Modeling: At a Glance

Modeling Approach

Why economic modeling?

Economic modeling enables projections to be made in order to objectively evaluate worldwide impacts from biofuels. Understanding global pathways of impact – how the expansion of biofuels affects international commodity markets and influences different countries in the developing world — is crucial for two reasons: 1) Large-scale global biofuels development will have sharp, direct effects on hunger and the timely achievement of the Millennium Development Goals through world agricultural prices. 2) Global biofuels expansion will fundamentally affect the economic environment in which more local biofuels projects are carried out.

Building an analytical platform, which tracks fluctuations of agricultural prices and their transmission into the developing world, allows us to measure and quantify the pathways of impact, as well as assess the feasibility of investing in biofuels systems in poor, developing countries.

How are these projections being made?

We are building on what already has been done – linking together and adapting existing models in order to capture the novel connections between the energy and food markets. Specifically, we are working with country modelers to input collected data into a general equilibrium, economy-wide trade model (GTAP), and a more highly disaggregated (by country) partial equilibrium agricultural market model (IMPACT), which together enable the tracking of fluctuating agricultural prices around the world and their transmission into the developing world.

There are a number of consistency checks which we should consider, when linking general- and partial-equilibrium models. Firstly, one can ensure consistency between the growth of total value-added from the agricultural sector within the economy-wide general equilibrium framework and the growth in agricultural output from the partial-equilibrium model. Another type of check is that for total population growth, which is considered exogenous to both models and which serves as an important driver of socio-economic change within both frameworks — especially with respect to energy and food demand.

What are the scenarious

After building linkages between the energy and food markets through economic modeling, projections are made utilizing scenarios. Simply put, separate scenarios have specific economic or policy-relevant conditions that are assumed, and influence projections about agricultural prices and production. By comparing results, the three scenarios evaluate the impacts of two important events over the past several years: the rise of world oil prices and the emergence of a global biofuels industry.

Modeling Linkage

What are we looking at specifically?

Modeling is necessarily limited to focus on the following main data types and key variables. Data for global modeling includes: world production, consumption, trade, processing of major feedstock crops for GTAP (soybeans, other oilseeds, palm oil, sugar cane, sugar beets, maize, sorghum, cassava) by country, and also world energy production major energy resources, energy consumption, energy trade for GTAP by country (crude oil, coal, gasoline, natural gas, diesel, biodiesel, ethanol). Data for domestic modeling includes basic production (disappearance) data, data for household linkages, data on biofuels production, other data.

Which countries and why?

According to expert opinion, based on decades of modeling and analyses, world agricultural markets are dominated by 8 to 10 countries. Supply and demand in the U.S., the European Union (EU), Canada, Australia, Russia, Brazil, China, India, and Indonesia make world markets due to the size of production and consumption in these countries. With biofuels, the behavior of the five largest producers – the U.S., Brazil, the EU, China, and India – is particularly critical. Therefore our focus is on documenting the policies, investments, technologies, trade policies and other factors that affect the rise of biofuels, and the degree to which supply changes within these countries are transmitted to world markets.

In order to understand the precise effects of biofuels on equity and other distributional measures, while accounting for regional variations within different countries, there are several strategic country case studies in South Asia (India) and Sub Saharan Africa (Mozambique in East Africa and Senegal in West Africa). These countries were selected because of four reasons: 1) All three countries have discussed biofuels goals. National policymakers are in need of information about deciding stances on national biofuels programs. 2) We believe some of the most adverse effects of the rise of biofuels will be on the landless poor in nations in three parts of the world – South Asia, West Africa, and East Africa. 3) Data is available because data requirements for this project are relatively high. 4) Good collaboration record since extensive collaboration is necessary.

What makes our modeling approach special?

This model focuses on impacts of biofuels in specifically poor countries. We believe this is the first analytical attempt to quantify, at regional and global levels, the effects of biofuels development on crop production, consumption, and food security in poor countries. Additionally this model aims to objectively assess connections between energy and food markets in ways that can inform investors (at a large scale) on projects to improve the well-being of the poor.