This repository houses a comprehensive collection of documents and code from a bi-disciplinary bachelor's thesis in mathematics and econometrics. This project delves into how work hours and income affect sleep patterns and their subsequent implications on health and productivity. Utilizing linear regressions and R programming, this thesis analyzes data from the US Time Use Study to explore these dynamics.
As our daily lives accelerate and our days stretch longer, sleep—a vital resource—often becomes a luxury that more and more find difficult to afford. Consider this alarming statistic: between 2001 and 2020, the age-adjusted prevalence of diabetes in the United States showed a constant increase, highlighting a public health crisis that coincides with increasingly long and stressful work periods (CDC). Furthermore, the sleep economy, valued at $432 billion in 2019 and expected to reach $585 billion by 2024, reflects a growing recognition of its importance for health and economic efficiency (Statista). The link between lack of sleep and chronic diseases such as diabetes, obesity, and cardiovascular diseases is well-established. According to Our World in Data, global obesity, often linked to insufficient sleep quality, worsens under the effect of long working hours and increasing economic pressure.
The research question we address is both direct and essential: "How do work hours and income influence sleep, and what are the implications for health and productivity?" This topic touches us personally. As students in a dual degree in economics and mathematics, we have constantly juggled a tight schedule, where every minute of sleep counted. Our own struggles with shortened nights and overloaded days reflect the experiences of millions of others, underscoring the urgency to understand the balance between professional life and personal well-being.
Contributors: A. AUGÉ. Supervision: Professor C. LELARGE. Thank you!
Here’s what you can find in this repository:
This document is the final written thesis that includes the introduction, literature review, methodology, results, discussion, and conclusion of the study. Highlights:
- Examination of sleep pattern disparities based on income and work hours.
- Analysis of health and productivity impacts due to varying sleep quality and duration.
This file contains all the R scripts used for data analysis in the project. It includes scripts for data cleaning, preprocessing, and detailed statistical modeling using linear regression techniques.
A compiled R Markdown document that visualizes the data analysis process and results. This PDF includes both the code and its outputs, such as graphs and tables, providing a visual and technical insight into the findings.
The raw dataset used in the thesis, formatted as a CSV file. It includes comprehensive time use data from the US Time Use Study, which has been analyzed to explore the impact of economic and behavioral factors on sleep.
Documentation of the dataset providing detailed descriptions of each variable used in the analysis. It explains the source, nature, and transformations applied to the dataset for the purposes of this research.
Contains the academic source utilized throughout the thesis. Ie the foundational paper "Sleep and the Allocation of Time" by Jeff E. Biddle and Daniel S. Hamermesh, Michigan State University.
Presentation slides for the thesis defense. This document summarizes the research question, methodology, key findings, and the significance of the results in a structured presentation format.
The AI-generated cover image for the project, used for presentation and promotional purposes. It visually represents the thematic focus of the thesis.
The R scripts can be run to reproduce the analysis presented in the thesis. The dataset 4.Data.csv must be in the same directory as the scripts for them to run correctly.
Interested in contributing to this project? Please read through the existing documents and understand the data and analysis before proposing changes or additions.
This project is licensed under the MIT License. If you use or reference this project in your research or work, please credit it by citing:
→ Piero PELOSI, Work Hours and Income: Effects on Sleep, available on GitHub.
For any further inquiries or possible collaborations, feel free to contact me on LinkedIn.