We investigate heterogeneous effects of new digital technologies on the individual-level employment- and wage dynamics in the U.S. labor market in the period from 2011-2018. We employ three measures that reflect different aspects of impacts of new digital technologies on occupations. The first...

Texas is the only state that does not mandate that employers carry workers' compensation insurance (WC) coverage. We employ a quasi-experimental design paired with a novel machine learning approach to examine the effects of switching from traditional workers' compensation to a so-called...

Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job...

This paper exploits novel data and empirical methods to examine parental preferences for child care. Specifically, we analyze consumer reviews of child care businesses posted on the website Yelp.com. A key advantage of Yelp is that it contains a large volume of unstructured information about a...

This chapter discusses the regulation of artificial intelligence (AI) from the vantage point of political economy, based on the following premises: (i) AI systems maximize a single, measurable objective. (ii) In society, different individuals have different objectives. AI systems generate...

Environmental research related to military activities and warfare is sparse and fragmented by discipline. Although achieving military objectives will likely continue to trump any concerns related to the environment during active conflict, military training during peacetime has environmental...

Common mental health problems impose significant costs on individuals and societies, yet healthcare systems often overlook them. We provide the first causal evidence on the effectiveness of a pioneering, nationwide mental health service for treating depression and anxiety disorders in England...

Childhood circumstances may impact senior health, prompting this study to introduce novel machine learning methods to assess their individual and collective contributions to health inequality in old age. Using the US Health and Retirement Study (HRS) and the China Health and Retirement...

Most definitions of algorithmic bias and fairness encode decisionmaker interests, such as profits, rather than the interests of disadvantaged groups (e.g., racial minorities): Bias is defined as a deviation from profit maximization. Future research should instead focus on the causal effect of...

Using provisions to ease the movement of business visitors in trade agreements, we show that removing barriers to the movement of business people promotes trade. We document the increasing complexity of Free Trade Agreements and develop an algorithm that combines machine learning and text...