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The increasing use of physiological recordings in experimental economics requires a precise timing of interesting events, such as the presentation of a set of choices, the decision-making moment and the reception of feedback through the display of a decision outcome. In this note we provide a simple, accurate and inexpensive solution based on the use of external photo-sensors that detect changes in light intensity on the participants’ screens occurring in synchrony with experimental events. This system ensures an accurate communication between standard programs broadly used to run behavioral economic experiments, such as z-Tree, and eye-tracking devices or biosignal acquisition systems recording physiological variables, such as skin conductance, heart rate and electroencephalogram. An example is briefly discussed, offering specific guidelines for the application of this methodology in economic contexts with strategic interaction.

The labor supply effects of becoming a grandmother are not well established in the empirical literature. We estimate the effect of becoming a grandmother on the labor supply decision of older workers. Under the assumption that grandmothers cannot predict the exact date of conception of their grandchild, we identify the effect of the first grandchild on employment (extensive margin). Our Timing-of-Events approach shows that having a first grandchild increases the probability of leaving prematurely the labor market. This effect is stronger when informal childcare is more valuable to the mother. To estimate the effect of an additional grandchild (intensive margin), we assume that the incidence of a twin birth among the third generation is not correlated with unobserved determinants of the grandmother's labor supply (first generation). Our respective instrumental variable estimations show a significant effect of further grandchildren. Our results highlight the important influence of the extended family on the decisions of older workers and point to mediating effects of different institutional settings.

This paper analyzes the interplay between early-life conditions and marital status, as determinants of adult mortality. We use individual data from Dutch registers (years 1815-2000), combined with business cycle conditions in childhood as indicators of early-life conditions. The empirical analysis estimates bivariate duration models of marriage and mortality, allowing for unobserved heterogeneity and causal effects. Results show that conditions around birth and school ages are important for marriage and mortality. Men typically enjoy a protective effect of marriage on mortality, whereas women suffer during childbearing ages. Having been born under favorable economic conditions reduces female mortality during childbearing ages.

This paper investigates employment effects of further vocational training, short classroom training, as well as One-Euro-Jobs for lone mothers receiving Unemployment Benefit II (UB II) in Germany. Lone mothers receiving UB II participate in these active labor market programs at very high rates. As soon as their youngest child is aged three or above, their program entry rates are as high as for childless singles. This paper examines whether lone mothers can actually profit from partici-pating in these programs, given low levels of childcare provision. The empirical analyses are based on administrative data. A timing-of-events approach is used to control for possible selectivity in program entries. Separate models are estimated for entries into minor employment, regular contributory employment in general, and regular contributory employment connected to a complete exit from benefit receipt. Findings are that lone mothers profit especially strongly from participating in voca-tional training programs in terms of entering regular contributory employment in general as well as regular contributory employment connected to a complete exit from benefit receipt. Presumably, they can particularly benefit from updating their job skills after interrupting their employment for some time to care for their children. Ef-fects of short classroom training programs are somewhat smaller, and One-Euro-Jobs have small positive effects for some, but not all, groups of lone mothers. Diese Studie beschäftigt sich mit Wirkungen der Förderung der beruflichen Weiter-bildung, schulischen Trainingsmaßnahmen sowie Ein-Euro-Jobs bei alleinerziehen-den Arbeitslosengeld-II- (ALG-II-)Bezieherinnen. Die Eintrittsraten von alleinerzie-henden ALG-II-Bezieherinnen in diese Maßnahmen sind sehr hoch. Für Alleinerziehende mit einem jüngsten Kind im Alter von mindestens drei Jahren sind die Maßnahmeeintrittsraten vergleichbar mit denen der kinderlosen alleinstehenden Frauen. Diese Studie untersucht inwiefern Alleinerziehende tatsächlich von solchen Maßnahmeteilnahmen profitieren können. Denkbar wäre, dass positive Effekte aufgrund der geringen Verfügbarkeit von Kinderbetreuungsplätzen ausbleiben könnten. Die empirischen Analysen basieren auf administrativen Daten. Es wird ein Timing-of-Events Ansatz angewendet um für mögliche Selektivität bei den Programmzugängen zu kontrollieren. Für Eintritte in Minijobs, reguläre sozialversicherungspflichtige Beschäftigung im Allgemeinen, sowie reguläre sozialversicherungspflichtige Beschäftigung verbunden mit einer Beendigung des ALG-II-Bezugs werden jeweils separate Modelle geschätzt. Die Ergebnisse zeigen, dass Alleinerziehende beson-ders von der Förderung der beruflichen Weiterbildung profitieren können im Sinne höherer Eintrittsraten in reguläre sozialversicherungspflichtige Beschäftigung im Allgemeinen, wie auch reguläre sozialversicherungspflichtige Beschäftigung verbunden mit einer Beendigung des ALG-II-Bezugs. Möglicherweise können sie besonders von einer Erneuerung ihrer beruflichen Kenntnisse nach längeren Kinderbetreuungsphasen profitieren. Effekte von schulischen Trainingsmaßnahmen sind etwas geringer, und Ein-Euro-Jobs haben bei einigen, jedoch nicht allen Gruppen von Alleinerziehenden positive Beschäftigungseffekte.

This paper analyzes the interplay between early-life conditions and marital status, as determinants of adult mortality. We use individual data from Dutch registers (years 1815-2000), combined with business cycle conditions in childhood as indicators of early-life conditions. The empirical analysis estimates bivariate duration models of marriage and mortality, allowing for unobserved heterogeneity and causal effects. Results show that conditions around birth and school ages are important for marriage and mortality. Men typically enjoy a protective effect of marriage on mortality, whereas women suffer during childbearing ages. Having been born under favorable economic conditions reduces female mortality during childbearing ages.

When treatments may occur at different points in time, most evaluation methods assume - implicitly or explicitly - that all the information used by subjects about the occurrence of a future treatment is available to the researcher. This is often called the no anticipation assumption. In reality, subjects may receive private signals about the date when a treatment may start. We provide a methodological and empirical analysis of this issue in a setting where the outcome of interest as well as the moment of information arrival (notification) and the start of the treatment can all be characterized by duration variables. Building on the Timing of Events approach, we show that the causal effects of notification and of the treatment on the outcome are identified. We estimate the model on an administrative data set of unemployed workers in France which provides the date when job seekers receive information from caseworkers about their future treatment status. We find that notification has a significant and positive effect on unemployment duration. This result violates the standard no anticipation assumption and rules out a threat effect of training programs in France.

Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution of treatment effects from duration data with selectivity, by means of a nonparametric maximum likelihood estimator with unrestricted numbers of mass points for the heterogeneity distribution. We find that specifying the treatment effect as homogenous may yield misleading average results if the true effects are heterogeneous, even when the sorting into treatment is appropriately accounted for. Specifying the treatment effect as a random coefficient allows for precise estimation of informative average treatment effects including the program's overall impact on the mean duration.