Veranstaltungen

We wrote the attached draft article, Valuing the Vaccine, in the context of debates over whether contracts to COVID-19 vaccine manufacturers for less than $40 per course were overcompensating those producers. In short, we argue that the right lodestar for valuing medical innovations is social value—not compensating R&D costs—and that even with low-end estimates of social value, current prices reward developers with a small fraction of those estimates.

During the talk, I will also explain our plans to extend this argument in a broader paper, tentatively titled Valuing Medical Innovation. Although cost-based pricing has attracted significant attention from scholars concerned with U.S. pharmaceutical pricing, our arguments for value-based pricing are not limited to the COVID-19 vaccine context. In some cases, such as drugs without rigorous evidence of comparative clinical efficacy, value-based pricing suggests that current rewards are too high. In other cases, such as for preventative medicines and treatments that require lengthy clinical trials, evidence suggests that current rewards are too low. 

Ansprechparterin: Lucy Xiaolu Wang

We investigate whether excessively optimistic beliefs play a role in the persistent demand for doctoral and postdoctoral training in science. We elicit the beliefs and career preferences of doctoral students through a novel survey and randomize the provision of structured information on the true state of the academic market and information through role models on nonacademic careers. One year later, both treatments lead students to update their beliefs about the academic market and impact career preferences. However, we do not find an effect on actual career outcomes two years postintervention.

Link to paper: https://research.upjohn.org/up_workingpapers/334/

Ansprechparter: Fabian Gaessler

How do children influence productivity, promotions, and participation in science? We investigate this question by analyzing biographies, patents, and publications for 82,094 American scientists in 1956, at the height of the baby boom. Output data indicate that mothers reach peak productivity in their mid 40s, nearly a decade after other scientists. Event studies of marriage show that mothers become more productive 15 years into marriage, when children are less work. Differences in the timing of productivity have important implications for tenure. Just 27% of academic mothers achieve tenure, compared with 48% of fathers and 46% of other women. Examining selection, we find that female scientists are more educated, half as likely to marry, one third as likely to have children, and half as likely to survive in science compared with men. While mothers who survive are positively selected, employment data indicate that a generation of baby boom mothers was lost to American science. (Joint work with Scott Kim)

Ansprechparter: Felix Pöge

Markush structures are molecular skeletons that contain not only specific atoms but also include one or several placeholders each representing a broad set of chemical (sub)structures. They are used by pharmaceutical companies to claim a large class of compounds without the necessity of writing out every fully defined single chemical entity in a patent application. (For instance, the Markush structures claimed within patent EP 0810 209 contain a total of 10^16 different compounds resulting from all possible permutations within the Markush structures.) After summarizing the ongoing policy debate regarding the use of Markush structures in patents, this paper provides first quantitative evidence regarding the use Markush structures in the pharmaceutical industry and their effects on important outcomes in the patent prosecution process.

Ansprechpartnerin: Marina Chugunova

In this paper, we argue that economic societies, established during the eighteenth-century, contributed to industrialization through the diffusion of new ideas generated during the Scientific Revolution in Europe. Local societies functioned as catalyst for the translation of scientific knowledge into useful knowledge and the diffusion to interested parties. We test this hypothesis by combining information on more than 3,300 society members from the membership lists of all active economic societies in the German lands with several measures of innovation and upper-tail human capital. We find a robust positive relationship between the local member density and the number of valuable patents, exhibitors at world fairs, and highly-skilled mechanical workers. We further show that grid-cell pairs with members from the same society show a higher technological similarity. We interpret this as evidence that economic societies generated information networks which fostered spatial knowledge diffusion and shaped the geography of innovation.

Ansprechpartner: David Heller

How much lower are the career earnings of workers who face large declines in demand for their occupations, compared to similar workers who do not? To answer this question we combine forecasts on occupational employment changes, measures of realized occupational decline and technological replacement, and administrative panel data on the population of Swedish workers, with a highly disaggregated initial occupational classification.  We find that compared to similar workers, those facing occupational decline lost about 2-5 percent of mean cumulative earnings from 1986-2013, with workers at the bottom of their occupation’s initial earnings distribution suffering substantially larger losses.  These earnings losses are partly accounted for by reduced employment and increased time spent in unemployment and retraining.

Ansprechparter: Michael E. Rose

In jobs where the cost of effort exhibits increasing differences in separate tasks, automation increases productivity by directly eliminating the automated tasks and indirectly by reducing the marginal cost of non-automated tasks. Here, I report a field experiment rotating supermarket cashiers between conventional (where they scanned and collected payment) and scan-only checkouts. Consistent with increasing differences in separate tasks, at conventional checkouts, cashiers who scanned faster collected payments more slowly. At scan-only checkouts, cashiers scanned 10 percent faster, consistent with lower marginal cost of effort in the non-automated task. The faster scanning was not due to learning, less task-witching, or differential shirking.

Ansprechparterin: Lucy Xiaolu Wang

Can artificial intelligence (AI) technologies complement or substitute for human managers in creating greater value for organizations? We argue that managers of the transformational leadership style with greater social skills benefit more from the assistance of AI than do managers of the transactional leadership style with fewer social skills. We provide causal evidence through a field experiment in a fintech firm whose managers provide training to employees on the calls made to collect overdue loans. We randomly assign employees to be trained by one of the following five options: an AI-bot, a transformational leadership-style manager, a transactional leadership-style manager, and both managers assisted by the AI-bot. We find that employees trained by each AI-assisted manager achieved higher performance, by collecting more payments, than did those trained by the manager alone, suggesting that both managers can gain from AI assistance. More interestingly, employees trained by the AI-assisted transformational manager outperformed both those trained by the AI-assisted transactional manager and by the AI-bot alone, indicating complementarity between transformational leadership and AI assistance. By contrast, the employees trained by the AI-assisted transactional manager underperformed those trained by the AI-bot alone, suggesting that the transactional manager is still at risk of being replaced by the AI-bot. These divergent performance outcomes occur because employees learn more from the AI-assisted transformational manager than from the AI-assisted transactional manager. Our findings suggest that, compared with transactional leadership, transformational leadership enable firms to obtain greater economic returns from their investment in deploying AI to manage employees.

Ansprechpartnerin: Marina Chugunova
 

Innovation under regulatory uncertainty and the role of expectations: Evidence from the U.S. drone market
Presenter: Virginia Herbst (TUM)
Discussant: Lucy Xialou Wang (Max-Planck-Institut für Innovation und Wettbewerb)

There and back again: Disruptive transitions in dyadic role relationships
Presenter: Maren Mickeler (LMU ISTO)
Discussant: Daniel Obermeier (TUM)

The rapid spread of the COVID-19 pandemic and the subsequent counter-measures, such as school closures, shift to working from home, and social distancing are disrupting economic activity around the world.  As with other major economic shocks, there are winners and losers, leading to increased inequality across certain groups.  In this project, we investigate the effects of COVID-19 on the gender gap in productivity among academics. First, we track the patterns of publications and working paper series submissions of male and female authors before and after COVID-19, performing a simple difference-in-difference analysis to see whether the trends diverge after COVID-19. Preliminary findings from economics suggest that female economists experienced significant declines in submissions in the early months of the pandemic, relative to the mean.  Second, we conduct a broad survey of academics across various disciplines to collect more nuanced data on the respondents’ circumstances, such as spouse employment, the number and age of children, and time use. We find that female academics, particularly those who have children, report a disproportionate reduction in time dedicated to research relative to comparable men and women without children.  Both men and women report substantial increases in childcare and housework burdens, but women experienced significantly larger increases relative to men.

Ansprechpartnerin: Marina Chugunova