Two Products
Meta Data Describing Content of LSMS Surveys
Comparative Data Base of LSMS actual data (variables/indicators)
What are LSMS surveys?
Multi-topic Household Surveys Relationships between/among topics Strong money-metric welfare measure
Demand driven relevant to a country at given time
(comparability issue) Coverage has large gaps Timing is not consistent
Designed for policy analysis and research
Getting Data Used Document and archive the 60+ LSMS
survey data bases Improvements in data access
policies/agreements Provide data and documentation to
researchers Each data set has
Data set (3 formats) Basic information document Questionnaire Additional Documentation
All in electronic format (and hardcopy) In-country activities
(collaboration,training)
Key problems in further dissemination/use of data
1. No easy way to determine the content of all the surveys
2. Not accessible to non-specialists (trained in micro-data analysis)
3. Start up costs for doing cross-country analysis
So how to meet the needs of these users, researchers and non-researchers?
Problem 1:
Researchers need to know which surveys have the topics they need
There is no source for this Need to go through all
questionnaires (or consult ‘institutional memory’
Solution 1: Meta Data of LSMS Surveys
Create web-based tool containing meta data describing the contents of existing LSMS data sets
Searchable Data Base Update continually May need to add new details
(LSMS-ISA)
Key Decisions: Content
Topics to include Identify the universe
Level of disaggregation Module (Education) Submodule (preschool, general,
training) Topics (preschool costs, type,
distance) Variables (cost of supplies, cost of
transport, cost of food) Interlinking
(ed->level->costs) vs. (exp.->educationlevel
Key Decisions: Search Results
Actual question vs Questionnaire? Depends on purpose ADP, IHSN question banks
Consistency in survey design Questionnaire development
LSMS- research data sets Context matters Need to know respondent, ages,
additional information
Development Path
Drafted list of topics (subtopics) Created first web interface Tested Substantially revised the interface Revised and expanded the list of
topics ‘Populated’ data base
Problem 2:
Many potential users do not have skills to analyze micro-data
Many potential users do not have time to analyze multiple data bases
Under-utilization of the data
Solution 2: Comparative Data Base (CLSP)
Database of a subset of variables/indicators from LSMS Surveys
Focus is on comparability across countries
Detailed documentation Allow ‘on-the-fly’ tables/statistics within
and among countries Respecting sampling (weights,
representat.) Respecting confidentiality
Key Decisions: Content
List of variables Needs vs Comparability Present vs Future
Define ‘Comparable’ Standard Definitions for Indicators When not to include a survey
(100% of all variables, 80%, 10%?) Test set of data- (issues in certain
regions, multi-year surveys)
Evolution
Consumption Aggregates Best possible, best comparable,
existing Completely non-intuitive to users Requires redefinition of poverty lines Stick with existing consumption
aggregates (well documented) Use existing poverty measures
Evolution
On-the-fly analysis Basic statistics can be constructed by
user Need for advanced statistical ability
Using public domain statistical software- all on our server (Qinghua Zhao’ adaptation of R)
Need for very straightforward abilities Created some ‘canned variables’ Commonly used/mis-used
Documentation Tie to output
Evolution
Platform to build on: RIGA: with FAO, collaborated in the
construction of income aggregates and variables
LMD: with PREM and DEC integrating labor variables
Integrate or stand alone
Development Path
Built on Sub-national data base Africa Standardized files
DDP Not interactive Costly to user Not maintained
Created new interface completely Iterative process