A meta-regression analysis on the willingness-to-pay for country-of-origin labelling - Ching-Hua Yeh; Stefan Hirsch (Journal of Agricultural Economics, 2023)
Food quality and food safety issues arouse increasing interest and concern among consumers and policy-makers. Consequently, the importance of country-of-origin labelling (COOL) is increasing in business, policy and research. Numerous studies have reported a wide range of estimates for consumers' willingness-to-pay (WTP) for COOL using stated preference methods and, in particular, discrete choice experiments. We apply meta-regression analyses to synthesise the heterogeneous results of 204 WTP for COOL estimates extracted from 59 studies which used discrete choice experiments and were published between 2009 and 2020. Meta-regression analysis allows an adjusted summary proxy to be derived for the WTP for COOL and the determinants of heterogeneity in reported WTP estimates are also investigated. Our results suggest that there is a significant positive WTP for COOL, and also reveal that the reported WTP estimates are unaffected by publication bias. In addition, they show systematic variation in WTP estimates across the context and methodological characteristics of the studies. More precisely, we find that the region and the product (animal- vs. plant-based) analysed, as well as certain characteristics of the choice design (e.g., the number of attributes used, or the inclusion of an opt-out option) can have a significant impact on the estimated WTP for COOL. Finally, our results reveal significant differences in price premiums between various types of COOL (e.g., domestic vs. foreign). This highlights that results from individual primary studies should not be generalised without further consideration of the underlying study design.
Keywords: 630; country-of-origin labelling; meta-regression analysis; publication bias; willingness-to-pay