Olivia Hwang

Based on the current trajectory of birth rates and potential events affecting birth rates, how will public school enrollment in the United States change by 2060?

Started June 16, 2023

Abstract or project description

I remember the walks home from my middle school. At 3:00 PM, on the dot, hoards of middle schoolers poured out of classrooms, crowding the streets daily with their bikes, band instruments, and roller backpacks. For us, the commute home was a time of relief, a comforting ritual almost, to chat and laugh with each other on the way home after a long day at school. I remembered these walks home as I read the report from Citizens Advisory Committee on Enrollment that listed my middle school to close in a plan for budget cuts due to declining enrollment in four of the six scenarios presented. It seemed almost impossible to me as I recounted the full classrooms, seemingly endless lunch lines, and crowds of children congregating in the campus quad. In the end, the school board decided to close two elementary schools, consolidate another, and leave my middle school on the table after seeing enrollment trends in the years after. Children, current and future, who were previously intending on attending these schools would miss out on their walks home from school. My experience is not unique, though. Birth rates around the U.S. have been declining ever since the Great Recession from 2007-2009, translating into lowering public school enrollment. Moreover, public school enrollment has similarly faced dwindling numbers in recent years due to the COVID-19 pandemic. This paper aims to provide evidence towards answering how current and potential birth rate trends could change public school enrollment by 2060. This paper uses secondary data analysis, sources from the Center of Disease and Control (CDC) and United States Census Data, compiled and organized by the Integrated Public Use Microdata Series (IPUMS). The data used from the CDC is out of the National Vital Statistics System (NVSS) which is collected through birth and death certificates of infants. Potential confounding is presented when considering not all data is complete or accurate due to changes made to legal records after the data is collected. The data used from the U.S. Census is collected from the American Community Survey (ACS), an annually conducted demographic survey which uses random sampling. Non-response sampling bias is addressed through offering multiple methods of conducting the survey (phone, mail-in, or a Census Bureau representative visit), imposing fines for non-response, and data weighting to correct the non-response bias. Since the ACS uses sampling, it still is subject to sampling bias, a factor important to note for when we manipulate data. We will use scenario-probability analysis to forecast the different outcomes of birth rate trends and subsequent school enrollment rates, demonstrating the effect of of these outcomes by estimating the human impact: the number of school closures, school district closures, and approximate change in school density (ie. how much larger would a school zone be?). Through this paper, I hope to inform policymakers and school districts of the potential scenarios, whether negative or positive, that could result from enrollment patterns.

How did the change in the cost of living in Silicon Valley, California in the past decade affect the economic growth of the area?

Started Aug. 17, 2022

Abstract or project description

The cost of living in Silicon Valley, California, has risen steadily over the past decade, seemingly while enrollment in public schools and birth rates in the area have been dropping. While analyzing how the change in the cost of living in Silicon Valley affects the economic growth of the area, a few assumptions must be asserted: The inverse relationship between the cost of living and birth rates, and the correlation between birth rates and enrollment in public school, and the direct relationship between birth rates and school enrollment with the economic growth of an area. While causation does not equal correlation, there are multiple pathways through which the increasing cost of living could impact economic growth, two of which will be analyzed in the following paper: 1. The rising cost of living causes more residents to have to move out and fewer residents wanting to move in, and consequently declining birth rates and school enrollment. This causes smaller school budgets and more school closures, then consequently the property value of the area decreases, and diminishes the attraction to live in the area. 2. The rising cost of living still causes residents to have to move out and fewer residents to want to move in, and the decline in school enrollment and consequent school budgets and closers cause the quality of schooling and education to go down. In the long run, this would cause more of the population to be less educated, negatively impacting the aggregate income, and consequently economic growth.