest number of threatened species internationally. Nyungwe supplies critical ecosystem services to the Rwandan population including water provisioning and tourism services. Tourism in the Park has strong potential for financing enhanced visitor experiences and the sustainable management of the Park. This paper explores quantitatively the economic impacts of adjustment in Park visitation fees and tourism demand as a source of revenues to improve Park tourism opportunities and ongoing operations and maintenance. The methods developed in this paper are novel in integrating the results of stated preference techniques with a regional computable general equilibrium modelling approach to capture multisectoral, direct, indirect and induced impacts. Such methods have strong potential for assessing revenue generation alternatives in other contexts where park managers are faced with the need to generate additional revenue for sustainable park management while facing diminishing budget allocations. Results of this analysis demonstrate that adjustment of Park fees has a relatively small impact on the regional economy and well-being when compared with a strategy aimed at generating increased tourism demand through investment in improving the visitor experience at Nyungwe National Park.     

Defect Detection Using Unanimous Vote Among Mahalanobis Classifiers for Each Color Component

In manufacturing industries, product inspection is automated and the use of image data is increasingly being employed for defect detection. A manufacturing company in Japan produces an item and inspects the produced products using image data. Reducing the error rate is important in product inspection because poor inspection of products might lead to the delivery of defective products to consumers (consumer’s risk) and strict inspection increases production cost (producer’s risk). To reduce the error rate, we highlighted fault points using a two-dimensional moving range filter and discriminated defect production through a unanimous vote among Mahalanobis classifiers for each color component. For results, we achieved a lower error rate than the current system. This research is an empirical study of how to use image data in defect detection.     

Broadband Demand Analysis for Network Building

An increase of broadband demand is forecasted by transitional methods that consider the effect of this increase through many factors, such as customer requirement diversification, and new service introduction and deployment under competition. Broadband demand forecasting has become important for closing the digital divide, promoting regional developments, and constructing networks economically; therefore, a demand forecast model that considers the mechanisms of market structure is necessary. In this paper, a demand analysis method for broadband access combining macro- and micro-data mining is proposed, and the service choice behaviour of customers is introduced as a customer model not only to express the macro trend of market structure, but also to consider area marketing. The proposed method can estimate the potential demand, determine the point at which broadband demand growth peaks in a specified area, and support a decision for ultra high-speed broadband access facility installation.     

Compensating Wage Differentials with Unemployment: Evidence from China

We estimate the economic value of mortality risk in China using the compensating-wage-differential method. We find a positive and statistically significant correlation between wages and occupational fatality risk. The estimated effect is largest for unskilled workers. Unemployment reduces compensation for risk, which suggests that some of the assumptions under which compensating wage differentials can be interpreted as measures of workers’ preferences for risk and income are invalid when unemployment is high. Workers may be unwilling to quit high-risk jobs when alternative employment is difficult to obtain, violating the assumption of perfect mobility, or some workers (e.g., new migrants) may be poorly informed about between-job differences in risk, violating the assumption of perfect information. These factors suggest our estimates of the value per statistical life (VSL) in China, which range from approximately US$30,000 to US$100,000, may be biased downward. Alternative estimates adjust for heterogeneity of risk within industry by assuming that risk is concentrated among low-skill workers. These estimates, which are likely to be biased downward, range from US$7,000 to US$20,000.