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xx Africa Region Survey-Based Harmonized Indicator Program (SHIP). By Andrew Dabalen , Saurabh Shome , and Xiao Ye Africa Region Statistical Practice Group June 6, 2013. Vision: Pillars of Renewal. Pillar 3: Provide public goods for the Region. Presentation outline. Why harmonizing?

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xx africa region survey based harmonized indicator program ship

xxAfrica Region Survey-Based Harmonized Indicator Program (SHIP)

By Andrew Dabalen, SaurabhShome, and Xiao Ye

Africa Region Statistical Practice Group

June 6, 2013

presentation outline
Presentation outline
  • Why harmonizing?
  • SHIP in a nutshell
  • How we harmonize and SHIP outputs
  • Challenges and limitations
  • Examples of analysis using SHIP
  • Dissemination and technical assistance
  • SHIP – next steps
  • Demonstration of SHIP indicators
why harmonizing
Why harmonizing?

A

B

Ghana

Ethiopia

Uganda

Nigeria

Cameroon

Mozambique

Mali

Côte d’Ivoire

Kenya

Zambia

Demographic information, access to services, household consumption, employment , household productions, etc.

harmonization in a nutshell from raw data to 200 harmonized variables replicable
Harmonization in a nutshell from raw data to 200 harmonized variables, replicable

CIV 2008

CIV

2002

CMR2001

CMR

2007

GHA 1998

GHA

2013

KEN1997

KEN

2005

MWI

2004

MWI

2010

MOZ

2003

MOZ

2009

ZMB2006

ZMB 2010

UGA2005

UGA2010

Four SHIP files for each survey: Expenditure file, Individual file, Household file, Labor file

shiping consumption aggregation
SHIPing consumption aggregation
  • Annualized regionally adjusted consumption aggregates (if regional price index available) deflated to 2005 PPP-USD
  • Rent is not included in the final consumption aggregate, but actual rent paid is available as a separate variable
  • Very large lumpy spending is excluded from final consumption aggregate, such as hospitalization expense and purchase of vehicles, but are available as separate variables
  • Only per capita food expenditures are regionally adjusted using the food price index, non-food expenditures are not adjusted
  • Outliers in food and non-food expenditure beyond three standard deviations are replaced by their respective median values
shiping income
SHIPing income
  • Incomes from wage work is captured at the individual level for cash payments only, not annualized, but payment period is included as a separate variable
  • Annualized gross incomes from different sources are captured at the household level, including wages, gross incomes from household enterprises, farms, as well as transfers
shiping labor variables where informal employment activities prevalent
SHIPing Labor variables (where informal employment/activities prevalent)
  • Information from all sections of the survey is used to capture employment data
  • Data from different sections are at different levels, including the individual / farm / enterprise / household level– SHIP output at individual level
  • Always merge data at the individual level – convert enterprise / farm level data into individual level
  • Keep an account of the number of individuals throughout the process
shiping other socioeconomic variables and shiping indicators
SHIPing other socioeconomic variables and SHIPing indicators
  • Demographic information (age, sex, relationship to the head)
  • Access to services at individual level (health, education, immunization, etc.)
  • Access to services at household level (water, sanitation, electricity, garbage collection, etc.)
ship outputs
SHIP Outputs
  • One manual
  • Four SHIP files per survey (200 variables), so far 21 countries (approx. 70% of population) 40 surveys have been completed
  • Sixty SHIP Indicators organized by national quintile, rural/urban quintiles and gender (serves as a tool to check data quality)
  • SHIP team provides feedbacks on questionnaire designs
  • Training workshops on SHIPing
limitations of ship files
Limitations of SHIP files
  • Extract most commonly available variables, thus rich information from special in-depth modules (sporadic availability only) may not be included
  • Household consumption in SHIP cannot be used to calculate poverty, but rank preserving, which enables distributional analysis
challenges faced initial design
Challenges faced – Initial design
  • Balancing between regional context and the flexibility to meet countries’ needs: creating “Lego” variables. Eg. SHIP labor variables
    • Ramifications for global harmonization of the regional harmonization programs
  • Balancing between most available variables in all surveys and analytical needs on a range of research topics, while keeping the complexity and the number of SHIP variables manageable
  • Thorough and consultative designing process with experts of different fields, minimizing changes once SHIP files finalized
challenges faced harmonization process
Challenges faced - harmonization process
  • Keeping assumptions relatively consistent across countries when compiling SHIP variables but also realistic in a given country context
  • Differences in questionnaire designs across countries
  • Changes in questionnaires design over time within the same country
analysis who benefits from fuel subsidy
Analysis: who benefits from fuel subsidy?

Featured in Africa Region Publication “Pulse”.

analysis w ho has access to electricity
Analysis: who has access to electricity?

Source: Africa Region SHIP indicators.

analysis t he garbage collection division
Analysis: the garbage collection division

Source: Africa Region SHIP indicators.

analysis mdg universal primary enrollment less obtainable for the poor and girls
Analysis: MDG universal primary enrollment less obtainable for the poor and girls

Source: Africa Region SHIP indicators.

use ship as a capacity building and dissemination tool
Use SHIP as a capacity building and dissemination tool
  • Communicating with national statistical offices
  • Provide training upon request; and
  • Introduce most recent thinking on questionnaire design
ghana workshop on shiping
Ghana workshop on SHIPing
  • Through our video conference with NSO on Ghana SHIP they requested training on SHIP methodology using their partially finished new survey
  • A four week intensive hands-on workshop for NSO staff achieved objectives (know how transfer)
  • Benefits were mutual, we learned about the country context, clever programing and made minor revisions to the SHIP manual based on NSO’s feedbacks
ship next steps
SHIP: next steps
  • Create public access
  • Involve more NSOs using SHIP procedures (requires resources and manpower)
  • Demonstrate analytical uses of SHIP data and increase local ownership
  • Outcomes: a wider use of household surveys in policy decision making and in monitoring of development outcomes