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Veranstaltungsformat: Hybrid

Three consecutive lectures will take place as part of this topic complex.

1:00 to 1:40 p.m.: Creative Disruption – Technology innovation, labour demand and the pandemic (Prof. Harald Dale-Olsen)

We utilize a new survey on Norwegian firms’ digitalization and technology investments, linked to population-wide register data and show that the pandemic massively disrupted the technology investment plans of firms, not only postponing investments, but also introducing new technologies. More productive firms innovated, while less productive firms postponed investments. In the short-term, both firm productivities and worker wages increase on average, but this is driven by wage growth for skilled workers. New technologies are associated with increased long-term expected labour demand for skilled workers, and reduced demand for unskilled workers, particularly for the more productive firms.

(joint work with Erlin Barth and Alex Bryson)

1:40 to 2:20 p.m.: Did Covid-19 Accelerate the Digital Transformation? (Terry Gregory)

Using longitudinal survey data on technology use by German firms, matched with administrative worker–firm registers, we assess whether the Covid-19 pandemic accelerated

the adoption of cutting-edge technologies. Our data break down technologies by their application and level of sophistication, as well as capturing the timing of investments and whether the pandemic prompted these investments. We do not find evidence for an overall acceleration effect: Cutting-edge investments did not spike, and while they were more common among firms with higher remote work potential, such firms invested at a greater rate even before the pandemic, and also had more ambitious investment plans pre-pandemic. However, we do find that technologies facilitating remote work were adopted at a greater rate due to the pandemic, and these technologies appeared to have helped firms mitigate the negative employment effects of the crisis.

(joint work with Melanie Arntz, Michael Böhm, Georg Graetz, Florian Lehmer and Cäcilia Lipowski)

2:20 to 3:00 p.m.: The Pandemic Push: Digital Technologies and Workforce Adjustments (Christian Kagerl)

Using novel survey and administrative employer-employee data, we demonstrate that the COVID-19 pandemic was a push factor for the diffusion of digital technologies in Germany. About two out of three firms invested in digital technologies, particularly in hardware and software to enable decentralized communication, management and coordination. These investments also fostered additional firm-sponsored training, underscoring the complementary relationship between investments in digital technologies and training. We then show that the additional investments helped firms to insure their workers against the economic downturn. Firms that made such additional investments were able to retain more of their employees on regular working hours and relied less on short-time work schemes. Low and medium-skilled workers benefited the most from the insurance effect of digital investments.

(joint work with Christina Gathmann, Laura Pohlan and Duncan Roth)

We analyze whether individuals who take on more non-routine job tasks characterized by a low automation risk are rewarded with higher wages.

Little is known about whether changes in job tasks due to technological progress affect personal wages and whether those changes in job tasks relate to the persistent gender wage gap in contemporary Western societies. Following the task-biased technological change approach, we analyze whether individuals who take on more non-routine job tasks characterized by a low automation risk (complex and autonomous tasks) are rewarded with higher wages. We separately analyze men and women and, due to the rigid German labor market, additionally account for job changes as a potential moderator. We use three-wave panel data covering a period of nine years from the German National Educational Panel Study.

Our results from fixed-effects regressions show substantial heterogeneity in the relationship between changes in non-routine job tasks and wages by gender and job change, which is masked when looking at average wage differentials by non-routine job tasks. While both genders benefit from increased task complexity in job changes, the impact is more pronounced for females, helping to slightly narrow the still persistent gender wage gap. However, when taking on more autonomous tasks in job changes, males experience significant benefits, further contributing to the widening of the gender wage gap. In essence, our findings underscore gender-specific monetary returns to increasing non-routine tasks, particularly highlighting the ability of male job changers to monetarize their newly assigned tasks. 

Joint work with Dr. Alexandra Wicht and Dr. Nora Müller.

Students often face incentives to reach performance goals, for instance, to receive a scholarship, enter a college, or be hired for a job.

Students often face incentives to reach performance goals, for instance, to receive a scholarship, enter a college, or be hired for a job. This paper uses a field experiment to study how incentives to reach performance goals affect students, whether the effects vary for students at different parts of the performance distribution, and whether allowing students to choose their own goal improves their performance. We find that incentives backfire: students offered incentives perform worse than their control counterparts.

These negative effects are mainly driven by mismatched goals: the negative treatment effects are concentrated among low-ability students who are assigned a high goal and among students with high aspirations who are assigned a low goal. The effects are also negative but not statistically significant from zero when students are allowed to choose their own goal. Our results show that incentives for performance goals can harm students' performance, especially among students whose goals are mismatched.

My presentation will cover results from two research projects on gender inequality in life courses and later life financial well-being in Germany.

My presentation will cover results from two research projects on gender inequality in life courses and later life financial well-being in Germany, which both rely on linked survey-administrative data. The first study examines how the life courses of couples in East and West Germany are associated with women’s income in later life using multichannel sequence analysis. By applying a couple perspective, we overcome the individualistic approach in most previous research analysing women’s old-age income. Detailed monthly information on spouses’ employment and earnings trajectories from age 20 to 50 for the birth cohorts 1925–1965 stems from SHARE-RV, a data linkage of the administrative records of the German public pension insurance with the Survey of Health, Ageing and Retirement in Europe (SHARE).

Seven clusters of couples’ life courses are identified and linked to women’s individual income in later life. By means of a cohort comparison, a polarization in dual-earner and male-breadwinner type clusters is identified. The former increasingly diverge into successful female-breadwinner constellations and those with both partners in marginalized careers. The latter polarize between persistent male-breadwinner constellations and those in which women increase their labour market engagement. Second, I will introduce first results from the project "Life Course, Assets and Retirement Income in East and West Germany". It examines gender-specific differences in the interplay of employment histories and the accumulation of wealth comparing East and West Germany. Data basis is the SOEP-RV that links the German Socio-Economic Panel (SOEP) survey to respondents’ Deutsche Rentenversicherung (German Pension Insurance) records.

Joint work with: Babette Bühler, Clara Overweg, Andreas Weiland

This study, investigates firm side responses to generous parental leave mandates.

In this study, we investigate firm side responses to generous parental leave mandates. Our primary focus is on firms’ adjustments in the gender and age composition of their workforce. To identify these effects, we use employer-employee matched data from Norway, and deploy a Bartik-type instrument exploiting variation in exposure and shifts across firms due to a series of expansionary reforms of the duration of paid parental leave. We find that in response to longer parental leave related absence, firms increase demand for young female employees but at lower wages. Heterogeneity analyses reveal that this is particularly the case in the private sector. We also document some positive effects on firm performance measured by investment and productivity. Increased part-time work by young women, and overtime hours by older workers emerge as important mechanisms explaining our results.

Our findings suggest that both small and large firms have successfully adapted to young women’s work interruptions linked to longer parental leave, an issue that has so far been overlooked in labor markets.

Big Data and the analysis thereof is considered of increasing importance, not only for big (tech) companies.

Big Data (BD) and the analysis thereof (i.e., Big Data Analytics, BDA) is considered of increasing importance, not only for big (tech) companies but also for small/medium-sized companies and, in particular, for new ventures. Despite or precisely due to its generally presumed relevance, the question arises whether applying BDA leads to better firm performance. Based on a large, representative sample of 3,700 German start-ups, we specifically study the adoption of BDA among start-ups and analyze its economic effects using various short- and longer-term performance measures. We show that start-ups adopting BDA significantly differ from non-adopters regarding their founders' age, education, team composition, and experience. Accounting for these differences, we then investigate the effect of adopting BDA on the new ventures' operating costs, sales, profits, survival rate, and (employee) growth. Our findings show that using BDA does not lead to a competitive advantage in terms of the classical short-term performance measures but is rather associated with greater sales/profit uncertainty, higher (personnel) costs, and a higher probability of failure. Yet, the increased risk of adopting BDA is at the same time compensated by a prospect for higher excess performance -- BDA-adopting start-ups perform significantly better than their peers at the 90%-quantile -- as well as by better expected longer-term performance, as measured by the start-ups' growth and by their ability to secure Venture Capital (VC). Our findings support the concept of a few Schumpeterian Entrepreneurs who adopt technology at the frontier of innovation and found high-risk start-ups with the prospect of high rewards.

A proposal for an occupation-specific end-of-life and late-life perspective on retirees.

Retirement marks a significant life transition, signaling the end of one's active work engagement and the beginning of a new phase of life. In the best-case scenario post-retirement life is characterized by increased time spend with friends and family, and a purpose in life that is perceived as meaningful. The reduced work load should be associated with improved health, because sources of physical and psychological stress should have far less impact. However, reality paints a different picture: The research on retirement shows a lot variation in retirement experiences, financial well-being, mental and physical health, social engagement, and overall life satisfaction.
The importance of pre-retirement occupations on individuals' lives cannot be overstated. However, the impact of occupations on people’s lives does not end with their retirement. Hence, I will propose a new perspective on employment and occupations by focusing on the retirees’ late life and end of life. In my presentation I will provide the theoretical foundations, why occupations (should) have a lasting impact. I will present a data source with which such analyses could be done and discuss outcome variables of interest. Examples for occupation-specific outcomes of interest are: years of life remaining after retirement, years in good health after retirement, years spend in loneliness, wealth, poverty, depression, political attitudes, decrease in cognitive capabilities, social networks, free-time activities, volunteering, housing, life satisfaction, etc.
From a policy perspective, understanding how different occupations influence post-retirement lives can inform retirement planning initiatives and social safety nets as well as occupation-specific training and safety regulations. On an individual level, insights gained from such research can assist individuals in making informed decisions about their vocational aspirations, careers, planned changes of occupations, retirement age, and financial preparations.

The literature on alternative methods for accounting for sample-independent variability is reviewed, a typology of sources of sample-independent variation is developed, and an empirical investigation is conducted estimating the relative and absolute importance of the different types of sample-independent variation.

Empirical economics papers report standard errors to take into account uncertainty associated with sampling variation but rarely consider non-sampling variation from researcher choices about measurement of key variables, functional form choice, identification strategy, and data set. In this paper, we review the literature on alternative methods for taking account of non-sampling variability, develop a typology of sources of non-sampling variation, and conduct an empirical exercise in which we estimate the relative and absolute importance of different types of non-sampling variation. The empirical exercise proceeds in the context of the literature that seeks to estimate the causal effect of college quality on educational and labor market outcomes.

This paper analyzes the open-economy spillover effects of labor market reforms under incomplete insurance. Using microeconomic data, we document a boost in the tradable sector in the aftermath of the German Hartz IV reform. In our model, this phenomenon can be explained by an increase in household savings due to higher precautionary savings in response to the reduction in the generosity of unemployment insurance (Hartz IV). Besides reducing unemployment in the reforming country, lower unemployment benefits generate long-run negative consumption spillovers in a monetary union, which we call the dark shadow of labor market reforms. Our model can match various German trends post Hartz IV reform, such as: i) a lasting increase in net foreign asset position, ii) short-term expansion of the tradable sector relative to the non-tradable sector, and iii) continued depreciation of the real exchange rate. By contrast, simulations of German wage moderation result in qualitatively different open-economy effects that are not in line with the empirical patterns for Germany.

Exploiting prospective data on a cohort born in 1958 we estimate the gender wage gap over the life-course between age 23 and 63, departing from the literature in two ways.

Most studies estimating the gender wage gap rely on linear regression of log hourly earnings.  Estimates often condition on potentially endogenous regressors such as labour market experience and family formation.  Exploiting prospective data on a cohort born in 1958 we estimate the gender wage gap over the life-course between age 23 and 63, departing from the literature in two ways.  First, we use matching estimators which are rarely used in the literature.  Like regression analyses matching relies on observed data to recover the effect of gender on earnings, but by explicitly considering the issue of common support it is more transparent in its treatment of men as counterfactuals for women.  We examine the importance of the common support issue for the size of the gender wage gap.  Second, we condition on pre-labour market variables to avoid conditioning on endogenous choice variables, such as family formation, which are made, in part, with knowledge regarding one’s potential earnings.  We argue our data are well-suited to the task because they contain a wide array of prospective data collected at birth, then at ages 7, 11 and 16, which might conceivably confound estimates of the GWG.  In contrast to findings in the literature in which the regression-adjusted GWG is considerably smaller than the raw gap, we find differences in log hourly mean earnings between men and women are of roughly similar size and, in some cases, wider than raw gaps conditioning on pre-labour market variables.  This is the case whether we use matching or linear estimation techniques. However, the PSM estimated GWG is above the raw gap when cohort members are in their 40s, 50s and 60s.  The implication is that women have pre-labour market traits which reduce their earnings later in life relative to men.  The gap follows an inverted-u shape over the life-course, reaching its maximum of around. .45 log points at age 42, after which it begins to decline, though it remains large among cohort members in their 60s.

Joint work with: Francesca Foliano, Heather Joshi, Bozena Wielgoszewska and David Wilkinson