We show that unemployed individuals maintain significant access to credit. Following job loss, the unconstrained borrow, while the constrained default and delever. Both defaulters and borrowers are using credit to smooth consumption. We quantitatively show that creditregistries and long-term credit relationships allow the unemployed to partially offset income losses using credit, despite various forms of adverse selection. We estimate the model and find that the optimal provision of public insurance is unambiguously lower as credit access expands. The median individual in our simulated economy would gain both in steady-state as well as during the transition if the income replacement rate from public insurance programs is lowered from the current US policy of 41.2% to 39.8%.
For whom has earnings risk changed, and why? To answer these questions, we develop a filtering method that estimates parameters of an income process and recovers persistent and temporary earnings for every individual at every point in time. Our estimation flexibly allows for first and second moments of shocks to depend upon observables as well as spells of zero earnings (i.e., unemployment) and easily integrates into theoretical models. We apply our filter to a unique linkage of 23.5m SSA-CPS records. We first demonstrate that our earnings-based filter successfully captures observable shocks in the SSA-CPS data, such as job switching and layoffs. We then show that despite a decline in overall earnings risk since the 1980s, persistent earnings risk has risen for both employed and unemployed workers, while temporary earnings risk declined. Furthermore, the size of persistent earnings losses associated with full year unemployment has increased by 50%. Using geography, education, and occupation information in the SSA-CPS records, we refute hypotheses related to declining employment prospects among routine and low-skill workers as well as spatial theories related to the decline of the Rust-Belt. We show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption. Lastly, we find that rising persistent earnings risk while employed (unemployed) leads to welfare losses equivalent to 1.8% (0.7%) of lifetime consumption, and larger persistent earnings losses while unemployed lead to a 3.3% welfare loss.
We examine the role of technological change in explaining the large and persistent decline in earnings following job loss. Using detailed skill requirements from the near universe of online vacancies, we estimate technological change by occupation and find that technological change accounts for 45 percent of the decline in earnings after job loss. Technological change lowers earnings after job loss by requiring workers to have new skills to perform newly created jobs in their prior occupation. When workers lack the required skills, they move to occupations where their skills are still employable but are paid a lower wage. (JEL J24, J31, J63, O33)
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.