Dissertations, Theses, and Capstone Projects

Date of Degree

2-2019

Document Type

Dissertation

Degree Name

Ph.D.

Program

Economics

Advisor

Liuren Wu

Advisor

Wim Vijverberg

Committee Members

Chu-Ping Vijverberg

Subject Categories

Econometrics | Finance | Macroeconomics

Keywords

Business cycles; Macroeconomic states; Markov Chain model estimation, evaluation, and forecast; K-fold cross-validation; U.S. Treasury yield curve.

Abstract

I analyze different shapes of Treasury yield curves in order to better reflect and predict the U.S. economy. Since the late 1980s, macroeconomists have found that the slope of the yield curve predicts economic activity such as inflation, output growth, and recessions, but they have not fully examined the links between various shapes of yield curve and the macroeconomy. To fill the gap, I classify yield curve shapes with the U.S. Treasury yield data, detect the shape patterns over the business cycles, and map these shapes onto corresponding inflation and production states. Although the downward-sloping yield curve reliably predicts U.S. recessions, its signals were present during some recessions. Moreover, the hump, flat and bowl-shaped yield curve also demonstrate their ability to forecast recessions and the prediction becomes more accurate after the 1982 recession. However, it is still challenging to establish the link between each shape and the macroeconomic state.

To forecast future economic states, I model and estimate the yield curve transition pro- cess, evaluate alternative models and perform validation tests. I find that the shape transition displays significant momentum and asymmetry. But the information from the shape transition is not quite helpful in forecasting macroeconomic states.

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