Date of Award

Summer 8-19-2022

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science in Economics (MSECO)

Department

Economics

Advisor

Andrew Crawley

Second Committee Member

Keith Evans

Third Committee Member

Caroline Noblet

Additional Committee Members

Kelsi Hobbs

Abstract

The first section of this thesis investigates the primary dynamics and trends of the labor market matching efficiency over time. Instead of utilizing the aggregate U.S. matching efficiency in our analysis, we instead use state-level data to create a measure of matching efficiency for each U.S. state in our panel dataset. We also utilize two empirical models: a “base” model, which covers the entire time period of analysis from 2001 to 2021, and a “pandemic” model, which focuses specifically on the time period the COVID-19 pandemic was present in the U.S. The base model attempts to control for supply-side childcare constraints by including a variable that reflects the level of employment in the NAICS Child Care Services industry, but this variable was found to be statistically insignificant. In the pandemic model, the childcare issues variable was created to control for demand-side childcare constraints as it represents the proportion of U.S. Census Household Pulse Survey respondents who reported themselves as unable to work due to caring for children at home. This novel metric of childcare issues was found to have a strong negative and statistically significant effect on the matching efficiency during the pandemic time period.

The second section of this thesis aims to investigate the role of gender in differences in the new hires rate. The variables included in our analysis are inspired by the findings in the first section of this thesis, which indicate childcare issues have a strong negative impact on the matching efficiency. Since the matching efficiency captures how well the unemployed match to vacant jobs as a new hire, this is a natural extension of this research. We utilize sector-level new hires rates and gender compositions to create a proportion of male-to-female new hires rates. We include several variables to reflect labor market and macroeconomic conditions including a gendered ratio of childcare constraints. This childcare issues ratio was created using response data from the U.S. Census Bureau CPS Basic Monthly survey which asks people to report the main reason they were unable to look for work in the past month. We collected all responses indicating issues with family responsibilities and obtaining a form of childcare and found that as the ratio of male to female childcare issues increases, the gap between male and female new hires rates also increases.

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