This project tackles three unresolved challenging problems in gender-stereotype reduction using the behavioral economics approach. First, how can we measure the impact of subconscious stereotypes on actual decisions and the resulting welfare costs? Whereas existing measurements are effective in detecting gender stereotypes, they are less effective in identifying the impact of stereotypes on actual decisions. Existing evidence of gender inequality is often confounded by innate abilities, social preferences and ambiguity attitudes. Part 1 of this project develops a new confound-free stereotype measure which directly reveals the impact of stereotypes on actual decisions and allows for the welfare costs estimation. The new measure complements existing measures, and will be effective in raising awareness of stereotypes and their economic consequences. Second, how do stereotypes evolve with new information? Despite the common view that given time and new information gender inequality will disappear, little is known about stereotype dynamics. Part 2 investigates stereotype dynamics. It identifies decision biases that prevent people from optimally processing and acting upon objective information, and thus trap people in stereotypes. For instance, the bias “ambiguity aversion” can deter women from entering male-dominant fields where career prospects are more ambiguous for women, thus reinforcing the vicious cycle of male-dominance. Eliminating decision biases will increase gender equality. Third, how can we improve policy effectiveness? Despite numerous initiatives and policy implementations, the convergence to equality has been stagnating. Part 3 provides new inequality-reducing tools. First, it estimates hidden costs for existing inequality-reducing policies. For instance, counter-intuitively, gender quota may in fact increase stereotypes as people attribute females’ success to the quota policy rather than to females’ competence. Second, it designs and evaluates two nudges that open new policy intervention channels.

Why do people facing low risks tend to purchase more insurance than people facing high risks? Why do attempts to provide affordable health insurance in developing countries typically result in very low enrolment rates? These behavioural patterns are puzzling given objective risk estimates (e.g. life expectancy, prevalence of health risks). The rational expectations paradigm assumes that people base their decisions on these objective risk estimates, but is this really so? Research in psychology shows many cognitive biases in belief formation, challenging the assumption of rational expectations. And even if expectations are rational, beliefs may deviate from risk estimates because of private information. Measuring (subjective) beliefs is crucial to understanding people?s behaviour. Moreover, since Keynes (1921), we know that the confidence an agent has in his beliefs can be as important as the beliefs themselves. Ellsberg (1961) introduced the term ?ambiguity? to describe situations in which decision makers are unsure about the risks they are facing. He showed how the classical expected utility model fails to describe agents? behaviour under ambiguity. The present research program will measure and model expectations in economics, using the most recent insights from the ambiguity literature. The first part of the program will develop new methods to analyze behaviour and to measure beliefs and confidence. These new methods will, for instance, allow us to reveal people?s true expected longevity to better understand pension decisions. The second part will apply the new methods. I will incorporate people?s real subjective beliefs about risks and life expectancy in the analysis of their insurance and pension decisions. I will also show how one of the new methods can be applied to how people evaluate their life satisfaction. The results of the research program will improve policy design by taking into account what people really believe when making their decisions.

The healthcare sector is one of the most carbon-intensive sectors. In response, the Dutch government has called for more environmentally sustainable healthcare. The project ESCH-R addresses this challenge with its mission to accelerate the adoption of circular interventions in hospitals and thereby lower the ecological footprint of the healthcare sector. Our research question is: How can hospitals move away from single use medical consumables and make the transition towards circularity? Together with societal partners, our interdisciplinary team will develop circular, safe and scalable strategies for circularity. In the long-run, the ESCH-R project contributes to a sustainable and resilient health system.

All European countries have programs that aim to increase the employment rates of disabled individuals and decrease Disability Insurance (DI) rolls. Unfortunately, knowledge of which of these policies work is very limited. Evaluations of programme effectiveness are scarce throughout the OECD. This research will provide empirical evidence on the effectiveness of several programmes to inform which policies work. Several reforms aimed at reducing the historically high number of claimants of the Dutch DI scheme have been introduced since the late 1980s. Descriptive evidence suggests that the share of DI recipients only started to decrease after the last decade reforms, which increased integration incentives for employers and employees and tightened up the medical criteria for DI entitlement. The proposed research will evaluate these reforms and identify the effects on employed individuals who become disabled and reemployment of unhealthy inactive individuals. I will use new rich and detailed administrative data containing health and employment information for large samples of the Dutch population (at least 5 Million) that allow identification of short-term and long-term causal effects on several employment-related outcomes including employment, wages and permanency of contract. In addition to evaluation of Dutch reforms, I will use European longitudinal survey data to investigate why some individuals with health limitations remain non-employed while others manage to get into work. I will first analyse the effects of non-policy variables using detailed health and employment longitudinal information for individuals aged 16-64 available in a few European countries. The research will also provide comparative cross-country analysis using longitudinal data from fifteen EU countries aimed at identifying DI policies that can explain different re-employment rates across EU-countries. These policies, together with the existence of mandatory employment quotas identified in my earlier research on effects of health on transitions out of employment, will be evaluated using non-experimental evaluation techniques.

Children inherit a random combination of their parent’s genes, but the non-random matching of parents contributes to the stratification of societies and the proliferation of socio-economic inequalities through generations. Gene-environment interaction studies may, however, improve our understanding of how environmental circumstances can change genetic influences on socio-economic inequalities. In this project, I will refine and extend statistical methodology to account for assortative mating in heritability and gene-environment interaction studies, and detach genetic from non-genetic assortative mating. By drawing on a unique combination of data, this project advances the gene-environment interplay and intergenerational mobility literature on both theoretical and empirical frontiers.