Poverty Reduction Effects of Agricultural Technology Adoption: The Case of Improved Cassava Varieties in Nigeria

We use DNA‐fingerprinting to estimate the poverty reduction effect of adoption of improved cassava varieties in Nigeria. We estimate the counterfactual household income distribution of cassava producers by combining farm‐level treatment effects with a market‐level model. Our results suggest that adoption of improved cassava varieties has led to a 4.6 percentage point reduction in poverty, though this is sensitive to the measurement of adoption status. Therefore, accurate measurement of adoption is crucial for a more credible estimate of the poverty reduction effect of adoption. Our analysis also suggests that farmers who are more likely to be adopters are also likely to face higher structural costs. Addressing structural barriers that make improved technologies less profitable for the poor would therefore be important to increase the poverty reduction effect of improved cassava varieties.     

Social capital,risk preference and adoption of improved farm land management practices in Ethiopia

Many developing countries grapple with high rates of farmland degradation and low agricultural productivity amidst increasing climate variability. Considerable efforts have been exerted to promote the diffusion of improved farmland management to address these challenges. Despite these efforts, adoption rates, especially of soil conservation and water harvesting technologies, are still low, which has been the subject of investigation in several studies in Ethiopia and elsewhere. Most studies on the adoption of these technologies, however, tend to focus on economic incentives only, paying little attention to the role of social capital. This article provides evidence of the effects of different dimensions of social capital on innovation adoption across households holding different levels of risk aversion. We address this issue by using cross section and panel data from Ethiopia. Results show that social capital plays a significant role in enhancing the adoption of improved farmland management practices. We also find evidence that the effect of social capital across households with heterogeneous risk taking behavior is different.     

Can smallholder farmers adapt to climate variability,and how effective are policy interventions? Agent‐based simulation results for Ethiopia

Climate variability with unexpected droughts and floods causes serious production losses and worsens food security, especially in Sub‐Saharan Africa. This study applies stochastic bioeconomic modeling to analyze smallholder adaptation to climate and price variability in Ethiopia. It uses the agent‐based simulation package Mathematical Programming‐based Multi‐Agent Systems (MPMAS) to capture nonseparable production and consumption decisions at household level, considering livestock and eucalyptus sales for consumption smoothing, as well as farmer responses to policy interventions. We find the promotion of new maize and wheat varieties to be an effective adaptation option, on average, especially when accompanied by policy interventions such as credit and fertilizer subsidy. We also find that the effectiveness of available adaptation options is quite different across the heterogeneous smallholder population in Ethiopia. This implies that policy assessments based on average farm households may mislead policy makers to adhere to interventions that are beneficial on average albeit ineffective in addressing the particular needs of poor and food insecure farmers.     

Sorting out the practical concerns in World Wide Web advertising

Although the World Wide Web has become an innovative way to reach an ever-fragmenting mass market, the effort to advertise on the Web has been frustrated by some technical and practical problems. This paper examines the current state of affairs and reflects on the equipment, software and measurement-related problems. By way of providing some practical strategies to advertisers, it appraises the software, hardware and measurement solutions.     

Advertising Implications of Millennials' Motives and Device-Platform Consideration Sets: An Exploratory Study

abstract

Comprising between 25 to 30 percent of the population with huge and growing purchasing power, Millennials, as a demographic group, are of great interest to advertisers and media companies alike. Their traits and characteristics have been studied extensively. This fact notwithstanding, reaching millennials continues to be a challenge. Based on Grounded Theory, the cohort's mind-set, behavioral tendencies as well as their perceived device-platform cognitive fit and device-platform consideration sets are explored. The study provides a window into the innovation-adoption process they go through, contributing to device-platform choice theory. The findings suggest that Millennials have an over-arching concern about availability/connectivity, responsiveness and reliability of internet access, followed by convergence across-platforms. The cohort exhibits control and decision anxiety over devices and platforms.     

The Effect of the World Wide Web on Agency—Advertiser Relationships: Towards A Strategic Framework

Buffeted by the fragmentation of media and markets, the World Wide Web has started transforming the competitive landscape in the advertising industry. Increasingly, advertising agencies are forced to compete with in-house CIS/MIS departments, public relations agencies and computer graphic studios and boutiques for Web-related accounts. Vis-à-vis the immediacy of the challenge, agencies are forced to either broaden their business horizon to include all aspects of communications or to stay focused on their core business-making advertisements for traditional media. This article examines the possible effects of the World Wide Web on the blurring of boundaries in advertiser- agency performed promotional activities, analyses the similarities in the strategies adopted in the transition from radio to television, and appraises the options which agencies face in adopting the Web.     

Mismeasurement and efficiency estimates: Evidence from smallholder survey data in Africa

Smallholder agriculture in sub-Saharan Africa is commonly characterised by high levels of technical inefficiency. However, much of this characterisation relies on self-reported input and production data, which are prone to systematic measurement error. We show theoretically that non-classical measurement error introduces multiple identification challenges and sources of bias in estimating smallholders' technical inefficiency. We then empirically examine the implications of measurement error for the estimation of technical inefficiency using smallholder farm survey data from Ethiopia, Malawi, Nigeria and Tanzania. We find that measurement error in agricultural input and production data leads to a substantial upward bias in technical inefficiency estimates (by up to 85% for some farmers). Our results suggest that existing estimates of technical efficiency in sub-Saharan Africa may be severe underestimates of smallholders' actual efficiency and what is commonly attributed to farmer inefficiency may be an artefact of mismeasurement in agricultural data. Our results raise questions about the received wisdom on African smallholders' production efficiency and prior estimates of the productivity of agricultural inputs. Improving the measurement of agricultural data can improve our understanding of smallholders' production efficiencies and improve the targeting of productivity-enhancing technologies.