Better than their reputation: enhancing the validity of contingent valuation mail survey results through citizen expert groups

Although contingent valuation is the dominant technique for the valuation of public projects, especially in the environmental sector, the high costs of contingent valuation surveys prevent the use of this method for the assessment of relatively small projects. The reason for this cost problem is that typically only contingent valuation studies which are based on face-to-face interviews are accepted as leading to valid results. Particularly in countries with high wages, face-to-face surveys are extremely costly considering that for a valid contingent valuation study a minimum of 1000 completed face-to-face interviews is required. This paper tries a rehabilitation of mail surveys as low-budget substitutes for costly face-to-face surveys. Based on an empirical contingent valuation study in Northern Thailand, it is shown that the validity of mail surveys can be improved significantly if so-called Citizen Expert Groups are employed for a thorough survey design.     

A data mining approach to simulating farmers' crop choices for integrated water resources management

Water and land resources in Thailand are increasingly under pressure from development. In particular, there are many resource conflicts associated with agricultural production in northern Thailand. Communities in these areas are significantly constrained in the land and water management decisions they are able to make. This paper describes the application of a data mining approach to describing and simulating farmers' decision rules in a catchment in northern Thailand. This approach is being applied to simulate social, economic and biophysical constraints on farmers' decisions in these areas as part of an integrated water management model.     

Farmer decision making and spatial variables in northern Thailand

This research has two interrelated objectives. The first is to determine the extent to which a relationship exists between farmer characteristics and farming practices in three villages in northern Thailand. The second is to use standard statistical methods for incorporating spatial variables into the analysis and to assess the effects of these variables on farmer decision making. The data base includes information on the location and size of villages, roads, streams, and fields; a digital elevation model with information on elevation, slope, and aspect; and information keyed to individual fields on crops and cropping methods and the ethnicity, income, and religion of farmers. The map data (517 plots) were entered into a computerized geographic information systems (GIS). Results suggest several hypotheses about the relationships between land use and owner characteristics. More significantly, the study concludes that spatial analysis appears to be most useful when the dependent variable is either continuous or ordinal. The outlook is not quite as optimistic when the dependent variable is a nonordinal categorical variable. Before spatial analysis can be applied regularly to social science data, better computational tools need to be developed.