Most discussions on the effect of in-migration on the local labor market have focused on causation flowing from migration to wages. The “textbook model” assumes a labor supply increase without a movement in the demand for labor, and holds that in-migration will cause the labor market to clear at a lower wage level. This conventional model makes the unlikely assumption that migration does not also expand local labor demand. We identify four channels through which migration will increase the demand for local labor: residential and non-residential construction and private and public demand for non-traded goods and services. In the moderate run, construction will move the labor demand curve more than any other factor. The elasticity of response of construction to changes in population differs across metropolitan areas. In the long run, construction will be completed; at all runs, both the private sector and public sector will expand purchases of non-traded goods and services to meet the needs of an expanded population. We then explore the factors that affect the magnitude of the response of labor demand through each of these channels, with particular emphasis on building supply elasticity as a key variable that characterizes different responses across different regions. We produce empirical estimates of the magnitude of induced labor demand through each of these channels, with the goal of measuring the effect of in-migration on labor demand. In some regions, preliminary estimates indicate that in the moderate run multipliers will produce an increase in labor demand greater than the increase in labor supply – a potentially destabilizing force for boom and bust.

The Federal Reserve wields enormous financial power through both policy and press. It is commonly understood in economics that the rational expectation of - and ensuing reaction to - an expected market phenomenon can be as impactful as the actual occurrence of the phenomenon itself. When the Federal Reserve helped form market-wide expectations of a “tapering” of their $85 billion per month quantitative easing program in September 2013 and then did not follow through, the overarching criticism from analysts was that the Federal Reserve “lost credibility” as a result of its apparent reneging. My goal is to quantify and measure the effect of such a change in credibility, should it exist, as its economic implications are immense in both theoretical and practical application. I aim to measure this change in credibility through changes in market volatility and inflationary expectations following a particular FOMC minutes release where the policy was considered to be "unexpected" as compared to historical time series data available. I expect recent data of unexpected decisions to show a trend of less "lost credibility" than previous data due to the differing and lesser known nature of the policy being exerted (quantitative easing as opposed to traditional monetary policy before the recession) and the inherent assumption of the temporariness of quantitative easing as recessionary policy. Should this prove to be the case, one could argue that quantitative easing has additional effectiveness as recessionary economic policy due to the Fed's ability to boost the economy with lesser inflationary horizons through expectation management as compared to the longer lasting inflationary horizons present in traditional monetary policy.

Humor is a universal part of every human life. Stoic philosophers like Plato emphasized self-control and believed that laughter diminishes self-control. Mark Twain said, “Humor is tragedy plus time.” The things that people find funny are deeply connected to what they regard as right and wrong. On the one hand, being ethical requires people to follow a set of moral principles that provides rules for their actions. On the other hand, humor often requires rule breaking and norm violation. Therefore the two concepts are often incompatible. Our experiment has shown the degree to which morals and humor correlate. Participants were randomly assigned to either the moral mindset or control condition. Participants in the moral mindset condition were instructed to write a story using a set of ethical words (e.g., honest, caring), whereas the control group was instructed to write a story using amoral words (e.g., banana, elephant). We then instructed participants to create a caption to a series of pictures that allowed us to assess their sense of humor. Finally the captions were rated by three trained research assistants for how humorous they were. Results suggest that participants in the moral condition produced less humorous captions compared to those in the control condition. We are currently extending the external validity of this finding by conducting this study in a business setting by soliciting responses to the survey from employees to rate fellow coworkers for their ethics and determining how humorous they are. Our research will have significant practical implications for hiring and human resource practices because a person that is humorous will have a better chance of being hired. Paradoxically, these employees are also likely to be less ethical and undermine organizational functioning in the long-term.

The abolition of capital and exchange controls in the UK in 1979 and the series of reforms and deregulations at the London Stock Exchange in October 1986, collectively termed the ‘Big Bang’, played vital roles in the revitalization of London as an international financial center. Beginning in the 1970’s with the revitalization of international finance, there were several key regulatory changes that impacted the relative competitive positioning of major stock exchanges. The first was the abolition of the historical cartel agreements for fixed trading commissions in the US in 1975. With the abolition of capital and exchange controls in the UK, competition from New York forced the unfixing of trading commissions, the allowance of dual capacity trading operations in financial institutions, the opening of the London Stock Exchange to foreign investors, and the implementation of new trading technologies. In this study, I will evaluate the impact that these deregulations had on the London Stock Exchange (LSE), the New York Stock Exchange (NYSE), and other major equity markets in terms of changes in trading volume. Using historic trading records of major cross-listed companies, I will conduct an event study to infer whether major shifts in trading volume between exchanges occurred as a result of these deregulations. I will also estimate the price elasticity of demand among the stock exchanges using data on commissions in different markets. I anticipate that a shift away from the LSE after 1979 to the lesser-regulated NYSE was due largely to the lifting of exchange controls in the UK. Similarly, I predict that the large-scale deregulations that came with the Big Bang will show to have caused the LSE to reclaim much of this lost trading volume and to grab order flow from neighboring European exchanges.

Teams are a common temporary system that can improve working efficiency. We define efficient work as the ideal outcome the team wants. Teams tend to work more efficiently than individual because the team members can double check each other’s work and teams can better handle more complex systems. Organizations such as hospitals utilize teams because they want high working efficiency and avoid low working efficiency caused by disruptions. Disruptions, the events that stop workflow, impact people’s way of working either positively or negatively. If disruptions strike a medical team it can have deadly consequences. Daily patients suffer and die when medical teams are disrupted, our study aims to identify and reduce the negative effects of disruptions. Common forms of disruptions are failure of communication, where teams are ill equipped or do not having enough information. Medical teams are not the only teams to be disrupted; the data we collect will also be used to improve the efficiency of production and service teams plagued by disruptions. We are using an I.R.B. (an ethic board with the goal of insuring subjects safety) approved interview scripts, online surveys, interview equipment, and professionals scheduled to be interviewed. Our study is proceeding in three phases. We have accomplished the first phase that consists of interviewing and surveying teams about events that disrupted their workflow. We are currently analyzing the interview using qualitative techniques and survey data using quantitative methods to find trends that identify the disruptions. In addition, we will design methods that teams can apply to decrease the negative effects of disruptions. The potential benefits from our research will aid teams to be efficient especially in the business and hospital settings where improved working efficiency can not only create value for the organizations, but also save people’s lives.

In the United States, the average woman intends to have 2.5 children, yet the US total fertility rate is just 1.89. Demographers and economists worry that below-replacement level fertility rates will impede economic growth and render the US incapable of supporting its aging population. To combat this problem, some governments in developed countries have implemented pronatalist policies to encourage women to have more children. This research seeks to discern whether such approaches are sound by analyzing the effect of the availability of more social services, especially childcare and health care, on a woman’s intention to have children. My data set consists of the 2008/2009 waves of the National Longitudinal Survey of Youth (NLSY) from the Bureau of Labor Statistics, one of the most comprehensive surveys in labor and family economics. My model consists of a multivariate linear regression with fertility as the dependent variable, and the availability and cost of social services, such as healthcare, childcare, and schooling, as well as demographic variables like age, ethnicity, and religion, as independent variables. I aim to show the impact of policy incentives on fertility at the individual level, and to discern what demographic factors make women more or less likely to have children. Furthermore, by using a recent data set, I hope to make timely and relevant conclusions and predictions about the childbearing intentions of young women in the United States that can inform current policy debates.