GETTING STARTED Workshop Track A Wednesday, June 5, 9am-10am Gretchen Donehower University of California at Berkeley, Demography United States.

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Presentation transcript:

GETTING STARTED Workshop Track A Wednesday, June 5, 9am-10am Gretchen Donehower University of California at Berkeley, Demography United States

Preliminaries Workshop objectives – Understand how to begin constructing NTA – Get started on macro controls, lifecycle accounts – Create country-team poster for Friday’s poster session Welcome and greetings! – Who are you? – What are your NTA objectives? – Tell us about your data, what you have, what you need to find Population counts National accounts Household surveys and administrative records Does everyone have access to the NTA wiki? (

Preliminaries What is an age profile? – A schedule of age-specific average flow amounts – Based on flow measure or proxy indicator from a household survey a government report other NTA age profiles NTA assumptions – Smoothed – Adjusted up or down so that aggregate flow matches an aggregate estimate from national accounts

Organization of Accounts Transfers have inflows and outflows. Also collect a full set of tax profiles.

Outline (follows the manual) 3.1 Materials3.2 Building a micro-level database3.3 Basic methods3.4 Steps to follow in completing the accounts

Outline 3.1 Materials3.2 Building a micro-level database3.3 Basic methods3.4 Steps to follow in completing the accounts

3.1 Materials Necessary human and computer resources – Helps to have a team – Knowledge of institutional features of the country – Computing skills (spreadsheets, survey data analysis and programming in Stata, R) – Use saved programs, not point-and-click Makes revision easier Makes sharing with others easier, across the NTA network and over time within your country

3.1 Materials Data requirements – General: same time period, nationally representative, sufficient age detail Also want detail on any sub-groups you are interested in studying (e.g. sex, region, urban/rural, SES indicators like educational attainment) – Population estimates Single year of age to 90+ Evaluate quality of estimates (see Appendix) Can use UN World Population Prospects if problems with national estimates Significant non-household population?

3.1 Materials Data requirements (cont.) – National accounts data Get as much of it as you can find – List of main SNA tables given in the manual – Need tables by SNA sector Which government agencies produce your accounts? How do they publish the results? What is available in international databases? Beware revision schedules! Will probably also need – government budget documents – entries for your country in the International Monetary Fund’s Government Finance Statistics (GFS) publications

3.1 Materials Data requirements (cont.) – Household surveys and administrative records Income and expenditure surveys – Direct measures or indicators of relative age pattern Specialized surveys on sub-groups – Older people – Persons not in households (e.g. nursing home population) Administrative data – Government reports on public program participation by age » May give monetary flows » May only have participation indicators

3.1 Materials Data requirements (cont.) – Household surveys and administrative records Features: – Nationally representative – Designated household head – Sufficient sample size – Household roster by age, sex, work/school status – Detailed income by source data – Detailed expenditure by type data

Outline 3.1 Materials3.2 Building a micro-level database3.3 Basic methods3.4 Steps to follow in completing the accounts

3.2 Building a micro-level database What goes in it? – Age profiles in the database Start with your income and expenditure survey, create NTA variables from survey items Merge on any external NTA variables to each person – Example: merge records on publicly provided health care by age of individual – Can use as many additional characteristics in the merge as data allows – Other information in the database Population counts Macro controls What can you do with it? – Calculate NTA age profiles For intra-household transfers, especially (must have a micro-level database with macro-adjusted individual-level age profiles for a set of variables to computer intra-household transfers) – Other interesting studies: Sub-groups (regions, sex, urban/rural, socio-economic status) Explore variability (medians instead of means, percentiles)

Outline 3.1 Materials3.2 Building a micro-level database3.3 Basic methods3.4 Steps to follow in completing the accounts

3.3 Basic methods Aspects of an NTA age profile – Per capita measure by age Can be direct measure or proxy – Smoothed Reduces noise from sampling Smooth lowest-level components Beware of eliminating “real” features of the age pattern – Peaks/valleys, elbows, zeros False negative values should be replaced with zeros Details and examples in Appendix

3.3 Basic methods Aspects of an NTA age profile – Macro-adjusted Scale Factor Calculation: Apply Scale Factor:

3.3 Basic methods Steps to follow in calculating an lowest-level age profile – Calculate the macro control – Identify measure or proxy indicator and make it a part of the micro-level database 1. From household survey (with survey weights if applicable) – Use individual-level data if available – Otherwise allocate household amount to individuals in the household 2. From administrative records (merge onto micro-level database) 3. On a priori grounds (i.e. assumed or calculated from other age profiles) – Calculate the single year age group averages – Adjust age shape for any missing populations (i.e. persons not represented in survey or administrative records) – Smooth Evaluate to ensure that no real variation has been eliminated – Adjust smoothed and non-smoothed profiles to controls Evaluate adjustment factor to test the validity of the age shape

3.3 Basic methods How many low-level age profiles to calculate? – Must have lowest-level of NTA reportable profiles, but below that, making sub-profiles can improve estimates Just need identifiable macro controls and different age pattern indicators (example of different levels of education) Build higher-level age profiles by adding up lower-level age profiles Don’t re-smooth higher-level profiles Don’t combine profiles with different final age categories

3.3 Basic methods How to evaluate resulting age profiles – Internal NTA validity checks Verify aggregate amount matches macro control Evaluate smoother (plot smooth and unsmoothed) Sub-profile consistency with higher-level profiles? Does age profile look reasonable compared to other countries in the NTA database? Is age profiles >0, <0 or =0 in appropriate age ranges? Role of children Do balancing flows actually balance? – External validity checks Are macro controls reasonable relative to SNA amounts from international databases? Do your estimates agree with other researchers who have studied the topic? Overall plausibility in the country context

3.3 Basic methods Document and archive estimates – Write up methods for each age profile with references and data sources In simple tables or a technical paper or country-specific NTA manual – Save all computer programs and add thorough comments – Upload finalized age profiles and documentation to on-line database at

Outline 3.1 Materials3.2 Building a micro-level database3.3 Basic methods3.4 Steps to follow in completing the accounts

Gather Data Identify available surveys, administrative records, national accounts, and population data Choose base year in which all necessary data are available Obtain data permissions and copies of datasets Evaluate data quality, coverage, usability Lifecycle Accounts (Ch 5) Calculate macro controls for components of consumptiona and labor income If you have extensive, detailed national account data, you may want to calculate all macro controls at this time to make sure your macro controls satisfy the flow constraint (See Appendix C) Estimate age patterns from administrative and survey data Smooth, adjust to controls, and evaluate Public Age Reallocations (Ch 6) Calculate macro controls for public reallocations (transfers, asset income and saving) Estimate age shapes for these variables from administrative and survey data Smooth, adjust to controls, and evaluate Private Age Reallocations (Ch 7) Calculate macro controls for private reallocations (transfers, asset income and saving) Estimate age shapes for these variables from survey data Smooth, adjust to controls, and evaulate Estimate components of intra-household transfers from already estimated profiles and sharing algorithm Smooth, adjust to modified control, evaulate Estimate private saving as the balancing item

Lab Exercise – Start Poster 1.Create “DATA” and “COUNTRY BACKGROUND” sections for poster – See list of example items 2.Plot age schedule of population for NTA year to create “POPULATION” section for poster; if possible add TFR and life expectancy