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Calculating NTTA Consumption Profiles

Calculating NTTA Consumption Profiles. Gretchen Donehower NTA Time Use and Gender Workshop Tuesday, October 23, 2012 Facultad de Ciencias Sociales, Universidad de la República Montevideo, Uruguay. Outline. Concepts involved in imputing consumption Consumption estimation strategy

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Calculating NTTA Consumption Profiles

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  1. Calculating NTTA Consumption Profiles Gretchen Donehower NTA Time Use and Gender Workshop Tuesday, October 23, 2012 Facultad de Ciencias Sociales, Universidad de la República Montevideo, Uruguay

  2. Outline • Concepts involved in imputing consumption • Consumption estimation strategy • Imputation assumptions • Simplified spreadsheet example

  3. Consumption Estimation Strategy • A Time Use Survey is: • A sample of time producers and types of activities they produce • A Time Use Survey is NOT: • A sample of all time produced in a household • A sample of time consumers and what they consumed • So what do we do to estimate consumption? • Impute consumption to producer’s household members and the general population by age and sex • Multiply by number of producers in the population by age and sex to get aggregate age-sex matrix • Divide by number of consumers to get consumption profile by age and sex

  4. Consumption Imputation Assumptions • For care activities • If care is for household members, divide equally among all household members in target age range • Example: for care of household children aged 0-18, divide time equally among all household members age 0-18 • If care is for non-household members, divide equally among general population in target age range • Example: for volunteering, divide time equally among total population • For general household activities • Divide equally among all household members

  5. Simplified Spreadsheet Example • Go to wiki and get copy of spreadsheet, or follow along on the projector

  6. A note of caution • Our allocation assumptions are equal for males and females • So, the only way males and females can differ is through household structure (e.g. if households with only baby girls have greater average production of childcare, baby girls will look like they have higher consumption of care than baby boys) • In contexts with heavy “son preference,” this may be a very bad assumption! • Do some sensitivity tests trying an allocation of childcare or other activities to girls of x% of boys • OR implement regression-based allocation to get a data-driven estimate (will only partially address the issue, but it’s a start)

  7. Finalizing • Reasonability checks • Look at production and consumption for each activity. Do they look reasonable? • Is childcare only being consumed by children? Adult care only by adults? • Is consumption of general household activities reasonably smooth? • Does aggregate consumption equal aggregate production for each type of activity? • Sensitivity tests • Smoothing • Adjust smoothed profiles to make sure that production equals consumption

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