Both the demand for skilled labour and the associated skill wage premium have become increasingly dispersed across the United States. This paper investigates how the impact of technological change within occupations shapes these uneven local trajectories. I develop a novel measure of technological change by tracking shifts in task intensities within detailed occupations. Combining this measure with patent data and microdata, I show that innovation reallocates labour towards cognitive-intensive tasks, especially in densely populated areas. Motivated by this finding, I use a Bartik-style shift-share design to show that greater exposure to technological change decreases the wages of the least educated workers, thereby widening the college wage premium. While almost 80 per cent of the low-skill wage decline can be attributed to diminishing non-cognitive returns within occupations, occupational re-sorting plays a comparatively smaller role.

Every fifth worker changes their occupation every year, whereas the mechanisms behind the observed mobility of workers still need to be fully understood. This paper studies the relationship between work-hour instability and occupational mobility in the U.S. labour market. I use the longitudinal dimension of the Current Population Survey (CPS) to measure workers’ intra-year work-hour variation and analyse their mobility through the lens of a balanced occupation panel. The results show that being in the highest quartile of work-hour variation increases the probability of changing occupations by 0.33% for men and 0.81% for women, compared to an average monthly mobility rate of 1.71%. An analysis of the marginal effects across different household compositions suggests that the substantial gender gap is related to intra-household specialisation, highlighting the male breadwinner role. The last part of the study shows that only workers with highly volatile work hours sort themselves systematically into more stable occupations.

Women are significantly underrepresented among innovation leaders, including startup founders, patent inventors and venture capitalists. This raises the question of whether technological change is gender-biased in a way that systematically favours masculine work values and male-dominated occupations. And if so, how does it affect the evolution of the female labour market? We investigate these questions for the U.S. labour market by constructing a measure of gender-biased technological change based on time-varying occupation-level skill demand data combined with female relative employment shares in occupations. We combine this measure with USPTO patent data, decennial Census survey data and political data. Our pre-analysis (see link above) finds that technological change in the twenty-first century has degraded typical feminine work values such as cooperation, social orientation and integrity. At the same time, female-dominated occupations experienced relative decreases in labour demand in general and demand for cognitive skills specifically compared to male-dominated occupations. While college-educated women reacted to these changes by adopting masculine work values and sorting into male-dominated, non-routine cognitive occupations, women without a college degree are much less flexible in adjusting to the technology-induced changes, enhancing their disempowerment. In particular, high-skilled women drift increasingly apart from low-skilled women in terms of their working activities, family and work orientation, and political ideologies. 

In this project, we leverage unique Polish registry data on ex-prisoners and exploit a policy reform that increased the minimum wage of prisoners to the same level as the statutory minimum wage. After a statewide implementation of this policy, it became more difficult for incarcerated individuals to find a job, which is essential for them to collect work days that qualify for unemployment benefits upon release. This setting creates a compelling quasi-experiment to study the effect of liquidity on re-employment outcomes for ex-prisoners. For causal identification, we use the prison entry date—which determines exposure to the high- or low-cost prison work regime—as an instrument for qualifying for unemployment insurance. Naïve OLS estimates suggest that benefit claimants reintegrate into the labor market more quickly compared to non-claimants. In contrast, using the IV identification strategy reveals that claimants fare worse than non-claimants, remaining unemployed for longer. These findings underscore the importance of accounting for selection into prison work and suggest that a within-prison work policy that eases liquidity after release may unintentionally discourage job search.

PhD and Pre-PhD Working Papers

The recent evolution of employment indicates that the growth in the demand for cognitive ability in the U.S. labour market has flattened since the 2000s. This paper sheds light on this puzzle using updated O*NET ability data to measure cognitive and manual task intensity changes within occupations between 2008 and 2017. Non-routine cognitive and high-wage occupations increased while routine-intensive and low-wage occupations decreased in cognitive intensity. At the same time, the decline in manual intensity is more substantial in non-routine-cognitive and high-wage occupations. The differential task demand changes between occupations imply heterogeneous effects on the segmented labour market. Young men, workers with college degrees, and workers in STEM occupations experienced the most substantial increase in the demand for cognitive ability. The effects of task changes within occupations account for an 8.3% increase in the return to cognitive task intensity between 2008 and 2017.