Data Review (Hands On)

1. Data Review (Hands On) Amonthep Chawla East-West Center & Nihon University Population Research Institute National Transfer Accounts

2. Objectives • To understand your surveys: your surveys may not provide all information needed to construct NTA • Understand purposes of surveys • Review questionnaires • Any missing information on income , expenditure and demographic characteristics • To aware that you may encounter estimation problems due to outliers, missing data, sampling weights, smoothing, etc. • To prepare survey data before estimating age profiles necessary for NTA National Transfer Accounts

3. Outline • I. Demographic variables • II. Data cleaning • III. Components and classifications of expenditures • IV. Components of income • V. Smoothing National Transfer Accounts

4. I. Demographic Variables • Age of individuals: what is the age limit? • Dummy for household headship • Dummy for school attendance (currently attending school or not) • Education level for school attendance (if currently attending school, what is the level of education: primary, secondary or higher education) • Health characteristics (number of times visiting hospitals, health usage or any information regarding to health condition) • Sampling weights (always use weight option) National Transfer Accounts

5. Household Heads • How household heads are defined: economic head or self-reported head? • Each household should have one person as a household head • Two or more household heads: pick the oldest or the highest income, depending on culture or norm • No head: assign one person • What is the minimum age for head?; should he/she be older than 15? Need to understand laws and culture of the country National Transfer Accounts

6. Education: Enrolment Rates • Plot enrolment rates by age and by education level • How does the result differ from other surveys, i.e. census and other government document? • Any information on private or public school enrolment • Check minimum and maximum age of school enrolment • Is there minimum age of school enrolment for the kindergarten level? • Be aware that childcare is not education National Transfer Accounts

7. II. Data Cleaning • Need to carefully check survey data in order to avoid or detect possible data problem by • summarizing data, using sampling weights, to check for missing data, outliers, data underestimating or overestimating, etc. • Using scatter plots to detect outliers: be aware that some extremely high health consumption (usually by the elderly) may be real • Missing data: replaced with 0 or imputed, depending on how serious this problem is National Transfer Accounts

8. III. Components and Classifications of Expenditures • Two types of expenditure: consumption and non-consumption expenditure • Avoid using non-consumption expenditure to estimate NTA private consumption • Examples of non-consumption expenditures are • transfers (i.e., taxes, gifts or other transfers made to other households) • asset income (negative asset income such as interest expense on mortgage or consumer debt) • Be cautious if using individual consumption rather than household consumption, i.e. missing data National Transfer Accounts

9. Including non-consumption Only consumption Double-hump consumption is more outstanding when non-consumption is included National Transfer Accounts

10. Income Tax • How to estimate income tax at the individual level: 2 methods • 1. Using household tax expenditures and allocating to each members proportionally to their taxable income • 2. Not using household tax data but using individual taxable income directly to measure individual tax payments • What are the tax rates in these two methods? • The first method allows for household level variation in the tax rate while the second method assumes that all household income is taxed at the same rate National Transfer Accounts

11. Income Tax (cont.) • Method 1 is preferred as it gives better information on who actually pay taxes • Be cautious: income tax data may be underestimated or not reported • If possible, check both methods and examine how different the age profiles of income tax based on two methods are National Transfer Accounts

12. Check: On what types of income is income tax levied in your economy? Not using household tax data leads to overestimate taxes paid at older ages in Japan National Transfer Accounts

13. IV. Components of Income • Household surveys report income either at the individual level or the household level • Unit of analysis for NTA is at the individual level: individual income is needed • Assignment of income • labor income: assigned to individual members • asset income and transfer income: assigned to household head National Transfer Accounts

14. National Transfer Accounts

15. Property Income • Possible components of property income in surveys: interest, rent and dividends; some surveys include property income with non-labor income • Tabulate the age profile of property income (assigned to household head) for estimating • corporate income tax, and • operating surplus of corporations National Transfer Accounts

16. V. Smoothing • Visually check if the beginning and ending of the smoothed and unsmoothed age profiles are different • Not over-smoothing: measure percentage errors between smoothed and unsmoothed profiles; choose span or bandwidth that yields the least percentage error between the two National Transfer Accounts

17. Some Rules for Smoothing • Smooth and aggregate: smooth components of the age profiles and aggregate them up, i.e. smooth earnings and labor’s share of self-employed income and add them up to measure the age profile of labor income • Do not smooth public and private education age profiles • Use unsmoothed health consumption for newborns because it is usual to have high health consumption at this age National Transfer Accounts

18. Rules for Smoothing (cont.) • Income, income taxes and familial transfer outflows: begin smoothing from the adults, excluding those younger age group who do not earn income. • However, problem arises when some beginning age group may appear to have negative values for these variables. • This could be solved by replacing the negative by the unsmoothed values for the beginning age group. National Transfer Accounts

19. Smoothed education consumption could eliminate age specific education consumption, i.e., primary school and college education expenses National Transfer Accounts

20. Use unsmoothed health consumption for newborns Different spans yield different results: always check for the variations among young and old ages National Transfer Accounts

21. Lower spans cause lower percentage difference between smoothed and unsmoothed age profiles than higher spans National Transfer Accounts

22. Conclusions • It is important to examine demographic characteristics, particularly education and health, reported in the surveys • Need to cleanup data set to avoid or detect data problem, which could cause serious mistakes while estimating age profiles for NTA • Avoid including non-consumption expenditure while estimating consumption age profile • Labor income is assigned to individuals while asset income and transfer income is assigned to head • Choose appropriate span or bandwidth that causes the least variation between smoothed and unsmoothed age profiles National Transfer Accounts