Connected-Farmers

Appendix 2
Data assumptions
and modelling
Data limitations
Given the type and origin of content, data was often limited in
its availability and robustness.
Where possible, data points were sourced from internationally
recognised bodies. In some instances, where data gaps were
identified or specific country data was unavailable, then
informed assumptions were taken to fill these gaps.
Data points used to calculate service adoption rates and
livelihood benefits were developed using benchmarks from
identified case studies or interview data.
Data collection methodology
Key data points were collected from available sources and
assumptions made to address data gaps and project key data
points to 2020.
Category Metric Primary source Limitations Assumptions
Basic demographics Total population World Bank and
GSMA
Employment metrics
Population by
age group
Urban and rural
population
Economically
active population
in employment
Employment by
sector
Workforce in
agriculture and
allied activities
Income of
farming
household
– Population projections till 2020 are
from GSMA
World Bank – Share of population by age group fixed
at 2013 levels
World Bank – Change in population share projected at
historic CAGR
World Bank
World Bank, WDI
World Bank, WDI
Indira Gandhi
Institute of
Development
Research
Gaps in historic
time series
Gaps in historic
time series
Gaps in historic
time series
Data only till
2003
Employment ratio is fixed up to 2020
using 2008–2012 average
Employment distribution across sectors
is extrapolated using historic sector
CAGR
Employment distribution across sectors
is extrapolated using historic sector
CAGR
The income figure is adjusted
for historic inflation and yield
improvements to 2012. Projections to
2020 account for yield improvements
at CAGR
Table continues on next page.
40 Vodafone Connected Farming in India