Abstract
We develop a novel indicator of aggregate and sectoral wage inflation by leveraging multiple sources of wage data with detailed sectoral information, using a hierarchical dynamic factor model. Our empirical approach controls for data-specific measurement errors and industry-specific developments; this feature makes it particularly effective in assessing wage inflation during the Covid era, which saw increased dispersion in wage inflation across industries and larger divergences between measures of the level and trajectory of wage inflation. Our findings indicate that as the labor market has cooled, aggregate underlying wage inflation has returned to pre-pandemic levels, with wage growth in some sectors even falling below its pre-pandemic rate.
Published Version
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