Systematic non-response in discrete choice experiments: implications for the valuation of climate risk reductions

Discrete choice experiments (DCEs) addressing adaptation to climate-related risks may be subject to response biases associated with variations in risk exposure across sampled populations. Systematic adjustments for such response patterns are hindered by the absence of rigorous, standardised selection-correction models for multinomial DCEs, together with a lack of information on non-respondents. This paper illustrates an empirical approach to accommodate risk-related response patterns in DCEs, where variations in risk exposure may be linked to observable landscape characteristics. The approach adapts reduced form response-propensity models to correct for survey non-response, capitalising on the fact that indicators of risk exposure may be linked to the geocoded locations of respondents and non-respondents. An application to coastal flood adaptation in Connecticut, USA illustrates implications for welfare estimation. Results demonstrate systematic effects of risk-related response patterns on estimated willingness to pay.