The Future of Antimicrobial Use in Livestock,  with Acosta, A., Nicolli, F., Van Boeckel, T., & Song, J.   Nature Communications, 16(1), 2469, April 2025.  

Abstract 

Governments worldwide have pledged to reduce antimicrobial use in the agri-food system. This study projects global livestock antibiotic use quantities through 2040 under various scenarios. This work indicates that under a business-as-usual scenario, global antibiotic use could reach ~143,481 tons by 2040, representing a 29.5% increase from the 2019 baseline of ~110,777 tons. However, alternative scenarios suggest that these projections could vary by +14.2% to -56.8%, depending on changes in livestock biomass and antibiotic use intensity. A key contribution of this research is the development of the Livestock Biomass Conversion method, a novel indicator offering improved accuracy in estimating livestock biomass. The findings have important policy implications, highlighting that meaningful reductions in antibiotic use quantity can only be achieved through coordinated efforts targeting both antibiotic use intensity and livestock biomass. 

Does neighborhood matter? The effect of spatial proximity on farmers technical efficiency level, with Atakelty Hailu,  Agricultural Economics, 1-13, Feb. 2022.

Abstract 

This article examines the effects of neighborhood on the farmer's technical efficiency (TE) level, adopting a stochastic frontier and spatial Durbin regression models. Our study exploits a three-wave household-level panel data from the Ethiopian Rural Socioeconomic Survey (ERSS) collected between 2011 and 2015. We find that farmers have an average TE score of 53%, implying a substantial potential for improvement in the production level. We further find that there is a positive and statistically significant spatial interdependence in TE levels between farms in neighboring communities. Input use, education, and other demographic characteristics are found to have significant positive direct and indirect effects. The findings suggest that policies and programs targeting productivity improvements in agriculture need to consider spatial spillover effects. 

Costs and equity of uncertain greenhouse gas reductions: Fuel, food and negative emissions in Sweden, with Ing-Marie Gren, Energy Economics, 105638, Dec. 2021.  

Abstract

Reducing emissions of greenhouse gases (GHG) by reduction of fuel and food consumption and by implementation of negative emissions (such as forest carbon sequestration and carbon capture and storage) has been suggested in both scientific literature and practice, but there exist no calculations of the cost efficient combination of these measures. One challenge for calculations is the uncertainty in reductions of GHG, in particular for negative emissions, depending on e.g. stochastic weather conditions. This paper develops a static model with probabilistic emission constraints to calculate cost efficient emission reductions in the transportation (gasoline and diesel) and food (meat and dairy products) sectors combined with negative emission (carbon sequestration and carbon capture and storage technologies) creation in Sweden under uncertainty. The results show that emission reductions in fuel and food consumption are relatively expensive, and that carbon sequestration are relatively low cost measures. We also show that the regional effects at the county level are regressive, that is, that relatively poor counties will carry large cost burdens in the cost efficient solutions and that this effect is increased when negative emissions are included but decreased when uncertainty is considered. 

Social capital, economic development and carbon emissions:  Empirical evidence from counties in Sweden, with George Marbuah and Ing-Marie Gren,  Renewable and Sustainable Energy Reviews, 152, 111691, Dec. 2021.

Abstract

Several studies have found empirical evidence for the role of social capital in environmental management where a high level of social capital reduces emissions of pollutants, and other studies point out a negative relation between income and environmental performance. Therefore, this paper examines if and how social capital explains Swedish county-level per capita CO2 emissions together with income in the period 2000–2017. A social capital composite index is constructed and different specifications of impacts on CO2 emissions of social capital and income and functional forms, linear and non-linear, are tested. The system generalized method of moments (GMM) is used to account for endogeneity in the presence of dynamic and spatial effects. Robust results are negative and significant effects of social capital on emissions, and positive effects of income. Other common results observed are significant dynamic and spatial carbon emissions effects.