4 Sampling Technique and Basic Sample Characteristics
As mentioned, in order to understand the kind of risk faced by the farmers as also
the mitigation strategies followed, a survey has been carried out in three districts in
the state of Karnataka. As in the absence of proper mitigation strategies farmers
tend to borrow at times of distress, we have therefore purposively selected three
districts viz., Mandya, Chamarajanagar and Haveri which have rather high level of
indebtedness as per NSSO survey (59th round). Mandya and Chamarajanagar are
among the top five highly indebted districts of South Karnnataka, while
Chamarajanagar has the highest indebtedness amongst all districts in Karnataka.
Among the districts of North Karnataka, Haveri has the highest level of
indebtedness.
Further, these three districts have been selected also considering their varied
performances levels in agriculture sector. Dr. D.M. Nanjundappa committee report
on regional imbalances provides a detail assessment of the Talukas of Karnataka in
terms of their agriculture productivity and infrastructure. The above report puts,
Mandya district under the group of districts with good agriculture infrastructure as
also performance. Using the same report, one can place Haveri as a middle performing district and Chamarajanagar as a low performing district. Using the agriculture infrastructure and performance indices constructed in Dr. Nanjundappa
committee report, one backward and one better performing Talukas from each
district were identified. Thus, as is clear, the purposive sampling technique is used
here to arrive at a balanced view on farmers’ situation in Karnataka.
Subsequently as mentioned, from each district, two Talukas were selected and
from each chosen taluka 50 households were selected where, in order to select our
samples in each Taluka, we took the assistance of Raita Samparka Kendras (RSK,
farmers' assistance centre) for the sampling frame. For example, in Mandya district
we selected two Taluks viz., Maddur (a better performing one) and Mallavalli (as a
backward taluka). There are four RSKs in Maddur Taluka and from the purview of
each RSK, we selected two villages. Further, from each village we have selected
about six households at random using the list of households provided by the RSKs.
Number of sample households selected from Maddur and Mallavalli Talukas is 50
each, making a total of 100 households. Similarly, we have selected two Talukas
from Chamarajanagar districts viz., Kollegal (having 5 RSKs) and Elandur (2
RSKs). We have selected five households from each village of Kollegal and in case
of Elandur, to arrive at a sample size of 50 respondent households, we selected four
villages from each RSKs and six households from each village. Following the same
procedure, we have selected 50 samples each from Kollegal (a backward taluka)
and Yelandur (a better performing Taluka). Similarly, in Haveri district, we have
selected two Talukas Viz., Haveri (backward), and Ranibennur (better performing)
and selected 50 households each.
An alternative approach would have been to select equal number of households
from each village. However that would make some Talukas much less representative in our sample and therefore we decided against this approach.
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M. Rajeev et al.
As mentioned, in order to understand the kind of risk faced by the farmers as also
the mitigation strategies followed, a survey has been carried out in three districts in
the state of Karnataka. As in the absence of proper mitigation strategies farmers
tend to borrow at times of distress, we have therefore purposively selected three
districts viz., Mandya, Chamarajanagar and Haveri which have rather high level of
indebtedness as per NSSO survey (59th round). Mandya and Chamarajanagar are
among the top five highly indebted districts of South Karnnataka, while
Chamarajanagar has the highest indebtedness amongst all districts in Karnataka.
Among the districts of North Karnataka, Haveri has the highest level of
indebtedness.
Further, these three districts have been selected also considering their varied
performances levels in agriculture sector. Dr. D.M. Nanjundappa committee report
on regional imbalances provides a detail assessment of the Talukas of Karnataka in
terms of their agriculture productivity and infrastructure. The above report puts,
Mandya district under the group of districts with good agriculture infrastructure as
also performance. Using the same report, one can place Haveri as a middle performing district and Chamarajanagar as a low performing district. Using the agriculture infrastructure and performance indices constructed in Dr. Nanjundappa
committee report, one backward and one better performing Talukas from each
district were identified. Thus, as is clear, the purposive sampling technique is used
here to arrive at a balanced view on farmers’ situation in Karnataka.
Subsequently as mentioned, from each district, two Talukas were selected and
from each chosen taluka 50 households were selected where, in order to select our
samples in each Taluka, we took the assistance of Raita Samparka Kendras (RSK,
farmers' assistance centre) for the sampling frame. For example, in Mandya district
we selected two Taluks viz., Maddur (a better performing one) and Mallavalli (as a
backward taluka). There are four RSKs in Maddur Taluka and from the purview of
each RSK, we selected two villages. Further, from each village we have selected
about six households at random using the list of households provided by the RSKs.
Number of sample households selected from Maddur and Mallavalli Talukas is 50
each, making a total of 100 households. Similarly, we have selected two Talukas
from Chamarajanagar districts viz., Kollegal (having 5 RSKs) and Elandur (2
RSKs). We have selected five households from each village of Kollegal and in case
of Elandur, to arrive at a sample size of 50 respondent households, we selected four
villages from each RSKs and six households from each village. Following the same
procedure, we have selected 50 samples each from Kollegal (a backward taluka)
and Yelandur (a better performing Taluka). Similarly, in Haveri district, we have
selected two Talukas Viz., Haveri (backward), and Ranibennur (better performing)
and selected 50 households each.
An alternative approach would have been to select equal number of households
from each village. However that would make some Talukas much less representative in our sample and therefore we decided against this approach.
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M. Rajeev et al.