Die Vorlesung diskutiert ausgewählte, aktuelle Themen der Arbeitsmarktökonomik wie die Effekte von Mindestlöhnen, die Auswirkungen der Hartz-Reformen, die Entwicklung von Lohnungleichheit und Diskriminierung. Hierbei liegt ein besonderer Fokus auf der Analyse von Friktionen und arbeitsmarktpolitischen Maßnahmen zur Optimierung des Marktergebnisses. Die Studierenden können anhand von ökonomischen Modellen empirische Beobachtungen auf dem Arbeitsmarkt erklären und die Auswirkungen von Reformen analysieren und beurteilen. In diesem Rahmen sind sie in der Lage, die Kompetenzen aus der Mikro- und Makroökonomik, die in den vorherigen Semestern entwickelt wurden, auf konkrete arbeitsmarktökonomische Fragestellungen anzuwenden. Zudem können die Studierenden die Vorteile und Grenzen von ökonomischen Modellen einschätzen und kritisch hinterfragen.

This module provides a hands-on introduction to the crypto world. In the first meetings, we mine our first coin and use our wallet to store it. We learn how the proof of work mechanism of bitcoin is different from more “novel” approaches like proof of stake. We also mint our own non-fungible token (NFT) and discuss potential real world applications of the technology. Moreover, we study whether DeFi (decentralized finance) that uses blockchain technology can be a substitute or complement to legacy finance (e.g., we will use a DEX (decentralized exchange) to trade one coin/token for another and discuss liquidity pools that can give rise to “impermanent loss”). After discussing the purpose and risks of stable coins like Tether or UST (Terra/Luna), we address the pros and cons of regulation and CBDCs (central bank digital currencies).

This module analyses the evolution of the economy in the long-run. It focuses on savings, investment, growth and development, as well as the sustainability of economic growth and government debt. Students will be enabled to i) critically evaluate macroeconomic models dealing with growth, ii) better understand empirical observations relating to economic growth, and iii) to better assess economic policy problems and reform proposals related to growth and development. In addition, they will be enabled to explain the purpose and limits of abstract economic models.

In this seminar, we discuss specific topics related to the theoretical background, applications, economic implications, and regulation in the areas of blockchains and cryptocurrencies. The specific topics can be found below. Each participant must write a paper (about 15 pages) and give a presentation (30 minutes) to obtain 6 ECTS. Participants must submit a preliminary table of contents no later than June 1st. The paper must be submitted no later than August 15th.

This module will cover the most relevant aspects of modern labour economics with a focus on economic theory. Amongst others, this module will discuss the effects of asymmetric information, discrimination, search fricitons and minimum wages on labour supply, investment in human capital, wage dispersion, automation, and efficiency.

The module familiarizes students with the essential concepts of modern macroeconomic theory at an advanced level. A particular focus will be placed on formal microfounded models to analyze and understand economic growth dynamics. The main topics are growth theory sustainable growth, and an introduction to real business cycle models.

We study whether and to what extent social media information can reduce (ethnic) discrimination in a two-sided market characterized by asymmetric information. We analyze whether information that breaks with prevailing ethnic stereotypes might induce the uninformed side of the market to update its probabilistic beliefs on a desired, but hidden quality of an ethnic minority applicant. We create eight social media profiles (male and female) and apply for 3,676 vacant room ads for shared housing on a two-sided platform. The profiles are each identical within one gender, except for the different names assigned to them: two profiles of each gender are assigned a Turkish-sounding name, two a German-sounding name. To each application, we randomly assign one of the eight names and whether it contains a link to the corresponding social media profile. When an application includes such a link, the otherwise substantial discrimination against applicants with Turkish-sounding names is not only significantly reduced, but almost eliminated — hinting at the potential of social media information that breaks with prevailing stereotypes to reduce (statistical) discrimination.

We conducted a correspondence test to identify the determinants and extent of ethnic discrimination in the market for shared housing in Germany. We establish a link between information about an applicant’s personality and her performance in the housing market. About 2,000 fictitious applications with randomly assigned German-, or Turkish-sounding, female or male names, with or without additional personality information were sent to vacant room ads. While the callback rate for German-sounding names is 52 percent, it drops to 37 percent for Turkish-sounding names. Female applicants receive significantly more callbacks than their male counterparts. Additional personality information is particularly beneficial to the group with the highest callback rate (German females) and the group with the lowest callback rate (Turkish males). Thus, personality information reduce the ethnic gap between Turkish and German males, whereas the gap among females increases. A simple theoretical model shows that the strong effect of information on German females can be explained by aggregation over rooms that differ in market tightness. Moreover, advertisers who only accept applications of one particular gender discriminate significantly more against Turkish applicants.

Numerous eligible German students do not apply for heavily subsidized student aid (BAföG). Our theoretical model shows how imperfect information, risk aversion, debt aversion, and student income can incentivize rational students to abstain from an application. We use GSOEP data from 2001 to 2013 to simulate BAföG eligibility and find that in particular risk averse students with low income are discouraged if they have little information about the application procedure. Moreover, debt-averse students are more reluctant to apply. This suggests that a non-transparent and complicated student aid system disproportionally discourages poor students with little experience with the BAföG system.

This theoretical model shows that students strategically overuse student loans. In imperfect labour and credit markets, firms compensate graduates for a share of their loans via higher wages. This shifts some costs to firms and low-skilled workers who suffer from higher unemployment and lower wages. While any student loan increases unemployment, the effects on welfare and inequality depend on the purpose of the loan: A loan for tuition fees reduces human capital and credit accessibility, the college premium increases significantly, and welfare declines. A loan spent on consumption increases education and credit accessibility, while wage inequality and welfare change marginally.

This paper shows that hiring discrimination against old workers occurs in imperfect labour markets even if individual productivity does not decrease with age and in the absence of a taste for discrimination. Search and informational frictions generate unemployment, with less productive workers facing higher risks of unemployment. Therefore, the employment status provides a signal for expected productivity. This stigma of unemployment becomes stronger with individual age and reduces the hiring opportunities of older workers. Political measures such as a reduction in dismissal protection can help to restore efficiency.

This paper studies ethnic discrimination in Germany’s labour market with a correspondence test. We send two similar applications to each of 528 advertisements for student internships, one with a Turkish-sounding and one with a German-sounding name. A German name raises the average probability of a callback by about 14%. Differential treatment is particularly strong and significant in smaller firms at which the applicant with the German name receives 24% more callbacks. Discrimination disappears when we restrict our sample to applications including reference letters which contain favourable information about the candidate’s personality. We interpret this finding as evidence for statistical discrimination. Download Article