This paper investigates the heterogeneous effect of access to remote work on the labor market outcomes of people with disabilities. I use a two-way fixed effects strategy exploiting the quasi-random variation in broadband access across the United States and industry-specific shocks in the demand for remote workers. I find that remote work access increases employment, hours worked, and wages of people with disabilities. This paper sheds light on how expanding remote work opportunities could play a crucial role in improving economic outcomes for people with disabilities.
Differential item functioning (DIF) occurs when individuals from different groups with the same level of ability have different probabilities of answering an item correctly. In this paper, we develop a Bayesian approach to detect DIF based on the credible intervals within the framework of item response theory models. Our method performed well for both uniform and non-uniform DIF conditions in the two-parameter logistic model. The efficacy of the proposed approach is demonstrated through simulation studies and a real data application.
When given time constraints, it is possible that examinees leave the harder items till later and are not able to finish answering every item in time. In this paper, this situation was modeled by incorporating a speeded-effect term into a three-parameter logistic item response model. Due to the complexity of the likelihood structure, a Bayesian estimation procedure with Markov chain Monte Carlo method was presented. The methodology is applied to physics examination data of the Department Required Test for college entrance in Taiwan for illustration.
This paper investigates if certain groups of minority workers are disproportionately harmed by negative remote work shocks. As Hispanic and Black workers are more concentrated in industries and occupation that are intensive in face-to-face interactions, such as the restaurant industry, they may experience larger employment losses when remote work becomes more prevalent.