Digital Inclusion in Rural India

1. INTRODUCTION
Tamil Nadu Kerala
• Has highest Human
Development Index, literacy
ratio, and sex ratio
• The least corrupt Indian state
as per Transparency
International
• Economy depends highly on
remittances from emigrants
• Ranked 6th according to the
Human Development Index in
2011
• The 2nd largest state economy
in terms of GDP
• The 2nd largest software
exporter in India

2. Objectives of 1998 IT Task Force includes:
• Transforming over 600,000 existing Public Telephones/Public Call Offices (PCOs) into
public tele-info-centres offering a variety of multimedia information services.
• Spreading IT awareness among the citizens and rural penetration of IT applications.
• Allowing Cable TV service providers to provide access to internet through authorised
Cable TV infrastructure, without additional licensing.
• Making IT more easily available, affordable, and to boost export through several financial
and legal benefits to the IT products and software providers.
• Encouraging the setting up of value-added network services (e.g. ATMs)

3. Brief Summary of Digital Penetration:
• In Kerala, on an average 11.2% households have computer among which 3.8% have internet
connection. In Tamil Nadu, 4.4% household have computer among which 0.9% have internet
connection.
• In Kerala, Land Phone and Mobile penetration stand at 41.9% and 76.8% respectively, while in
Tamil Nadu these percentages stand at 8.7% and 60.8%.
• In Kerala, 94.7% villages have PCOs while 68.5% have internet cafes. In Tamil Nadu, 72.8%
villages have PCOs while only 7.2% have internet cafes.
• Villages in Kerala receives domestic power supply for 23.6 hours a day, while villages in Tamil
Nadu receives power for 16.0 hours a day on an average.

4. • Averages in Tamil Nadu and Kerala stand at 4.4% and 11.2% respectively.
• Tamil Nadu villages have more dispersed data, but plots are showing narrower range because sub-
district level data is used for Tamil Nadu for better identification of descriptive parameters.

5. 0
50
100
150
200
250
300
350
400
0% 3% 6% 9% 12% 15% 18% 21% 24% 27% 30%
Computer penetration - Rural Kerala
• The Digitalization in Kerala seems to be normally distributed with the data being evenly distributed around
its mean, as the histograms are taking a bell curve shape. It is positively skewed in Tamil Nadu with 72.3%
data falling below the mean, and the mean being almost twice the median (4.4% vs. 2.6%).
• Around 68.5% villages in Kerala have internet cafes / Common Service centres while it is 7.2% in Tamil
Nadu.
• Among the villages with population of 1,000 or more in Tamil Nadu, 90.8% villages show 10% or lesser
penetration. The remaining villages with penetration ratio of 10-95% are not covered in the above chart.
0
500
1000
1500
2000
2500
3000
0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10%
Computer Penetration (<=10%) in Rural
Tamil Nadu

6. Rural Tamil
Nadu (%)
Urban Tamil
Nadu (%)
Rural Kerala
(%)
Urban Kerala
(%)
Minimum 0.0 0.3 0.4 5.8
First Quartile 1.4 5.1 8.1 13.2
Median 2.6 8.5 10.9 15.9
Mean 4.4 10.8 11.2 17.3
Third Quartile 4.8 13.4 14.0 20.0
Maximum 94.8 57.3 28.6 55.6
Standard Deviation 6.12 8.20 4.41 6.13
• Tamil Nadu shows higher deviation with lower average, while Kerala shows more consistent
digitalization with higher average.
• The Gap between rural and urban digitalization is much lower in Kerala as compared to Tamil Nadu.
• Urban data does not include Chennai for Tamil Nadu as, being a megacity, data from Chennai would
not be comparable to other urban areas.
Summary of Rural and Urban Digitalization:

7. Mobile Phone Usage and Digitalization:
• In Kerala, 41.9% household relies on Land Phone as compared to only 8.7% in Tamil Nadu, while 60.8% in Tamil
Nadu rely on Mobile Phone as compared to 76.1% in Kerala.
• Digitalization in Kerala shows correlations of 0.59 and 0.30 with Land Phone and Mobile phone respectively. In a
contrast, Tamil Nadu shows 0.23 and 0.54.
• It appears that Mobile penetration in villages near the towns are having stronger positive relation with
digitalization, probably because of proximity to other amenities. Mobile penetration is consistent across distances in
Kerala (at 76%) and ranges from 59.5% to 63.0% in Tamil Nadu.

8. Land Phone Usage and Digitalization:
• In Kerala, villages within 5km to town are having 46.1% Land Phone penetration as compared to 40.0% for
villages beyond 10km. In Tamil Nadu, the difference is less as it ranges from 9.7% to 8.3% across distances.
• Land Phone being the most common channel to access internet in villages, the potential to expand internet is
higher in Kerala, and it would require some infrastructure development in Tamil Nadu to reach at similar level.

9. Land Phone Usage and Internet:
• Among 11.2% households having Computer, only 3.8% have internet connection in Kerala. In Tamil
Nadu, among 4.4% households having computer, only 0.9% have internet connection.
• Kerala shows 0.63 correlation of internet connection and Land Phone, while Tamil Nadu shows 0.28.

10. • Kerala shows smaller difference in
female literacy and overall literacy
• Both the states show positive relation
of female literacy with digitalization,
with correlation of 0.40 and 0.52 for
Tamil Nadu and Kerala
• Overall literacy ratio also shows the
similar positive relation, with slightly
lower correlations
• Tamil Nadu shows higher percentage
of working population for overall as
well as female
• Both states show negative relation
with overall as well as female working
population with correlations ranging
from (0.40) to (0.45)
• Overall working population also show
similar negative relation
• Is the Digitalization driven only by
younger population (students) with less
participation from working people?
Literacy, Working Population (Overall and within Female Population) and Digitalization:

11. • Around 52.6% working people
depend on Agriculture in Tamil Nadu,
while 19.7% do in Kerala.
• Tamil Nadu shows (0.57) correlation
while Kerala shows (0.42)
• Dependence in measured by
cultivators and agricultural labour
population as a percentage of working
population
Agriculture, size of House and Household and Digitalization?
• Around 80.0% houses in villages of
Tamil Nadu have zero to two rooms,
while in Kerala it is 31.5%
• percentage of smaller houses show
around (0.40) correlation in the both
states
• However, digitalization does not show
meaningful correlation with household
size in terms of number of members.
• For this plot and correlation, smaller
house is defined as <3 rooms for Tamil
Nadu and <4 rooms for Kerala.

12. Demographic Differences Between States:
• While Tamil Nadu and Kerala
shows similar correlation with
treated tap water, the Kerala
Village data shows non-linear
relation with (0.11) correlation as
compared to 0.05 in Tamil Nadu
• At Sub-District level, the
correlation in both states are
between 0.19 and 0.23.
• In Kerala, 15% household have
bicycles while it is 47% in Tamil
Nadu
• In a stark difference, Kerala
shows 0.31 correlation as against
(0.24) in Tamil Nadu.
• Possibly, higher bicycle in Kerala
means more plain areas where
development has concentrated,
while in Tamil Nadu it means
remote villages.

13. Availability of Amenities and Digitalization:
The x-axis covers till 10% digitalization for Tamil Nadu (91% of large villages) and 25% for Kerala (nearly 100% of villages).

14. Availability of Amenities and Digitalization:
The x-axis covers till 10% digitalization for Tamil Nadu (91% of large villages) and 25% for Kerala (nearly 100% of villages).
NOTES:
• Higher level of digitalization is observed closer to the amenities including school, health centre, post office,
banks and ATMs. It is not closely related to public or private bus facility.
• Around 34.7% and 83.1% villages have secondary school in Tamil Nadu and Kerala respectively. The percentages
of healthcare centre stood at 10.7% and 56.5%.
•In Tamil Nadu the availability matters more than the distance, as the peaks for different ranges of distance are
falling more closely. In Kerala, the different ranges of distance have distinct peaks.

15. • With much larger percentages
of households having TV and/or
Motorcycles
– This plot shows that having a
computer has much lower
priority for households when
compared to TV and Motorcycle,
even when they can afford
similar assets
– it appears that the awareness
about the benefit of digitalization
is bigger hurdle than affordability
• Kerala shows higher computer
penetration and percentages
household having motorcycle,
and lower percentage of
household having television
Other Household Amenities and Digitalization:
*These plots show the Tehsil level data, with Tehsils in x-axis

16. Commercial Banks and ATMs:
• As evident from the
percentages of villages having
ATM compared to having
Banks–
The target of setting up of
value-added network services
needs to be emphasized
further.
• In Tamil Nadu 22% villages
have Banks while 4% have
ATMs, as compared to 96% and
42% respectively in kerala
-As a percentage, the gap is
wider in Tamil Nadu, so it will
reap more benefit if ATM
facility is expanded in all the
banks.
• However, still the coverage
will be lower due to lower
percentage of villages having
banks
*These plots show the Tehsil level data, with Tehsils in x-axis

17. Internet Cafe and Other Amenities:
• With only 7% villages having
Internet Cafe as compared to
73% having PCO in Tamil Nadu
– a lot is left to be desired in
terms of converting PCOs into
information service centres.
• In Kerala, 69% villages have
internet cafe while 99% have
PCO
• Tamil Nadu has post offices in
10% villages while Kerala has in
95% villages, so even if
information centre is
established in all such
government facilities, there will
be much larger gap to cover in
Tamil Nadu
*These plots show the Tehsil level data, with Tehsils in x-axis

18. Decision Tree Analysis for Digitalization in Rural Tamil Nadu:

19. Decision Tree Analysis for Digitalization in Rural Kerala:

20. Summary of Regression Analysis:
Tamil Nadu Kerala
Positive coefficients with high
significance
• Having Land Phone/ Mobile
• Good condition of Household
• Access to treated tap water
• Working population
• Having Latrine within house
• Having Land Phone/ Mobile
• Good condition of Household
• Water source within house
• LPG/PNG connection
• Female literacy ratio
Positive coefficients with
questionable significance
• Water source within house
• LPG/PNG connection
• Having Television
Negative coefficients with high
significance
• Dependence on Agriculture
• Having Television
• Female literacy ratio
• Dependence on Agriculture
• Working population
Negative coefficients with
questionable significance
• Distance from Town • Domestic power - hours per day
• Access to treated tap water
• The regression model for Tamil Nadu shows much lower Adjusted R2 than that for Kerala, implying less predictive power, most
likely due to dispersed data. As such, regression result from Kerala can be relied upon in the case of any contradiction.
• Female literacy ratio in Tamil Nadu is showing negative relation while percentage of working population is showing positive
relation, which contradicts the results from Kerala and also the study of correlations for Tamil Nadu – hence these can be ignored
for the above mentioned reason.
• Kerala shows access to treated tap water as a negative factor, which is counter-intuitive but is confirmed through study of
correlations.

21. Key Observations:
Based on Study of correlations, visualization, Decision Tree and Regression analyses, following observations are
made:
• Digitalization seem to be the second priority after a good living condition:
o Villages with higher level of Good households, in-house water supply and sanitation within house,
LPG/PNG connection and Literacy ratio are showing higher level of digitalization
o However, Access to treated tap water, availing banking services and hours of availability of
domestic power per day do not show very strong relation with digitalization
o Bigger houses and households with motor vehicles have shown higher digitalization
• Both Land Phone and Mobile show strong positive relation with Digitalization. The correlation is stronger
with Land Phone in Kerala while in Tamil Nadu it is stronger with Mobile – may be because low
penetration of Land Phone in Tamil Nadu.
• Villages with higher dependence on Agriculture are showing lesser penetration
• Digitalization rate is higher in villages near towns and having amenities such as secondary schools and
health centres.
• Working population is not driving the digitalization

22. Recommendation:
Based on the analysis conducted and observation made, below are some recommendations:
• Digitalization seems to be the second priority after a good living condition, so overall living condition has
to be improved. The parameters include Literacy, household amenities such as access to treated water,
LPG, Land Phone etc among others. While these developments are a bigger goal in itself, it will drive
digitalization too.
• The level of e-governance ,and digitalization of other services e.g. Banking, have not gained much
traction yet. As such, working population is showing negative correlation with digitalization. Increased
level of e-governance will save time and money and improve lifestyle of working people, which would give
a big push towards digitalization.
• The level of digitalization is comparatively lower in the remote villages, and villages which are depending
more on Agriculture. Higher level of e-governance, online Agriculture helpline or tutorials along with
overall expansion of literacy and other developments should improve the scenario.
Cont.

23. Recommendation:
Based on the analysis conducted and observation made, below are some recommendations:
• The target of transforming PCOs into public information centre has left a lot to be expected as the
availability of internet cafes are much lower than the PCOs. This needs to be considered with higher
priority for a higher level of internet penetration.
• Additionally, if the premises for public amenities such as post offices are appended with public-tele-info
centre, it will boost digitalization further .
• The prices for entry level computer fit for fulfilling basic requirements should be slashed . Manufacturing
of Indian brand with indigenous component and tax benefits for such manufacturing and distribution could
be possible ways to achieve it.
• Infrastructure development is required in terms of Land Phone penetration and expansion, along with
other channels of internet such as cable connection.
• Setting up of value-added network services such as ATMs need to be improved as the villages in both
states have more branches of commercial banks than ATMs.

25. Appendix

26. Assumptions
• Villages in Tamil Nadu with 0-100 population are not included in analysis.
Further, <1000 population villages are also excluded as those were leading to
non definitive trends due to extreme data.
• For the purpose of visualization and study of the interaction of the variables,
the sub-district level data is used for Tamil Nadu, while village level data is
used for Kerala as the trends are prominent
• Urban data does not include Chennai for Tamil Nadu as, being a megacity, data
from Chennai would not be comparable to other urban areas.
• The measure for Digitalization is considered to be the sum of percentages of
computer with without internet, unless otherwise specified.

27. Visualization with Village level data in Tamil Nadu
Because the village level data in Tamil Nadu is highly dispersed, positively
skewed, and not showing any definitive trend, the Sub-District Level data is
used for visualization and study of correlation.
E.g. LPG/PNG in Tamil Nadu shows 0.13 and 0.57 correlations with village
data and Sub-District data respectively.

28. ONLY Mobile Phone Usage and Digitalization:
(previously used)

29. Logistic Regression for Kerala ..and Linear regression with same variables
•Initially it seemed that logistic regression will be more appropriate for probability data as dependent
variable, however, looking at the linear model resulting in more statistically significant coefficients – it
seems linear model might be better fit here.
•I have asked this to Jigsaw and awaiting a response

30. • For most of the variables the 10-50% group is showing more developed population or amenities than those
in the 50% plus group
• Only 0.2% have more than 50% penetration, while 9% have penetration between 10-50%
• Based on this observation, it can be considered that the highest penetration group is actually outlier
• Question is where should the range of outlier begin
• Removed 30%+ penetration to rerun regression, resulted in 138 row removal (1.25%)
• The high percentages among the larger villages are more concentrated around Kancheepuram,
Ramanathapuram and Virudhunagar districts among others (concentration ranges from 0.4% to 3.3%)
Checking Tamil data for ranges of computer penetration

31. Regression of Tamil data with and without outliers

32. The linear regression model that is finalized