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Impact Evaluation Training with AERC: China Cash Transfer Programme Technical Proposal

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A hypothetical technical proposal for China's conditional cash transfer programme from our impact evaluation training with AERC in Nairobi, Kenya in July 2019.

Published in: Government & Nonprofit
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Impact Evaluation Training with AERC: China Cash Transfer Programme Technical Proposal

  1. 1. CHINA CONDITIONAL CASH TRANSFER PROGRAM AERC/Transfer Project IE Training Workshop June24-July 4 2019 GROUP MEMBERS 1. Uche Abamba Osakede 2. Kingstone Mujeyi 3. Happiness Saronga 4. Eric Allara Ngaba 5. Rachel Namulondo
  2. 2. PresentationOutline •Description of the intervention •Hypotheses •Research question and Indicators •Conceptual Framework •Identification strategy •Estimation strategy •Other reflections and comments
  3. 3. Descriptionoftheintervention The program : Conditional Cash Transfer Program (CCTP) The CCTP: flat cash transfer provided monthly and paid at the local health facility General Objective: to address maternal, child birth and child nutrition outcomes Specific Objectives : To improve Maternal health outcome (Delivery by skilled birth attendant) Child birth outcome (Birth weight) Young child nutrition ( age appropriate child development at age 1 and 2 years, linear growth in height (cm), Age appropriate infant and young child feeding practices at home)
  4. 4. Descriptionoftheintervention • The target group  ALL pregnant women and women with children under 1 year of age • Eligibility criteria Adherence to national public health protocols: immunization schedules, ante-natal & post-natal health check ups for mother & baby and well baby visits • Selection process  Self selection (enrollment into program) after awareness campaign • Geographical location Rural areas of a province in China
  5. 5. Descriptionoftheintervention • The start and end dates  6 Months enrollment before introduction of the intervention End date 36 months (3 years) after introduction of intervention • Time limits to participation  6 months window for enrollment in order to participate • Time frame for the evaluation  3 years long enough to show an impact ? YES
  6. 6. Hypotheses • Statement of Hypothesis • Intermediate to final outcome  Intermediate Outcome hypothesis : Participation in the CCTP increases maternal and child utilization of public health facilities  Final Outcome hypothesis : The CCTP improves: maternal health outcome Child health and outcome Young child nutrition • The CCTP improves final outcomes through utilization of Public Health Facilities
  7. 7. Researchquestions& PrimaryIndicators • Research questions • What is the impact of the CCTP on - maternal health outcome? - Child health outcome? and - Young child nutrition? • Primary indicators and their units Primary Indicator Unit No of Delivery by skilled birth attendant Pregnant women Birth weight Newborn children  Gross and Fine motor skills , cognition 11 to 12 months old Gross and Fine motor skills , cognition 22 to 24 months old  Linear growth in height (cm) At birth, 1 and 2 years of age  Age appropriate infant and young child feeding practices at home (index) All children 6-24 months
  8. 8. Secondaryorintermediate indicatorstomeasure Secondary Indicators  No. of antenatal & postnatal health checkups for mother & baby  Immunization rates Well baby visits
  9. 9. ConceptualFramework Observable and unobservable Characteristics Enrollment in Cash Transfer Program Intermediate Outcome Final Outcome Maternal Observables - Age, Education, Household wealth and SES - Employment status - Marital Status - Religion - Parity - Awareness - Child spacing - HHD size - Unobservable: Biological Endowments - Community Observables: - Distance to the health facility - Water and Sanitation - Availability of health facility - Availability of skilled Health personnel - Unobserved : Culture, rurality Enrollment in CCTP No of antenatal and postnatal health checkups for mother and baby - Delivery by skilled birth attendant - Birth weight
  10. 10. Conceptual FrameworkObservable and unobservable Characteristics Enrollment in Cash Transfer Program Intermediate Outcome Final Outcome Child Observables: Birth Order Sex Birth weight Unobservable: Biological Endowments Mothers characteristics - Community Observables: - Distance to the health facility - Sanitation - Type of water source - Availability of health facility - Availability of skilled Health personnel - Unobserved : Culture, rurality Enrollment in CCTP Immunization rates Well baby visits - Age appropriate child development at age 1 - Age appropriate child development at age 2 : 22 to 24 months old - Linear growth in height (cm)s - Age appropriate infant and young child feeding practices at home
  11. 11. IdentificationStrategy • Obtaining comparison group to identify impact Randomly select districts Randomly select sub-districts Sample size for the number of communities or rural areas to cover Randomly assign the treatment to rural communities (Rural level : Treatment and Control group)
  12. 12. IdentificationStrategy •Random assignment at Cluster level • Strengths of RCT cluster sampling  Random assignment at community level reduces spill over and cross over effects  It alleviates equity issues  Increases the likelihood that program and control areas are similar in observed characteristics. • Weaknesses of RCT cluster sampling  It is expensive to Implement It is difficult to design and implement it is not easy to understand
  13. 13. EstimationStrategy Difference in Difference Model •At Base line: Base line data from both groups (T0 and C0) • At End line: Survey both T1 and C1 •Take difference for (T1-T0 ) – (C1-C0) • Not following up same individual to end line. • Not necessary to follow up exactly same individual • Just collect end line data from a cohort in the same cluster
  14. 14. ModelSpecification Difference in Difference Model • 𝑌 = 𝛽0 + 𝛽1P + 𝛽2 𝑇 + 𝛽3 𝑃 ∗ 𝑇 + 𝛽4 𝑋 + 𝜀 • Where: • 𝑌 Outcome • 𝑃 Program • 𝑇 Time • 𝑃 ∗ 𝑇 Interaction of program and time • 𝑋 Covariates • 𝜀 Error term
  15. 15. ModelSpecification Difference in Difference Model Appropriate given the data to be collected? •YES • Because we will not meet the same cohort because the child at 1 year will not be same 1 year at end line. So cohorts at base and end line are not same but can get outcome in the same cohort (T) and (C) •Data will be collected at base mid and end line
  16. 16. ModelSpecification Difference in Difference Model •Strength of DID • Can measure the impact of the intervention using different cohorts • Weaknesses of DID It requires the parallel trend assumption which may not be observed except we take pre-baseline data . Existence of the parallel trend at base line for the outcome variable does not guarantee parallel trend for other variables
  17. 17. ModelSpecification Difference in Difference Model • Estimator: The ATT • This is because: • the intervention is at the village cluster level, and • we can randomize village clusters into treatment and control with very small chance of contamination and cross over
  18. 18. Otherreflectionsor comments • Key strengths •Already provided outcome measures • Internal and external validity •Using rural areas in similar sub district as treatment and control enhances similarity • External Validity : Equal representation for treatment and control clusters from each sub district
  19. 19. Otherreflectionsor comments • Sampling issues •Insufficient information for sample size determination (E.g average number of clusters) •Time frame • End of 6 months of awareness campaign, we get base line data and introduce the intervention • Midline at 18 months and • End line at 36 months
  20. 20. • ASANTENI SANA !!! • GRACIAS !!! • GRAZIE !!! • MEDASE !!! • MERCI BEAUCOUP !!! • ESE !!! • SIYABONGA !!! • MWEBALE NYO !!! • TINOTENDA !!! • THANK YOU VERY MUCH !!!

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