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Field
Secondary Outcomes (End Points)
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Before
Further, we identify channels of persistence with the following outcomes:
• Labour Markets and Migration
– Occupational shifts (livestock to microbusiness, wage employment, migration)
– Wage earnings (local vs. migrant earnings, remittance levels)
– Migration patterns (duration, destinations)
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After
Further, we identify channels of persistence with the following outcomes:
• Labour Markets and Migration
– Occupational shifts (livestock to microbusiness, wage employment, migration)
– Wage earnings (local vs. migrant earnings, remittance levels)
– Migration patterns (duration, destinations)
Adult job loss and job transitions. This will be separated by migrants and nonmigrants.
– Experienced earnings loss after the job loss
– Switched occupation (from blue-collar to white-collar or vice versa)
– Switched job industry
– Took up government work programs
– Passed away
• Migrants’ job loss and travel back to villages. We will report the share of migrants
who respond ”yes” to the following binary indicators:
– Lost job in migration destination
– Traveled back to home village
• Share of households that report any business loss, non-farm business closure during
COVID lockdowns.
• Share of households that report any sale of land or other assets during lockdown.
• Social protection services during COVID lockdowns. This will be reported as an
index, constructed as the normalized number of transfers that a household received
from:
– extra food ration
– bank deposits as part of existing social welfare schemes
– asset or cash transfers from the local government
– asset or cash transfers from local non-government bodies
• Social protection services in the last 12 months. Takeup will equal 1 if the HH applied
for OR received the scheme in the last 12 months. The index is a normalized count
summing the following indicators:
– work in an employment generating scheme
– old age or widow pension
– Indira Aawas housing plan
– other assets gifted by the Panchayat (village government)
– vocational training through the Panchayat
– Lakshmir Bhandar monthly bank transfer for women
– AAY card
– any ration card (BPL or Annapura rationing)
– Krishak Bandhu scheme
• Healthcare seeking behavior in last month.
• Index for extent that household delayed major events due to COVID. This index is
a normalized count summing the indicators:
– delayed wedding or engagement
– delayed funeral
– delayed opening new business
– delayed taking a large loan
– delayed a child starting or progressing in school
– delayed migration
• Index for household consumption smoothing during lockdown. The index is a normalized
count summing the following indicators:
– consumed goods that you were planning to sell or consume later
– take a loan to buy food or goods that are regularly consumed
– increase time spent foraging
– increase time spent begging
– delayed purchasing essential household items other than food
– sought a loan from anyone
– conditional on having savings, drew down savings to cover expenses
INTERGENERATIONAL OUTCOMES
We are interested in outcomes for beneficiaries’ children, who are now adults. Outcomes in this analysis include:
• educational attainment
• occupation and income
• access to credit and financial inclusion
• type of job (public sector, private white collar, private blue collar, farm wage employment,
business)
We will also investigate outcomes for children aged 3 to 16, disaggregated by whether they
are children or grandchildren of the beneficiary, where it is possible to distinguish. Child’s
outcomes are:
• height and weight
• age-adjusted middle-upper arm circumference percentile
• share that attend school or anganwadi
• child age distribution
Finally, if sufficient tracking information is available, we will investigate beneficiary mortality.
Specifically we will report the share of original beneficiaries who have died since the
original intervention in 2007, conditional on age at baseline.
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Field
Secondary Outcomes (Explanation)
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Before
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After
COVID-19 pandemic outcomes:
There are few studies quantifying the long-run impacts of the COVID-19 pandemic on the
rural poor in a developing country. Therefore we are not only interested in estimating the
treatment effect, but also in describing the overall experiences of the sample during and in
between the 2020 and 2021 COVID-19 lockdowns. In order to publish the descriptives, we
will present tables with 4 columns: control group mean, treatment group mean, combined
mean, and p-value for difference between control and treatment group.
Intergenerational outcomes:
Secondary outcomes regarding intergenerational effects on beneficiary’s children and grandchildren
will be tested.
We are interested in outcomes for beneficiaries’ children, who are now adults. However,
we only observe beneficiaries’ adult children if the children still live in the same household as the beneficiary, or replaced a deceased beneficiary as household head. Estimates based
on coresident adult children may be biased if treatment changes coresidence patterns.
Therefore we will first test for a treatment effect on household division using the share of
beneficiaries’ daughters (and separately sons) who live with the beneficiary, conditional on
child age. We will estimate treatment effects separately for sons and daughters, and only
if we find no evidence of a treatment effect on probability of coresidence for that group.
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