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on Neuroeconomics |
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Issue of 2021‒10‒11
two papers chosen by |
| By: | Dang, Hai-Anh H.; Trinh, Trong-Anh; Verme, Paolo |
| Abstract: | Hardly any evidence currently exists on the causal effects of mental illness on refugee labor market outcomes. We offer the first study on this topic in the context of Australia, one of the host countries with the largest number of refugees per capita in the world. Analyzing the Building a New Life in Australia longitudinal survey, we exploit the variations in traumatic experiences of refugees interacted with time as an instrument for refugee mental health. We find that worse mental health, as measured by a one standard deviation increase in the Kessler mental health score, reduces the probability of employment by 14.1% and labor income by 26.8%. We also find some evidence of adverse impacts of refugees' mental illness on their children's mental health and education performance. These effects appear more pronounced for refugees that newly arrive or are without social networks, but they may be ameliorated with government support. Our findings suggest that policies that target refugees' mental health may offer a new channel to improve their labor market outcomes. |
| Keywords: | refugees,mental health,labor outcomes,instrumental variable,BNLA longitudinal survey,Australia |
| JEL: | I15 J15 J21 J61 O15 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:949&r= |
| By: | Christian Turk; Nicholas Polson; Shiva Maharaj |
| Abstract: | Gambits are central to human decision making. Our goal is to provide a theory of Gambits. A Gambit is a combination of psychological and technical factors designed to disrupt predictable play. Chess provides an environment to study Gambits and behavioral economics. Our theory is based on the Bellman optimality path for sequential decision making. This allows us to calculate the Q values of a Gambit where material (usually a pawn) is sacrificed for dynamic play. On the empirical side, we study the effectiveness of a number of popular chess Gambits. This is a natural setting as chess Gambits require a sequential assessment of a set of moves (a.k.a. policy) after the Gambit has been accepted. Our analysis uses Stockfish 14 to calculate the optimal Bellman Q values. To test whether Bellman's equation holds in play, we estimate the transition probabilities to the next board state via a database of expert human play. This then allows us to test whether the Gambiteer is following the optimal path in his decision making. Our methodology is applied to the popular Stafford, Reverse Stafford (a.k.a. Boden-Kieretsky-Morphy), Smith-Morra, Goring, Danish, and Halloween Gambits. We conclude with directions for future research. |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2110.02755&r= |