Ilse Lindenlaub Publications

We develop a new equilibrium model in which households’ labour supply choices form the link between sorting on the marriage market and sorting on the labour market. We first show that in theory, the nature of home production—whether partners’ hours are complements or substitutes—shapes equilibrium labour supply as well as marriage and labour market sorting. We then estimate our model using German data to empirically assess the nature of home production, and find that spouses’ home hours are complements. We investigate to what extent complementarity in home hours drives sorting and inequality. We find that home production complementarity strengthens positive marriage sorting and reduces the gender gap in hours and in labour sorting. This puts significant downward pressure on the gender wage gap and on within-household income inequality, but fuels between-household inequality. Our estimated model sheds new light on the sources of inequality in today’s Germany, and—by identifying important shifts in home production technology toward more complementarity—on the evolution of inequality over time.

We analyze sorting in a frictional labor market when workers and jobs have multidimensional characteristics. We say that matching is positive assortative in dimension (j, k) if workers with higher endowment in skill k are matched to a job distribution with higher values of attribute j in the first-order stochastic dominance sense. Crucial for sorting is a single-crossing property of technology. Sorting is positive between worker-job attributes with strong complementarities but negative in other dimensions. Finally, sorting is based on comparative advantage: workers sort into jobs that suit their skill mix rather than their overall skill level.

The onset of the Covid-19 pandemic has led to a dramatic reduction in employment and hours worked in the US economy. The decline can be measured using conventional data sources such as the Current Population Survey and in the number of individuals filing for unemployment. However, given the unprecedented pace of the ongoing changes to labor market conditions, detailed, up-to-date, high frequency data on wages, employment, and hours of work is needed. Such data can provide insights into how firms and workers have been affected by the pandemic so far, and how those effects differ by type of firm and worker wage level. It can also be used to detail – in real time – the state of the labor market.