adept a utomated de c’s p overty t ables
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ADePT A utomated DE C’s P overty T ables. Michael Lokshin, Zurab Sajaia and Sergiy Radyakin DECRG-PO The World Bank. Step 1: Data and Output. Step 2: Household variables. Step 3: Individual variable. Step 4: Tables and Graphs. Why to automate?. - PowerPoint PPT PresentationTRANSCRIPT
ADePTADePT AAutomated utomated DEDEC’s C’s PPoverty overty TTablesables
Michael Lokshin, Zurab Sajaia and Sergiy Radyakin
DECRG-PO
The World Bank
Step 1: Data and Output
Step 2: Household variables
Step 3: Individual variable
Step 4: Tables and Graphs
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Why to automate?
To free resources for more meaningful and interesting tasks.
Minimize human errors. Significantly speed-up production of basic results. Produce print-ready tables/graphs/reports Easily introduce new cutting-edge techniques and
methods of poverty analysis. The automation tools could be used as valuable
research instruments, tools for sensitivity analysis and educational tools.
Might be helpful in situation of a limited data access Simple checking of the previous reports/results
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Main Components of Poverty Assessment
Welfare
Indicators
Poverty
Lines
Poverty
Assessment
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Possibilities for automation: Welfare indicator
Low automation (even if standardized): High degree of subjective of the algorithm Should reflect country-specific characteristics Different countries require different algorithms Possible to automate some tasks, not the whole
process: Hedonic price regressions (housing prices) Flow of services from durable good consumption The economies of scale Imputation of expenditures from consumption of
home-produced goods.
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Possibilities for automation: Poverty Line
Moderate-to-high automation: There is a standard “World Bank”
methodology for deriving the poverty lines. Some subjective decisions need to be made,
but most of them could be programmed as options in the algorithm.
Could be an important sensitivity analysis, research and educational tool: would allow fast comparison of poverty profiles under various assumptions.
But: the new poverty lines are calculated only once in several years.
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Possibilities for automation: Poverty Update
High automation: It is possible to define almost an exhaustive
set of tables/graphs that are commonly used for poverty updates.
Minimal requirements on the data Possibility to introduce an extensive set of
controls and sensitivity tools. It is easy to integrate the latest methods into
the report Production of print-ready tables/reports in very
short time. Substantial budget savings
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ADePTADePT: Data and Variables Accepts individual or household level data One or more years of data Required variables:
Household ID Consumption aggregate: per person or per equivalent adult Poverty line: up to two lines, numbers or variables Urban-rural indicator
Optional variables: Regions Weights Land-ownership Income Relation to the head Age Gender Education Employment Status More could be added …
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ADePTADePT: Checks and filters
All variables are checked: Correct type of variables Correct values (e.g., gender has only 2 values). Presence of a variable in all data files. Variable consistency over the years of data
All the constructed variables are generated automatically: household size, shares of different age/gender groups, etc.
The program produces report with basic statistics on all variables.
Possible control for influential outliers in terms of values or observations.
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ADePTADePT: Tables and Graphs
Tables and graphs are selected based on PA from: Bulgaria, Bangladesh, Honduras, Georgia, Jordan, Mongolia, Nepal, Sri Lanka, Ukraine
The program automatically generates the list of tables/graphs that could be produced based on the defined variables.
Three versions of each table: actual table, table with standard errors, table with frequencies in each cell.
Users can apply “IF” conditions and change titles of the tables/graphs.
ADePTADePT was tested on datasets from Georgia, Jordan, Serbia, Ukraine, Montenegro.
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ADePTADePT: Tables and Graphs
Report on variables in every dataset Report on possible errors in variables,
inconsistencies between the datasets, other warnings and notes
Overall Poverty, Expenditure Inequality Decompositions of poverty changes Poverty profiles by socio-demographic
categories Consumption regressions Poverty simulations Sensitivity analysis
Table 2.1 withStandard Errors
Table 2.1 Frequencies
Table 2.1 Original
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ADePTADePT: What to expect in the nearest future? Testing on data from other countries More tables More graphs Extended set of variables for analysis Smart Graphs/Tables: program can automatically
format graphs, control for outliers, generate warning messages
Ability to save and load predefined program configurations
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ADePTADePT: Directions for future development ADePTADePT: Public Release mid-June 2007
Multiple extensions of ADePTADePT that can cover other areas of the typical PA: Labor, Health, Education, etc.
Automated Poverty Lines (expected in fall 2007)
Set of tools to simplify the construction of consumption aggregates.