Technological innovation, such as self-driving trucks, threatens occupations, such as truck drivers, with sudden obsolescence. Using a bare-bones overlapping generations model, we examine an occupation facing possible obsolescence. The occupation pays ‘obsolescence rents,’ with fewer and older workers remaining in the occupation. We study teamsters at the dawn of the motor truck, current occupations threatened by computerization, and truckers dreading robotic trucks. As predicted, wages in threatened occupations rise, employment falls, and the occupations become ‘grayer’. Older workers become more likely to enter and less likely to exit the occupation than young ones and sometimes even increase in number.

African Americans face shorter employment durations than similar Whites. We hypothesise that employers discriminate in acquiring or acting on ability-relevant information. In our model, monitoring Black, but not White, workers is self-sustaining. New Black hires were more likely fired by previous employers after monitoring. This reduces firms’ beliefs about ability, incentivising discriminatory monitoring. We confirm our predictions that layoffs are initially higher for Black than non-Black workers, but that they converge with seniority and decline more with the Armed Forces Qualification Test for Black workers. Two additional predictions, lower lifetime incomes and longer unemployment durations for Black workers, have known empirical support.