Understanding the gender pay gap between and within occupations in Germany: What role do individual job tasks play?

We analyse whether gender differences in individual job tasks explain part of the gender pay gap between and within occupations. Theoretically, we combine the economic task-based approach with sociological considerations of gender essentialism and male primacy to discuss systematic variation in the demand for and remuneration of job tasks. Results of hybrid models and Blinder-Oaxaca decompositions reveal that women perform lower-paid job tasks more often than men do, which contributes to the gender pay gap between and within occupations. However, not all tasks performed by women pay less, pointing towards an interdependence between skill-biased technological change and gender-essentialist task selection.

Can't we all just get along? Citizen scientists interacting with algorithms

Responding to the continued and accelerating rise of Machine Learning (ML) in citizen science, we organized a discussion panel at the 3rd European Citizen Science 2020 Conference to initiate a dialogue on how citizen scientists interact and collaborate with algorithms. This brief summarizes a presentation about two Zooniverse projects which illustrated the impact that new developments in ML are having on citizen science projects which involve visual inspection of large datasets. We also share the results of a poll to elicit opinions and ideas from the audience on two statements, one positive and one critical of using ML in CS. The discussion with the participants raised several issues that we grouped into four main themes: a) democracy and participation; b) skill-biased technological change; c) data ownership vs public domain/digital commons, and d) transparency. All these issues warrant further research for those who are concerned about ML in citizen science.

The path of US inequality rests on political progress

Significance Burgeoning international trade and skill-biased technological change has raised the fortunes of university graduates while lowering the prospects of those with less education. President Joe Biden's administration is seeking to address many of the areas that have been identified as underlying sources of inequality. Impacts Vicious cycles of poor health, education and declining personal finances have created a group of society with reactionary political views. Populist politicians benefited from a generation of lost economic prospects, but state intervention and redistribution are winning support. Rising numbers of very rich people backed policies to raise their own wealth, and the wealthy continue to influence the political process.

Risk, the College Premium, and Aggregate Human Capital Investment

Despite increases in the college earnings premium to persistently high levels, investment in college education remains low. We can understand this apparent puzzle by considering the risk of attending college and, in particular, the possibility of failing to graduate. Students with a reasonable probability of completing college already enroll, and for those who do not enroll, the low chance of completion blunts the impact of the rising college premium. In the absence of improved college readiness, our quantitative results suggest that continuing long-standing trends in skill-biased technological change can be expected primarily to increase earnings inequality rather than college attainment. (JEL E24, I22, I23, J24, J31, O33)

Mechanisms of Environmental Regulation’s Impact on Green Technological Progress—Evidence from China’s Manufacturing Sector

As the world’s largest developing country, and as the home to many of the world’s factories, China plays a crucial role in the sustainable development of the world economy regarding environmental protection, energy conservation, and emission reduction issues. Based on the data from 2003–2015, this paper examined the green total factor productivity and the technological progress in the Chinese manufacturing industry. A slack-based measure (SBM) Malmquist productivity index was used to measure the bias of technological change (BTC), input-biased technological change (IBTC), and output-biased technological change (OBTC) by decomposing the technological progress. It also investigated the mechanism of environmental regulation, property right structure, enterprise-scale, energy consumption structure, and other factors on China’s technological progress bias. The empirical results showed the following: (1) there was a bias of technological progress in the Chinese manufacturing industry during the research period; (2) although China’s manufacturing industry’s output tended to become greener, it was still characterized by a preference for overall CO2 output; and (3) the impact of environmental regulations on the Chinese manufacturing industry’s technological progress had a significant threshold effect. The flexible control of environmental regulatory strength will benefit the Chinese manufacturing industry’s technological development. (4) R&D investment, export delivery value, and structure of energy consumption significantly contributed to promoting technological progress. This study provides further insight into the sustainable development of China’s manufacturing sector to promote green-biased technological progress and to achieve the dual goal of environmental protection and healthy economic growth.