Title of Abstract

Determinants of Unemployment: An Analysis of US States from 2002 to 2020

Poster Number

3

Submitting Student(s)

Joseph Yakabowskas

Session Title

Poster Session 1

Faculty Sponsor (for work done with a non-Winthrop mentor)

Danko Tarabar, Ph.D.

College

College of Business Administration

Department

Accounting, Finance & Economics

Abstract

This paper examines the determinants of unemployment in the United States by using a panel data set from the 50 U.S. states between the years 2002 to 2020. The main variables considered are population, union membership, education, personal income, GDP, and political party control of state legislatures. This paper uses a pooled OLS regression, a fixed-effects regression, a random-effects regression, and a logistic regression to examine the effects of these variables on unemployment. The main finding was that the determinant of GDP was the main indicator of the unemployment rate, with the variables being negatively correlated. This paper also finds that having split legislatures is linked to lower probabilities of high unemployment, using the logistic regression model.

Start Date

15-4-2022 12:00 PM

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Apr 15th, 12:00 PM

Determinants of Unemployment: An Analysis of US States from 2002 to 2020

This paper examines the determinants of unemployment in the United States by using a panel data set from the 50 U.S. states between the years 2002 to 2020. The main variables considered are population, union membership, education, personal income, GDP, and political party control of state legislatures. This paper uses a pooled OLS regression, a fixed-effects regression, a random-effects regression, and a logistic regression to examine the effects of these variables on unemployment. The main finding was that the determinant of GDP was the main indicator of the unemployment rate, with the variables being negatively correlated. This paper also finds that having split legislatures is linked to lower probabilities of high unemployment, using the logistic regression model.