contemporaneous weather outcomes are muted. In general, fertilizer applications are made before weather outcomes are known, although farmers can make adjustments when fertilizer is applied in a series of doses and also reduce fertilizer applications when rains are late. As discussed, the practice of applying fertilizer in stages is reportedly uncommon in Ethiopia and our results indicating that farmers make other adjustments are mixed. The estimates for both models suggest that fertilizer use is reduced when rains are lower than normal, but the findings are statistically robust only when group means are included. And finally, the time effect estimates suggest that fertilizer demand increased between the first and second waves, even after adjusting for changes in other determinants. This provides indirect evidence of a positive trend in the adoption of fertilizer-using technologies that is consistent with technology adoption theory (Feder and Umali 1993).

# Conclusion

In this paper, we develop a conceptual framework in which the decision environment faced by agents providing inputs and services influences the farming methods (technologies) available to farmers and the relative profitability of those technologies. This and exogenous features of households and the land they farm combine to create the decision environments that lead to observed choices about applied technologies and derived fertilizer demand. Through this mechanism, the conceptual model suggests that heterogeneity in household decision environments explains the pervasive heterogeneity of household choices about using fertilizer observed in African survey data.

We then develop a consistent statistical model in which the implicit adoption function is influenced by market performance and the capacity of households to overcome market shortcomings. We argue that heterogeneity in the set of available technologies has ramifications for statistical models since the observed set of fertilizer-using technologies are not drawn from identical sets of locally available technologies, potentially leading to biased estimates. We address this problem by using a panel-selection model.

Results from the estimated model are consistent with the notion that adverse market conditions limit the availability and therefore the adoption of fertilizer-using technologies. Nevertheless, the results suggest that markets are present in rural Ethiopia and that, despite variations in market performance, farmers in the aggregate respond to relative prices. This provides a potential pathway for subsidies to stimulate demand. Still, lowering fertilizer prices may not change the decision environment for agents and farmers in fundamental ways, with the consequence that market performance and farmer choice revert to old equilibriums if subsidies are not maintained. Other research has shown that high transport and transaction costs in rural Ethiopia are structural constraints that penalize farmers by raising input prices and lowering output prices at the farmgate, setting economic perimeters on the adoption of fertilizer-using technologies. The conceptual model and findings from the empirical model suggest that policies that lower transaction costs, by supporting infrastructure improvements and by improving the business environment in which commercial agents operate, can generate deeper effects than do subsidies by expanding the technologies 21