Conference Agenda

This study estimates a Multiple Discrete-Continuous model to obtain demands for new fruits using combined stated preference (SP) and revealed preference (RP) data. The combined model is an application of the Multiple Discrete-Continuous Extreme Value (MDCEV) model which accounts for the continuous aspect of consumer choice. The SP data are obtained from an expenditure-based choice experiment, and the RP data are household-level scanner data collected by the Rural Development Administration of the Republic of Korea. Estimation results show that new varieties are always preferred over existing varieties in general. A likelihood ratio test suggests that the preference structure of the SP data is different to that of the RP data, yet incorporating RP data in a combined estimation greatly enhanced the significance of estimates. Using estimation results, we apply a forecasting method to derive price elasticities and expenditure elasticities of demand, willingness to pay for new varieties, and market shares. In the case of own-price elasticities, watermelon and cherry tomato are fruits where the new variety is more elastic to price change than the existing variety. On the other hand, for nectarine, tomato, and plum, the elasticity of existing variety is higher than the new variety. In all fruit types except tomato, the expenditure elasticity of the new variety is larger than the existing variety. Willingness to pay results show that consumers are willing to pay a substantial amount of money for the introduction of new varieties, although with large variability. Market share results show that introducing a new variety increases the market potential for that fruit, as the new variety does not fully replace the existing variety. These results support the importance of variety diversification for both consumers and producers in the fruit market.

Pulses can play a key role in sustainable and healthy food systems, as their high protein content can replace proteins obtained from meat. Yet, previous findings indicate that consumers consider pulses a complement, not a substitute, to meat. This may complicate the design of pulse-promoting policies. Contributing to the limited literature investigating the pulse-meat relationship, we analyse food choices from 3,237 Danes in a Basket-Based Choice Experiment. Using the eMDC modelling framework, we find that respondents generally consider pulses and meats as substitutes. Providing nutritional information appears to have no effect on the extent to which this substitution takes place.

Food production and consumption account for a third of global greenhouse gas emissions and, therefore, offer a large mitigation potential. Policies such as carbon taxation and carbon labelling can contribute to correcting such externalities, by encouraging consumers to substitute away from carbon intensive food products. We employ data from a survey-based, randomized experiment simulating an online supermarket, administered to a representative sample of the UK population. Using a structural demand system based on the Exact Affine Stone Index model with censoring, we estimate the greenhouse gas emission reductions and welfare effects associated with a range of demand-side policy scenarios, combining carbon labelling and carbon taxation. Our results show that the application of carbon labels leads to a 5.60% decrease in the carbon content of the average food basket. A £60 tax per ton of CO2e on the most carbon intensive products would yield a 9.89% reduction in the carbon footprint, while also decreasing consumer welfare by £78.71 per person per year. Combining carbon taxation and carbon labelling would allow to reach the same CO2e emissions reduction as the carbon tax, with only a £27.86 tax rate per ton of CO2e, thereby reducing welfare losses to £33.52 per person per year. These findings imply that carbon taxation and carbon labelling can be complementary policies to abate GHGs emissions, while limiting the negative impacts on welfare.

The growing unpredictability of climate change in recent years has increased the vulnerability of agri-food systems to meet the household food demand. In addition, the inefficiencies in agri-food supply chains, combined with household food waste, further aggravate the food, economic and resource use losses. Given that India boasts the largest global population and continually rising living standards, this situation is quite alarming. This study intends to comprehensively analyse the economic, environmental and resource use impacts across three stages of the food cycle: i) The climate change on agricultural yield at the pre-harvest stage using Panel Corrected Standard Errors Model; ii) The Post-Harvest Losses due to inefficiencies in the agri-food supply chain and iii) Household food waste and circular economy potential using various waste treatment methods by 2030 using the Environmentally Extended Waste Input Output model. Results indicate that the increase in maximum temperature levels leads to a reduction in agricultural yield by 2.52%, with rice and cereals being affected the most. The Post-harvest losses and Household food waste combined account for 77%, 76% and 78% of Water, Electricity and Land footprint losses. Efficiency interventions will not only reduce the resource burden but also include the potential to serve as many as 242 million people through food rescue operations. On the other hand, the treatment of residual food waste has the potential to generate 50 Gwh electricity, 25,400 tonnes of Biogas and 16.5 million tonnes of organic compost. This research advocates for

technological interventions at the pre-harvest stage to improve the resilience of crops to climate change variations, accelerate the improvements in Post-Harvest management practices and avoidable household Food Waste to meet the SDG 2 and 12 targets.