Pursuit of the triple bottom line of economic, community and ecological sustainability has increased the complexity of fishery management; fisheries assessments require new types of data and analysis to guide science-based policy in addition to traditional biological information and modeling. We introduce the Fishery Performance Indicators (FPIs), a broadly applicable and flexible tool for assessing performance in individual fisheries, and for establishing cross-sectional links between enabling conditions, management strategies and triple bottom line outcomes. Conceptually separating measures of performance, the FPIs use 68 individual outcome metrics—coded on a 1 to 5 scale based on expert assessment to facilitate application to data poor fisheries and sectors—that can be partitioned into sector-based or triple-bottom-line sustainability-based interpretative indicators. Variation among outcomes is explained with 54 similarly structured metrics of inputs, management approaches and enabling conditions. Using 61 initial fishery case studies drawn from industrial and developing countries around the world, we demonstrate the inferential importance of tracking economic and community outcomes, in addition to resource status.

Household investment in preventative health products in developing countries is typically low even though the returns to such products are high. In this paper, we experimentally estimate demand curves for health products and test whether (1) information about health risk, (2) cash liquidity, (3) peer effects, and (4) intra-household differences in preferences affect demand. In our main experiment in Kenya involving children's shoes -critical for preventing hookworm infection -price is by far the most important predictor of purchase. Providing liquidity and targeting women also increased demand. Information had no effect even though we find that genuine learning occurred. We find no peer effects even though people discussed the product purchase decision extensively. We find similar results for price and information in three smaller studies in Guatemala, India, and Uganda in experiments involving soap and multivitamins. We are grateful to research assistance from

Household investment in preventative health products is low in developing countries even though benefits from these products are very high. What interventions most effectively stimulate demand? In this paper, we experimentally estimate demand curves for health products in Kenya, Guatemala, India, and Uganda and test whether (1) information about health risk, (2) cash liquidity, (3) peer effects, and (4) intra-household differences in preferences affect demand. We find households to be highly sensitive to price and that both liquidity and targeting women increase demand. We find no effect of providing information, although genuine learning occurred, and we find no evidence of peer effects, although subjects discussed the product purchase decision extensively.

Household investment in preventative health products is low in developing countries even though benefits from these products are very high. What interventions most effectively stimulate demand? In this paper, we experimentally estimate demand curves for health products in Kenya, Guatemala, India, and Uganda and test whether (1) information about health risk, (2) cash liquidity, (3) peer effects, and (4) intra-household differences in preferences affect demand. We find households to be highly sensitive to price and that both liquidity and targeting women increase demand. We find no effect of providing information, although genuine learning occurred, and we find no evidence of peer effects, although subjects discussed the product purchase decision extensively.

Household investment in preventative health products is low in developing countries even though benefits from these products are very high. What interventions most effectively stimulate demand? In this paper, we experimentally estimate demand curves for health products in Kenya, Guatemala, India, and Uganda and test whether (1) information about health risk, (2) cash liquidity, (3) peer effects, and (4) intra-household differences in preferences affect demand. We find households to be highly sensitive to price and that both liquidity and targeting women increase demand. We find no effect of providing information, although genuine learning occurred, and we find no evidence of peer effects, although subjects discussed the product purchase decision extensively.

No abstract

No abstract