Field and Online Experiments on Procrastination and Willpower

Self-control problems have recently received considerable attention from economic theorists. We conducted two studies to test the benefits of externally imposed deadlines and how willpower depletion affects behavior, providing some of the first data in these areas. Each study involved a behavioral intervention designed to affect performance. We find that for a lengthy task, regular deadlines neither reduce procrastination nor increase completion rates. Second, a willpower-depleting task reduces initial effort but increases overall task-completion rates. Our results help to inform ongoing efforts to understand and model procrastination, willpower and commitment mechanisms.Experiment, Behavioral Interventions, Procrastination, Willpower

Best Practices in Behavior Management Strategies for Classroom Teachers

In recent years, school districts have begun to utilize evidence-based approaches to teaching and promoting appropriate behaviors such as Positive Behavioral Interventions and Supports (PBIS), Responsive Classroom and Developmental designs. While these programs have been shown to be successful in a variety of settings, there continues to be an alarming increase in the amount of students who engage in a range of highly disruptive behaviors in school. Teachers report being underprepared, or not prepared at all, to effectively manage challenging behaviors from students, which leads to high rates of teacher burnout and attrition. Teacher preparation institutions need to provide classroom and behavior management methodology to ensure that their teachers are entering the field fully prepared to successfully create safe and accessible learning environments for all of their students, regardless of the challenges they bring with them to school. The purpose of this project is to explore general education teachers\u27understanding of and training in positive, proactive behavior management strategies and how to incorporate them into daily classroom practice

Coastal armoring and sinking property values: the case of seawalls in California

Rising sea levels necessitate careful consideration of different forms of coastal protection but cost-benefit analysis is limited when important non-market social costs have not been measured. Seawalls protect individual properties but can potentially impose negative externalities on neighboring properties via accelerated beach loss. We conduct a hedonic valuation of seawalls in two coastal California counties: San Diego and Santa Cruz. We find no strong evidence to suggest that the presence of a seawall is positively correlated with the value of the home protected. However, we find that seawalls are strongly negatively correlated with the value of neighboring properties in Santa Cruz but not in San Diego county, suggesting that the effect of seawalls depend on certain geographical attributes. Our results are robust to accounting for the public-good nature of locational attributes and the potential spatial dependence of housing prices. Simulation reveals that doubling the extent of seawalls in San Diego and Santa Cruz could reduce property tax revenues by $7 million and$54 million, respectively

Online Segregation

A large number of agents from two groups prefer to interact with their own types online and also have preferences over two online platforms. We find that an online platform can be tipped from integrated to segregated without any change in the ratio of the two groups interacting on the platform. Instead, segregation can be triggered by changes in the absolute numbers of both groups, holding the Schelling ratio fixed. In extreme cases, the flight of one group from a platform can be triggered by a change in the group ratio in favor of the group that ends up leaving

The 1960 Tsunami in Hawaii: Long Term Consequences of a Coastal Disaster

Research on the economic and human toll of natural disasters focuses on the short-term, often ignoring the important long-term impacts of these catastrophic events. The main reason for the lack of empirical research on the long-term is the inherent and unavoidable difficulty in identifying any long-term impacts and attributing them to the disaster. On the 23rd of May 1960, a devastating tsunami struck the city of Hilo on the island of Hawaii. Remarkably, there was no significant injury or damage elsewhere in the Hawaiian Islands. This tsunami provides a unique natural experiment as the tsunami was unexpected, and the other Hawaiian Islands, which were not hit by the tsunami, provide an ideal control group that enables us to precisely identify the counter-factual. We use a newly developed synthetic control methodology formalized in Abadie et al. (2010) to measure the long-term impacts of the tsunami. We find that while wages did not decline noticeably, population and employment trends shifted. Fifteen years after the event, unemployment was still 32% higher and population was still 9% lower than it would have been had the tsunami not occurred. We also find a corresponding decrease in the number of employers and sugar production in the county

Vog: Using Volcanic Eruptions to Estimate the Health Costs of Particulates

The high correlation of industrial pollutant emissions complicates the estimation of the impact of industrial pollutants on health. To circumvent this, we use emissions from Kīlauea volcano, uncorrelated with other pollution sources, to estimate the impact of pollutants on local emergency room admissions and a precise measure of costs. A one standard deviation increase in particulates leads to a 20-30% increase in expenditures on ER visits for pulmonary outcomes mostly among the very young. No strong effects for SO2 pollution or cardiovascular outcomes are found. Since 2008, the volcano has increased healthcare costs in Hawai'i by an estimated $60 million

Measuring cognition across mood and psychotic disorders

Cognitive impairments are present in both schizophrenia and bipolar disorder and are strong predictors of functional outcomes for patients. One barrier in cognitive research of these disorders is the lack of large, well-characterised cross-disorder samples with cognitive data. The aims of this thesis were to examine cognition across the bipolar / schizophrenia diagnostic spectrum and to develop a new online cognitive battery for use in psychiatric research. Cognition was examined in participants with bipolar disorder, schizoaffective disorder and schizophrenia through a meta-analysis of existing studies and analysing data from a large well-characterised sample. The main finding was that there is a gradient of increasing cognitive impairment from bipolar disorder through schizoaffective disorder – bipolar type to schizoaffective disorder – depressive type and schizophrenia. Participants with the subtypes of schizoaffective disorder differed in their cognitive performance. Lifetime history of psychosis was associated with cognitive performance across disorders. An online cognitive battery was developed to assess the domains outlined by the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative. The battery was validated against the MATRICS Consensus Cognitive Battery and showed that the tasks provided valid measurements of the majority of the MATRICS domains. A large sample of participants with a range of psychiatric disorders was recruited online. An examination of cognition in participants with major depressive disorder, bipolar disorder and schizophrenia showed that cognitive profiles were similar across disorders but participants with schizophrenia have more severe impairments than participants with bipolar disorder. An important concluding observation was that poorer cognitive performance was associated with poorer functional outcome across disorders. The findings of this thesis add to a growing literature showing the importance of examining cognitive function across psychiatric disorders. To date, it is the first study to develop and utilise an online cognitive assessment for psychiatric research

Information Spillovers Among Resource Extractors

Whilst the study of resource extraction under uncertainty has a long history in resource economics, there has been less attention paid to endogenous efforts to reduce uncertainty through learning and information acquisition. An unresolved empirical question is the degree to which individual extractors learn from the behavior of other extractors. The question is difficult to resolve because there is always the possibility that an unobserved influence on an individual extractor happens to be correlated with the behavior of other extractors. The difficulty is further compounded by the fact that an unobserved influence on one individual indirectly affects everyone who is influenced by that individual. We propose an identification strategy to overcome this concern by isolating individuals who have strong incentives to pay attention to their peer group but who do not themselves influence their peer group. The approach is particularly well-suited to natural resources that experience a gold rush of new entrants. Fueled by a booming Japanese economy, the northern California sea urchin fishery experienced a surge of new entrants in the late 1980s and early 1990s. We use these new entrants to cleanly identify strong information spillovers