CEF.UP – WiP Seminar/Webinar

Tuesday – January 25^th, 2022 at 1:00 p.m. | Room 305 | Online

“Firm-level Labor Shares and Technology-driven Occupational Changes”.

Ana Oliveira – FEP

Abstract:

Technological advances have decreased labor demand for occupations with high routine task content and increased it for occupations that are either cognitively complex or require non-repetitive social interactions. Technology has also been one of the key drivers of the changes in the labor share of income. Our paper investigates whether the evolution of occupational employment shares and occupation-specific wage rates explains firm-level labor share dynamics. Using rich administrative data for Portugal, we show that the S-shaped dynamics of the aggregate labor share between 2004 and 2019 are mostly driven by changes in firms’ labor share rather than value-added reallocation across the labor share distribution. Our findings suggest that firm-specific labor shares rise due to positive growth in hourly wages, particularly high among Routine Manual and Non-Routine Manual occupations. We also show that changes in task group employment shares have limited effects on the firm-level labor shares, due to the stabilization of occupational employment shares since 2010.

CEF.UP – WiP Seminar/Webinar

Friday – October 22^nd, 2021 at 1:00 p.m. | Room 305 | Online

“Specialists or All-Rounders: How best to select university students?”.

Pedro Luís Silva – CIPES and FEP

Abstract:

This paper studies whether universities should select their students only using specialised subject-specific tests or based on a broader set of skills and knowledge. I show that even if broader skills are not improving graduates’ outcomes in the labour market, the university chooses to use them as a criterion for selection alongside the mastery of more subject-specific tools. Empirically, I exploit the variation between subject-specific and non-specific entrance exam sets on Portuguese students’ large administrative dataset. My central finding is that, on average, universities with less specialised admission policies admit a pool of students who obtain a higher final GPA.

CEF.UP – WiP Seminar/Webinar

Tuesday – September 21^st, 2021 at 1:00 p.m. | Room 305 | Online

“Do in-group biases lead to overconfidence in performance? Experimental evidence”.

Lia Flores – FEP (joint work with Miguel Fonseca)

Abstract:

“Psychologists have long identified the tendency of humans to overestimate their skill relative to their peers (overplacement). We investigate whether this phenomenon is exacerbated by group affiliation: social identity theory predicts people evaluate in-group members more positively than out-group members, and we hypothesized that this differential treatment may result in greater overplacement when interacting with an out-group member. We tested this hypothesis with 301 US voters affiliated with either the Republican or Democratic party in the run-up to the 2020 Presidential election, a time when political identities were salient and highly polarized. We found there is a higher tendency for overplacement when faced with an out-group opponent than with an in-group opponent. Decomposition analysis suggests this difference is due to underestimating the opponent, as opposed to overestimating one’s own performance to a higher degree. Moreover, any tendency to incur in overplacement is mitigated when faced with an opponent with the same political-identity relative to one with a neutral one. While group affiliation biases initial priors, such effect is unchanged when participants are asked to update their beliefs.”

CEF.UP – WiP Webinar

Tuesday – May 4^th, 2021 at 3:00 p.m.

“Automation, Education and Demographic Dynamics: Growth Effects in an OLG Model of Endogenous Fertility”.

Catarina Peralta – FEP

Abstract:

” We address two main structural changes occurring in developed countries: the rise of automation and population ageing. We use an R\&D-based growth model in an OLG framework with endogenous education and fertility, and automation in the production process. Our model is able to combine the growth of real wages over time and either a fall or an increase in birth rates, consistent with recent data regarding the birth rate by skill group. Moreover, our model allows for the study of the interplay between the effects of population ageing and those of automation. The results show a dynamics consistent with the US trends for the period covering 1970 to 2019.”