Valentin Lindlacher

Digital Infrastructure and Local Economic Development: Early Internet in Sub-Saharan Africa

with Moritz Goldbeck (R&R at Journal of the European Economic Association)
latest version here
CESifo Working Paper
job market paper
runner-up for the Distinguished CESifo Affiliate Award at the CESifo Area Conference on the Economics of Digitization 2022

We investigate the impact of early internet availability at basic speeds on local economic development in remote areas of developing countries by analyzing nighttime light emissions across towns in Sub-Saharan Africa. Using a difference-in-differences approach, we exploit submarine cable arrivals, which established countrywide internet connections, and the rollout of the national backbones, which defines internet access within countries. Estimating on incidentally connected mid-sized towns, we find that early internet availability increases nighttime light intensity by 10 percent. We consider increased employment as the main explanation. Our findings highlight the importance of closing the digital divide for regional development.

Keywords: Internet; Regional development; Towns; Nighttime light; Sub-Saharan Africa
JEL-Codes: L86, O18, O33, R11

Training, Automation, and Wages: International Worker-Level Evidence

with Oliver Falck, Yuchen Guo, Christina Langer, and Simon Wiederhold (submitted)
latest version here
CESifo Working Paper



Job training is widely regarded as crucial for protecting workers from automation, yet there is a lack of empirical evidence to support this belief. Using internationally harmonized data from over 90,000 workers across 37 industrialized countries, we construct an individual-level measure of automation risk based on tasks performed at work. Our analysis reveals substantial within-occupation variation in automation risk, overlooked by existing occupation-level measures. To assess whether job training mitigates automation risk, we exploit within-occupation and within-industry variation. Additionally, we employ entropy balancing to re-weight workers without job training based on a rich set of background characteristics, including tested numeracy skills as a proxy for unobserved ability. We find that job training reduces workers’ automation risk by 4.7 percentage points, equivalent to 10 percent of the average automation risk. The training-induced reduction in automation risk accounts for one-fifth of the wage returns to job training. Job training is effective in reducing automation risk and increasing wages across nearly all countries, underscoring the external validity of our findings. Women tend to benefit more from training than men, with the advantage becoming particularly pronounced at older ages.



Keywords: Job training, Human capital, Digital skills, Entropy balancing
JEL-Codes: J24, J31, J61, O33

Leapfrogging Telecommunication: Did the Roll-Out of Mobile Coverage Structurally Change Labor Markets?

with Marta Bernardi

Keywords: Mobile coverage, Structural transformation, Technological development
JEL-Codes: O33, O12, O14




Should I Mail or Should I Go: Voting Behavior After a One-Time All-Postal Election

with Marius Kröper

Keywords: Mail-in voting, Voter turnout, Local elections, Habit formation, COVID-19 pandemic, Bavaria
JEL-Codes: D72, H11, H70, R50




Commuting and Subjective Well-Being in Times of Mobile Network Rollout

with Katharina Bettig

Keywords: Commuting, Well-being, Internet availability, Life satisfaction, Marginal effect
JEL-Codes: D1, I31, R41