Posts Tagged ‘India’

Poverty mapping based on livelihood assets: A meso-level application in the Indo-Gangetic Plains, India

Posted by on , in Journal Articles

Published in Applied Geography 30(1):112-125, 2010

Poverty mapping based on livelihood assets: A meso-level application in the Indo-Gangetic Plains, India

Olaf Erenstein, Jon Hellin and Parvesh Chandna

Poverty maps are an increasingly popular mode of visualizing the spatial dimension of poverty. They help guide priority-setting and target poverty-alleviation interventions. The utility of poverty maps can be enhanced by spatially disaggregating the underlying causes of poverty. One promising approach explored in this paper is the use of livelihood assets – natural, physical, human, social and financial – the building blocks of sustainable livelihoods. We illustrate the approach by mapping and contrasting poverty and livelihood assets within the Indian Indo-Gangetic Plains drawing on district-level indicators and livelihood asset-based principal components. The relatively low poverty incidence in the north-western plains is associated with an overall favorable livelihood asset base, particularly pronounced for natural and financial capitals. There is a marked gradient with poverty increasing eastwards, reflecting a similarly marked decline in livelihood assets. The overall unfavorable livelihood asset base in the mid-Gangetic Plains of Bihar and Eastern Uttar Pradesh provides a particularly challenging spatial poverty trap. The maps and regional contrasts of poverty and livelihood assets provide a foundation for future research and development work and reiterate the need for cross-sectoral and inter-disciplinary approaches.

Maize-poultry value chains in India: Implications for research and development

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Published in Journal of New Seeds 10: 245-263

Maize-poultry value chains in India: Implications for research and development

Jon Hellin, Olaf Erenstein

Rapid growth of the poultry industry in India has caused an increased demand for maize (Zea mays L.). Poultry feed contains 60-65% of maize and approximately 50% of India’s annual maize harvest of 19 million tons is used for poultry feed. This article reports on a qualitative study of maize-poultry value chains. It identifies bottlenecks in the value chains and highlights some of the impediments to the uptake of quality-protein maize (QPM; maize with elevated levels of the essential amino acids lysine and tryptophan), which is being heavily promoted by Indian maize breeders. Further research is needed to produce QPM varieties that outperform normal maize varieties and to work more closely with the poultry industry so that QPM value chains become more demand than supply-driven.

Specification effects in zero tillage survey data in South Asia’s rice-wheat systems

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Published in Field Crops Research 111(1-2): 166-172

Specification effects in zero tillage survey data in South Asia’s rice–wheat systems

Olaf Erenstein

Specification effects in terms of how technology options are contrasted can introduce bias in impact assessment. In a companion paper we evaluated the on-farm impacts of zero tillage (ZT) wheat as a resource-conserving technology in the rice–wheat systems of India’s Haryana State and Pakistan’s Punjab province [Erenstein, O., Farooq, U., Malik, R.K., Sharif, M., 2008. On-farm impacts of zero tillage wheat in South Asia’s rice–wheat systems. Field Crop Res. 105, 240–252]. The underlying field work surveyed plots of full adopters (only ZT plots), partial adopters (ZT and conventional tillage [CT] plots on same farm) and non-adopters (only CT plots). The companion paper assumes that the comparison between the ZT plots of full plus partial adopters and CT plots of partial adopters is the least-biased assessment of ZT’s on-farm impact. Here we revisit this underlying assumption and draw on complementary farm survey findings to illustrate the extent of specification effects in the assessment of on-farm impacts of ZT wheat in the same study areas. The study thereby distinguishes between three contrasts between ZT and CT within the same dataset: (1) plain contrast (all plots of adopters and non-adopters); (2) adopter-only contrast (full and partial adopters only, as used in Erenstein et al. [Erenstein, O., Farooq, U., Malik, R.K., Sharif, M., 2008. On-farm impacts of zero tillage wheat in South Asia’s rice–wheat systems. Field Crop Res. 105, 240–252]); (3) pair-wise contrast (partial adopters only). Proceeding from type 1 to type 3 comparisons the number of observations decrease but this is compensated by an increasing ability to control for variation. The ability of type 3 comparisons to pick up relatively small but significant differences is an important consideration in farm survey impact assessment. However, there is also an increase in partial adoption bias and further follow-up studies are needed to understand the implications of this. The comparisons show that the ZT effects on savings for diesel, tractor time and cost for wheat cultivation are particularly robust. In Haryana ZT’s positive implications for yield and the other financial indicators were also statistically robust, but in Punjab these were sensitive to specification effects. Particularly sensitive to specification effects were the ZT effects on the productivity of applied water in both sites.

Specification effects in zero tillage survey data in South Asia’s rice–wheat systems

Posted by on , in Journal Articles

Published in Field Crops Research 111(1-2): 166-172

Specification effects in zero tillage survey data in South Asia’s rice–wheat systems

Olaf Erenstein

Abstract:  Specification effects in terms of how technology options are contrasted can introduce bias in impact assessment. In a companion paper we evaluated the on-farm impacts of zero tillage (ZT) wheat as a resource-conserving technology in the rice–wheat systems of India’s Haryana State and Pakistan’s Punjab province [Erenstein, O., Farooq, U., Malik, R.K., Sharif, M., 2008. On-farm impacts of zero tillage wheat in South Asia’s rice–wheat systems. Field Crop Res. 105, 240–252]. The underlying field work surveyed plots of full adopters (only ZT plots), partial adopters (ZT and conventional tillage [CT] plots on same farm) and non-adopters (only CT plots). The companion paper assumes that the comparison between the ZT plots of full plus partial adopters and CT plots of partial adopters is the least-biased assessment of ZT’s on-farm impact. Here we revisit this underlying assumption and draw on complementary farm survey findings to illustrate the extent of specification effects in the assessment of on-farm impacts of ZT wheat in the same study areas. The study thereby distinguishes between three contrasts between ZT and CT within the same dataset: (1) plain contrast (all plots of adopters and non-adopters); (2) adopter-only contrast (full and partial adopters only, as used in Erenstein et al. [Erenstein, O., Farooq, U., Malik, R.K., Sharif, M., 2008. On-farm impacts of zero tillage wheat in South Asia’s rice–wheat systems. Field Crop Res. 105, 240–252]); (3) pair-wise contrast (partial adopters only). Proceeding from type 1 to type 3 comparisons the number of observations decrease but this is compensated by an increasing ability to control for variation. The ability of type 3 comparisons to pick up relatively small but significant differences is an important consideration in farm survey impact assessment. However, there is also an increase in partial adoption bias and further follow-up studies are needed to understand the implications of this. The comparisons show that the ZT effects on savings for diesel, tractor time and cost for wheat cultivation are particularly robust. In Haryana ZT’s positive implications for yield and the other financial indicators were also statistically robust, but in Punjab these were sensitive to specification effects. Particularly sensitive to specification effects were the ZT effects on the productivity of applied water in both sites.