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Can Machine Learning on Economic Data Better Forecast the Unemployment Rate?

Kreiner, Aaron S
http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1576798517511887

Abstract Details

2019, BA, Oberlin College, Economics.
This paper examines different machine learning methods to project the U.S. unemployment rate one year ahead. The forecasts include a naive forecast equal to the current unemployment plus the change of unemployment over the last year, along with forecasts from a Lasso regression and a neural network model. The last two models, which can be quickly run using an SQL database, select data from the Federal Reserve Economic Database (FRED) and are fitted (trained) in-sample from 1970 to 2000 to forecast quarterly unemployment rates over 2001 to 2018. The training window is updated in each forecast quarter to include new data. A rolling-window and non-rolling window period are tested for the training window. This paper finds that a non-rolling neural network model forecasts bests and outperforms the Survey of Professional Forecasters (SPF) across all time periods as does our Lasso regression model, though to a lesser extent. From experiments dropping broad categories of FRED, international data were the most important in forecasting the unemployment rate, followed in order by data from the FRED categories: Population, Employment, Labor Markets; and Money, Banking, and Finance.
John V. Duca (Advisor)
Edward F. McKelvey (Advisor)
Barbara J. Craig (Advisor)
32 p.
Economics
machine learning; forecasting; neural networks; artificial intelligence; unemployment rate

Recommended Citations

Citations

  • Kreiner, A. S. (2019). Can Machine Learning on Economic Data Better Forecast the Unemployment Rate? [Undergraduate thesis, Oberlin College]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1576798517511887

    APA Style (7th edition)

  • Kreiner, Aaron. Can Machine Learning on Economic Data Better Forecast the Unemployment Rate? 2019. Oberlin College, Undergraduate thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1576798517511887.

    MLA Style (8th edition)

  • Kreiner, Aaron. "Can Machine Learning on Economic Data Better Forecast the Unemployment Rate?" Undergraduate thesis, Oberlin College, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1576798517511887

    Chicago Manual of Style (17th edition)

oberlin1576798517511887
760
© 2019, all rights reserved.
This open access ETD is published by Oberlin College Honors Theses and OhioLINK.