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Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper seeks to analyze the relationship between energy subsidies on fossil fuels by countries and corresponding energy consumption, specifically electricity, by its citizens and occupants. The purpose of this was to determine whether pre-tax subsidies and post-tax subsidies have an effect on that consumption. This paper will discuss the prospect of accounting for post-tax subsidies as a method to curb rampant energy consumption throughout the world, with the focus being on residential electricity use. The two case studies, the Netherlands and Saudi Arabia, will illustrate the consumption patterns in relatively similar economic societies with different subsidy policies. Saudi Arabia will be a high pre-tax subsidy example while the Netherlands will be shown to account for some of the post-tax subsidies through an externality tax system. At the end of this analysis, this paper will show that the heavy subsidization of electricity production is strongly correlated to residential electricity consumption at levels that many officials would deem unsustainable, and that as such, subsidy reform is both beneficial and necessary.
ContributorsCorona, Kyle (Author) / Kelman, Jonathan (Thesis director) / Breetz, Hanna (Committee member) / School of Sustainability (Contributor, Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting any of these options, there has been very few alternatives. Now, the emergence of the continuing care at home program is providing hope for a different method of elder care moving forward. CCaH programs offer services such as: skilled nursing care, care coordination, emergency response systems, aid with personal and health care, and transportation. Such services allow seniors to continue to live in their own home with assistance as their health deteriorates over time. Currently, only 30 CCaH programs exist. With the growth of the elderly population in the coming years, this model seems poised for growth.
ContributorsSturm, Brendan (Author) / Milovanovic, Jelena (Thesis director) / Hassett, Matthew (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This project seeks to provide a general picture of the economic dependence on fossil fuels per County in the United States. The purpose for this study is creating a foundation for conversations about the future of fossil fuel workers and counties that depend heavily on fossil fuels. The main indicators utilized for this were employment and payroll data extracted from United States Census Bureau’s County Business Patterns dataset. A section on similarities between fossil fuel workers and other occupations was included, which shows possible alternative industries for fossil fuel workers. The main goal of the project is to provide possible solutions for mitigating job losses in the future. Some proposed solutions include retraining, expanding higher education, and investing in new industries. It is most important for future work to include input from most vulnerable counties and understand the social and cultural complexities that are tied to this problem.
ContributorsRamirez Torres, Jairo Adriel (Author) / Miller, Claek (Thesis director) / Shutters, Shade (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Electrical Engineering Program (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be taken into account while estimating unpaid claims. Reserve-estimating functions such as glmReserve from the “ChainLadder” package in the statistical software R were experimented with to produce their own results. Because of their insufficiency, a manual approach to building the model turned out to be the most proficient method. Utilizing the GLM function, a model was built that emulated linear regression with a factor for COVID-19. The effects of such a model are analyzed based on effectiveness and interpretablility. A model such as this would prove useful for future calculations, especially as society is now returning to a “normal” state.
ContributorsKossler, Patrick (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
Description
The objective of this study is to build a model using R and RStudio that automates ratemaking procedures for Company XYZ’s actuaries in their commercial general liability pricing department. The purpose and importance of this objective is to allow actuaries to work more efficiently and effectively by using this model that outputs the results they otherwise would have had to code and calculate on their own. Instead of spending time working towards these results, the actuaries can analyze the findings, strategize accordingly, and communicate with business partners. The model was built from R code that was later transformed to Shiny, a package within RStudio that allows for the build-up of interactive web applications. The final result is a Shiny app that first takes in multiple datasets from Company XYZ’s data warehouse and displays different views of the data in order for actuaries to make selections on development and trend methods. The app outputs the re-created ratemaking exhibits showing the resulting developed and trended loss and premium as well as the experience-based indicated rate level change based on prior selections. The ratemaking process and Shiny app functionality will be detailed in this report.
ContributorsGilkey, Gina (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05