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Research Approach

We combine detailed micro-level socioeconomic data from household surveys with high-definition GIS (Geographic Information System) data, adapting a stochastic profit frontier approach to the multi-product farm reality of the rural areas in developing countries. This statistical method allows us to diagnose bottlenecks (problem definition) while simultaneously informing adequate policy formulation and narrowing down the portfolio for the selection of the preferred policy option.

By recognizing the fact that farmers are productive units optimizing an objective function subject to a set of constraints, we ground our analysis within the framework of agricultural household models and consumer and producer theory. The typology resulting from the stochastic profit frontier analysis deals with many of the problems that previous typologies have suffered from. The efficiency indicator is a continuous measure, similar to a score, and its interpretation is direct and simple. The functional form used for its estimation is flexible and imposes a limited structure on the analysis. Moreover, it is possible to calculate the stochastic profit frontier using both semi- and fully non-parametric estimation methods. Finally, the stochastic profit frontier approach can estimate the parameters involved in a constrained optimization process and allows for random shocks, a setup that is suitable to model farmers‘ decision-making processes and analyze the opportunities and challenges they face.

Progress, Research Results, and Major Research Findings in 2010

The project‘s results have been validated by the main stakeholders in Peru (Ministry of Finance, Ministry of Agriculture, Ministry of Trade, and IADB) and by many academics specializing in rural development and spatial typologies in Ecuador (RIMISP, Universidad Andina Simon Bolivar). The typology constructed with our methodology allows for the construction of micro-regions based on the following dimensions: agricultural potential, farm efficiency, district level poverty, and access costs. In order to assess the robustness of our frontier estimations and resulting typologies to less restrictive parametric assumptions, we have also developed a semi-parametric approach to estimate stochastic profit frontiers with environmental variables. Our preliminary results indicate ranking of farmers (micro- regions) by efficiency estimates are extremely similar to rankings from parametric assumptions, though the order of magnitudes are very different.

Finally, a version for Guatemala is currently being used for discussions with Guatemalan policymakers to develop the country‘s strategic plan for food security; data collection to construct a typology for Mexico, Honduras, Paraguay, Uganda, and Tanzania is also underway.

Plans for 2011

We expect to finalize the work on semi-parametric estimation of stochastic profit frontiers by May 2011, out of which a methodological journal article will be produced. With data collection finished by February 2011 for Mexico, we expect a first version of that typology to be ready by April 2011, with validation activities with Mexican stakeholders to follow. For Guatemala, current work on adapting the typology to a nutrition-oriented welfare measure (instead of standard poverty indices) should be delivered by June 2011. It is expected that the outputs from the stochastic profit frontier analysis will be combined with relevant information and indicators for food security in Guatemala to build a typology that will be a central piece of the government‘s strategic plan for food security. We will also finish a similar typology for Honduras, Paraguay, Uganda, and Tanzania.


Project Duration: Objectives of project

Maximo Torero, Carlos Martins-Filho, Miguel Robles, Manuel Hernandez, Cristina Chiarella January 2009 – August 2011

Recent drastic volatility in food prices has raised serious concerns about food and nutrition security across the world. While a coordinated response is urgently needed at the international and regional levels, the effectiveness of various country-level responses is also critical for responding to the crisis. Coherent action is needed to help vulnerable populations cope with the hikes in their food bills, to assist farmers in developing countries respond to the opportunity posed by rising demand for their products, and to provide information for evidence- based related macro-economic policies. Since the implications of high and volatile food prices are radically different across countries and population groups, the appropriate policy responses, as well as their scale, prioritization, and sequencing, must be developed and adapted to country-specific needs and conditions.

The goal of this project is improved food security for the poor in developing countries during the current food crisis and increased resilience of developing countries‘ food systems against future crises. The project focuses on building a global research-based monitoring and capacity-strengthening device for successful identification and implementation of the appropriate policy actions in response to the food crisis.

Research Approach

Food price and food security information tends to be outdated, spotty, and insufficiently disaggregated to local levels. The main innovation of this project is the creation of an open-access policy information Food Security Portal, launched in January 2010 and designed to strengthen the ability of policymakers around the globe to respond quickly and effectively to changes in the dynamic world food system. The Portal presents food price and security datasets, drawing on food price and security data from the FAO, WFP,World Bank, USDA, and other organizations, as well as key IFPRI publications. The project also emphasizes the development of food price policy analysis tools designed to provide simple, visual analysis of global and regional price data. These tools utilize both qualitative and quantitative approaches and provide simulations of the effects of various fiscal policies and price scenarios.

2010 Internal Program Review-Markets, Trade and Institutions Division Page 18

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