Presentation on theme: "ADePT Automated DECs Poverty Tables Michael Lokshin, Zurab Sajaia and Sergiy Radyakin DECRG-PO The World Bank."— Presentation transcript:
ADePT Automated DECs Poverty Tables 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
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 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 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 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 ADePT was tested on datasets from Georgia, Jordan, Serbia, Ukraine, Montenegro.
14 ADePT 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
Table 2.1 with Standard Errors Table 2.1 Frequencies Table 2.1 Original
16 ADePT 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 ADePT: Directions for future development ADePT ADePT: Public Release mid-June 2007 ADePT 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.