Graduation Year


Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts


Mathematical Economics

Reader 1

Patrick van Horn

Reader 2

Sean Flynn

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Despite opinion and confidence in leading economic indicators varying widely, many economists, businessmen, and central bankers continue to use these predictors to help forecast future macroeconomic conditions and guide decision-making processes. These indicators have been combined to create various indices that aim to anticipate trends and changes in the business cycle. This study investigates the predictive power and accuracy of four popular leading economic indices through an empirical comparison. The comparative analysis of six linear regression models leads to the conclusion that lagged output (real GDP) provides the best forecast for economic growth and that popular indices comparatively lack accuracy. Additionally, no lagged variable is able to predict turning points in the economy and instead can only predict macroeconomic conditions with continuing trends.

This thesis is restricted to the Claremont Colleges current faculty, students, and staff.