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ADePT A utomated DE C’s P overty T ables

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?.

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ADePT A utomated DE C’s P overty T ables

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  1. ADePTAutomated DEC’s Poverty Tables Michael Lokshin, Zurab Sajaia and Sergiy Radyakin DECRG-PO The World Bank

  2. Step 1: Data and Output

  3. Step 2: Household variables

  4. Step 3: Individual variable

  5. Step 4: Tables and Graphs

  6. 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

  7. Main Components of Poverty Assessment Welfare Indicators Poverty Lines Poverty Assessment

  8. 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.

  9. 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.

  10. 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

  11. ADePT: 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 …

  12. ADePT: 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.

  13. ADePT: 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. • ADePT was tested on datasets from Georgia,Jordan, Serbia, Ukraine, Montenegro.

  14. ADePT: 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

  15. Table 2.1 Original Table 2.1 with Standard Errors Table 2.1 Frequencies

  16. ADePT: 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

  17. ADePT: Directions for future development • ADePT: Public Release mid-June 2007 • Multiple extensions of ADePT 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.

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