This project aims to capture the medium to long-term spillover effects of financial markets and related stakeholders such as regulatory institutions on climate relevant emissions from land-use and changes to its pattern. Previous research has emphasized the spillovers of shocks, volatilities, and policy decisions from financial markets to commodity prices and thus on agricultural decisions. However, the long-term impacts of these spillovers, in terms of emissions have not been explored yet in a systematic global manner.

Quantifying such interrelations would have wide-reaching implications, not only in terms of highlighting possible pathways to minimize spillover effects, but also for financial market policies as well. In order to capture the nexus of financial and commodity markets, food price expectations, and its effects on planting decisions, we employ a state-of-the-art Bayesian vector autoregression (BVAR) model. In a second stage, we use the estimated BVAR framework to calibrate a partial equilibrium global integrated assessment model (IAM) of the agricultural sector. Speciffically, the BVAR model informs the IAM on agricultural price expectations, accounting for market volatilities and policies. The IAM provides long-term projections of the impact of future financial market scenarios, coupled with uncertainties of long-term climate change impacts.

The modeling frameworks

A Bayesian factor-augmented panel VAR model

A VAR framework for price expectations of global agricultural producers for the four most important primary food crops (corn, rice, soybean, and wheat) is developed in this project. The annual price expectations are modeled in a joint framework with past prices and climate data, as well as main indicators of world-wide agricultural markets, economic per capita growth, and monetary policy and market volatility indicators. The economic output, population, and financial policy indicators enter the model exogeneously. When using the VAR for future development projections, we will assume narrative scenario pathways for these indicators and assess multiple future (long-term) developments in-line with the sustainable socio-economic pathways framework (Fricko et al., 2015).

The annual GLOBIOM

The annual GLOBIOM model to measure land use responses resulting from the difference between the VAR-informed expected agricultural prices and the commodity prices impacted by financial and climate shocks, as well as their results on emissions. Specifically, the one-step ahead forecast of price expectations from the VAR model is used to construct price expectations of farmers. Based on these price expectations, agricultural producers allocate land for crops, livestocks, or forestry used. Future pathways of climate change are used as exogenous climate change shocks, which can impose shifts in the realized yields of crops. The resulting equilibrium price can differ from the initial one-term ahead forecast of the VAR model. The new equilibrium prices, as well as climate patterns are used to update the VAR model to obtain the forecasts for the next projection year. The results of these scenario will be used to quantify the impact of policies and volatility spillovers in terms of market disturbances, emissions, and deforestation.