Yiyong Cai

A framework for integrated assessment of food production economics in South Asia under climate change

Agriculture is a sector vulnerable to climate change. The potential decline of crop yields from this vulnerability has important policy implications for food security in South Asia. In this study an integrated assessment modelling framework is proposed to link a global economic model with global climate models via an econometric model of crop productivity. It is then used to examine the impact of climate change on food security in individual South Asian countries by exploring the interaction between climate-induced productivity change and changes in food production and food prices. The results of our simulations suggest that unfavourable climate change can reduce food production significantly from the historical trend and create upward pressure on food prices. This, in turn, will have serious adverse impacts on food security in the South Asian region. We present an integrated model of food security in South Asia under climate change.We link a CGE model with climate models via an econometric model of crop yields.We explore interactions among climate change, food production and food prices.Climate change is expected to have serious impacts on food security in South Asia.

Oil, Gas and Conflict: A Mathematical Model for the Resource Curse

Oil and natural gas are highly valuable natural resources, but many countries with large untapped reserves suffer from poor economic and social-welfare performance. This conundrum is known as the resource curse. The resource curse is a result of poor governance and wealth distribution structures that allow the elite to monopolize resources for self-gain. When rival social groups compete for natural resources, civil unrest soon follows. While conceptually easy to follow, there have been few formal attempts to study this phenomenon. Thus, we develop a mathematical model that captures the basic elements and dynamics of this dilemma. We show that when resources are monopolized by the elite, increased exportation leads to decreased domestic production. This is due to under-provision of the resource-embedded energy and industrial infrastructure. Decreased domestic production then lowers the marginal return on productive activities, and insurgency emerges. The resultant conflict further displaces human, built, and natural capital. It forces the economy into a vicious downward spiral. Our numerical results highlight the importance of governance reform and productivity growth in reducing oil-and-gas-related conflicts, and thus identify potential points of intervention to break the downward spiral.

Patterns of crop cover under future climates

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

Disaggregating Electricity Generation Technologies in CGE Models

We illustrate the importance of disaggregating electricity generation when considering responses to environmental policies. We begin by reviewing various approaches to electric sector modelling in Computable General Equilibrium (CGE) models, and then clarify and expand upon the structure and calibration of the “technology bundle” approach. We also simulate the proposed U.S. Clear Power Plan and show how a disaggregate electricity sector can change results. Our simulations indicate that both the ability to switch between generation technologies and the manner of aggregation in electricity production are important for quantifying the economic costs of the plan.

Effects of foreign direct investment in African agriculture

Purpose – The purpose of this paper is to review the key issues surrounding foreign direct investment (FDI) in agriculture, and examine the potential impacts of FDI in African agriculture. Design/methodology/approach – The dynamic Global Trade Analysis Project model (GDyn) is used to analyse the potential impacts of improvements in land productivity and FDI in Africa. Findings – The results illustrate that combined efforts to improve land productivity and growth in FDI could potentially increase Africa’s share in global agricultural output and exports, particularly with respect to oil seeds, sugar, and cotton. Originality/value – The authors employ a global economy-wide modelling framework to simulate the effects of growth in FDI in African agriculture.

Simulating emissions intensity targets with energy economic models: algorithm and application

Pressure on developing economies to make quantifiable emissions reduction commitments has led to the introduction of intensity based emissions targets, where reductions in emissions are specified with reference to some measure of economic output. The Copenhagen commitments of China and India are two prominent examples. Intensity targets substantially increase the complexity of policy simulation and analysis, because a given emissions intensity target could be satisfied with a range of emissions and output combinations. Here, a simple algorithm, the Iterative Method, is proposed for an energy economic model to find a unique policy solution that achieves an emissions intensity target at minimum economic loss. We prove the mathematical properties of the algorithm, and compare its numerical performance with other methods’ in the existing literature.

Modelling Complex Emissions Intensity Targets with a Simple Simulation Algorithm

Designing, modelling and analysing global emissions policies are becoming increasingly complex undertakings. Pressure on developing economies to make quantifiable emissions reduction commitments has led to the introduction of intensity based emissions targets, where reductions in emissions are specified with reference to some measure of output, generally gross domestic product. The Copenhagen commitments of China and India are two prominent examples. From a modelling perspective, intensity targets substantially increase the complexity of analysis, with respect to both theoretical design and computational implementation. Here, a clear and practically relevant theoretical design is used to present a new algorithm that can be applied to frameworks that model the complex interaction that occurs between emissions policy instruments, emissions levels and output effects under an emissions intensity target. The coding of the algorithm has been simplified to allow for easy integration into a range of modelling frameworks. Further development of the algorithm that allows for more complex theoretical design structures is possible.

Economic shifts in agricultural production and trade due to climate change

In addition to expanding agricultural land area and intensifying crop yields, increasing the global trade of agricultural products is one mechanism that humanity has adopted to meet the nutritional demands of a growing population. However, climate change will affect the distribution of agricultural production and, therefore, food supply and global markets. Here we quantify the structural changes in the global agricultural trade network under the two contrasting greenhouse gas emissions scenarios by coupling seven Global Gridded Crop Models and five Earth System Models to a global dynamic economic model. Our results suggest that global trade patterns of agricultural commodities may be significantly different from today’s reality with or without carbon mitigation. More specifically, the agricultural trade network becomes more centralised under the high CO2 emissions scenario, with a few regions dominating the markets. Under the carbon mitigation scenario, the trade network is more distributed and more regions are involved as either importers or exporters. Theoretically, the more distributed the structure of a network, the less vulnerable the system is to climatic or institutional shocks. Mitigating CO2 emissions has the co-benefit of creating a more stable agricultural trade system that may be better able to reduce food insecurity.