roughly 30-220 percent more likely to have ever had contact with an extension agent than female-headed households. Similarly, Doss and Morris (2001) find in their study of Ghana that, on average, female farmers reported significantly fewer contacts with extension agents than male farmers; at the same time, they find that extension visits are a significant positive determinant of decision to adopt new technologies.

Doss and Morris (2001) argue, however, that the differential pattern of extension contact by gender may have less to do with gender per se and more to do with the fact that extension agents tend to approach farmers who are relatively better-off in terms of access to and/or endowments of land, labor, and capital (both human and financial), and who might already have a history of adopting technological innovations, given that these factors are often important for the decision to adopt new technologies. To the extent that women are under-represented among these betteroff farmers, the more likely extension agents are to overlook them in their extension programs.

In addition, the standard extension models used to provide information and training on new technologies to farmers are often not explicitly designed to reach women. In recent years, however, many countries in sub-Saharan Africa have intensified their efforts to reach female farmers, oftentimes with success. For example, Due et al. (1997) find in Tanzania that the hiring of female extension officers contributed to increased extension contact with female farmers. Furthermore, they find that, with the hiring of female extension agents, male extension agents became more effective in reaching female farmers. The use of female extension agents might be particularly important in settings where cultural or social norms restrict the interaction of unrelated men and women.

_Credit._ The lack of credit also often acts as an important constraint to technology adoption for poor households, given that they may not be able to afford the investment costs associated with introducing a new technology and/or the often higher working capital requirements associated with its use. In many cases, the ability of the farmer to obtain (sufficient) credit depends on land tenure status and land size, as land often is the main collateralizable asset in the hands of farmers. To the extent that farmers have weaker land tenure rights or possess small or lessproductive lands, obtaining credit, particularly from institutional sources, might be more difficult (or costlier). Careful studies of differential adoption rates owing to differential access to credit based on gender are largely unavailable. As Section 6 discusses, however, women are often more likely to be credit-constrained than men, which allows us to infer that the adoption rate among women is more likely to be lower as a result.

# _Effects of technology adoption on women’s individual agricultural production_

Several studies in sub-Saharan Africa find that women’s individual agricultural productivity and control over resources and decision-making have declined as households have increasingly adopted new technologies and shifted to commercial crop production. For example, Kumar (1994) finds in Zambia that women either independently or jointly managed 60 percent of the area under local maize cultivation but only 25 percent of the area under hybrid maize cultivation, with women’s involvement in decision-making related to agricultural production lower in households that adopted hybrid maize. Similarly, von Braun and Webb (1989) find that with the 27