Presentation on theme: "Centre for Market and Public Organisation Understanding the effect of public policy on fertility Mike Brewer (Institute for Fiscal Studies) Anita Ratcliffe."— Presentation transcript:
Centre for Market and Public Organisation Understanding the effect of public policy on fertility Mike Brewer (Institute for Fiscal Studies) Anita Ratcliffe (CMPO, University of Bristol) Sarah Smith (CMPO and IFS)
Background Falling total fertility rates sparking interest in pro-natalist policies (France, Italy, Japan, Germany) UK: TFR fell from 2.93 (1964) to 1.63 (2001) –No explicit pro-natalist stance –This is not breed our way to economic success But, recent reforms (WFTC, CTC) increased financial help for families Does (changing) financial support for families affect fertility?
Phase 2: The effect of WFTC on fertility Working Families Tax Credit introduced in 1999 –More generous credits for families with at least one partner in work –More financial support with childcare if single parent/ both partners work –Accompanied by more general increase in child-related cash transfers Evaluation strategy: Difference-in-differences –Compare fertility before and after the reform for couples affected by WFTC reform (the treatment group) –Contrast with change over the same time period for couples not affected by the reform (the control group) –Use education level of adults as proxy for affected by reforms Data – British Household Panel Survey, Family Expenditure Survey
Phase 1: Understanding trends in fertility Key questions: –What have been the main changes in fertility behaviour? –(How) do these trends vary by education? –What factors appear to underlie the change in fertility? Family Expenditure Survey (1968-2003/4) & Family Resources Survey (1995/6-2004/5) –Use age of mother and children to infer age of birth; birth order –Construct (age-specific) parity progression ratios by cohort and period
1955 cohort: What proportion have a first birth at age 25? Combine current estimate: those aged 25 who have one child aged 0 in 1980 survey… … and backwards estimates: 1981 survey – those aged 26 whose oldest child is aged 1 1982 survey – those aged 27 whose oldest child is aged 2 and so on… Do the same for births at each age, and for different birth orders Current and backwards estimates are assumed to be equally valid; preliminary regression analysis shows no systematic effect of distance of survey year on estimated probability of birth Constructing fertility histories
Potential measurement error/ selection problems Mothers and childrens ages measured imprecisely –know interview date, age in completed years, DOB only sometimes Infant mortality Household re-formation –Rely on the fact that most children remain with natural mother Children leaving home –Higher order births are wrongly classified as first births –Solution: ignore births after certain age Trade off: selection on older fertility versus selection on younger fertility Choose age threshold of 38. Misses c. 3% births (increasing over time) Advantages (compared to eg retrospective fertility histories) –Long time-series (cohorts born 1935 – 1980) –Large sample sizes
Summary Statistics CohortSample SizeAges observed% with higher ed 193562133-37** 1945217623-379% 1955277716-3716% 1965697216-3720% 1975433216-3338% 1980381016-2838%