On Monday, November 4 2019, 14:00 - 15:30, Hans Sievertsen (University of Bristol) will present:
Beyond Treatment Exposure: The Timing of Early Interventions and Children’s Health
This paper analyzes the impact of the timing of nurse home visiting (NHV) on infant and maternal health. We study universal NHV in Denmark, where nurses (i) monitor and screen infant and post-partum maternal health, (ii) provide information and counselling to new parents, and (iii) refer families with identified problems to other health care professionals. We exploit exogenous variation in the timing of forgone visits induced by the 2008 national nurse strike. Using data on the population of children born in Copenhagen in the period up to the strike and in control years, we show that children (and mothers) who missed early nurse visits after birth have more general practitioner contacts in their first five years of life compared to those who missed visits later. We speak to mechanism for these effects by showing (i) that nurses in control years perform well in identifying health risks during early home visits, and (ii) that children of parents with no educational background in health and childcare and first-parity children drive the health effects. Taken together, our findings provide evidence for the importance of universal screening and timely provision of information and counselling to new parents. A stylized cost-effectiveness calculation confirms that early universal NHV is worth the while.
Room: WST-C.02.12, Weststadttürme Berliner Platz 6-8, Essen
On Monday, October 28 2019, 14:00 - 15:30, Jody Sindelar (Yale University) will present:
Health Behaviors: Big Data, New Tech and Big New Opportunities for Research
Health behaviors are critical, and sometimes overlooked, components of health and productivity. Some risky behaviors have been studied seriously, e.g. smoking, alcohol abuse, and illicit drug use. Other behaviors may be important to these outcomes but there is insufficient evidence to support or quantify their importance. For example, good sleep may enhance physical and mental health, productivity, and reduce driving accidents, but to what extent and for whom?
Recent advances in new technology open opportunities to study behaviors that have not been well-studied and to re-examine other behaviors that can now be measured more in-depth, often capturing important intra-daily variability. Wearables, for example, produce real-time, frequent, multi-dimensional measures 24/7/365; these are Big Data. They are continuously and passively measured instead of being recalled after a few years.
Building on my previous work on health behaviors, this presentation will explore and present some of the opportunities for economic research using Big Data, new measures, new methods (AI, innovations in randomized experiments: ‘in the wild,’ ‘smart,’ A/B testing). These allow more rigorous and precise analyses and determination of causality, e.g. by use of timing or controlling for key omitted variables (ability to control for geocodes, genes/biology). The large size of data sets allows determination of heterogenous impacts of policies and interventions. Economists are well-poised to push the frontiers of this research.
A new working paper has been added to the CINCH working paper series: “Preventive Home Visits” byNorman Bannenberg, Oddvar Førland, Tor Iversen, Martin Karlsson and Henning Øien.
Abstract: This paper evaluates the introduction of preventive home visits (PHV) for older people in Norway. Their purpose is to support autonomy and independence as well as preventing disability and nursing home admissions. We contribute to the literature by exploiting a natural experiment in Norwegian municipalities. Our results show that the introduction of a PHV program significantly changes the use of local public resources away from nursing homes, while increasing the utilization of home-based care. Further, PHVs lead to a decline in hospital admissions by 8 percent – whereas treatments for mental health conditions remain unaffected. Mortality is reduced by 4 percent in the age group 80 and above.