Latest version, January 2022
NBER working paper, December 2020
We construct a framework for integrated epi-econ assessment: theory, calibration to micro-, macro-, and epi-data, and numerical methods for quantitative policy evaluation. The model has an explicit microeconomic, market-based structure. It highlights trade- offs, within period and over time, associated with activities that involve both valuable social interaction and harmful disease transmission. We compare market solutions with socially optimal allocations. Our calibration to covid-19 implies that households shift their leisure and work activities away from social interactions. This is especially true for older individuals, who are more vulnerable to disease. The optimal allocation may or may not involve lockdown and changes the time allocations significantly across age groups. In this trade-off, people’s social leisure time becomes an important factor, aside from deaths and GDP. We finally compare optimal responses to different viruses (SARS, seasonal flu) and argue that, going forward, economic analysis ought to be an integral element behind epidemiological policy.
First version, November 2021
NBER working paper, December 2021
We adapt the wage contracting structure in Chari (1983) to a dynamic, balanced-growth setting with re-contracting à la Calvo (1983). The resulting wage-rigidity framework delivers a model very similar to that in Jaimovich and Rebelo (2009), with their habit parameter replaced by our probability of wage-contract resetting. That is, if wage contracts can be reset very frequently, labor supply behaves in accordance with King et al. (1988) preferences, whereas if they are sticky for a long time, we obtain the setting in Greenwood et al. (1988), thus allowing significant responses of hours to wage changes.
Latest version, October 2021
CEPR discussion paper, October 2021
Older version (with different title), July 2020
We quantify the unemployment-risk channel in business-cycle fluctuations, whereby an initial contractionary shock is amplified through workers reducing their demand in fear of unemployment. We document two stylized facts on how unemployment and unemployment risk respond to identified demand and supply shocks in US data. First, separation and job-finding rates play similar important roles in accounting for the overall unemployment response. Second, separations are more important early on, while job-finding rates respond with a lag. We show how a tractable heterogeneous-agent new-Keynesian model with a frictional labor market matches both facts once we include endogenous separations and sluggish vacancy creation. Relative to a model with exogenous separations and free entry, our framework attributes almost twice as large a share of output fluctuations to the inefficient unemployment-risk channel, and thus gives a larger role to stabilization policy.
CBS working paper, December 2020
I introduce a simple model which endogenously generates a Pareto distribution in top earnings, consistent with empirics. Workers inhabit different niches, and the earnings of a worker is determined by the niche-specific supply of labor and a constant-elasticity labor-demand curve. The highest paid workers are the ones that inhabit a niche with few other workers. A Pareto tail in earnings emerges as long as the distribution of workers over niches satisfies a regularity condition from extreme-value theory, satisfied by virtually all continuous distributions in economics.
(R&R at the International Economic Review, previously circulated as Harmenberg and Sievertsen)
Latest version, November 2017
I use Danish administrative data 1980-2013 to study the underlying mechanisms generating fluctuations in income-shock moments. I partition the population into 37 narrowly defined educational categories and document the cyclicality of labor-income shock moments for each category separately. For the individual educational categories, mean income growth is strongly correlated with income-growth skewness, with an average correlation of 0.87 − 0.88. The connection between income-growth skewness and mean income growth is not only strong in the time dimension, but also in the cross section. Across the 37 educational categories, the correlation between mean income growth and income growth skewness is 0.93 − 0.96. Labor-market frictions together with variations in productivity growth can generate the relationship between mean income growth and income growth skewness. In a quantitative job-ladder model, variations in productivity growth quantitatively capture both the time-series and cross-sectional relationship.