Kenneth Arrow Econ 490 fall 2019

At my software development internship last Summer that I have written on a few times I participated in a Triangular Principal-Agent relationship. I had a manager, who was the manager of the overall software team, as well as a mentor who was a normal member of the team that was tasked with being in charge of me. I did most of my work with the mentor, and I received tasks from both the mentor and the manager. Most of the time these tasks lined up roughly, in a way that I could complete everything for both of them in the given time. There were a few weeks, though, in which the tasks did not line up well and I did not have enough time to finish them. I think hypothetically it would have made more sense to complete the tasks given by the manager rather than the mentor, as he was the one with the overall vision of where the project was going. In reality, though, I found myself completing the mentor tasks first.    I felt like he was more in tune with my exact role in the project and what I

Last year I was a member of the Data Science and Statistics club on campus. The group was project-based. At the beginning of the semester, any interested students could present a data science project idea they had, then the rest of the students could join whatever group they found interesting. Most of the projects had a scope of about a semester, and even completely inexperienced students were allowed to join. The team I joined set out to do an analysis of NBA data. From the start, there was some conflict on whether the NBA had enough easily accessible data for us to use to complete the project. Some members of the group thought that college football would be an easier sport to analyze. They said that we should do college football as a way of getting our toes wet, then we could move onto the NBA. We started out using NBA data for the first couple of weeks, but the college football supporters were pretty adamant in their idea. We finally relented and started using football data. As

During high school as well as my first year of college I worked at a country club. I would set up weddings, serve food, then clean up at the end. From this job I have several examples of very different types of management and punishment styles, some being completely counterproductive, some not really achieving any at all, and some actually working out in the end. An example of a counterproductive punishment style came from a manager that disliked seeing employees sitting in the break room. The job as a whole had a 'hurry up and wait' mindset towards everything. We would set up for the entire night ahead of time before the wedding even started, which led to a more fluid evening. This meant that for most weddings we would be ready to go for everything at a moment's notice, but we would have to wait for that notice as the planners were the ones timing us. This obviously led to downtime, and there was only so much cleaning we could do before we legitimately ran out of tasks.

One interesting example of team production with gift exchange that also includes some elements of choosing risk levels is cryptocurrency mining. In short, cryptocurrencies are decentralized, digital mediums of exchange. They are not backed by any government. A famous example of this is Bitcoin. The way each Bitcoin is initially distributed is through mining. Mining is performing mathematical problems that prove bitcoin transactions are not fraudulent. Anyone can mine Bitcoin using their own home computers. Essentially these bitcoin miners take the place of your credit card company, in terms of tracking and okaying purchases. The first miner to solve the problem correctly is awarded bitcoin. When Bitcoin first started this worked out reasonably well, as there were fewer miners so there was a greater chance to be the 'winner'. However, as the popularity of bitcoin grew, people began to make specialized mining machines whose performance blew that of the home miners out of the wa

Luckily most of my decisions about major and job thus far have been both effective in reducing income risk while also feeling like good decisions here and now. I was accepted to UIUC into the Pre Engineering track. I wanted to be a computer science major because I had enjoyed all of the programming classes I took in high school. After a disastrous and stressful first year, I embraced the idea of being an economics major. This decision definitely did decrease my right out of college future earning potential, but it was one that had to be made. Luckily I am happy with the choice, and I believe that it is low enough risk to not be very worried about the future. Now, as an Economics major, I have been involving myself in data science research and extracurricular activities. These are both a good decision looking forward because it is easier to sell myself to recruiters, but they also are good decisions now because I enjoy both the work and activities. I involve myself in a few other ex

1. Common Post Themes: Each post is based on the most recent class topic, and each topic builds off the last. Transfer costs, for example, could be brought up in basically any prompt so far. In the Illinibucks hypothetical could be brought up in up in terms of how such a vast organizational change would certainly bring up some difficulties. They could have also been talked about in the description of an effective team one has worked on if the individual chose to write about how the team used to be less effective then changed. Another common theme is team organization. Beyond the blog post it is explicitly tied to, it could be related to the Illinibucks post in how an effective team could be organized to carry out the project. It could have also been a part of the transfer pricing blog post where the writer could have talked about how exactly the changing organization switched up its structure. Finally, team organization could have been brought up in opportunism by speaking of what s