Struggling with Time: Investigating Coupling Constraints

Figures & data

Figure 1 Cumulative prospect theory’s (CPT) value and weighting functions (Tversky and Kahneman, 1992)

Figure 2 Sample question from the experiment.

Table 1. Characteristics of participants in the stated adaptation exercise

		%
Educational attainment	low/medium	19.8
	high	80.2
Country of origin	Netherlands	94.9
	other	5.1
Gender	mother	49.7
	father	50.3
Number of children	one child	48.8
	two children	45.3
	three children	5.9
Age of child(ren)	at least one child aged 0–1 years	63.3
	at least one child aged 2–3 years	50.8
	at least one child aged 4–5 years	14.3
	at least one child aged 6–8 years	7.0
Childcare use	daycare only	84.5
	day and after‐school care	12.2
	after‐school care only	3.3
Residential location	city of Utrecht	37.6
	surrounding suburbs	62.4

Table 2. Estimated coefficients for cumulative prospect theory’s (CPT) value and weighting functions

	Original data^a
	Model 1	Model 2	Manipulated data
α for mothers (shape, value function)	1.09	1.07	1.33
α for fathers (shape, value function)	0.99	0.79	0.99
λ (loss aversion coefficient)	1.36	1.40	3.99
γ (shape, the weighting function)	0.84	0.84	0.83
Goodness of fit^b	0.539	0.539	0.552
^aA genetic algorithm used for the estimation can produce multiple statistically equivalent solutions. The equivalent sets of parameters with the smallest and largest gender difference are presented here (cf. Schwanen and Ettema, 2007)^bIndicator ranges from zero to 1, with zero indicating a perfect fit.

Tversky , A. and Kahneman , D. 1992 . Advances in prospect theory: cumulative representation of uncertainty . Journal of Risk and Uncertainty , 5 : 297 – 323 .

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Schwanen , T. and Ettema , D. . Coping with unreliable transportation when collecting children: examining parents’ behavior with cumulative prospect theory . Proceedings of the 86th Annual Meeting of the Transportation Research Board . January 2007 , Washington, DC, USA.

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