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Evaluation of OAP in Karnataka - Final Report - Phase 100011

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					                       Evaluation of Old Age Pension schemes in Karnataka –Final Report


the elderly in a positive way, there are systemic, logistic and infrastructural
challenges that have to be overcome to achieve the expected results. However, the
important aspects of the scheme: application processing, monitoring the eligibility
criterion, delivery of pensions on time (including budgetary and fiscal planning) are
all crucial factors on which the success of the schemes depend.


Most of the previous studies reviewed her have focussed on evaluating the process
of old age pension delivery from the taluk level to the individual beneficiary in
selected locations. These studies have not looked at the larger trends in utilization of
the pension schemes in terms of inter-district/taluk trends in expenditure,
beneficiary growth, and duration of pensions which are crucial in evaluating the
utility of the scheme and providing strategic feedback in increasing the efficiency
and effectiveness of the pension schemes. Previous studies have focussed on the
reach and spread of pensions in the selected field locations. However, they have not
attempted to identify the exact administrative and logistical bottlenecks that result in
higher transaction costs and delays in delivery and further suggest possible solutions
for the same. Hence, this study is phased out into two stages wherein, at the first
stage, the larger state-wide patterns and trends (keeping the taluk as the unit) are
understood and in stage two, the issues and concerns found in stage 1 are studied
further based on extensive field validations.


Additionally, in the first phase of the study, the focus is on determining whether the
issues and concerns raised in previous studies are visible through an analysis of
existing beneficiary data. Further, in this phase of the study, not all issues of concern
raised from literature review can be addressed. Field validation is required for
understanding implementation bottlenecks and utility of the scheme from the
perspective of the beneficiaries. Hence, in this phase of the study, effort is made to
identify suitable field locations where all the identified issues of concern can be
observed and validated. With these broad inputs, the data analysis during the
secondary study phase has been prepared.




GRAAM – An SVYM Initiative                                                                  19
                          Evaluation of Old Age Pension schemes in Karnataka –Final Report



                      5. Data collection and Analysis methodology

    5.1 Requirement analysis and consultation
Based on the project objectives, the requirement analysis for the study was
conducted by meeting with the officials of the Directorate of Social Security and
Pensions (DSSP), Revenue Department, Bangalore. The availability of the data, the
feasible outputs of the study and the methodology were discussed.



    5.2 Secondary data collection
The most important source of data for this project is the beneficiary list of the entire
state, maintained by the Treasury in soft-copy format. Details related to financial
allocation to the various schemes implemented by the department: expenditure
statements for NSAP (2007-08 to 2011 – 12), state’s budget allocation and expenditure
in the financial year of 2011-12 up to December 2011, and physical progress in these
years were given to the project team. Further, another important source of the data
is the NSAP MIS maintained by the NSAP division the Ministry of Rural
Development. The data extracted from the NSAP MIS includes Annual reports,
scheme guidelines and national and inter-state allocations of budget for IGNOAPS.

    5.3 Limitations of the secondary data
As mentioned above, the most important data set for the project is the beneficiary list
for different schemes being implemented by the DSSP. This data, although
comprehensive in capturing individual beneficiary details of different schemes, had
crucial limitations.
                            Table 6. Details of data in the beneficiary data set
Variable                       Explanation
Treasury code and name         Name and code of sub-treasury
Category of pension            Scheme to which the beneficiary belongs (OAP, SSY, DWP, PHP etc)
Pensioner name                 Name of the beneficiary
Pension status                 Pension active/suspended
Pension commencement date      Date on which pension was approved
Pension start date             Date on which pension was first released
Residential address            Address of the beneficiary
Date of Birth                  Date of birth of the beneficiary
Date of Death                  Date of death of the beneficiary (if deceased)
Sex                            Gender of the beneficiary
Bank account                   Bank account number if the beneficiary receives pension from the bank
Post Office code               Post office code if the beneficiary receives pension through the Post Office


Table 6 displays the important column headers present in the data set. Although the



GRAAM – An SVYM Initiative                                                                                    20
                            Evaluation of Old Age Pension schemes in Karnataka –Final Report


data set looks comprehensive based on the variables listed in the dataset, most of the
crucial information necessary for the study was either not filled for most of the
beneficiaries or was not reliable.
         The demographic details of the beneficiary, like date of birth of the pensioner
          and date of death were mostly left empty.
         The gender variable was filled for approximately 40% of beneficiaries.
         Bank account details and post office codes were unreliable to be used for a
          state-wide analysis.
         The difference between the pension commencement date and pension start
          date would be useful to analyze the fund flow of the schemes and understand
          the time-lag between approval of the beneficiary and the first pension release.
          However, the start-date for most of the data was after the year 2002, although
          pension was granted in the 80s and the 90s. Hence, this analysis is done only
          for the pensions that were granted after the year 2002.
In the discussions with the department officials about the limitations, it was learnt
that, at present, although all these details exist in hard copy for all the existing
beneficiaries, a majority of the beneficiary information was not entered in the digital
format. The department is in the process of physically validating and correcting the
beneficiary data and it would take too long to wait for the validation to be over.
Further, the department personnel informed the project team that they do not have
beneficiary data segregated based on social groups (SC/ST/OBC etc). Further,
although the department has the list of suspended beneficiaries, the date of
suspension of the beneficiary is not available. Due to these limitations in data
availability, secondary data analysis has been able to achieve some of the objectives
only partially. The list of objectives from the secondary data analysis as mentioned in
the TOR and the accomplished objectives together with the explanation
                                      Table 7. Objectives of the study
                     Objectives                         Status           Explanation
1. Identification and comparison of taluk/district
trends
      Analysis of beneficiary demographic details       Accomplished     Analysis restricted to
                                                        partially        available gender data and
                                                                         mode of pension delivery
        Allotment of new beneficiaries                  Accomplished     -
        (taluk/district)
        Average duration of pensions for                Accomplished     Analysis restricted to active
        beneficiaries                                                    beneficiaries
        Trend of accepted and rejected applications     Accomplished     Application status data not
                                                        partially        available with the
                                                                         department. However
                                                                         analysis of delay between



GRAAM – An SVYM Initiative                                                                               21

				
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