Geir Wæhler Gustavsen

Research Scientist

(+47) 907 01 453


Visiting address
Storgata 2-4-6, 0155 Oslo

To document


Consumer resistance against GM crops is still substantial in the United States and Europe. We conducted an internet survey in the United States and Norway with more than 1,000 respondents in each country to estimate consumers’ willingness to pay (WTP) for GM soybean oil, farmed salmon fed with GM soy, and GM salmon. The differences in WTP for the conventional as compared with the GM alternatives are relatively small. Only between 7 and 13% of the respondents indicated that they were willing to pay more than a 20% premium for each of the conventional alternatives as compared to the corresponding GM alternatives. The average WTP premiums range from 7.5 to 9.2%. This suggests a large similarity in WTP in Norway and the United States and across the three products.


Food production contributes considerably to global greenhouse gas (GHG) emissions. Animal products – particularly meat from ruminants – generally have higher GHG emissions than plant products. Over the last few decades the global per capita consumption of animal products has increased. This has a negative impact on climate change, land and water availability, and human health. We are faced with the two-fold challenge of reducing GHG emissions while still producing enough food for our growing population. Part of the solution could be for consumers to change towards a more sustainable diet. In this paper we take Norway as a case study for estimating optimal taxes and subsidies on different food items which can change consumption patterns in order to reduce the GHG emissions derived from the average Norwegian diet. In the estimate we ensure that the average calorie intake with the new diet remains the same as with the current diet, and factor in other health considerations. Our findings suggest that limited but useful emission reduction targets can be set with only a few changes in diets. The methodology presented in this paper may be used to estimate optimal climate taxes and subsidies under different emission, quantities, taxes, subsidies, and health constraints.