Author: M árton Varga 27/01/2012

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“Will I Ever?”: Estimating the Probability and Speed of Progression to the Consequent Childbirth Author: Márton Varga 27/01/2012

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“ Will I Ever? ” : Estimating the Probability and Speed of Progression to the Consequent Childbirth. Author: M árton Varga 27/01/2012. Can we predict their childbearing decisions?. QUESTIONS. DATA and METHODOLOGY. How many children will women have?. When do they give birth?. - PowerPoint PPT Presentation

Transcript of Author: M árton Varga 27/01/2012

Page 1: Author: M árton Varga 27/01/2012

“Will I Ever?”:Estimating the Probability and Speed of

Progression to the Consequent Childbirth

Author: Márton Varga

27/01/2012

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Main source: Fertility and Family Survey

How many children will women have?

When do they give birth?

Technique: Split-population survival estimation

Sample: 5484 Portuguese women (1947-79)

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Education leads to delayed childbearing and a longer interval between the second and third birth. University graduates are more likely to have the third child.

More siblings are associated with a higher probability of having the second child.

Younger cohorts are more likely to postpone childbearing, to remain childless, and to have fewer children.

Changes in the unemployment rate and childcare availability do not influence fertility timing.

Mothers, who were older at their last delivery, have a lower probability of the consequent birth, but they wait less if they decide to have another child.

10% remain childless, 30 % stop at one child, while 70% stop at two children.

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FIGURE 1. KAPLAN MEIER SURVIVAL ESTIMATESNote: Duration is measured from the age of 14 and from the 3rd quarter after the last birth.

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TABLE 1 - TRANSITION TO THE FIRST BIRTHα β

Secondary -0.183 0.373***(0.113) (0.042)

University 0.072 0.571***(0.214) (0.075)

One -0.087 -0.004(0.121) (0.046)

Two 0.010 -0.008(0.123) (0.047)

Three or more -0.114 -0.096**(0.107) (0.041)

Born 1960-79 -0.149** 0.000(0.060) (0.036)

Unemployment change -0.024**(0.011)

Childcare change -0.006(0.004)

Constant 0.876*** 2.774***(0.119) (0.053)

District dummies YES YESPeriod effects NO YESln σ -0.956***

(0.039)κ 0.516***

(0.053)Log-likelihood -11042.97Number of subjects 5484Observations 63,593Note: Standard errors in parentheses. ***Significant at 1%. **Significant at 5%. *Significant at 10%.

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TABLE 2 - TRANSITION TO THE SECOND BIRTHα β

Secondary -0.030 0.010

(0.093) (0.067)

University 0.078 -0.119

(0.140) (0.095)

One 0.229** 0.070

(0.113) (0.079)

Two 0.348*** 0.085

(0.116) (0.082)

Three or more 0.427*** 0.051

(0.102) (0.069)

Born 1960-79 -0.209*** -0.097

(0.070) (0.071)

Unemployment change 0.015

(0.027)

Childcare change -0.007

(0.008)

Age at first birth -0.074*** -0.046***

(0.008) (0.006)

Constant 1.904*** 2.916***

(0.221) (0.197)

District dummies YES YES

Period effects NO YESln σ -0.700***

(0.062)

κ 1.489***

(0.123)

Log-likelihood -6108.71

Number of subjects 3353Observations 21,139Note: Standard errors in parentheses. ***Significant at 1%. **Significant at 5%. *Significant at 10%.

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TABLE 3 - TRANSITION TO THE THIRD BIRTHα β

Secondary 0.054 0.592**

(0.241) (0.265)

University 1.286*** 0.808**

(0.379) (0.361)

One -0.147 -0.381

(0.262) (0.284)

Two 0.082 -0.109

(0.263) (0.284)

Three or more 0.396* -0.221

(0.234) (0.249)

Born 1960-79 -0.310*** -0.062

(0.111) (0.152)

Unemployment change -0.016

(0.062)

Childcare change -0.012

(0.018)

Age at second birth -0.181*** -0.040**

(0.013) (0.016)

Constant 4.076*** 2.738***

(0.403) (0.517)

District dummies YES YES

Period effects NO YESln σ -0.121

(0.086)

κ 0.401**

(0.188)

Log-likelihood -2310.73

Number of subjects 2101Observations 18,169Note: Standard errors in parentheses. ***Significant at 1%. **Significant at 5%. *Significant at 10%.

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Probability of stop at two

children33.9%

Probability of stop at two

children81.7%

Probability of stop at two

children86.3%

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Results are robust

Deserves more investigation

Results are plausible

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Thank you for the attention!