Filtering by
- All Subjects: risk
- All Subjects: Actuarial
- Creators: Zicarelli, John
- Creators: Economics Program in CLAS
- Resource Type: Text
This paper examines infrastructure spending in a model economy. Infrastructure is subdivided into two types: one that makes future production more efficient, and another that decreases the risk of devastation to the future economy. We call the first type base infrastructure, and the second type risk-reducing infrastructure. Our model assumes that a single representative individual makes all the decisions within a society and optimizes their own total utility over the present and future. We then calibrate an aggregate economic, two-period model to identify the optimal allocation of today’s output into consumption, base infrastructure, and risk-reducing infrastructure. This model finds that many governments can make substantive improvements to the happiness of their citizens by investing significantly more into risk-reducing infrastructure.
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.