An Economic Assessment of Banana Genetic Improvement and ...
An Economic Assessment of Banana Genetic Improvement and ... An Economic Assessment of Banana Genetic Improvement and ...
CHAPTER 6 A Trait-Based Model of the Potential Demand for Transgenic Banana Cultivars in Uganda Svetlana Edmeades and Melinda Smale This chapter derives farmer demand for planting material from the demand for genetic traits and cultivar attributes in an agricultural household model with missing markets, building on the general model presented in Chapter 2. 1 Applied to the sample data described in Chapter 2 and Appendix D, the econometric approach is used to explore several issues of importance to national decisionmakers. We begin by identifying the determinants of farmer demand for planting material of cooking banana cultivars that are candidate hosts for insertion of pest and disease resistance by NARO. At the level of the individual farm household, demand for planting material is defined by the decision to “adopt” (use) and the scale of use (number of mats). We then use the fitted equation to generate three pieces of information. First, we develop client prototypes by describing the characteristics of farm households with high and low predicted demands for particular cultivars. This exercise illustrates how the choice of host planting material for genetic transformation can have social consequences. Second, we use the example of Nakitembe to estimate the total size of industry demand for planting material of a genetically transformed host cultivar. Third, we simulate changes in demand for planting material when resistance traits are inserted, with varying degrees of effectiveness, and when other supporting public investments are made in extension, market infrastructure, and education. The simulation demonstrates how the magnitude of the payoff to research investment crucially depends on other types of investments. This point reiterates that, as documented in other literature about agricultural innovations (see Chapter 1), seed-based technical change depends not only on the release of an improved cultivar, but also on the markets, information, and policies that enable its widespread adoption. Theoretical Model The trait-based model in this chapter (Edmeades 2003) derives the demand for planting material in the decisionmaking framework of the agricultural household with imperfect markets (Singh, Squire, and Strauss 1986). The conceptual framework draws from Lancaster’s theory of consumer choice (1966) and models of demand for farm input and output characteristics (Ladd and Martin 1976; Ladd and Suvannunt 1976). The model focuses on the demand for planting material, or seed in the broad sense, including endemic farmers’ cultivars, cultivars improved through crossing, and genetically engineered cultivars as special cases. 1 A more detailed version of this chapter was published in Agricultural Economics in 2006. 75
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CHAPTER 6<br />
A Trait-Based Model <strong>of</strong> the Potential Dem<strong>and</strong><br />
for Transgenic <strong>Banana</strong> Cultivars in Ug<strong>and</strong>a<br />
Svetlana Edmeades <strong>and</strong> Melinda Smale<br />
This chapter derives farmer dem<strong>and</strong> for planting material from the dem<strong>and</strong> for genetic<br />
traits <strong>and</strong> cultivar attributes in an agricultural household model with missing markets,<br />
building on the general model presented in Chapter 2. 1 Applied to the sample data described<br />
in Chapter 2 <strong>and</strong> Appendix D, the econometric approach is used to explore several<br />
issues <strong>of</strong> importance to national decisionmakers. We begin by identifying the determinants <strong>of</strong><br />
farmer dem<strong>and</strong> for planting material <strong>of</strong> cooking banana cultivars that are c<strong>and</strong>idate hosts for<br />
insertion <strong>of</strong> pest <strong>and</strong> disease resistance by NARO. At the level <strong>of</strong> the individual farm household,<br />
dem<strong>and</strong> for planting material is defined by the decision to “adopt” (use) <strong>and</strong> the scale <strong>of</strong><br />
use (number <strong>of</strong> mats). We then use the fitted equation to generate three pieces <strong>of</strong> information.<br />
First, we develop client prototypes by describing the characteristics <strong>of</strong> farm households with<br />
high <strong>and</strong> low predicted dem<strong>and</strong>s for particular cultivars. This exercise illustrates how the<br />
choice <strong>of</strong> host planting material for genetic transformation can have social consequences.<br />
Second, we use the example <strong>of</strong> Nakitembe to estimate the total size <strong>of</strong> industry dem<strong>and</strong> for<br />
planting material <strong>of</strong> a genetically transformed host cultivar. Third, we simulate changes in<br />
dem<strong>and</strong> for planting material when resistance traits are inserted, with varying degrees <strong>of</strong> effectiveness,<br />
<strong>and</strong> when other supporting public investments are made in extension, market infrastructure,<br />
<strong>and</strong> education. The simulation demonstrates how the magnitude <strong>of</strong> the pay<strong>of</strong>f to<br />
research investment crucially depends on other types <strong>of</strong> investments. This point reiterates that,<br />
as documented in other literature about agricultural innovations (see Chapter 1), seed-based<br />
technical change depends not only on the release <strong>of</strong> an improved cultivar, but also on the<br />
markets, information, <strong>and</strong> policies that enable its widespread adoption.<br />
Theoretical Model<br />
The trait-based model in this chapter (Edmeades 2003) derives the dem<strong>and</strong> for planting material<br />
in the decisionmaking framework <strong>of</strong> the agricultural household with imperfect markets<br />
(Singh, Squire, <strong>and</strong> Strauss 1986). The conceptual framework draws from Lancaster’s theory<br />
<strong>of</strong> consumer choice (1966) <strong>and</strong> models <strong>of</strong> dem<strong>and</strong> for farm input <strong>and</strong> output characteristics<br />
(Ladd <strong>and</strong> Martin 1976; Ladd <strong>and</strong> Suvannunt 1976). The model focuses on the dem<strong>and</strong> for<br />
planting material, or seed in the broad sense, including endemic farmers’ cultivars, cultivars<br />
improved through crossing, <strong>and</strong> genetically engineered cultivars as special cases.<br />
1<br />
A more detailed version <strong>of</strong> this chapter was published in Agricultural <strong>Economic</strong>s in 2006.<br />
75