" Trends and Cycles of Wage Inequality: A Bayesian Approach"
Dr. Diana Alessandrini
St. Francis Xavier University
Friday Nov 27 ¨ 4:00-5:15pm ¨ MULH 3022
Abstract:
We estimate a Bayesian unobserved components model to separate wage inequality in the U.S. into its long run trend and its cycle. We then investigate whether wage inequality is related to business cycle fluctuations. Existing studies generally find that hourly wage inequality is acyclical, implying that wage percentiles move similarly over the business cycle and leave wage dispersion largely unaffected. We show that this apparent acyclicality masks substantial time variation in the relationship between wage inequality and aggregate fluctuations. Wage inequality has alternated between pro-cyclical and counter-cyclical regimes over time but has become predominantly counter-cyclical after the mid-1990s, implying that wage inequality is now more likely to rise during recessions rather than expansions. To uncover these changes, we construct time-varying measures of cyclical co-movement. Our framework allows for correlation between trends and cycles, persistence in cyclical fluctuations, and time variation in the relationship between GDP and inequality cycles. We conclude by investigating possible explanations for the evolution of cyclicality over time.
