How do we track change in rural poverty
? A permanent investigator collects detailed information over time (5 years using the experience of the 30 years data collection effort of Village Level Studies
in 6 villages of Maharashtra and Andhra Pradesh since 1975) at village and household level (micro level).
Data at national and district level are also collected, like crop area, livestock numbers, farm harvest prices, agricultural wages and monthly rainfall, to determine the different agro ecologies and priority poverty areas. Trends analysis of these meso level data highlights emerging issues like climate change, urbanization and water scarcity.
Village data include demographic changes, socio-economic issues, land use and cropping patterns, investments in infrastructures / basic services and their maintenance, the management of common property resources and the local governance. Household data help define the poor economics, like family assets, incomes from farm and non farm activities, consumption patterns (eg level of self-consumption), education, health and nutrition situation, gender status, what government welfare programmes the household benefits from ; and whether the crop and livestock activities are profitable.
A recent study shows there is no bias (treatment effect) induced by the permanent presence of village investigators that would make the villagers more progressive and knowledgeable.
Well-thought indicators are measured such as land ownership, characteristics of the farming systems, education rate across gender, non-farm employment and nutrition status. This rich time-series data allow us to compare population segments more susceptible to poverty. For example, whether certain minorities more vulnerable to persistent poverty or if there a "geographical trap" reflecting the role of environment degradation.
Drivers of change in rural semi-arid tropics
Tackling low agricultural productivity is important but not enough to reduce poverty. Introduction of a new farming technology like an improved sorghum variety or water and soil conservation practices may greatly improve agriculture productivity and growth, but large-scale uptake depends on different factors including social learning.
Access to learning facilities to acquire new skills is a key driver of change within a community.
Some social factors may drastically change poverty dynamics. For instance, changes in social networks or family structure like the slow disappearance of joint families [ref changes in agriculture and village economies], the gender status, or health situation [eg impact of HIV on livelihoods], can change the way individuals and households cope with poverty, or acquire new skills and knowledge to improve their situation.
Even though agricultural growth plays a strong role in reducing rural poverty, diversification of village economies is very important too. A comparison between 6 VLS villages [link "Drivers of change: dynamics of rural livelihoods and poverty in SAT India"] shows the importance of non-farm and urban economy to drive smallholder farms out of poverty in rural India, demonstrating that rural development programmes have to look beyond agriculture.
IMPACT of poverty dynamics studies
Poverty dynamics studies influence research and policy decision-makers.
Defining research priorities: In the 1970s ICRISAT decided not to invest in herbicide and weed science as VLS research found out that the use of herbicide was not profitable for farmers, that crop value was more dependent on erratic rainfall and soil fertility; and that hand weeding was an important share of women incomes.
Influencing development policy-making: Demonstration that common property resources were important in the incomes and nutrition of the poor led to a decision by the Indian government not to hand over wastelands to private industry for afforestation.